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Acute Myeloid Leukemia ( AML ) is a fatal hematological cancer . The genetic abnormalities underlying AML are extremely heterogeneous among patients , making prognosis and treatment selection very difficult . While clinical proteomics data has the potential to improve prognosis accuracy , thus far , the quantitative means to do so have yet to be developed . Here we report the results and insights gained from the DREAM 9 Acute Myeloid Prediction Outcome Prediction Challenge ( AML-OPC ) , a crowdsourcing effort designed to promote the development of quantitative methods for AML prognosis prediction . We identify the most accurate and robust models in predicting patient response to therapy , remission duration , and overall survival . We further investigate patient response to therapy , a clinically actionable prediction , and find that patients that are classified as resistant to therapy are harder to predict than responsive patients across the 31 models submitted to the challenge . The top two performing models , which held a high sensitivity to these patients , substantially utilized the proteomics data to make predictions . Using these models , we also identify which signaling proteins were useful in predicting patient therapeutic response .
AML is a potent malignancy of the bone marrow . It is characterized by the production of dysfunctional myeloid cells , incapable of carrying out their normal differentiation into mature blood cells , ultimately leading to hematopoietic insufficiency , infection , hemorrhage , and anemia [1 , 2] . The last decade has seen significant revision in the diagnosis and classification of AML . Classification has shifted from a morphology and lineage centered paradigm , described by the French-American-British ( FAB ) system , to a system which focuses on genetic anomalies , as described by the new World Health Organization ( WHO ) guidelines [3] . While this includes many of the genetic mutations now recognized to commonly occur in AML [4] , recent sequencing efforts [5] have revealed many previously unrecognized mutations in AML which will require further modification of classification schemes . Moreover , genetic events related to epigenetics and non-coding RNAs have yet to be incorporated into classification . Unfortunately , devising an accurate prognosis for AML patients , particularly those with normal cytogenetics , remains very challenging as the combinatorial potential of genetic events makes for tremendous heterogeneity in both classification and outcome interpretation [6] . This can be attributed , in part , to the fact that only a minority of genetic mutations are driver mutations that lead to functional changes in cellular pathways that translate into physiological outcomes . High-throughput proteomics studies , such as Reverse Phase Proteomic Arrays ( RPPA ) , have the potential to bridge the gap between the underlying genetic alterations and functional cellular changes . Thus far , proteomics has been used successfully to profile AML patients based on alterations in several key signaling pathways , including highly implicated proteins like FLi1 [7] and FOXO3A [8] . However , these studies also confirm that AML remains a very heterogeneous disease , even on the level of protein signal transduction . It is clear that leveraging high-throughput proteomics to improve the accuracy of prognosis for AML patients will require the development of robust quantitative tools . To date , we did not find any studies which address this issue . The Dialogue for Reverse Engineering Assessment and Methods ( DREAM ) is a crowdsourcing platform which has accelerated the development of computational tools in the most pertinent areas of biology and medicine , unraveling gene networks [5 , 9] , predicting drug sensitivity [10] , and harnessing predictions to improve prognosis accuracy [11 , 12] . Using a challenge based design , DREAM attracts expertise and fosters collaboration across academic fields while providing a mechanism for the robust and unbiased evaluation of computational methods [13–15] . We developed the DREAM Acute Myeloid Leukemia Outcome Prediction Challenge ( AML-OPC ) following this paradigm . The DREAM9 AML-OPC was designed to facilitate both the improvement and comprehensive assessment of quantitative AML prognosis methodologies . Challenge participants were provided access to data from 191 AML patients ( the training set ) seen at the MD Anderson Cancer Center ( Houston , TX ) , while data from an additional 100 AML ( the test set ) patients was withheld for model evaluation . We chose Response to Therapy ( RT ) as the primary clinical endpoint because it is a potentially actionable prognosis criterion . However , since a patient’s Remission Duration ( RD ) and Overall Survival Time ( OS ) can be informative in planning patient care , these were also included in the challenge objectives . The DREAM9 AML-OPC included over 270 registered participants and 79 contributing teams , many of which contributed to multiple sub-challenges . Over 60 algorithms were contributed , many of which were refined during the challenge , yielding several innovative and accurate top performing models . We identify these models , test them for robustness , and determine which scoring metrics differentiate the top performers . We also evaluate whether prediction accuracy can be improved by aggregating predictions from the many diverse models we tested . In addition , we evaluate RT predictions over the population of models to determine which outcomes are more difficult to predict accurately . Finally , we investigate the top two performing models to determine the extent their RT predictions were improved by the RPPA data .
The challenge data consisted of 40 clinical indicators ( see S1 Table ) and 231 RPPA measurements ( Fig 1 ) . Three separate sub-challenges were defined to independently address each pertinent aspect of AML prognosis , namely RT for sub-challenge 1 ( SC1 ) , RD for sub-challenge 2 ( SC2 ) , and the OS for sub-challenge 3 ( SC3 ) ( Fig 1 ) . Two metrics were used to evaluate the performance of models within each sub-challenge . In SC1 , RT predictions were contributed as list of confidences indicating the probability that each patient would respond to therapy . The area under the receiver operating characteristic ( AUROC ) and balanced accuracy ( BAC , defined as the average of true positive rate and true negative rate ) were selected to assess the RT predictions given their wide use and well documented utility in evaluating classification problems . For SC2 and SC3 , RD and OS predictions were submitted as a list of remission or survival times ( weeks ) , respectively , along with a list of corresponding prediction confidences . Both SC2 and SC3 were assessed using the concordance index ( CI ) , which evaluates the ranks of predicted versus actual times when there is censored data and is commonly used in survival analysis . Since the CI considers only the order but not the actual values of the predictions , the Pearson correlation ( PC ) was also used to evaluate RT and OS . The number of teams contributing model predictions increased for each sub-challenge throughout the DREAM9 AML-OPC ( S1A Fig ) . Participants were allowed to test predictions once per week for a total of 12 weeks ( Fig 2 ) . The same test set was used in the leaderboard phase as well as in the final evaluation . Therefore , predictions were scored on a different subsampled ( ~75% ) subset of the 100 patient test set each week to avoid over-fitting . See Materials and Methods for a more detailed description of the challenge design . Final predictions were collected on the 13th week following the challenge opening . In SC1 ( Fig 2A ) , the difference in performance between the top RT predictions from the first week and that from the best performing predictions observed during any week of the competition was an increase of 6 . 21% when evaluated by the AUROC metric alone , 9 . 20% when evaluated by the BAC alone , and 6 . 33% when calculating the best average of the two metrics scored by any model . Here , we used the average of both metrics as a summary statistic for the two metrics . The maximum performance observed during individual weeks is shown in S1B–S1D Fig ( red line ) . The performance of predictions submitted for the final scoring ( week 13 ) were distributed in a manner distinct from random predictions ( see Fig 2B , p< 0 . 01 for AUROC and BAC , Wilcoxon rank sum test ) , with the top scores being significantly better than random . Note , the median score for each of the previous weeks was also consistently higher than that associated with random predictions ( S1B Fig ) . The scores from predictions made on the final submission test data ( week 13 ) were frequently lower compared to those made on the training data ( S2 Fig ) , particularly for the lower ranked models , suggesting that over-fitting was an important factor in determining model performance . For SC1 , the top-performing model used a novel evolutionary weighting approach to feature selection ( see S1 Text ) , yielding a final AUROC score of 0 . 796 and a BAC of 0 . 779 . The initial performance of models in predicting RD in SC2 was much lower than observed for RT in SC1 , revealing RD predictions were considerably more challenging ( Fig 2C ) . Even so , generous improvement was seen in both the peak PC and CI scores when comparing the initial scores to the best score observed during the challenge , 47 . 43% and 11 . 99% respectively . The highest average metric scores observed during the challenge also showed a marked increase ( 24 . 43% ) . While the distributions of CI and PC scores in the final submission were not as separated from random as the RT predictions ( p<0 . 01 for CI , p<0 . 025 for PC , Wilcoxon rank sum test ) ( Fig 2D ) , the top scores were higher than expected for random predictions . With the exception of the PC metric in the first week , median scores were higher than expected for random predictions ( S1C Fig ) . In SC3 , OS predictions showed significant improvement when assessing by the CI alone ( 10 . 53% ) , however , the PC showed less increase ( ~3% ) ( Fig 2E ) . The top average of both metrics showed significant improvement ( 8 . 99% ) as well . The OS final CI and PC predictions were both significantly shifted from random ( p<0 . 01 , Wilcoxon rank sum test ) ( Fig 2F ) . The top performing approach for both SC2 and SC3 was developed by a single team and based on Cox Regression ( see supplemental text ) . The model achieved final CI and PC scores of 0 . 655 and 0 . 773 for RD predictions in SC2 , while obtaining scores of 0 . 730 and 0 . 740 for SC3 . A unique facet of community based model development is the ability to examine whether the diverse population of submitted models can be combined to either assure or improve predictive power . Previous DREAM challenges have shown that this approach , often referred to as the “wisdom of crowds” , generates ensemble prediction scores that are comparable in performance , and often times better , than the top performing models [16] . This is particularly useful in real situations when we don’t have a gold standard and therefore we are not certain of which one is the top performing model . Here we aggregate model predictions by calculating the arithmetic mean for the predictions of each model and those models with superior performance . These averaged predictions are then scored to determine aggregate model performance . We tested the performance of aggregate predictions for RT in SC1 and found that the performance increased above the top performing model by 0 . 04 ( ~5% improvement based on the average of AUROC and BAC scores ) when combining predictions for the top 3 models ( Fig 3 , leftmost panel ) . The performance remained higher than the top performing model even after combining the top 5 models and only decreased by 0 . 11 when combining all 31 models . This score , however , was significantly better than the corresponding score of the 31st ranked model ( 0 . 67 compared to 0 . 42 ) . Similarly , aggregating RD predictions from the top 5 models in SC2 ( Fig 3 –middle panel ) also increased performance above the top performing model by 0 . 02 . The aggregate score from all 15 model predictions was only 0 . 04 less than the top performing score but was 0 . 24 better than the worst performing model ( rank 15 ) . While the aggregate score for OS predictions in SC3 was not higher than the top performing model score ( Fig 3 , rightmost panel ) , combining all 17 model predictions results in a prediction that is between the best and second best , only reduced the performance by 0 . 08 with respect to the top performing team , and resulted in an aggregate score that was 0 . 25 better than the worst performing model . A key element in assessing model performance is determining the robustness of the final rankings with respect to perturbations of the test set . We evaluated the stability of the final scores by sampling ~81% of the week 13 test set patients ( 60 patients out of 74 ) , re-scoring each model , and then repeating 1000 times for each sub-challenge ( Fig 4 ) . For SC1 , the top performing model ( Challenge Rank = 1 ) had a combined metric score that was significantly better than all the lower ranked models ( average of AUROC and BAC , Bayes Factor ( BF ) >6 . 3 with maximum score overlap of 13 . 7% , see S3 Fig and Materials and Methods ) . When examining each metric separately for the top two teams , we found that the distribution of AUROC scores overlapped 33 . 8% ( BF = 1 . 95 ) , meaning that the BAC set these models apart ( overlap of only 3% , BF = 32 . 3 ) . As indicated earlier , the same model held the best performance in both SC2 and SC3 ( Fig 4B , left and right ) . In SC2 , the combined metric score of the top performing model was significantly better than any of the lower ranked models ( maximum overlap of 3 . 1% , BF = 31 . 3 ) due to superior performance when evaluated using the PC metric . In contrast , the top model’s resulting CI and PC scores were both superior to the lower ranked models in SC3 ( maximum overlap of 3 . 1% , BF = 31 . 3 ) . We next investigated prediction errors in more detail , focusing on SC1 , since RT is a potentially actionable part of prognosis . Specifically , we asked whether either outcome , Complete Remission ( CR ) or Resistant , was more difficult to predict . Patients in the test set were grouped based on outcome and the predictions from each model were re-scored . The resulting accuracy , taken as the positive prediction value , was distributed distinctly for each outcome ( Fig 5A ) . The median accuracy for Resistant patients was much lower than CR patients ( 0 . 42 vs 0 . 73 , p<0 . 01 , Wilcoxon rank sum test ) , suggesting they are more difficult to classify ( Fig 5B , left ) . Moreover , 6 of the 7 top performing models achieved accuracies near or above 75% for classifying Resistant patients ( Fig 5B , right ) , well above the median accuracy for that patient group ( Fig 5B , left , red box ) . These same 6 models held accuracies near 70% for CR patients , which were below the median ( Fig 5B , left , green box ) , indicating that accurately classifying Resistant patients set these top models apart . We also examined whether any particular class of learning algorithm was better at predicting the Resistant class of patients , but found a high degree of performance variability amongst implementations that used the same base learners ( S4 Fig ) . One of the goals of the DREAM9 AML-OPC was to promote the development of a quantitative method which could utilize the high-throughput RPPA proteomics data to make more accurate prognosis predictions . We examined RPPA data usage for the two highest ranked models from SC1 . To do so , we tested each model on scrambled RPPA data , meaning the original trends and RPPA data patterns that were present during model training were removed . Note , scrambled protein data was generated by randomly shuffling patient protein values for each individual protein , meaning the distribution and associated statistics were maintained for each protein . Both models were first tested on data with protein values simultaneously scrambled for all 231 proteins a total of 100 times and scored using the AUROC and BAC metrics . Neither model completely lost predictive power , having median scores of 0 . 69 and 0 . 65 for the first and second ranked model , respectively , as evaluated using the average of the AUROC and BAC . However , the resulting scores were much lower when the models made predictions using scrambled data compared to the original scores using the actual RPPA data ( Fig 5C ) . For both models , the original scores lay at the upper edge of the distribution of scrambled data scores ( top 95% ) . Using the difference between the original scores and the median scrambled RPPA data scores as an estimate , the performance loss was 0 . 10 ( 10 . 7% ) and 0 . 11 ( 14 . 6% ) for the top and second ranked model ( Fig 5C , compare box midline to diamond for the ‘average’ metric ) , indicating the RPPA data contributed substantially to each model’s predictions . We next wanted to determine which specific signaling proteins were most pertinent to the performance of the two top models from SC1 . To test this , we scrambled the data for each of the 231 proteins separately over 100 iterations , running each model on a total of 23 , 100 scrambled data sets . We then evaluated these predictions using a combined metric based on the average of the AUROC and BAC . The percent difference between the original score ( unscrambled data ) and the score achieved using data with individually scrambled proteins was used to describe the models dependence on each protein ( Fig 5D ) . If a protein was found to influence model performance , data pertaining to that protein was scrambled 10 , 000 iterations to more accurately assess its impact . For the top performing model ( rank #1 ) , randomizing signaling proteins one at a time reduced the model performance in more than 65% of the permutations for 26 proteins ( S5A and S5B Fig ) . For the rank #2 model , 65% or more of the randomizations for each of 4 different proteins decreased model performance ( S5C and S5D Fig ) . Interestingly , perturbing the PIK3CA ( Phosphoinositide-3-Kinase , also known as PI3k ) signaling protein , an important cell cycle regulator , greatly impacted both models ( reducing model performance in more than 96% of the cases , Fig 5D , compare top and bottom heat map , also S5 Fig ) . Indeed , patients that were classified as resistant to therapy were biased towards low levels ( <0 ) of PIK3CA ( chi-squared test , p<0 . 00018 , also see S6 Fig ) . In addition , the performance of the rank #1 model was also dependent on two other signaling proteins involved in PIK3CA signaling , GSKAB and PTEN . Both models were also dependent on NPM1 ( 94 . 36% and 81 . 43% of permutations reduced performance , rank #1 and rank #2 , respectively ) , a protein which contributes to ribosome assembly and chromatin regulation . Note , both models also utilized several clinical variables ( S7 Fig ) , including Age , Chemotherapy , and AHD .
The absence of new and informative prognostic information has stunted the improvement of AML prognosis accuracy and the advancement of treatment for the last two decades . The DREAM 9 AML-OPC gathered researchers from all around the world to address this problem , successfully providing a competitive incentive for progress while maintaining a collaborative environment . This was evident from both the improvement seen in the challenge leaderboards and the wide use of the challenge forums during the competition to convey ideas and voice questions and concerns . In addition , the DREAM9 AML-OPC carried out a webcast “hackathon” , a collaborative tool new to DREAM challenges , where several teams shared insights and local experts presented ideas . By evaluating the predictions from both good and poor performing models , we were able to use the DREAM9 AML-OPC as a crowdsourcing platform to gain general insight into making more accurate RT predictions . Although many of the models in SC1 were robust , we determined that higher ranked models were distinct in having an elevated and stable median BAC score . In this case , it is likely that the AUROC metric was less sensitive to the class imbalance inherent in the AML data ( as discussed in the methods ) . As this implies the top performers held greater capacity to predict the minority class , i . e . , the Resistant patients , we investigated performance on each class in more detail . Indeed , the overall accuracy observed across all the contributed models was lower in predicting the Resistant cases . The top performing models , however , held accuracies well above the median accuracy for the Resistant class , indicating their ability to predict these patients allowed them to obtain higher BAC scores and higher ranks . Accordingly , future efforts in developing RT prognostic models would benefit from improving predictive ability for Resistant patients . Each sub-challenge resulted in the development of a refined and robust quantitative method to predict a different aspect of patient prognosis . The top model in SC1 used a random forest learning algorithm coupled with a novel form of feature selection called “evolutionary weighting” . Since no general class of learning algorithms could be identified as more accurate in predicting RT , the success of this algorithm likely stems from its implementation and effective feature selection . While the DREAM 9 AML-OPC focused on clinically actionable RT predictions , the challenge also resulted in the development of a refined Cox regression model capable of predicting RD and OS . In addition , some participants were also inspired to pursue interesting lines of research beyond the specific aims evaluated by the DREAM9-AML-OPC , for example , exploring characteristics specific to subpopulations of patients [17] . It is important to note , however , potential limitations in our challenge design . The scarcity of AML patient proteomics data available required us to use data from the test set to provide participants with feedback on the weekly leaderboard . This represents an indirect form of information leakage which could potentially lead to the development of over-optimistic models . However , we limited feedback to 12 scorings per participant and used random test set subsamples to minimize potential model overfitting . Moreover , the top model from sub-challenge 1 only submitted to the leaderboard 1 time prior to final judging . Another potential source of information leakage was the availability of data describing clinical variables and outcomes for a limited number of patients that were used in this study [18] . This data , however , was released many years prior to the DREAM9 AML-OPC and did not have updated patient outcomes . The proteomics data also originated from a different source , and it does not correlate with the data released for the DREAM9 AML-OPC without informed cross normalization . Therefore , it is unlikely this data would be generally informative if participants decided to use it for model training . As a precaution , data pertaining to these patients was excluded from the final model evaluation ( week 13 ) and therefore did not impact the study results . Beyond developing accurate prognostic models , participants were provided novel clinical RPPA proteomics data and tasked with developing a means to use this information in conjunction with clinical data to improve prognosis accuracy . To our knowledge , the DREAM9 AML-OPC represents the first attempt at both developing a quantitative means to utilize this information and providing a rigorous way to assess the resulting models . Accordingly , we tested the two top performing models for SC1 to see the extent to which their RT predictions depended on the RPPA data . Our findings indicate that the performance of these models was enhanced by using RPPA data , suggesting that clinical proteomics has the potential to become a valuable component to AML prognosis . Moreover , the performance of both models , though derived from very different approaches , was heavily dependent on PI3KCA , suggesting PI3KCA could be a highly informative protein biomarker for predicting AML patient response to therapy . This is congruent with recent studies suggesting PI3KCA mutation is a prognostic factor for AML [19 , 20] and that this protein and pathway is potentially an effective therapeutic target [21] . Both models were also dependent on NPM1 . The role of NPM1 mutation as a prognostic factor may be unclear . While it is typically associated with higher survival rates in AML [22 , 23] , a recent study indicates it is not a prognostic factor for AML patients with normal cytogenetics [24] . Our analysis , based on the performance of predictive models that utilize proteomics data rather than genetic data , indicates that NDM1 is an informative feature in predicting AML patient response to therapy .
The dataset used for the DREAM 9 AML-OPC consisted of 291 patients seen at the MD Anderson Cancer Center ( Houston , TX ) , for which clinical attributes and RPPA data from bone marrow biopsies was obtained , processed , and normalized as described previously [25–28] . A genetic algorithm was designed to partition the dataset into training and test datasets which have equivalent distributions of clinical and RPPA data . The training set consisted of 191 patients , while the test set held 100 patients . These datasets are available on the Synapse online repository . Note , the clinical outcomes in the overall dataset were imbalanced , with the percent of CR and Resistant patients being approximately 71% and 29% respectively . This ratio was believed to be generally congruent with the overall low survival rate for AML patients and was preserved in both the training and test datasets . The training data was released to participants on June 16th , 2014 . Participants were allowed to submit test set predictions for feedback once a week for 13 weeks , from June 23rd to September 8th , 2014 ( see Fig 1 for timeline ) . For each sub-challenge , models were evaluated using two different metrics , and the values for these metrics were posted to the leaderboard each week . Metrics were the AUROC and BAC for SC1 , and the CI and PC for both SC2 and SC3 . To prevent model over-fitting , 75 out of 100 patients were selected at random for scoring for weeks 1–11 . For weeks 12 and 13 , 74 patients were selected to exclude patients for which limited amounts of data might have been available from other sources . Note , SC2 and SC3 required censoring of patients for the purposes of scoring . In SC2 , the PC was calculated for RD predictions based solely on patients that responded to therapy and underwent a subsequent relapse . Likewise , for OS predictions in SC3 , the PC was determined only for patients that were known to be deceased . For both SC2 and SC3 , the CI was determined using right censoring . Final submissions were taken on September 15th , 2014 and scored as described above . Part of the challenge design included fostering collaboration amongst participants . During the challenge , model scores were posted on a weekly leaderboard so that the progress of every participant was shared throughout the DREAM community . An open “Hackathon” took place on July 26th as part of an effort to foster collaboration in the challenge community . In addition , a community forum was set up so registered participants could ask both technical and administrative questions about the challenge , share ideas , and voice concerns . To check if the ranking resulting from the final model predictions is robust to perturbations of the test set ( e . g . , removing some of the patients ) , we re-evaluated each model’s predictions on 1000 sub-samples of the final ( week13 ) test patients . The results of the performance comparison between the model ranked 1st ( Rank #1 ) using the final test set and the models ranked 2nd , 3rd , etc ( Rank #2 , Rank #3 , etc ) are shown in S3 Fig . More precisely , if we call ΔM1k the difference in performance metrics of the Rank #1 model ( M1 ) and model Rank k ( Mk ) , then ΔM1k = M1—Mk , under the same sub-sample . S3 Fig shows the distribution of values of ΔM1k as a function of k . For SC1 , the Rank #2 model scores better than Rank #1 in the averaged AUROC and BAC score ( that is , ΔM12 is negative ) in 13 . 7% of the sub-samples tested . Therefore , while the Rank #1 model does not perform better than the Rank #2 model in all sub-samples , it scores higher with a frequency of 86 . 3% . If we call Prob ( M1 > Mk | D ) the probability that Model Rank#1 scores higher than model Rank k , and Prob ( Mk > M1 | D ) the probability that model Rank k scores better than model Rank #1 given the data , then the posterior odd ratio is defined as: Opost ( 1 , k ) =Prob ( M1>Mk|D ) /Prob ( Mk>M1|D ) This ratio measures the fold change of the frequency of model Rank #1 performing higher than model Rank k to the frequency of model Rank k performing better than model Rank #1 given the data at hand . This unprejudiced prior was that mode Rank #1 and model Rank k have equal odds of winning . Therefore the prior odds ratio is given by: Oprior ( 1 , k ) =Prob ( M1>Mk ) /Prob ( Mk>M1 ) =1 The Bayes Factor K is defined as the ratio between posterior odds and prior odds ratios: BF ( 1 , k ) =Opost ( 1 , k ) /Oprior ( 1 , k ) For hypothesis testing , where the conventional statistical significance is given by p-values < 0 . 05 , well established guidelines for the interpretation of Bayes Factors [29] suggest that BF ( 1 , k ) > 3 , 20 and 150 gives positive , strong , and very strong evidence in favor of M1 > Mk . For sub-challenges 1 , 2 and 3 we have that BF ( 1 , 2 ) is equal to 6 . 3 , 332 and >999 , indicating a robustness of the relative ranking between Rank #1 and Rank #2 models in the Challenge . This robustness holds for all metrics and all sub-challenges , except for metric AUROC in SC1 , for which model Rank #1 cannot be considered to be better than model Rank #2 , #3 or #4 . Use of the RPPA data was determined for the two top scoring models in SC1 by scrambling the protein data , making predictions with the previously trained models , and comparing the scores to those from the original predictions that were made with the unscrambled RPPA data . The data was scrambled by randomly shuffling the values for each individual protein across the 100 patients in the test dataset . In this way , the statistical properties , e . g . , the mean , variance , range , etc , were preserved for every protein . All proteins in the dataset were scrambled in this manner for each assessment and a total of 100 assessments were conducted . Note , each model was scored using the final ( week 13 ) test dataset ( 74 patients ) . Reduction in model performance was measured by the percentage of scores that were lower than the original predictions , i . e , dividing the number of scores that were less than the original ( unscrambled ) by the total number of scores from scrambled RPPA assessments . The procedure to determine which specific proteins were informative to the two top performing models was the same as described above , with the exception that only 1 protein was scrambled for each of the assessments . Again , this was repeated 100 times , making a total of 23 , 100 scrambled assessments for the 231 proteins . To more accurately determine the percentage of perturbations that decreased model performance , an additional 10 , 000 assessments were performed for proteins that altered model performance under the initial 100 assessments . Challenge results were analyzed using the statistical computing language R [30] . Figure plots were developed using the package ggplot2 [31] .
|
Acute Myeloid Leukemia ( AML ) is a hematological cancer with a very low 5-year survival rate . It is a very heterogeneous disease , meaning that the molecular underpinnings that cause AML vary greatly among patients , necessitating the use of precision medicine for treatment . While this personalized approach could be greatly improved by the incorporation of high-throughput proteomics data into AML patient prognosis , the quantitative methods to do so are lacking . We held the DREAM 9 AML Outcome Prediction Challenge to foster support , collaboration , and participation from multiple scientific communities in order to solve this problem . The outcome of the challenge yielded several accurate methods ( AUROC >0 . 78 , BAC > 0 . 69 ) capable of predicting whether a patient would respond to therapy . Moreover , this study also determined aspects of the methods which enabled accurate predictions , as well as key signaling proteins that were informative to the most accurate models .
|
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"Abstract",
"Introduction",
"Results",
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"Materials",
"and",
"Methods"
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2016
|
A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis
|
Argonaute ( AGO ) proteins partner with microRNAs ( miRNAs ) to target specific genes for post-transcriptional regulation . During larval development in Caenorhabditis elegans , Argonaute-Like Gene 1 ( ALG-1 ) is the primary mediator of the miRNA pathway , while the related ALG-2 protein is largely dispensable . Here we show that in adult C . elegans these AGOs are differentially expressed and , surprisingly , work in opposition to each other; alg-1 promotes longevity , whereas alg-2 restricts lifespan . Transcriptional profiling of adult animals revealed that distinct miRNAs and largely non-overlapping sets of protein-coding genes are misregulated in alg-1 and alg-2 mutants . Interestingly , many of the differentially expressed genes are downstream targets of the Insulin/ IGF-1 Signaling ( IIS ) pathway , which controls lifespan by regulating the activity of the DAF-16/ FOXO transcription factor . Consistent with this observation , we show that daf-16 is required for the extended lifespan of alg-2 mutants . Furthermore , the long lifespan of daf-2 insulin receptor mutants , which depends on daf-16 , is strongly reduced in animals lacking alg-1 activity . This work establishes an important role for AGO-mediated gene regulation in aging C . elegans and illustrates that the activity of homologous genes can switch from complementary to antagonistic , depending on the life stage .
As components of the microRNA ( miRNA ) induced silencing complex ( miRISC ) , miRNAs use partial base pairing to tether Argonaute ( AGO ) and associated proteins to specific target RNAs , typically resulting in RNA destabilization [1] . Each miRNA has multiple targets and regulation of individual targets ranges from fine-tuning to robust silencing [2] . Across multicellular organisms , miRNAs play integral roles in many different pathways , and changes in miRNA expression or function have been linked to numerous human diseases , including cancer , heart ailments and neuronal pathologies [3 , 4] . Target regulation by miRNAs is dependent on the availability and function of AGO proteins . Of the 25 different AGOs in C . elegans , only three appear to be dedicated to the miRNA pathway [5–7] . ALG-1 ( AGO-Like Gene 1 ) and ALG-2 are broadly expressed and bind most miRNAs , whereas ALG-5 is restricted to the germline and associates with a small subset of miRNAs [5 , 8] . The alg-1 and alg-2 genes encode proteins that are over 75% identical at the amino acid level and appear to share similar spatiotemporal expression patterns during embryogenesis and larval development [8 , 9] . Although alg-1 loss-of-function mutants exhibit mild to severe developmental defects , alg-2 null mutants appear to develop normally [6 , 8–10] . Furthermore , global misregulation of miRNA biogenesis and target regulation is observed in animals deficient in alg-1 alone [10–12] . Although alg-2 cannot fully compensate for the absence of alg-1 during larval development , embryonic lethality is only observed when both of these AGOs are depleted [6 , 8] . Additionally , loss of either alg-1 or alg-2 results in a reduced brood size , decreased numbers of oocytes and defects in ovulation [5 , 13 , 14] . Overall , ALG-1 appears to serve as the primary AGO for the miRNA pathway during development with ALG-2 contributing mostly redundant functions . MiRNA activity is also important for the viability of adult C . elegans . Depletion of alg-1 or alg-2 by RNAi has been shown to reduce the lifespan of adult animals [15 , 16] . Likewise , animals deficient in Pasha/ DGCR8 , an RNA binding protein required for the processing of most miRNAs , are short lived [17] . Thus , the general loss of mature miRNAs or the AGOs needed for their function reduces lifespan . However , individual miRNAs have also been found to regulate nematode longevity . In some instances loss of specific miRNAs ( lin-4 , miR-71 , miR-238 , miR-246 or miR-228 ) has resulted in shortened lifespan , whereas in others ( miR-80 or miR-239a/b ) lifespan extension has been observed [18–23] . Presumably , misregulation of specific targets in the miRNA mutant backgrounds is responsible for the effects on lifespan . In the case of lin-4 mutants , up-regulation of the lin-14 target seems to underlie the reduced lifespan of this strain [18] . In general though , it is largely unknown how the changes in gene expression caused by loss of individual miRNAs or their AGO cofactors affect aging . Studies in C . elegans and other short-lived model animals have revealed that organismal lifespan is shaped by several , partially distinct , genetic pathways . Reduced insulin signaling , dietary restriction , diminished mitochondrial respiration , and germline removal are all examples of conditions that increase longevity in a conserved fashion [24] . In C . elegans , the lin-4 miRNA functions within the Insulin/ IGF-1 signaling ( IIS ) pathway [18] , miR-80 responds to dietary restriction [23] , and let-7 family miRNAs promote the longevity of animals lacking germ cells [25] . In the canonical C . elegans IIS pathway , insulin-like peptides bind and activate the Insulin/ IGF-1 receptor DAF-2 , which leads to a signaling cascade that ultimately phosphorylates the FOXO transcription factor DAF-16 and sequesters it from the nucleus [26] . In long-lived daf-2 mutants , phosphorylation-mediated inhibition of DAF-16 is relieved , allowing it to enter the nucleus and induce the expression of downstream targets that promote longevity . These up-regulated genes ( Class I ) are considered to be under the direct regulation of DAF-16 [27 , 28] , whereas another set of genes ( Class II ) , involved in growth and development , undergo down-regulation when DAF-16 is active [27 , 28] . Upon increased insulin signaling , the transcription factor PQM-1 localizes to the nucleus and induces the expression of Class II genes , while DAF-16 is restricted to the cytoplasm [28] . When insulin signaling is reduced , DAF-16 enters the nucleus and promotes the expression of Class I genes; at the same time , PQM-1 exits the nucleus , effectively preventing Class II gene transcription . Overall , shifts in the balance between Class I and Class II gene expression contribute to the lifespan phenotypes of mutants in the IIS pathway [28] . In this study , we discovered that the miRNA AGOs , ALG-1 and ALG-2 , have distinct expression patterns and activities in aging C . elegans . We show that during adulthood the expression of alg-1 is rapidly down-regulated , whereas that of alg-2 is sustained . Surprisingly , the maintenance of alg-2 does not simply provide a replacement for alg-1 activity . Instead , we found that the two AGOs play opposing roles during adulthood , with alg-1 promoting longevity and alg-2 suppressing it . We detected differential expression patterns for specific miRNAs in alg-1 and alg-2 mutants that were consistent with their opposite lifespan phenotypes . Although largely distinct sets of protein-coding genes were misregulated in each of the AGO mutants , they converged on the IIS longevity pathway . We observed that Class I daf-16 targets were enriched in the genes down-regulated in alg-1 or up-regulated in alg-2 mutants . Consistent with these expression patterns , the extended lifespan of daf-2 , which requires active daf-16 , was significantly reduced in alg-1 mutants . Moreover , we found that daf-16 and two Class I genes , cest-1 and asah-1 , were required for the enhanced longevity of alg-2 mutants . Altogether , our studies reveal opposing roles for two miRNA AGOs in the conserved IIS longevity pathway .
Previous studies have shown that the predominant miRNA Argonautes , ALG-1 and ALG-2 , are expressed constitutively in developing C . elegans , with the highest levels detected in embryos [5 , 8] . To analyze the expression of these AGOs in adult animals , we used genome editing methods [29] to tag the N-termini of the protein-coding sequences of the endogenous alg-1 and alg-2 genes with FLAG::GFP ( ALG-1 ) or FLAG::RFP ( ALG-2 ) moieties . To confirm that the tagged AGO proteins retained function , we subjected the strains to a sensitive phenotypic assay . The individual loss of alg-1 or alg-2 has no effect on embryonic viability . However , disruption of both genes results in nearly complete embryonic lethality [6 , 8 , 30] . While depletion of alg-2 by RNAi caused highly penetrant embryonic lethality in alg-1 ( gk214 ) loss-of-function mutants , the same RNAi treatment had no effect on embryo viability in the GFP::ALG-1 strain , demonstrating functionality of the edited gene ( S1 Fig ) . Likewise , alg-1 ( RNAi ) resulted in embryonic lethality in alg-2 ( ok304 ) mutants but not in the RFP::ALG-2 strain , confirming that the edited alg-2 gene retained function ( S1 Fig ) . The tagged genes produced the expected size AGO proteins , as detected with an anti-FLAG antibody ( Fig 1A and 1B ) . While ALG-2 levels remained relatively constant from the fourth larval stage ( L4 ) through day 11 of adulthood , ALG-1 levels decreased precipitously during adulthood ( Fig 1A and 1B ) . The rapid decline in ALG-1 expression as animals entered adulthood was also observed using antibodies against the untagged ALG-1 protein in wildtype , as well as in the sterile spe-9 ( hc88 ) strain ( see later for examples ) . Analysis of GFP::ALG-1 and RFP::ALG-2 in live animals revealed broad spatial expression patterns for these AGOs ( Fig 1C and 1D ) . In agreement with a previous study [8] , we observed that both proteins were expressed in most somatic cells but exhibited some tissue specificity in the head region . Pharyngeal cells predominantly expressed GFP::ALG-1 , while certain head neurons adjacent to the pharynx were enriched for RFP::ALG-2 ( Fig 1C–1E ) . Consistent with the Western blot results , there was a global decline in expression of GFP::ALG-1 but not RFP::ALG-2 as the animals aged ( Fig 1C–1E ) . We also analyzed the mRNA levels of alg-1 and alg-2 , using the sterile spe-9 ( hc88 ) background to avoid signal from progeny developing inside of adult animals . Similar to the pattern of ALG-1 protein expression , we observed strong down-regulation of alg-1 mRNA levels in adult compared to L4 stage animals ( Fig 1F ) , as previously reported [31] . Likewise , levels of alg-2 mRNA were unchanged or slightly elevated in adult versus L4 animals ( Fig 1F ) , mirroring the expression of ALG-2 protein . Altogether , these results indicate that alg-1 and alg-2 have distinct spatial and temporal expression patterns . The differential regulation of alg-1 and alg-2 expression at the onset of adulthood prompted us to investigate potential roles for these AGOs in aging . It was previously shown that depletion of alg-1 by RNAi treatment starting at the L4 stage leads to a shortened lifespan [15] . Consistent with this observation , we found that alg-1 ( gk214 ) loss-of-function mutants , which display mild developmental defects [10] , have an average lifespan that is significantly shorter than that of WT ( Fig 2A; S1 Table ) . Surprisingly , alg-2 ( ok304 ) loss-of-function mutants exhibited the opposite lifespan phenotype , living significantly longer than WT animals ( Fig 2A; S1 Table ) . Initially , these results seemed to contradict a previous report that RNAi of alg-2 shortens the lifespan of WT and long-lived daf-2 mutant animals [16] . In that study , RNAi targeted a conserved domain in the alg-2 coding sequence ( CDS ) , which shares a high degree of similarity with alg-1 ( Fig 2B ) . To specifically repress alg-2 alone , we created an RNAi construct for targeting the alg-2 3’UTR , which lacks extensive sequence homology with alg-1 . When WT animals were subjected to RNAi targeting either the alg-2 CDS or the 3’UTR , we observed opposite lifespan phenotypes ( Fig 2C; S1 Table ) . In agreement with the aforementioned study [16] , the original alg-2 CDS ( RNAi ) caused a significantly shortened lifespan . However , the extended lifespan of animals treated with alg-2 3’UTR ( RNAi ) was consistent with the phenotype of alg-2 ( ok304 ) genetic mutants . To further establish that lifespan extension was specifically associated with loss of alg-2 activity , we created a new alg-2 loss-of-function allele . The new alg-2 ( ap426 ) allele has an 8-nt deletion in the second exon ( Fig 2B ) , which leads to a frameshift mutation and brings a premature stop codon into frame . The inability of this strain to produce viable embryos when treated with alg-1 ( RNAi ) confirmed that alg-2 ( ap426 ) is a new loss-of-function allele ( S1 Fig ) . As observed for the alg-2 ( ok304 ) mutant , the lifespan of the alg-2 ( ap426 ) strain was significantly extended in comparison to WT animals ( Fig 2D; S1 Table ) . Although both alg-2 genetic mutant strains exhibit increased longevity , the reason for the difference in the degree of lifespan extension is unclear . In summary , our studies show that miRNA AGOs play opposing roles during aging in C . elegans and suggest that alg-1 positively regulates lifespan , whereas alg-2 negatively impacts it . Since loss of alg-1 reduces C . elegans lifespan and expression of this AGO was observed to be down-regulated with age , we considered the possibility that alg-2 mutants might express higher levels of ALG-1 and depend on this factor for their extended lifespan phenotype . Consistent with this idea , we found that the lifespan of alg-2 ( ok304 ) mutants was significantly shortened when alg-1 was depleted by RNAi starting at the L4 stage ( Fig 3A; S1 Table ) . The lifespan of the alg-2 ( ok304 ) animals subjected to alg-1 ( RNAi ) was even shorter than that of WT animals treated with alg-1 ( RNAi ) , indicating that loss of both miRNA AGOs during adulthood greatly reduces survival . Furthermore , we detected higher ALG-1 protein levels in alg-2 ( ok304 ) adults ( Fig 3B ) . The sterile spe-9 ( hc88 ) background was used for analyses of ALG-1 protein levels to restrict detection to adult tissues . Although ALG-1 protein expression still decreased in the alg-2 mutant background , the levels were about 2-fold higher at days 2 and 5 of adulthood compared to the ALG-1 levels in WT animals ( Fig 3B ) . The increased expression of ALG-1 in alg-2 ( ok304 ) mutants was also apparent in live animals , as detected by GFP::ALG-1 fluorescence ( Fig 3C ) . To test if elevated ALG-1 expression would be sufficient to induce longevity phenotypes , we created a new allele of alg-1 . Since ALG-1 targets its own 3’UTR via multiple miRNA binding sites ( Fig 3D ) [12 , 31 , 32] , we reasoned that replacement of the entire endogenous 3’UTR with one considered not to be a target of the miRNA complex might result in higher expression of ALG-1 . The gene Y45F10D . 4 was chosen because it appears to be stably expressed , is commonly used as a control gene in quantitative RT-PCR experiments , and its short 3’UTR lacks ALG-1 binding sites [12 , 33 , 34] . Replacement of the native alg-1 3’UTR with that of Y45F10D . 4 ( swap 3’UTR ) resulted in ~2-fold increase in ALG-1 protein levels ( Fig 3E ) , which was similar to the degree of up-regulation observed at days 2 and 5 of adulthood in alg-2 ( ok304 ) mutants ( Fig 3B ) . Also comparable to alg-2 mutants , ALG-1 protein levels expressed from the edited gene still decreased as the animals transitioned from L4 to adult stages . This is likely due to transcriptional repression of alg-1 , as a GFP-reporter driven by the alg-1 promoter is down-regulated in adult compared to L4 animals ( S2 Fig ) . Overall , these results indicate that 3’UTR-mediated regulation does not fully account for the decline in ALG-1 levels during adulthood . When we performed lifespan assays , we detected no significant difference between strains with the alg-1 gene affixed to its native 3’UTR or to the swapped 3’UTR ( Fig 3F; S1 Table ) , which produced ALG-1 protein at levels similar to that of alg-2 ( ok304 ) ( Fig 3B and 3E ) . It therefore seems unlikely that the dependence of alg-2 on alg-1 for increased lifespan ( see Fig 3A ) is simply through up-regulation of ALG-1 protein . Instead , it is possible that , while the loss of both miRNA AGOs is detrimental , ALG-1 and ALG-2 have some unique targets whose misregulation contributes to the opposite longevity phenotypes . Previous studies have implicated several individual miRNAs as regulators of C . elegans lifespan ( Fig 4A ) [18 , 20 , 23] . To test if the expression of these aging-associated miRNAs is altered in alg-1 and alg-2 mutants , we analyzed their levels in RNA samples collected from WT and each of the AGO mutants at day 5 of adulthood . Day 5 was chosen because by this point the animals are mostly post-reproductive but still viable . In this panel , only two miRNAs , lin-4 and miR-71 , were specifically down-regulated in alg-1 but not alg-2 mutants ( Fig 4A ) . Conversely , the levels of miR-239a/b were increased in alg-1 ( gk214 ) and decreased in alg-2 ( ok304 ) ( Fig 4A ) . These differential expression patterns in the AGO mutants are consistent with previously reported longevity phenotypes associated with these miRNAs; lin-4 or miR-71 mutants exhibit shortened lifespans , whereas miR-239a/b mutants display enhanced longevity [18 , 20] . We also asked if there was preferential binding to either AGO by the aging-associated , or any other miRNAs , in day 5 adults . Through co-immunoprecipitation assays , thirteen and eleven different miRNAs were found to be predominantly associated with ALG-1 or ALG-2 , respectively ( Fig 4B and S2 Table ) . Notably , lin-4 and miR-71 were among the miRNAs enriched for binding to ALG-1 compared to ALG-2 ( Fig 4B and S2 Table ) . This preference could underlie the reduced levels of lin-4 and miR-71 in alg-1 mutant animals ( Fig 4A ) , since AGO-association stabilizes mature miRNAs [35] . Based on the differences in miRNA expression and AGO-binding , we predicted that distinct sets of protein-coding genes would be misregulated in alg-1 and alg-2 mutants . Transcriptome profiling revealed extensive changes in gene expression in the alg-1 ( gk214 ) mutants compared to WT day 5 adults . We detected significant up-regulation of 3 , 184 and down-regulation of 5 , 742 genes in the alg-1 ( gk214 ) mutants ( S3 Table ) . In contrast , only 81 and 133 genes were up- or down-regulated , respectively , in alg-2 ( ok304 ) mutants compared to WT animals ( S3 Table ) . Notably , there was minimal overlap in genes up-regulated in both AGO mutants ( Fig 4C ) , and each set of genes was enriched for distinct Biological Process Gene Ontology ( GO ) terms ( Fig 4C; S4 Table ) . Two-thirds of the genes down-regulated in alg-2 ( ok304 ) mutants were also down in alg-1 ( gk214 ) animals . Despite this overlap , the unique down-regulated gene sets in each AGO mutant were also enriched for distinct GO terms ( Fig 4C; S4 Table ) . We next asked if the differential gene expression patterns might be associated with the altered miRNA levels in the alg-1 mutants; too few genes were changed in alg-2 ( ok304 ) to test for enrichment or depletion of miRNA target sites . Strikingly , genes up-regulated in alg-1 ( gk214 ) were enriched for 3’UTR sequences that could pair to the seed region , nucleotides 2–7 , of lin-4 and miR-71 ( Fig 4D ) . While the increased levels of miR-239a/b in alg-1 mutants were expected to result in stronger target repression , this signature was not observed in the alg-1 down-regulated gene set ( Fig 4D ) . When we considered only conserved miRNA targets sites predicted by the TargetScan algorithm [36 , 37] , over 50% of the lin-4 targets were up-regulated in alg-1 mutants ( Fig 4E ) . Additionally , almost twice as many conserved miR-71 targets were in the up- compared to down-regulated alg-1 ( gk214 ) genes ( Fig 4E ) . There are four genes up-regulated in alg-1 mutants that have conserved target sites for both lin-4 and miR-71 in their 3’UTRs . One of these targets , lin-14 , has previously been shown to contribute to the shortened lifespan of lin-4 mutant animals [18] . Taken together , the decreased expression of lin-4 and miR-71 in alg-1 mutants likely results in the up-regulation of lin-14 and other predicted targets of these miRNAs , which contributes to their shortened lifespan . Loss of lin-4 or miR-71 reduces lifespan and loss of miR-239a/b extends it , at least partially through the insulin signaling pathway [18 , 20] . Since these miRNAs were differentially expressed in the AGO mutants ( Fig 4A ) , we asked if the IIS pathway would also be affected by alg-1 or alg-2 deficiency . The nuclear residence of the FOXO transcription factor DAF-16 is an indicator of insulin signaling levels , with reduced signaling promoting nuclear accumulation , transcription of Class I DAF-16 targets and lifespan extension [28 , 38–40] . If the AGOs function upstream of DAF-16 , then the prediction is that nuclear residence of DAF-16 will be reduced in alg-1 and increased in alg-2 mutant backgrounds . Examination of strains expressing a DAF-16::GFP transgene that rescues the short lifespan of daf-16 ( mu86 ) mutants [41] revealed no obvious differences in the diffuse pattern of DAF-16 localization in the alg-2 ( ok304 ) background compared to WT ( Fig 5A; S3 Fig ) . When nuclear accumulation was detected in these strains , it was restricted to the most anterior intestinal cells . In contrast , nuclear accumulation of DAF-16::GFP in multiple intestinal cells of daf-2 ( e1370 ) mutants was readily detected ( Fig 5A; S3 Fig ) . Interestingly , the nuclear localization of DAF-16::GFP was significantly lower in alg-1 mutants than in WT animals ( Fig 5A; S3 Fig ) . These results suggest that loss of alg-1 , but not alg-2 , alters the nuclear residence of DAF-16 . To further explore the possibility that alg-1 and alg-2 differentially impact the IIS longevity pathway , we examined the expression of genes considered positive ( Class I ) and negative ( Class II ) targets of daf-16 regulation in each of the AGO mutants at day 5 of adulthood [27 , 28] . Consistent with reduced nuclear localization of DAF-16::GFP ( Fig 5A ) , there was substantial overlap between the most strongly down-regulated genes in alg-1 ( gk214 ) mutants and those positively regulated by daf-16 ( Fig 5B ) . We observed that 33% of the genes reduced by at least 4-fold in the alg-1 ( gk214 ) mutants belong to Class I ( Fig 5B ) . Some of these Class I down-regulated genes encode proteins with cytochrome P450 ( cyp-35B2 ) , oxidoreductase ( sodh-1 ) and glutathione-S-transferase ( ortholog of human GSTP1 ) activities , and RNAi depletion of these factors in WT animals shortens lifespan [27 , 42] . Unexpectedly , the set of highly down-regulated genes in alg-1 ( gk214 ) was also enriched for Class II genes ( Fig 5B ) . The alg-1 up-regulated genes were not enriched for either Class , although the total number of Class I genes in this category exceeds that in the down-regulated gene set ( Fig 5B ) . Thus , the relationship between the effect of alg-1 on DAF-16 nuclear localization and regulation of Class I and II genes is not straightforward . Although nuclear accumulation of DAF-16::GFP in intestinal cells was indistinguishable in alg-2 ( ok304 ) versus WT animals ( Fig 5A ) , we observed a striking signature of altered daf-16 output in the alg-2 mutants . We found that 35% of all the genes significantly up-regulated in alg-2 ( ok304 ) mutants compared to WT animals were Class I DAF-16 targets ( Fig 5B ) , including three genes ( lea-1 , asp-3 and cdr-6 ) previously implicated in C . elegans stress tolerance or lifespan control [27 , 43 , 44] . Additionally , of the genes down-regulated in alg-2 mutants , more than five times as many are considered Class II versus Class I genes ( Fig 5B ) . Thus , alg-2 regulates the expression , directly or indirectly , of many positive and negative targets of daf-16 activity . Since the gene expression profiles of alg-1 ( gk214 ) and alg-2 ( ok304 ) mutants indicated that the IIS pathway is perturbed in these mutants , we next asked if their altered lifespan phenotypes were dependent on key regulators of this pathway . We found that the reduced lifespan of alg-1 ( gk214 ) mutants was suppressed in the daf-2 ( e1370 ) mutant background ( Fig 5C; S1 Table ) . However , the mean lifespan of the alg-1 ( gk214 ) ; daf-2 ( e1370 ) double mutant was about 30% shorter than that of daf-2 ( e1370 ) alone . Although caution must be exerted when interpreting the combined effect of incomplete loss-of-function mutations , the results suggest that daf-2 mutants are partially dependent on alg-1 activity for their extended lifespan phenotype . When alg-1 ( gk214 ) was combined with daf-16 ( mu86 ) , the mean lifespan of the double mutants was slightly shorter than that of either single mutant ( Fig 5C; S1 Table ) , making it likely that the reduced lifespan of alg-1 ( gk214 ) mutants is not entirely through down-regulation of daf-16 activity . This is not surprising given the large fraction of genes misregulated in alg-1 ( gk214 ) mutants at day 5 of adulthood , and the previous reports that loss of lin-4 or miR-71 can impact multiple longevity pathways [18–20 , 22 , 31] . Interestingly , the long lifespans of alg-2 ( ok304 ) and daf-2 ( e1370 ) single mutants were additive in strains harboring both mutations ( Fig 5D; S1 Table ) . One interpretation of this result is that independent pathways contribute to the long lifespan of each mutant strain . However , the data are also consistent with the possibility that the loss of alg-2 further weakens daf-2 signaling , since the daf-2 ( e1370 ) allele is non-null . For example , it has been shown that the long lifespan of a hypomorphic daf-2 mutant strain can be further extended by daf-2 ( RNAi ) treatment [45] . Regardless of mechanism , the long lifespan of alg-2 ( ok304 ) mutants was completely suppressed by the daf-16 ( mu86 ) mutation ( Fig 5D; S1 Table ) . The nearly identical short lifespan curves of daf-16 and alg-2; daf-16 mutants indicate that the long lifespan of alg-2 ( ok304 ) animals is dependent on daf-16 . Overall , these results illustrate the disparate effects of two miRNA AGOs on the regulation of gene expression and lifespan through the IIS pathway during C . elegans aging . Since the genetic evidence indicates that daf-16 is required for the extended lifespan of alg-2 mutants , we asked if up-regulated Class I genes in alg-2 ( ok304 ) contribute to their longevity phenotype . We focused on asah-1 ( N-Acylsphingosine amidohydrolase 1; K11D2 . 2 ) because it was previously reported that RNAi of this gene partially reduced the extended lifespan of daf-2 mutants [27] and cest-1 ( carboxyl esterase domain containing 1; T02B5 . 1 ) because it is the highest ranking Class I gene ( 13 out of 1663 ) up-regulated in the alg-2 mutants [28] . We found that the extended lifespan of alg-2 ( ok304 ) was almost completely suppressed in animals subjected to RNAi of asah-1 or cest-1 starting at the L4 stage of development ( Fig 5E and 5F ) . Notably , RNAi of asah-1 or cest-1 , compared to vector control RNAi , had no significant effect on the lifespan of WT animals ( Fig 5E and 5F ) , indicating that this treatment did not generally reduce viability . These results suggest that increased expression of asah-1 , cest-1 and possibly other Class I targets in alg-2 mutants contributes to the extended lifespan of these animals . The IIS pathway also controls the ability of larval C . elegans to arrest development and enter a specialized stage called dauer [46] . Normally , entry into the dauer stage occurs in response to harsh environmental conditions . However , animals with mutations in certain daf ( dauer formation ) genes inappropriately become dauers under favorable conditions . For example , daf-28 ( sa191 ) mutants produce an aberrant version of the DAF-28 insulin-like peptide that reduces DAF-2 signaling and causes dauer formation during optimal culture conditions at 20°C [47 , 48] . Although alg-1 ( gk214 ) and alg-2 ( ok304 ) mutants did not form dauers at 20°C ( S4 Fig ) , we asked if loss of either of these AGOs would modify the dauer phenotype of daf-28 ( sa191 ) animals . In this sensitized background , dauer formation was significantly suppressed by alg-1 ( gk214 ) and enhanced by alg-2 ( ok304 ) mutations ( S4 Fig ) . Importantly , dauer formation in the alg-1;daf-28 and alg-2;daf-28 mutants was entirely dependent on daf-16 ( S4 Fig ) . These results further demonstrate a role for the miRNA AGOs in IIS and exemplify their contrasting activities during another life stage .
As the core effector protein of miRISC , Argonaute is expected to display a broad spatiotemporal expression pattern . Previous work has shown that the C . elegans miRNA AGOs exhibit largely overlapping expression domains in most embryonic and larval tissues , which is consistent with their redundant functions at these stages [5 , 8–10] . However , we observed a distinct pattern in adults where global ALG-1 levels plummeted as ALG-2 levels remained constant ( Fig 1 ) . Whereas the protein coding sequences of these AGO genes are ~75% identical , the regulatory sequences , including promoter and untranslated regions ( UTRs ) , are highly divergent . Additionally , modENCODE data show very different transcription factor binding profiles for alg-1 and alg-2 [49] , suggesting that these genes may be subject to distinct transcriptional control mechanisms . The down-regulation of alg-1 as animals enter adulthood appears to be mediated by both transcriptional and post-transcriptional mechanisms . The alg-1 3’UTR contains many predicted miRNA target sites and biochemical experiments have detected association of this 3’UTR with ALG-1 and specific miRNAs , including miR-71 , at the L4 stage ( Fig 3D ) [32] . Recently , Slack and colleagues confirmed that alg-1 is subject to regulation by miR-71 in adults; loss of this miRNA or its target sites in the alg-1 3’UTR resulted in increased ALG-1 levels [31] . Not surprisingly , then , exchange of the entire alg-1 3’UTR with one unlikely to be targeted by the miRNA complex resulted in higher levels of ALG-1 protein ( Fig 3E ) . This increase resembled the elevated levels of ALG-1 observed in alg-2 ( ok304 ) adults ( Fig 3B ) , raising the possibility that alg-2 directly or indirectly regulates the expression of alg-1 through its 3’UTR at this life stage . However , this pathway is only partially responsible for the down-regulation of ALG-1 in adult animals , since levels of ALG-1 still decreased in the absence of alg-2 or the native alg-1 3’UTR ( Fig 3B and 3E ) . A GFP reporter fused to only the promoter sequences of alg-1 also displayed marked down-regulation at the adult compared to larval stages , pointing to a layer of transcriptional control for limiting alg-1 expression in adults ( S2 Fig ) . While the alg-1 and alg-2 genes have maintained a very high degree of protein sequence identity , they apparently have evolved distinct regulatory elements that drive divergent expression patterns in C . elegans transitioning from the larval to adult stages . The previously described complementary roles of alg-1 and alg-2 during embryogenesis and larval development are consistent with the similar expression patterns of these highly homologous proteins at these stages [5 , 6 , 8–10] . The opposing effects of alg-1 and alg-2 on lifespan seem to act specifically at adulthood , since depletion of either gene starting at the L4 stage was sufficient to produce longevity phenotypes ( Figs 2C and 3A ) . Notably , RNAi targeting sequences in the alg-2 3’UTR that lacked homology with alg-1 was necessary for observing a lifespan extension phenotype similar to that exhibited by alg-2 loss-of-function genetic mutants ( Fig 2 ) . This illustrates that while RNAi can be useful for depleting the expression of related genes that might have redundant functions , it can also obscure potentially distinct phenotypes of individual homologs . Presently , it is unclear if the contrasting roles of alg-1 and alg-2 during aging are due to differences in expression or protein function . We found that alg-1 is strongly down-regulated in adult animals ( Fig 1 ) . Yet , genetic or RNAi-induced loss of alg-1 shortened lifespan ( Figs 2 and 3 ) , suggesting that the residual expression of ALG-1 in WT animals is important for longevity . However , increasing ALG-1 protein levels by ~2-fold did not produce a lifespan phenotype ( Fig 3E and 3F ) . Thus , normal aging depends on a minimal level of ALG-1 , but doubling its expression does not have an obvious effect on lifespan . Although the ALG-1 and ALG-2 proteins are predicted to be structurally very similar given their high degree of sequence identity [6 , 8 , 9] , a few functional differences have been reported . Non-overlapping sets of genes have been found to have synthetic lethal interactions with alg-1 or alg-2 mutant animals [9] . This study also reported that ectopically expressed ALG-1 and ALG-2 fractionate into distinct complexes , yet associate with the same populations of miRNAs [9] . However , other studies found that some miRNAs were enriched for association with ALG-1 or ALG-2 in different stages of larval development [5 , 8] , consistent with our observations in adult animals ( Fig 4B ) . Finally , through unique sequences in its N-terminal domain , ALG-1 , but not ALG-2 , binds the Receptor for Activated C-Kinase ( RACK1 ) [50] . This interaction was shown to contribute to the repressive function of miRISC in C . elegans [50] , although additional roles for RACK1 in miRNA biogenesis and stability have been proposed [51–53] . Some of these reported differences in alg-1 and alg-2 might be related to the contrasting roles of these genes during aging . However , since alg-1 and alg-2 functionally overlap during embryonic and larval development , there would need to be an adult-specific mechanism to convert these AGOs into proteins with opposing activities . For example , protein modifications or the expression of different binding partners restricted to adulthood could enable the regulation of distinct targets by ALG-1 and ALG-2 . Our identification of miRNAs and protein-coding genes differentially regulated by alg-1 and alg-2 at day 5 of adulthood further illustrates the divergent activities of these AGOs during aging and points to a common pathway that could explain the opposite effects of these genes on lifespan . Regulation of lifespan through the IIS pathway is almost entirely dependent on the conserved transcription factor DAF-16 . When IIS is low , activated and nuclear localized DAF-16 promotes the transcription of hundreds of genes , which ultimately results in animals with longer and healthier lifespans [24] . Although some individual DAF-16 targets have been shown to regulate longevity , in general the cumulative up- or down-regulation of many genes controlled by daf-16 is likely responsible for the impressive lifespan phenotypes exhibited by mutants with reduced insulin signaling [54] . Considering the central role of daf-16 in longevity control by IIS , the misregulation of many DAF-16 targets in alg-1 and alg-2 mutants suggests that these AGOs regulate lifespan , at least in part , via this pathway . Consistent with the reduced nuclear residence of DAF-16 detected in alg-1 mutants ( Fig 5A ) , about one-third of the most strongly down-regulated genes in these animals are classified as high confidence direct DAF-16 targets ( Class I ) ( Fig 5B ) [28] . Since individual depletion by RNAi of some of the genes on this list , such as cyp-35B2 and sodh-1 , results in reduced longevity [27] , it is likely that decreased expression of these and many other DAF-16 targets in alg-1 mutants contributes to their shortened lifespan . Since we also found that alg-1; daf-16 double mutants have slightly shorter lifespans than either mutant alone ( Fig 5C ) , the loss of alg-1 likely impacts other mediators of longevity . A good candidate is the heat-shock factor , hsf-1 , which we found to be down-regulated in the alg-1 mutant , and expression of its target hsp-12 . 6 was three-fold lower than that detected in WT animals at day 5 of adulthood ( S3 Table ) . The reduction of hsf-1 or hsp-12 . 6 levels by RNAi has been shown to decrease lifespan [55 , 56] , and the overexpression of hsf-1 can extend lifespan [56] , at least in part by supporting cytoskeletal integrity [57] . Thus , alg-1 activity may affect the output of two central transcription factors in the C . elegans aging program . Additionally , given the examples of individual miRNAs influencing aging through mechanisms other than IIS [19 , 23] , it is likely that alg-1 and alg-2 function in multiple longevity pathways . Consistent with an extended lifespan phenotype , 35% of the genes up-regulated in alg-2 mutants are Class I DAF-16 targets ( Fig 5B ) . Since RNAi depletion of two of the genes on this list , asp-3 and cdr-6 , was previously reported to decrease the lifespan of WT animals [27 , 44] , it is possible that even a modest increase in a combination of these and other daf-16 targets could extend lifespan . We found that the Class I targets , asah-1 and cest-1 , are up-regulated in alg-2 ( ok304 ) mutants and are required for the extended lifespan of these animals ( Fig 5E and 5F ) . While these genes are predicted to encode broadly conserved enzymatic proteins , little is yet known about their functions in C . elegans . CEST-1 belongs to a large family of carboxylesterases , which generally catalyze the hydrolysis of carboxylic ester substrates [58] . In mammals , some carboxylesterases function in detoxification pathways , which could be relevant for a role in longevity [59] . Previously , RNAi depletion of asah-1 was shown to partially reduce the extended lifespan of daf-2 mutants , further implicating it as an important player in lifespan determination through the IIS pathway [27] . ASAH-1 is homologous to human N-Acylsphingosine amidohydrolase 1 ( ASAH , also known as acid ceramidase ) , a lipid hydrolase that converts ceramide into sphingosine and fatty acids in lysosomes [60] . In humans , loss-of-function mutations in ASAH lead to Farber’s disease , a rare inherited metabolic disorder [60] . Additionally , altered expression of ASAH has been observed in some cancers , Alzheimer’s disease , and type II diabetes , which are all diseases associated with aging [61] . Our finding that cest-1 and asah-1 contribute to the extended lifespan of alg-2 mutants suggests that these predicted enzymes have longevity roles in adult animals . The distinct set of miRNAs we found to be bound and regulated by ALG-1 and ALG-2 also reflects the divergent longevity roles of these AGOs in adult animals . Our data are consistent with a model where lin-4 and miR-71 , in association with ALG-1 , regulate IIS by repressing lin-14 and other factors in this pathway , such as daf-2 , which has a conserved miR-71 site directly bound by this miRNA at the L4 stage [32 , 36 , 37] . Although we did not detect up-regulation at the mRNA level for daf-2 or any other core genes in the IIS pathway in day 5 alg-1 ( gk214 ) adults ( S3 Table ) , the reduced nuclear localization of DAF-16 , decreased expression of Class I genes and genetic interactions with daf-2 imply a role for ALG-1 in restricting insulin signaling . The up-regulation of miR-239a/b in alg-1 ( gk214 ) may also contribute to the shortened lifespan of these animals , since deletion of this miRNA locus results in increased longevity [20] . Likewise , reduced levels of miR-239a/b in alg-2 ( ok304 ) may factor into their extended lifespan . While previous genetic studies have shown that daf-16 is required for the extended lifespan of miR-239a/b mutants , direct targets of this miRNA that could be responsible for the longevity phenotype are yet to be identified [20] . In conclusion , our transcriptome profiling of day 5 adults revealed distinct gene expression patterns in alg-1 and alg-2 mutant animals . Although the differential expression of specific aging-associated miRNAs and daf-16 target genes is consistent with the opposite lifespan phenotypes , there may be other relevant changes not detectable by RNA expression analyses . Differences in protein levels or modifications may also contribute to lifespan regulation by the AGOs . Although the full set of molecular changes induced by loss of alg-1 or alg-2 is yet to be revealed , our gene expression analyses point to changes in IIS output and our genetic experiments confirm opposing roles for these miRNA AGOs in the regulation of longevity and dauer formation through the IIS pathway . Overall , this study establishes an important role for AGO-mediated gene regulation in C . elegans aging and reveals divergent activities for highly related proteins during specific life stages .
C . elegans strains were cultured under standard conditions and synchronized by hypochlorite treatment [62] . Lifespan analyses were conducted at 20°C in the absence of FUdR , as previously described [63] . Embryos were plated on NGM plates containing OP50 and the first day after the L4 stage was regarded as adult day 0 ( AD 0 ) . Worms were picked on fresh food every other day until reproduction ceased , and scored for viability every 2 to 3 days . Animals that died by bagging , bursting , or crawling off the plates were censored . JMP IN 8 . 0 software was used for statistical analysis and P-values were calculated using the log-rank ( Mantel-Cox ) method . Statistics for all assays are shown in S1 Table . RNAi experiments were conducted by feeding the animals dsRNA-expressing bacteria , as previously described [64] . See Supplemental Materials for a list of strains and details on generation of new strains ( S1 Text ) . Western blotting was performed as previously described [12 , 65] using mouse monoclonal antibodies against tubulin ( Sigma ) , FLAG ( Sigma ) , or a custom rabbit polyclonal antibody against ALG-1 [12] . Quantitative RT-PCR analyses of mRNA ( SYBR Green ) and miRNA ( Taqman ) levels were performed according to manufacturer’s instructions with the StepOnePlus and QuantStudio 3 Real-Time PCR Systems ( Applied Biosystems ) . Levels were normalized to Y45F10D . 4 for mRNAs and U18 snoRNA for miRNAs . Synchronized WT , alg-1 ( gk214 ) and alg-2 ( ok304 ) animals cultured at 20°C were collected at adult day 5 after removing eggs and progeny larvae . Adult C . elegans were separated from eggs and progeny on a daily basis by washing plates with M9 into conical tubes and allowing the adults to settle by gravity for a few minutes on a bench top . The supernatant containing larvae and eggs was then removed , and this process was repeated 3–7 times until eggs and larvae were no longer visible . Three independent RNA samples of each strain were prepared for RNA sequencing with the TruSeq Stranded Total RNA Library Prep Kit ( Illumina ) according to the Low Sample Protocol . 50-bp single-end indexed RNA sequencing libraries were prepared from 1 μg of RNA of each sample and used for sequencing on an Illumina HiSeq platform . Subsequent mapping of sequencing reads to the C . elegans genome ( ce10 ) was performed using RNA-STAR [66] . Total read counts for each gene were then quantified using HTSeq [67] . These read counts were then input into DESeq [68] to determine log2-fold change and differential expression between the mutant and WT strains . Synchronized FLAG::GFP::ALG-1 ( PQ530 ) and FLAG::RFP::ALG-2 ( PQ582 ) animals cultured at 20°C were collected at adult day 5 after removing eggs and progeny larvae . Samples were collected and sonicated in 100 mM NaCl , 25 mM HEPES , 250 μM EDTA , 2 mM DTT , 0 . 1% ( w/v ) NP-40 , 0 . 1% SDS , 1X Complete Mini Protease Inhibitor ( Sigma Aldrich ) , and 25 U/mL rRNasin ( N251A ) . Cell debris was removed by centrifugation and lysates were incubated with anti-FLAG ( F1804 ) bound to Protein G Dynabeads ( 10004D ) for 1 hour at 4°C . Following co-immunoprecipitation , beads were washed as previously described [65] . RNA was isolated to use for small RNA library preparation . Two independent RNA samples of each strain were prepared for RNA sequencing with the TruSeq small RNA Library Prep Kit ( Illumina ) . RNA sequencing libraries were prepared from 1 μg of RNA of each sample and sequenced on an Illumina HiSeq 4000 . Adapter sequences were removed , and using miRDeep2 small RNA sequences were mapped to the C . elegans genome ( WS261 ) and quantified based on miRNA annotations from miRBase release 21 [69 , 70] . To identify miRNAs that were enriched with ALG-1 or ALG-2 , we first calculated the normalized reads ( reads per million in the library ) . MiRNAs with more than 1 . 5-fold the number of normalized reads in one Argonaute co-IP versus the other , from independent replicates , were considered enriched . MiRNAs with less than 1000 reads across the libraries were not included in the enrichment analyses . The results are summarized in S2 Table . Synchronized HT1889 ( daf-16 ( mgDf50 ) ; unc-119 ( ed3 ) ; lpIs14 ) , HT1883 ( daf-16 ( mgDf50 ) ; daf-2 ( e1370 ) unc-119 ( ed3 ) ; lpIs14 ) , PQ585 ( alg-1 ( gk214 ) ; daf-16 ( mgDf50 ) ; unc-119 ( ed3 ) ; lpIs14 ) and PQ586 ( alg-2 ( ok304 ) ; daf-16 ( mgDf50 ) ; unc-119 ( ed3 ) ; lpIs14 ) animals cultured at 20°C were grown to L4 before being anesthetized with 1 mg/ml of Levamisole and imaged within a 20 min period at 40X magnification . Images of individual worms ( n ≥ 11 for each strain ) were presented to four blinded scorers who rated the degree of intestinal nuclear localization based on a provided key .
|
Tiny non-coding RNAs called microRNAs ( miRNAs ) are broadly conserved across animal species and have established roles in regulating development , metabolism and behavior . In humans , aberrant expression or function of specific miRNAs has been associated with a wide variety of diseases , underscoring the critical role of these molecules in organismal viability . Argonaute ( AGO ) proteins are essential co-factors for miRNAs to regulate the expression of target genes . In C . elegans nematodes , two highly related AGOs ( ALG-1 and ALG-2; Argonaute-Like Genes ) play largely overlapping roles in the miRNA pathway during development . Here we report that the activities of these two AGOs diverge in aging animals , as loss of ALG-1 shortens lifespan , while loss of ALG-2 extends it . These opposite longevity phenotypes are associated with differential regulation of specific miRNAs and protein-coding genes that act in the Insulin/ IGF-1 Signaling ( IIS ) pathway . Furthermore , we present genetic evidence that alg-1 and alg-2 operate within this pathway to impact aging . In sum , our findings reveal that two related AGOs function antagonistically within the conserved insulin signaling pathway that regulates longevity .
|
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2018
|
Opposing roles of microRNA Argonautes during Caenorhabditis elegans aging
|
Although acute lung injury ( ALI ) is a common complication of severe malaria , little is known about the underlying molecular basis of lung dysfunction . Animal models have provided powerful insights into the pathogenesis of severe malaria syndromes such as cerebral malaria ( CM ) ; however , no model of malaria-induced lung injury has been definitively established . This study used bronchoalveolar lavage ( BAL ) , histopathology and gene expression analysis to examine the development of ALI in mice infected with Plasmodium berghei ANKA ( PbA ) . BAL fluid of PbA-infected C57BL/6 mice revealed a significant increase in IgM and total protein prior to the development of CM , indicating disruption of the alveolar–capillary membrane barrier—the physiological hallmark of ALI . In contrast to sepsis-induced ALI , BAL fluid cell counts remained constant with no infiltration of neutrophils . Histopathology showed septal inflammation without cellular transmigration into the alveolar spaces . Microarray analysis of lung tissue from PbA-infected mice identified a significant up-regulation of expressed genes associated with the gene ontology categories of defense and immune response . Severity of malaria-induced ALI varied in a panel of inbred mouse strains , and development of ALI correlated with peripheral parasite burden but not CM susceptibility . Cd36−/− mice , which have decreased parasite lung sequestration , were relatively protected from ALI . In summary , parasite burden and CD36-mediated sequestration in the lung are primary determinants of ALI in experimental murine malaria . Furthermore , differential susceptibility of mouse strains to malaria-induced ALI and CM suggests that distinct genetic determinants may regulate susceptibility to these two important causes of malaria-associated morbidity and mortality .
Pulmonary complications have been reported in malaria caused by infection with Plasmodium falciparum , Plasmodium vivax and Plasmodium ovale [1] , [2] . Pulmonary edema , with features of acute lung injury ( ALI ) and the acute respiratory distress syndrome ( ARDS ) , occurs in approximately 20% of severe malaria patients [3] , often in association with cerebral malaria ( CM ) , acute renal failure and high parasitemia [3] , [4] , [5] , [6] , [7] , [8] . ARDS in adults is an important predictor of mortality in malaria , and is associated with a greater than 70% case fatality rate [3] . Although ALI and ARDS are rare in the pediatric population [9] , respiratory distress accompanying severe metabolic acidosis is common in children and predicts poor outcome [10] . While pulmonary involvement is a recognized complication of malaria infection , little is currently known about its pathogenesis [11] . A spectrum of severity exists with respiratory involvement in malaria infection . Cough is a common presentation in uncomplicated malaria due to P . falciparum , P . vivax and P . ovale infections [1] , [2] . Reduced gas transfer and impaired alveolar-capillary membrane function have been correlated with severe disease [2] . Patients can rapidly progress to respiratory failure , either in association with severe disease or shortly after treatment [9] . Studies suggest that this post-treatment lung injury may be associated with prolonged alveolar-capillary inflammation [1] , [12] . Lung ultrastructural studies from individuals with fatal P . falciparum-induced lung injury indicate endothelial cell cytoplasmic swelling and edema in the lung interstitium , with monocytes and parasitized erythrocytes ( PE ) adherent within the capillaries [13] , [14] . Additionally , septal or interstitial edema occurs in regions of PE adherence [15] . Lung endothelium likely plays an important role in malaria lung injury , in response to PE adhesion , parasite-induced inflammation ( for example , by malaria GPI ) and leukocyte adhesion . In vitro , P . falciparum PEs have been shown to promote oxidative stress [16] , and activate caspases leading to apoptosis in human primary lung endothelial cells [16] . Both P . falciparum PEs and GPI induce up-regulation of endothelial inflammatory markers , including intracellular cell adhesion molecule-1 ( ICAM-1; NP_000192 ) and interleukin-6 ( IL-6; NP_000591 ) [17] , [18] , [19] . An increase in cell adhesion molecules may further enhance leukocyte and PE adhesion , contributing to localized endothelial damage . Although the murine malaria model of P . berghei ANKA ( PbA ) has primarily been used to study CM [20] , pulmonary pathology has also been described in some previously published studies that employed this model of severe malaria [20] , [21] , [22] , [23] , [24] , [25] , [26] . Lung histopathology of PbA-infected mice has been reported to show endothelial adhesion of pigment-containing monocytes and neutrophils , and a “septal pneumonitis” [24] . Immunoglobulins , complement 3 , complement 4 and parasite antigens in the lung interstitium and alveoli were detected by immunohistochemistry one to three hours prior to death in CM-susceptible mice [22] . Studies have also demonstrated increased pulmonary vascular permeability in PbA infection [20] , [23] , [25] , which may be influenced by CD11a-positive neutrophil and monocyte sequestration [23] . Additionally , PbA parasites sequester in lung tissue in a CD36-dependent manner [27] , and the lung may be a preferential site of PbA biosynthesis and/or proliferation [28] . Collectively , these data suggest that significant lung pathology occurs in PbA infection and contributes to malaria-associated morbidity and mortality . Since relatively little is known about lung injury in malarial disease , a mouse model could lead to pathophysiological insights with potential relevance to human disease . We hypothesized that ALI would occur in the PbA mouse model and would be mediated by parasite sequestration in the lung . Similar to severe malarial syndromes in human disease , we show that ALI develops in PbA infection , and is influenced by both parasite burden and local sequestration .
In order to characterize PbA infection as a model of malaria lung injury , bronchoalveolar lavage ( BAL ) was performed on C57Bl/6 mice 1–2 days prior to the development of CM symptoms and death and the BAL fluid ( BALF ) was examined for protein content . Increased levels of total protein , and more specifically IgM , in the BALF are indicative of alveolar-capillary membrane barrier disruption and are hallmarks of ALI [29] , [30] , [31] . Levels of total protein were significantly elevated at day 7 post-infection ( Figure 1A , one-way ANOVA with Bonferoni's multiple comparison correction , Day 7 vs . Day 0: p<0 . 01 ) . Furthermore , IgM was increased at both Day 6 and Day 7 compared to baseline ( Figure 1B , p<0 . 001 ) . These data showed that a disruption of the alveolar-capillary membrane barrier and ALI occur as a result of PbA infection . To examine pulmonary inflammation induced during PbA infection , a panel of cytokines and chemokines were examined in plasma , lung tissue homogenate and BALF . PbA failed to induce proinflammatory cytokine production in the alveoli of infected mice , as measured in the BALF ( Figure 2 ) . In contrast , proinflammatory cytokine production was increased both locally ( in lung tissue ) and peripherally ( in plasma ) during the course of PbA infection . Tumor necrosis factor ( TNF; NP_038721 , Fig . 2A ) , macrophage inflammatory protein-2 ( MIP-2; NP_033166 , Fig . 2B ) , interleukin-10 ( IL-10; NP_034678 , Fig . 2C ) , IL-6 ( NP_112445 , Fig . 2D ) , keratinocyte-derived cytokine ( KC or murine IL-8; NP_032202 , Fig . 2E ) and interferon-γ ( IFN-γ; NP_032363 , Fig . 2F ) levels were all significantly increased in plasma at day 6 compared to baseline ( Kruskal-Wallis test with Dunn's multiple comparison test; p<0 . 05: TNF , IFN-γ; p<0 . 01: IL-10 , KC; p<0 . 001: MIP-2 , IL-6 ) . Lung homogenate levels of IL-6 and KC were significantly increased at Day 6 ( p<0 . 01 and p<0 . 05 , respectively ) and tissue levels of MIP-2 and IFN-γ were significantly elevated at both days 6 and 7 compared to day 0 ( D6 vs . D0: p<0 . 01; D7 vs . D0: p<0 . 05 ) . Overall , both systemic and local tissue inflammation occur as a result of PbA infection , however , cytokine and chemokines are produced in the plasma and lung interstitium rather than in the alveolar spaces . To further characterize PbA-induced ALI , both alveolar cell counts and lung histology were examined for pathological changes . No cellular infiltration into the alveoli occurred over the course of PbA infection , but rather BALF cell counts were decreased at day 7 compared to day 6 ( Figure 3A , Kruskal-Wallis test with Dunn's multiple comparison test: p<0 . 05 ) . Histopathological analysis revealed interstitial pulmonary inflammation at day 6 post-infection , with increased numbers of inflammatory cells in the alveolar septae ( Figure 3B , upper panel ) . However , consistent with the BALF cell count data , the alveolar spaces were free of inflammatory cells . By day 7 post-infection the lungs remained inflamed , with no alveolar cellular infiltration . However , lung architecture was lost in some areas and interstitial hemorrhages were seen in individual animals ( Figure 3B , upper panel ) . Additionally , microscopic analysis of BAL cells showed few changes in cell type ( Figure 3B , lower panel ) . Interestingly , erythrocytes , and rarely PEs , could be found in the alveoli of PbA-infected mice . To summarize , these data indicate that ALI occurs in the PbA model of severe malaria , characterized by pulmonary edema and interstitial inflammation initiated via an “inside-out” mechanism that fails to induce transmigration of inflammatory cells to the alveolar spaces . To examine mechanisms underlying the pathophysiology of PbA-induced ALI , expression microarray analysis of mouse lung tissue was performed . Three hundred and eighty differentially expressed genes were identified in the lungs of PbA infected C57BL/6 mice at day 6 , compared to uninfected controls , at a false discovery rate of 1% using Exploratory Differential Gene Expression ( EDGE ) analysis [32] . Functional analysis of the differentially up-regulated genes revealed significant enrichment in the gene ontology ( GO ) categories of host defense and immune response , response to stress , and ribosomal activity , whereas down-regulated genes were enriched in metabolism pathways and ATPase activity ( Table 1 ) . Because defense and immune response GO categories were highly enriched in the PbA model of ALI , differentially expressed genes within this functional category were further explored using network analysis . In addition to the differentially expressed genes identified using the EDGE analysis , cytokines significantly increased in lung homogenate ( MIP2 , IL-6 , KC , and IFN-γ; Figure 2 ) were included in the analysis , for a total of 27 gene products . The resultant gene-gene interaction network ( or interactome ) , created from previously identified gene product interactions , consisted of 21 genes ( Figure 4 ) . Many of these genes were up-regulated cytokines and chemokines . Additionally , the structure of this interactome was dependent upon three hubs , or nodes of high interconnectivity: namely , IFN-γ ( NM_008337 ) , TNF ( NM_013693 ) and IL-6 ( NM_031168 ) . To investigate whether genetic determinants regulating susceptibility to CM in the PbA model correlate with ALI , the responses of two pairs of CM-resistant and CM-susceptible in-bred mouse strains infected with PbA were compared . At day 6 post-infection , despite their divergent outcome , C57BL/6 ( CM-susceptible ) and BALB/c ( CM-resistant mice ) have equivalently elevated BALF IgM concentrations ( Figure 5A ) and parasitemia ( Figure 5B ) , although this study is limited by its small sample size ( N = 6 ) . However , CM-hyper-susceptible 129SV/J mice developed significantly higher BALF IgM levels than CM-resistant AKRJ mice ( Figure 5C , Mann-Whitney test: p = 0 . 0012 ) . This coincided with the 129SV/J developing significantly higher parasitemia than the AKRJ mice ( Figure 5D , Mann-Whitney U test p = 0 . 0022 ) . Therefore , in this model , genetic resistance to CM for example in BALB/c mice does not necessarily confer resistance to ALI . Since no association was found between the development of CM and ALI , the effect of parasite burden on the development of ALI was examined . Mice with higher parasitemias were more likely to show correspondingly high levels of IgM and total protein in the BALF ( Table 2 ) . This observation led to the hypothesis that the extent of lung injury may be influenced by peripheral parasitemia , which likely reflects local parasite burden in the lung . Because diverse genetic factors influence infection in the different in-bred strains , this question was addressed using escalating parasite inocula in order to induce a spectrum of parasitemia in ALI-susceptible C57BL/6 . Consistent with this hypothesis , mice that received a higher inoculum of PbA had increased concentrations of BALF IgM at day 6 post-infection ( Figure 6A; Kruskal-Wallis test with Dunn's multiple comparison test , 1×106 vs . 1×105 PE: p<0 . 05 ) corresponding with elevated circulating parasitemias ( Figure 6B; Kruskal-Wallis test with Dunn's multiple comparison test , 1×106 vs . 1×105 PE: p<0 . 05 ) . Parasitemia was positively correlated with BALF IgM log concentration ( Figure 6C; r2 = 0 . 73 ) . These findings suggest that ALI is influenced by parasite burden and that increasing levels of circulating infected erythrocytes result in increasing levels of ALI . A high peripheral parasite burden may not only stimulate proinflammatory processes but also increase the number of parasites available for sequestration in vital organs , including the lung . P . berghei parasites preferentially bind in the lungs of infected mice in a CD36-dependent manner ( CD36; NP_031669 ) [27] . Given their reduced lung parasite burden , we hypothesized that Cd36−/− ( Cd36; NM_007643 ) mice would be expected to be protected from ALI caused by P . berghei infection . Additionally , CD36 is a receptor for thrombospondin-1 ( Thbs-1; NP_035710 ) , which was identified in the defense response interactome ( Figure 4 ) . Thbs-1 ( NM_011580 ) was up-regulated in the lungs of mice at day 6 post infection , compared to uninfected animals . This observation was confirmed using quantitative real-time RT-PCR analysis of an independent PbA infection ( mean normalized copy number±standard deviation: Day 6 1193 . 3±199 . 2 , Day 0 545 . 6±11 . 9 , 2-tailed t-test with welch's correction p<0 . 03 ) . Similar to previously published work , PbA-infected Cd36−/− mice were not protected from death secondary to CM ( data not shown ) . However , Cd36−/− mice developed significantly less ALI during PbA infection compared to their wild type counterparts , as measured by BALF IgM concentration ( Figure 7A , 2-tailed t-test , p<0 . 0001 ) , despite having an equivalent parasitemia ( Figure 7B ) . In summary , ALI induced by experimental murine malaria was CD36-dependent .
This study provides a detailed analysis of ALI that occurs in experimental murine malaria , which may provide an informative tool to study ALI and ARDS associated with human malaria infection . Mice infected with PbA develop septal inflammation and disruption of the alveolar-capillary membrane barrier , leading to a proteinaceous non-cardiogenic pulmonary edema , dependent on parasite burden and CD36 . Interestingly , susceptibility to ALI does not necessarily correlate with CM development in genetically in-bred mouse strains . While all CM-susceptible strains tested developed ALI , there was differential susceptibility of CM-resistant strains to ALI , for example BALB/c develop ALI whereas others did not ( AKR/J ) . These data suggest that ALI occurs via a mechanism distinct from the pathogenesis of CM in the PbA model . ALI in experimental murine PbA malaria may , at least partially , represent a clinically relevant model of ALI seen in individuals with severe human malaria , since both share similar histopathology features , parasite sequestration in the lung capillaries and alveolar-capillary membrane barrier disruption leading to pulmonary edema . Lung histology from both PbA and P . falciparum infections shows an edematous interstitium with leukocyte infiltration [13] . PEs and leukocytes sequester in the pulmonary microvasculature in human malaria infections , as demonstrated by both ultrastructural studies [13] , [14] , [15] and a reduced pulmonary capillary vascular component volume [2] , [12] . Additionally , hemorrhage is a classic feature of non-malarial human ALI/ARDS [29] , [33] and histopathological reports on malaria-induced ALI indicate that focal alveolar hemorrhages occur in humans [34] , [35] , similar to those observed in the PbA model . Progressive alveolar-capillary dysfunction has been reported in individuals with malaria immediately following appropriate antimicrobial therapy [2] , [12] . This post-treatment lung damage has been attributed to the host inflammatory response , and it appears that pulmonary complications in human malaria result from a combination of PE sequestration , and the corresponding host inflammatory response to parasite burden . As in human malaria , ALI in the PbA model is partially mediated by parasite burden and sequestration ( Figures 5 & 6 ) , but also likely occurs as a response to parasite-driven inflammatory responses . Indeed , work using an anti-P . falciparum GPI vaccine in the PbA model showed markedly reduced pulmonary edema in immunized versus sham-immunized animals [26] . As with any animal model of disease , there are limitations to the correlations that can be drawn to human disease , especially since limited studies have examined ALI in human malaria infection . It is not possible to comment on how the BAL findings from this model relate to human malaria , because these studies have not been performed and obtaining BAL samples from severe malaria patients , especially in a field setting , may present challenges . Additionally , while certain in-bred mouse strains show differential susceptibility to PbA-induced ALI and CM–BALB/c mice develop ALI but are resistant to CM–this may not necessarily reflect what occurs in human malaria . Although case reports and other studies have demonstrated that respiratory involvement and ALI can occur in non-cerebral malaria [1] , [2] , [4] , [12] , other studies have shown that lung parasite burden parallels that in the brain [34] and that ALI commonly occurs in conjunction with CM [3] , [8] , [34] , [35] . This study examined transcriptional profiles from the lungs of PbA infected mice . The defense/immune response interactome ( Figure 4 ) is structured around three hubs of high interconnectivity–TNF , IFN-γ and IL-6 , all of which play significant roles in host pro-inflammatory responses to malaria [36] , [37] , [38] . The functional stability of genetic networks is highly dependent on nodes of high interactivity [39] , indicating they may play a pivotal role in the transcriptional response to PbA-induced ALI and thus may be promising therapeutic targets . TNF has been well-established as a key mediator of ALI [40] , [41] , [42] , which is also likely the case in PbA , since TNF levels were significantly increased in the lung tissue of infected mice . However , since IFN-γ , TNF and IL-6 are involved in multiple biological processes in PbA infection , it may be possible to more effectively modulate these key hubs by targeting a molecule or pathway shared by them , such as THBS-1 ( Figure 4 ) . THBS-1 was of particular interest among the interactome because it binds and signals primarily via CD36 ( NP_000063 ) [43] , [44] . THBS-1 ( NP_003237 ) has also been identified as an cellular receptor for PE adhesion [45] , and additionally , soluble THBS-1 binds to PEs , augmenting adhesion to endothelial cells via CD36 under physiological flow conditions [46] , [47] . The upregulation of thbs-1 expression could play an important role in PbA-induced ALI by increasing CD36-mediated cytoadherance in the lung , especially since CD36 is a primary receptor for PEs in the pulmonary vascular endothelium [27] . Although CD36 deficiency does not affect CM development and survival in the PbA model [27] , our work demonstrates that Cd36−/− mice develop significantly less ALI compared to wild-type controls . This finding suggests that malaria-induced ALI occurs via a CD36-dependent pathogenic mechanism . These findings may appear to conflict with previous work by our group , which has argued that CD36 may be beneficial in the immune response to malaria via its role as a receptor for non-opsonic phagocytosis of PEs by macrophages [48] , [49] , [50] , [51] . Recent studies , using chimeric mice expressing CD36 only on hematopoietic cells , showed that CD36 on myeloid cells ( i . e . the hematopoeitic compartment ) but not on endothelial cells ( the non-hematopoeitic compartment ) conferred protection to CM in the PbA model [52] . However , there is conflicting evidence that PEs that bind CD36 are associated with severe disease . Parasites isolated from severe malaria patients in Thailand were shown to preferentially bind ICAM-1 on lung endothelium in vitro compared to those from uncomplicated patients [53] . Similarly among children with severe malaria in Africa , parasite binding to CD36 was inversely related to disease severity [54] , but another study found that CD36 binding was equivalent between parasitized erythrocytes derived from CM patients or community controls [55] . However none of these studies specifically examined parasite isolates from patients displaying symptoms of ALI . Additionally , polymorphisms in CD36 , and CD36 deficiency , exist as natural variants in malaria endemic regions , including Asia [56] and Africa [57] . CD36 polymorphisms have been associated with both increased [58] and decreased susceptibility to CM [59] . Moreover , a specific non-sense mutation in CD36 was shown to be significantly associated with protection from respiratory distress in African children [60] . These studies examined different polymorphisms , which may reflect differential protein function or expression in different cell types . If CD36 mutations do confer susceptibility to cerebral malaria [53] , these mutations may be maintained in human populations through selection pressure of another prevalent infection other than malaria , or perhaps even by resistance to malaria-associated ALI . Additional studies are required to clarify the association between CD36 polymorphisms and severe malaria including ALI . Taken together , the available data suggest a dual role for CD36 in malaria infection . Specifically , as a pattern recognition receptor on myeloid cell lineages , CD36 may contribute to innate immune response and parasite clearance but at high parasite density , endothelial cell CD36 may also play a role , at least in the mouse model , in the development of tissue injury at sites such as the lung .
Animal use protocols were reviewed and approved by the Faculty of Medicine Advisory Committee on Animal Services at the University of Toronto and all experiments were conducted according to the animal ethics guidelines of the University of Toronto . C57Bl/6 and BALB/c mice were obtained from Charles River Laboratories ( Senneville QC ) , and 129SV/J and AKR/J were purchased from Jackson Laboratories ( Bar Harbor ME ) . CD36−/− mice ( on a C57Bl/6 background , a gift from Maria Febbraio ( New York NY ) ) were bred and maintained at the University of Toronto animal facility . Mice were 8–12 weeks of age and groups were matched by sex . Each experiment was performed twice , with 6–10 mice per group , as outlined in individual figure legends . Cryopreserved PbA ( MR4 , Vannassas MA ) was thawed and passaged through naïve C57Bl/6 donor mice until parasitemia in the passage animals reached approximately 10% . On day 0 , experimental mice were infected by intraperitoneal injection with freshly isolated PbA . Male mice were inoculated with 5×105 PE and females with 1×106 PE , inocula that reproducibly show 100% mortality in C57BL/6 mice . Parasitemia was monitored daily after Day 3 using thin blood smears stained with modified Giemsa ( Protocol Hema 3 Stain Set; Sigma , Oakville ON ) . At Day 6 or 7 , infected mice and uninfected controls were euthanized using isofluorane and BALF of both lungs was obtained by instillation and aspiration of three 0 . 5 ml aliquots of Dubecco's Phosphate Buffered Saline ( PBS; Gibco/Invitrogen , Burlington ON ) [33] . The BALF was spun at 800×g at 4°C for 5 min , and the supernatant was removed and stored at −80°C for further protein analysis . The cell pellet was resuspended in 1 ml ice-cold PBS . Total cell numbers were determined using a hemocytometer and differential cell counts were determined by cytocentrifugation and modified Giemsa staining . BALF concentrations of MIP-2 , mouse keratinocyte-derived cytokine ( KC or IL-8 ) , IL-1α ( NP_034684 ) , IL-6 , IL-10 , TNF-α , ( that measures TNF and LT-α ) and IFN-γ were determined by multiplex immunoassay ( Luminex 100 ) using cytokine-specific bead kits according to the manufacturer's protocols ( R&D Systems , Minneapolis MN ) . TNF-α levels in lung homogenates were confirmed using a standard sandwich ELISA according to the manufacturer's protocol ( eBioscience , San Diego CA ) . BALF total protein concentration was measured using a BCA protein assay ( Sigma ) , and BALF IgM concentration was determined by ELISA ( Bethyl Laboratories , Montgomery TX ) . Lungs were excised , weighed and homogenized in 2ml PBS/0 . 5g lung tissue for 30 sec . using a ULTRA -TURRAX® disperser ( IKA , Wilmington NC ) . Homogenates were stored at −80°C for further cytokine analysis . Cytokine concentrations were measured as described above . Lungs were fixed for histology at 20cm H2O with 4% paraformaldehyde buffered in PBS . After fixation , the lungs were embedded in paraffin , cut into 4-µm sections , and stained with hematoxylin and eosin ( H&E ) . Lungs were excised immediately following euthanasia , snap-frozen in liquid nitrogen and stored at −80°C until use . Total RNA was extracted using Trizol reagent ( Invitrogen ) according to the manufacturer's instructions , and mRNA was purified using an Oligo-dT cellulose column ( NEB , Mississauga , ON ) as described previously [61] . cDNA with incorporated 5- ( 3-aminoallyl ) -2′deoxyuridine-5′-triphosphate ( AAdUTP; Sigma , Oakville ON ) was reverse-transcribed from 1–2 µg mRNA . Purified cDNA was coupled with N-hydroxysuccinimide esters of Cy3 or Cy5 ( GE Lifesciences , Baie d'Urfe QC ) . Cy3 and Cy5-labeled cDNA pairs and Agilent control spots were added to a final volume of 0 . 5ml hybridization buffer ( 1 M NaCl , 0 . 5% sodium sarcosine , 50 mM methyl ethane sulfonate ( MES ) , pH 6 . 5 , 33% formamide and 40 µg salmon sperm DNA ( Invitrogen ) ) . Hybridizations were performed in Agilent hybridization ( Agilent , Palo Alto CA ) chambers at 42°C with rotation for 18–24 hours . Slides were washed in 6×SSPE , 0 . 005% sarcosine , followed by 0 . 06×SSPE , allowed to dry and scanned with a 4000A microarray scanner ( Axon Instruments , Union City CA ) . TIFF images were quantified with GenePix ( Axon Instruments ) . Variance stabilizing normalization [62] and loess smoothing were applied in Bioconductor [63] and the data were transformed to log2 scale . Each array was hybridized with cDNA transcribed from an RNA pool of 5 C57BL/6 mice per timepoint ( Day 0 and 6 ) and technical replicates ( dye-swap ) experiments were performed for both time points . The PbA ALI dataset ( GSE9497 ) and mouse/PbA microarray platform ( GPL4220 ) were deposited in the GEO database ( www . ncbi . nlm . nih . gov/projects/geo/ ) in accordance with MIAME guidelines . Probe mapping was performed as previously described [28] and a total of 9724 unique mouse genes , annotated using the Entrez Gene database , were included in the analysis . Since RNA was pooled from whole lung homogenates and replication was limited to dye-switching experiments , a statistical framework developed for the analysis of single cDNA microarray experiments–Exploratory Differential Gene Expression ( EDGE ) –was utilized [32] . This program was implemented in the R software environment ( www . r-project . org ) to determine statistical significance in each microarray experiment . The problem of multiple hypothesis testing was addressed using false discovery analysis based on Q-values [64] . A gene was deemed significantly differentially expressed if its Q-value was ≤0 . 01 in at least one of the dye-switching experiments and the direction of change ( i . e . , up or down-regulation relative to uninfected controls ) was consistent in both experiments . Functional annotation of the genes was obtained from Gene Ontology Consortium's database [65] , based on their respective molecular function , biological process , or cellular component . Enriched functional categories within differentially expressed genes were determined using the Expression Analysis Systematic Explorer ( EASE ) algorithm [66] . A variant of the one-tailed Fisher exact probability test based on the hypergeometric distribution was used to calculate P-values . Generated P-values indicated whether a given GO process is over-represented compared to what would be expected by random sampling . Multiple hypothesis testing was addressed by performing permutation analysis ( n = 1000 ) and selecting a false discovery rate cutoff of ≤0 . 001 . A gene-gene interaction network was created by mining gene product interactions from the following databases: Ingenuity [67] , Adriadne [68] , and Human Protein Reference Database [69] . These knowledge bases have been manually and computationally compiled through extensive literature searches . Molecular relationships consisting of direct physical , transcriptional , and enzymatic interactions among gene products serve as the basis for creating genetic networks from gene or protein expression data . cDNA was synthesized from 0 . 5 µg of mRNA using Superscript II reverse transcriptase with Oligo ( dT ) 12-18 primers ( Invitrogen ) . Serial dilutions of mouse genomic DNA were used as standards [70] . gDNA standards or cDNA were added to the qPCR reaction containing 1× Power Sybr Green Master Mix ( Applied Biosystems ) and 0 . 5 µM primers in a final volume of 10 µl . qPCR was performed using the ABI Prism® 7900HT Sequence Detection System ( Applied Biosystems ) . Copy numbers were normalized to 3 mouse housekeeping genes–Hprt , Sdha , and Ywhaz [71] . Forward ( fwd ) and reverse ( rvs ) primer sequences are as follows: Thbs1-fwd: TGT GGA CTT CAG CGG TAC CTT CTT; Thbs1-rvs: GGA CTG GGT GAC TTG TTT CCA CAT; Hprt-fwd: GGAGTCCTGTTGATGTTGCCAGTA , Hprt-rvs: GGGACGCAGCAACTGACATTTCTA; Sdha-fwd: TCACGTCTACCTGCAGTTGCATCA , Sdha-rvs: TGACATCCACACCAGCGAAGATCA; Ywhaz-fwd: AGCAGGCAGAGCGATATGATGACA , Ywhaz-rvs: TCCCTGCTCAGTGACAGACTTCAT .
|
Acute lung injury ( ALI ) and acute respiratory distress syndrome ( ARDS ) can occur in adult malaria infections with a case fatality rate of 70%–100% . ALI and ARDS are characterized by protein-rich fluid in the lungs , with reduced gas exchange , and in malaria , often accompany high parasite levels and severe or cerebral disease . In this work we have examined lung physiology , pathology and genomics in mouse malaria—Plasmodium berghei ANKA—to show that mice develop malaria-induced ALI . Infected mice have proteinaceous fluid in their lungs , have a migration of inflammatory cells from the blood into the lung walls , and express immune response–related genes . We also found that severity of ALI depended on high parasite levels , both overall and specifically in the lung tissue , but was not consistent with whether the mice developed cerebral malaria . ALI due to Plasmodium berghei ANKA infection models prominent characteristics of human malaria-associated ALI , and we have better defined this model of malaria ALI so it may be used to further explore disease mechanisms and eventual treatment .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"infectious",
"diseases",
"genetics",
"and",
"genomics/gene",
"expression",
"microbiology/innate",
"immunity",
"pathology/histopathology",
"immunology/genetics",
"of",
"the",
"immune",
"system",
"microbiology/parasitology"
] |
2008
|
Parasite Burden and CD36-Mediated Sequestration Are Determinants of Acute Lung Injury in an Experimental Malaria Model
|
Regulatory T cells ( Treg ) diminish immune responses to microbial infection , which may contribute to preventing inflammation-related local tissue damage and autoimmunity but may also contribute to chronicity of infection . Nasopharyngeal carriage of pneumococcus is common in young children and can persist for long periods but it is unknown whether the presence of Treg in the nasopharynx contributes to this persistence . We have investigated the numbers and activities of Foxp3+Treg in adenoidal tissues and their association with pneumococcal carriage in children . Expression of Treg cell-related markers including Foxp3 , CD25 , CD39 , CD127 and CLTA4 were analysed by flow-cytometry in adenoidal mononuclear cells ( MNC ) and PBMC from children . Unfractionated MNC or Treg-depleted MNC were stimulated with a pneumococcal whole cell antigen ( WCA ) and T cell proliferation measured . Cytokine production by MNC was measured using a cytometric bead array . Higher numbers of CD25highFoxp3high Treg expressing higher CD39 and CTLA4 were found in adenoidal MNC than in PBMC . Children with pneumococcus positive nasopharyngeal cultures had higher proportions of Treg and expressed higher levels of CD39 and CTLA-4 than those who were culture negative ( − ) . WCA induced adenoidal Treg proliferation which produce IL10 but not IL17 , and CD4 T cell proliferation in Treg-depleted MNC was greater in pneumococcal culture positive than negative children . Significant numbers of Treg with an effector/memory phenotype which possess a potent inhibitory effect , exist in adenoidal tissue . The association of pneumococcal carriage with an increased frequency of adenoidal Treg suggests that Treg in nasal-associated lymphoid tissue ( NALT ) may contribute to the persistence of pneumococcus in children . Further studies to determine what component and mechanisms are involved in the promotion of Treg in NALT may lead to novel therapeutic or vaccination strategy against upper respiratory infection .
Regulatory T cells ( Treg ) play a key role in the control of various aspects of the immune response including maintenance of immune tolerance and prevention of autoimmunity [1] . Progress has been made in recent years in the characterization of regulatory cells , including Foxp3+ Treg . Until recently , the expression of the transcription factor Foxp3+ on CD4 T cells was believed to indicate thymus-derived natural Treg . However , there is mounting evidence that Foxp3+ Treg also develop extrathymically , i . e . adaptive Treg [2] . Studies in vitro show conversion of naïve T CD4+CD25− T cells into Foxp3+ Treg through TCR ligation in the presence of TGF-β [3] . Up until now , intracellular expression of Foxp3 is still considered the most specific single marker of Treg , although a combination of phenotypic expression of CD4+CD25+CD127low has also been established as a useful marker for natural Treg [4] , [5] . Some phenotypic markers such as CD39 and CTLA-4 have been found to be associated with the activity of Treg [6]–[9] . In particular , CD39 expression on Treg has been found to be correlated with the inhibitory potency of Treg , and in humans it is considered to be a marker of effector/memory Tregs [10] . Recently , a growing number of studies suggest that Treg play an important role in the control of immunity to microbial pathogens including bacteria , viruses and parasites [11] . The repertoire of antigen specificities of Treg is considered to be broad , recognizing both self and non-self antigens . It has been suggested that Treg can be activated and expanded against a wide range of different pathogens in vivo . Such pathogen-specific Treg may prevent the infection-induced immunopathology but may prolong pathogen persistence by inhibiting protective immunity favoring chronicity of infections [12] . For example , Treg may contribute to the immunopathogenesis of chronic infections including Human Immunodeficiency virus ( HIV ) , Hepatitis C virus ( HCV ) and Tuberculosis ( TB ) [13]–[15] . Mucosal Treg have been shown to be important in the modulation of gastrointestinal tract inflammation such as that related to Helicobacter pylori and HIV infection [12] , [16] . However , data on mucosal Treg in the respiratory tract infections in humans are limited . Streptococcus pneumoniae ( pneumococcus ) is a leading cause of bacterial pneumonia , meningitis and septicemia , and kills millions of people each year worldwide , especially children . Nasopharyngeal colonization with pneumococcus is common in young children , as are mucosal pneumococcal infections such as otitis media and pneumonia . By the age of three years , most children develop natural T- and B-cell specific immune responses to several pneumococcal protein antigens [17] , [18] presumably due to previous colonization . These responses may protect against pneumococcal carriage either by preventing acquisition or hastening clearance or both and are induced in “nasal-associated lymphoid tissue” ( NALT ) [19] , [20] . Nevertheless , pneumococcal nasopharyngeal carriage may be prolonged and may recur throughout life . Therefore we hypothesized that significant Treg activity in the nasopharynx may contribute to the persistence of pneumococcus and perhaps , recurrent infection in some cases , in children in the face of demonstrable mucosal specific immunity . Establishment of chronic intracellular infections such as HIV and tuberculosis is associated with attenuated cell-mediated immunity [21] , [22] . Pneumococcus is classically considered to be an extracellular bacterium against which antibody responses play a primary role in protection . However , recent studies in mice suggest that CD4+T cell-mediated immunity to pneumococcal protein antigens may play a major role in either preventing or reducing the duration of pneumococcal mucosal colonization [23]–[25] . Our own results also suggest that naturally developed CD4 T cell-mediated immunity to pneumolysin , an intracellular pneumococcal antigen released on autolysis , may be protective against pneumococcal carriage in children [18] . No previous data are available on the role of Treg in the regulation of CD4 T cell immunity to pneumococcus or other upper respiratory tract-colonising bacteria in humans . Understanding the regulation of naturally-acquired mucosal immunity should help inform the design of novel vaccination strategies against pneumococcal colonization and/or infection . In this study , we investigated both the association between numbers and activities of Treg in adenoids and nasopharyngeal carriage of pneumococcus in children , and the effects of Treg on CD4+ T cell responses induced by pneumococcus in vitro .
Adenoidal tissues and peripheral blood samples were obtained from children ( aged 3–6 years ) undergoing adenoidectomy . Patients who received antibiotics or systemic steroids within 3 weeks of surgery or who had any known immunodeficiency were excluded from the study . A nasopharyngeal ( NP ) swab was taken on the day that the operation was performed which was stored and cultured for pneumococcus as described previously [18] . The study was approved by the local Research Ethics Committees ( Liverpool Paediatric Research Ethics Committee and South Bristol local research ethics committee ) and written informed consent was obtained from parents or carers in all cases . Adenoidal mononuclear cells ( MNC ) and peripheral blood mononuclear cells ( PBMC ) were isolated by Ficoll gradient centrifugation ( GE Healthcare ) . Depletion of CD25+ cells was performed using MACS magnetic microbeads separation ( Miltenyi ) . To ensure purity , CD25+ cell-depleted cells were passed through a second column and purity was confirmed by CD4/CD25/CD127 and Foxp3 staining ( both <1% positive in CD4 T cells by flow-cytometry ) . Adenoidal MNC , Treg-depleted MNC or PBMC were cultured in RPMI medium ( containing penicillin , streptomycin and glutamine ) with or without the addition of an ethanol-killed unencapsulated pneumococcal whole cell antigen ( WCA ) at 106 or 107 colony-forming unit ( CFU ) equivalents [26] for up to 7 days . The WCA was derived from strain Rx1AL- , a capsule- and autolysin-negative mutant described previously [26] . Briefly , the organism was grown to mid-log phase in Todd-Hewitt Broth supplemented with yeast extract , killed by the addition of 70% ethanol , after which the cell pellet was harvested and resuspended . A pneumolysin-negative WCA was made in the same fashion , using an Rx1AL- strain in which the pneumolysin gene was replaced by the Janus cassette , as previously described [27] . In some experiment , WCA was treated with proteinase K ( 200 ug/ml ) for 1 hour at 37°C followed by heating ( 98°C , 30 min ) before cell stimulation . In some experiments , Treg were purified using magnetic microbeads ( MACS , Miltenyi ) following manufacturer's instructions . Briefly , CD4+ T cells were purified from adenoidal MNC using negative selection followed by positive selection of CD25+ cells . To ensure CD25high T cell separation , the amount of anti-CD25 antibody-labelled microbead was titrated , and the optimal quantity was used . Also , to ensure purity , cells were passed through magnetic columns twice for each separation . Purity ( >96% ) of isolated Treg was confirmed by flow-cytometry following Foxp3 staining . Multi-color flow-cytometry was performed to analyze the phenotypic expressions of different cell subsets . Cells were stained with fluorescence-labeled mouse anti-human antibodies to CD4 , CD25 and CD127 , CD39 , CD69 , CD45RO following standard procedures and analyzed on a FACSCalibur ( BD Bioscience ) . Intracellular expressions of Foxp3 and CTLA-4 ( CD152 ) were analysed by flow-cytometry following cell permeabilization ( eBioscience ) . Carboxyfluorescein diacetate 5 , 6 succinimidyl ester ( CFSE ) ( Molecular Probes ) was used to label adenoidal MNC or PBMC before cell culture , allowing for tracking of cell division after stimulation as described previously [18] , [28] . Percentage of proliferative T cell subpopulations including Foxp3+ subsets was analyzed by CFSE and T cell marker staining followed by flow-cytometry . Following cell culture and stimulation by antigens , cell culture supernatants were collected and analysed for production of IL2 , IL4 , IL5 , IL10 , IFNγ and TNFα using a cytometric bead array ( BD Bioscience ) , and for IL17 using ELISA ( R&D Systems ) following manufacturers' instructions . Intracellular cytokine staining was performed in some experiments to determine the cellular sources of cytokine production after stimulation by WCA as described previously [29] . Briefly , adenoidal MNC were co-cultured with WCA for 6 hours and together with brefeldin A ( eBioscience ) in the last 4 hours . Cells were stained with fluorescence-labeled anti-human CD4 , followed by fixation , permeabilization and staining with fluorescence-labeled Foxp3 , anti-IL10 or anti-IL17 ( BD Biosience ) , and were then analyzed by flow cytometry . Two-group comparisons were analyzed using Student's t test , and multiple group comparisons by ANOVA . Correlation was analysed by Pearson's correlation . Analysis was performed using SPSS software ( SPSS version 16 , SPSS Inc ) .
The numbers of Treg ( as percentage of CD4 T cells ) in both PBMC and adenoidal MNC were counted by staining for intracellular Foxp3 and/or CD4 , CD25 and CD127 . The use of CD4+CD25+ CD127low as a phenotype for Treg correlated well with intracellular Foxp3 expression , both measured by flow-cytometry , in both PBMC and adenoidal MNC ( r = 0 . 91 and 0 . 90 respectively , n = 12 , p<0 . 01 ) . The proportion of Foxp3+Treg in CD4+ T cells was higher in adenoidal MNC than PBMC ( Table 1 ) and the percentages of adenoidal Treg expressing CD45RO or CD69 were also higher , in both cases , than in PBMC ( both p<0 . 01 , Table 1 ) . Similarly , levels of CD39 and intracellular CTLA-4 expression were higher in adenoidal than in PBMC Treg ( Fig . 1A–C ) . Higher levels of CD25 expression were observed in adenoidal Treg than in PBMC when paired samples from each individual were analyzed ( data not shown , p<0 . 01 ) . Co-staining for CD25 and Foxp3 showed significant numbers of Treg with a CD25highFoxp3high phenotype in adenoidal MNC which were lacking in PBMC ( Fig . 2A+B , region 3 ( R3 ) ) . This phenotype of Treg exhibited higher levels of expression of both CD39 and CTLA-4 than CD25intermediateFoxp3intermediate cells ( Fig . 2C ) . In comparison with R3 , R4 region ( CD25intermediateFoxp3low ) which represents activated CD4+ T cells , showed higher CTLA-4 but lower CD39 levels of expression ( Fig . 2C ) . Children who had positive nasopharyngeal cultures for pneumococcus ( + ) had higher proportions of Treg ( Foxp3+ and/or CD4/CD25/CD127low ) among CD4+T cells in adenoidal MNC than those who were culture negative ( − ) ( Fig . 3A , p<0 . 05 ) but no such difference in Treg numbers was seen in PBMC ( Fig . 3A , p>0 . 05 ) . The adenoidal Treg from culture-positive children also expressed higher levels of CD39 and intracellular CTLA-4 , again with no such differences seen in PBMC ( Fig . 3B and C ) . Pneumococcal WCA stimulation of adenoidal MNC induces a dose-dependent increase in the numbers of Foxp3+ Treg compared to unstimulated control cells ( Fig . 4A , p<0 . 01 ) . Pre-treatment of pneumococcal WCA with proteinase K followed by heating significantly reduced this effect ( Fig . 4A ) , suggesting that WCA-induced increase in Treg is protein-dependent . The mean % increase in the Treg ( of CD4 T cells ) after WCA stimulation is significantly higher in adenoidal MNC from pneumococcal culture+ children than from culture− children ( Fig . 4B , p<0 . 01 ) . A small increase was also observed in PBMC after stimulation with WCA ( data not shown ) . Measurement of CD4+T cell proliferation using CFSE confirmed that stimulation with WCA induces both proliferation of Foxp3+ Treg and Foxp3− effector CD4+T cells in adenoidal MNC ( Fig . 4C ) . To assess inhibition of T cell proliferation by adenoidal Treg , CD25+ cell-depleted adenoidal MNC were analyzed for CD4+ T cell proliferation following stimulation with pneumococcal WCA . WCA induced significantly higher CD4+ T cell proliferation in CD25+ cell-depleted MNC in those children who were pneumococcal culture positive than in those who were culture negative ( Fig . 5a ) . The WCA-induced CD4+ T cell proliferation in CD25+cell-depleted MNC was suppressed when purified Treg ( CD4+CD25+ ) were added back to the CD25+ cell-depleted MNC ( Fig . 5B , p<0 . 01 ) . Depletion of Treg from adenoidal MNC resulted in a significant decrease in IL10 and IL5 but an increase in IL17 , IFNγ and TNFα concentrations in the cell culture supernatant after WCA stimulation ( data not shown ) . The increase in concentrations of IL17 , IFNγ and TNFα in Treg-depleted adenoidal MNC following WCA stimulation was inhibited when purified Treg were reintroduced , which also restored the IL10 and IL5 production ( Fig . 5C ) . Intracellular cytokine staining shows that Foxp3+ Treg in adenoidal CD4+ T cells secrete IL10 but not IL17 following stimulation by WCA ( Fig . 6 ) .
Recent studies have suggested that human Treg are functionally and phenotypically diverse . Foxp3+ Treg can be divided into naïve and effector/memory phenotypes according to the expression of CD45RA or RO , CD69 and CD25 [30] . Naïve Treg are characterized by their expression of CD45RA and low levels of Foxp3 , and effector/memory Treg by expression of CD45RO and Foxp3high [30] , [31] . Although data in humans are lacking , animal studies suggest that CD45RA+Foxp3low Treg are thymus-derived natural Treg [30] , [31] which is supported by the finding that almost all Foxp3+ CD4 T cells found in human cord blood are CD45RA+Foxp3low T cells [32] , [33] . In this study , we found that the majority of Treg in PBMC in children express CD45RA ( i . e . not expressing CD45RO ) , low levels of Foxp3 , and do not express CD69 ( Table 1 ) . Thus these Treg are likely to be thymus-derived naïve Treg . In contrast , over 50% Treg in adenoidal tissues express CD45RO and CD69 , and among them , a significant proportion expressing Foxp3highCD25high . Together with the high levels of CTLA-4 and CD39 expression ( Fig . 1 ) , these Foxp3high CD25highTreg are likely to be of the effector/memory phenotype with potent suppressive properties [30] , [34] . CD4+ T cells with the highest expression of CD25 were found to have the strongest suppressive activity , and thus CD25high was used as a marker of Treg [34] , However , in humans , levels of CD25 expression tend to show a continuous distribution and there is no consensus as to where the boundary lies between CD25high and CD25low to intermediate expression . In this study , with a combination of staining of Foxp3 , CD4 and CD25 , we demonstrate that Foxp3+ cells can be divided into two populations , Foxp3highCD25high and Foxp3intermediateCD25intermediate ( Fig . 1A , region 3 and 2 respectively ) . Significant numbers of the Foxp3+ Treg in adenoids are of the former phenotype and express high levels of CD39 , CTLA-4 and CD69 . These results suggest that in human NALT there is a pool of effector/memory phenotype of Treg with potent suppressive function . These CD69+ Foxp3highCD25high effector Treg differ phenotypically from the activated ( non-Treg ) CD4+ T cells which express intermediate to high levels of CD25 but low levels of Foxp3 and marked levels of CTLA-4 ( Fig . 2A and C , region 4 ) . We demonstrate here that the proportion of Foxp3+ Treg , especially those of effector/memory phenotype , in adenoidal tissues is significantly higher than in peripheral blood . High numbers of Treg in NALT tissues could be induced by local colonization with microbes or antigens , as there is mounting evidence suggesting that the induction of Foxp3+ Treg occurs in peripheral tissues in humans . HIV , TB and Leishmania infections promote pathogen-specific Treg in the local inflammatory site including lymphoid tissues [35]–[38] . It has been postulated that the presence of microbial pathogens in peripheral tissues could lead to the accumulation of activated Treg ( both natural and inducible ) that help maintain host immune homeostasis [2] , [35] , [39] . In this study , we show that the proportion of adenoidal CD4+T cells that are Treg in adenoids , but not in peripheral blood , was significantly higher in children who were culture positive for pneumococcus in their nasopharynges than in those who were culture negative . This is the first report showing evidence of such an association for any extracellular pathogen in the human nasopharynx . This suggests that pneumococcal colonization in the nasopharynx may contribute to the induction and/or promotion of adaptive Treg in adenoids , and that these Treg may contribute to the delayed clearance or persistence of pneumococcal carriage in children . We also show that in vitro stimulation with a pneumococcal whole cell antigen ( WCA ) can induce an increase in the numbers of Treg in adenoidal MNC , and the increase is significantly higher in those children who are culture positive for pneumococcus . This would be consistent with the hypothesis that local colonization with pneumococcus promotes antigen-specific Treg in vivo in local lymphoid tissues adjacent to the site of colonization , which proliferate upon pneumococcal WCA stimulation . To determine whether these Treg in adenoidal tissues are functional and induce antigen-specific inhibition of T cell responses , we compared the WCA-induced effector CD4 T cell proliferation in the presence or absence of Treg . We show that depletion of adenoidal Treg leads to marked increase in WCA-induced CD4+ T cell proliferation and proinflammatory cytokines including IL17 , TNFα and IFNγ and replacement of the Treg abolished such effects . We also show that the increase in CD4+ T cell proliferation was significantly higher in children who were culture positive for pneumococcus than those who were culture negative . These results are consistent with the hypothesis that the adenoidal Treg are potent inhibitors and have antigen-specific inhibitory effects on CD4 T cell responses . Recent data in mice suggest that Th17 cells which secrete IL17 may play a critical role in protection against nasopharyngeal carriage of pneumococcus through promoting neutrophil-mediated phagocytic killing [40] . It is now well recognized that Treg and Th17 are two T cell subsets with opposing actions and interplay in the regulation of inflammation and autoimmunity [41] . This is supported by our results here that adenoidal Treg secrete the inhibitory cytokine IL10 but not IL17 ( Fig . 6 ) . The results in this study suggest a potent inhibitory effect on Th17 cells by adenoidal Treg which would be consistent with a role of Treg in the persistence of pneumococcal carriage in children . It is unclear what component of pneumococcus may contribute to the promotion of Treg in adenoids . Proteinase treatment of WCA reduced the inhibitory effect on WCA-induced CD4+ T cell proliferation , suggesting that pneumococcal protein ( s ) may contribute to the accumulation of adenoidal Treg . No difference was shown in the increased frequency of Treg induced by the wild-type WCA and an isogenic pneumolysin-negative WCA ( data not shown ) , which suggests pneumolysin may not contribute significantly in this respect . It has been reported previously that Treg numbers at the mucosal site , tonsil and lymph node , were highly increased in untreated patients with HIV infection , whereas in contrast , the Treg numbers in peripheral blood of these patients were not increased compared to healthy controls [12] , [35] , [42] . Taken together , these results support the hypothesis that chronic infection or persistent antigen promotes the expansion and activation of antigen-specific Treg in the local tissues [43] . In conclusion , significant numbers of Treg exist in adenoids of children with an effector/memory phenotype which possess potent inhibitory effect on CD4 T cell proliferation . The association of pneumococcal carriage in the nasopharynx with an increased frequency of Treg in adenoids suggests that local colonization with pneumococcus promotes pathogen-specific Treg of the effector/memory phenotype which may contribute to the delayed clearance or persistence of pneumococcus in children . Further studies to determine which pneumococcal components and what mechanisms are involved in the promotion of antigen-specific Treg in the nasopharynx may lead to novel therapeutic or vaccination strategies against upper respiratory colonization and/or infection .
|
Streptococcus pneumoniae ( pneumococcus ) is a bacterium that causes pneumonia , meningitis and blood poisoning . Colonization with pneumococcus is common in young children , which may be why they are prone to some common infections such as otitis media ( ear infection ) and pneumonia . As children age , most develop natural immunity to pneumococcus due to previous colonization . This immunity helps to prevent new infection and/or clear carriage of pneumococcus . However , persistence of carriage occurs in some children . The mechanisms for this are not clear . A good understanding of this phenomenon would help us to develop better ways to prevent pnemococcal infection . We have found that the immune tissues called adenoids ( at the back of nose ) in children contain some immune cells called “regulatory cells” that inhibit the naturally developed immunity to pnemococcus . While the presence and action of these cells is important to prevent self-tissue damage during infection ( due to excessive immune response ) , they contribute to the persistence of pneumococcal carriage . We show evidence that these cells may develop from the action of some component of pneumococcus . Further studies are underway to determine what component and how it promotes these cells , which may lead to better vaccines to prevent pnemococcus and other similar infections .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"medicine"
] |
2011
|
Characterisation of Regulatory T Cells in Nasal Associated Lymphoid Tissue in Children: Relationships with Pneumococcal Colonization
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The high-resolution crystal structure of the leucine transporter ( LeuT ) is frequently used as a template for homology models of the dopamine transporter ( DAT ) . Although similar in structure , DAT differs considerably from LeuT in a number of ways: ( i ) when compared to LeuT , DAT has very long intracellular amino and carboxyl termini; ( ii ) LeuT and DAT share a rather low overall sequence identity ( 22% ) and ( iii ) the extracellular loop 2 ( EL2 ) of DAT is substantially longer than that of LeuT . Extracellular zinc binds to DAT and restricts the transporter‚s movement through the conformational cycle , thereby resulting in a decrease in substrate uptake . Residue H293 in EL2 praticipates in zinc binding and must be modelled correctly to allow for a full understanding of its effects . We exploited the high-affinity zinc binding site endogenously present in DAT to create a model of the complete transmemberane domain of DAT . The zinc binding site provided a DAT-specific molecular ruler for calibration of the model . Our DAT model places EL2 at the transporter lipid interface in the vicinity of the zinc binding site . Based on the model , D206 was predicted to represent a fourth co-ordinating residue , in addition to the three previously described zinc binding residues H193 , H375 and E396 . This prediction was confirmed by mutagenesis: substitution of D206 by lysine and cysteine affected the inhibitory potency of zinc and the maximum inhibition exerted by zinc , respectively . Conversely , the structural changes observed in the model allowed for rationalizing the zinc-dependent regulation of DAT: upon binding , zinc stabilizes the outward-facing state , because its first coordination shell can only be completed in this conformation . Thus , the model provides a validated solution to the long extracellular loop and may be useful to address other aspects of the transport cycle .
The dopamine transporter ( DAT ) is a member of the neurotransmitter∶sodium symporter family [1] . DAT actively removes dopamine ( DA ) from the synaptic cleft by re-uptake into the presynaptic neuron , utilizing the electrochemical sodium gradient . Thus , DAT is a key regulator of the spatial and temporal extraneuronal DA concentration [2] . Human DAT is of particular clinical relevance because dopaminergic transmission plays a key role in several disease entities , e . g . schizophrenia , Parkinson's disease , addiction and drug dependence . Illicit drugs which target DAT , such as cocaine and amphetamine , are among the most commonly abused drugs worldwide . Accordingly , the molecular mechanisms by which DAT operates are a subject of intense scientific and public interest [3] . Translocation of a hydrophilic substrate across the lipid bilayer has been conceptualized by a theoretical framework that posited an alternating access mechanism [4] . This model is supported by a number of recent crystallization studies that provided snapshots of various conformations of a NSS homologue from the thermophilic bacterium Aquifex aeolicus ( LeuT ) [5]–[7] . The crystals showed a movement of the bundle domain ( consisting of helices 1 , 2 , 6 and 7 ) relative to the scaffolding domain [8]–[10] , of which the core helices 3 , 4 , 8 and 9 are arranged in a hash-like shape . Accordingly , this internal scaffold is also referred to as hash domain . The bundle domain rotates by 30–40 degrees during the transition from the open-outward facing to the inward-facing conformation [5] . Although the substrate binding pocket shows a sequence identity of ∼50% , the overall sequence identity between LeuT and DAT is less than 25% . LeuT has also a much shorter second extracellular loop than DAT and lacks a critical Cl− binding site , which is necesscary for DAT substrate translocation [11]–[14] . The relationship between DAT structure and function has been extensively studied using numerous strategies , including mutagenesis and chimeric domain swapping [15] , selected cysteine accessibility studies [16] and by examination of a high-affinity zinc-binding site [17] . Extracellular zinc is a potent inhibitor of dopamine re-uptake in both , synaptosomes and heterologous expression systems with an IC50 in the low µM range [18] , [19] . The zinc-binding site can serve as a DAT specific molecular ruler which defines the spatial micro-environment between the transmembrane helices 7 , 8 and extracellular loop 2 ( EL2 ) . Three amino acid side chains have been identified in DAT which co-ordinate zinc: H193 in EL2 , H375 in the first helical part of extracellular loop 4 ( EL4A ) and E396 in the second helix of extracellular loop 4 ( EL4B ) [18] , [20] . The norepinephrine transport ( NET ) contains two out of the three zinc co-ordinating residues found in DAT , but transport catalyzed by NET is insensitive to zinc . If the third DAT zinc co-ordinating residue ( H193 ) is grafted into NET ( position 189 ) , NET becomes susceptible to inhibition by zinc [18] . Similarily , the serotonin transporter ( SERT ) is also insensitive to inhibition by zinc [21] , but can be rendered susceptible by appropriate mutations [22] . Extracellular zinc can reach concentrations of up to 10–30 µM in the brain under normal physiological conditions [23] , [24] . Given the low µM IC50 values observed for zinc inhibition of dopamine uptake in vitro , there is strong evidence to suggest that zinc may be a physiologically important regulator of DAT function [25] . Importantly , extracellular zinc exerts effects on DAT function that go beyond mere uptake inhibition: zinc can also enhance amphetamine-induced , transporter-mediated release [21] , [26] and DAT-mediated currents [26] , [27] . Binding of zinc to the coordinating residues in the DAT ( H193 , H375 and E396 ) alters the conformational equilibrium between the inward- and outward-facing state of the DAT [28] . Thus , zinc constrains the movement of the DAT by selectively binding to one conformation . Interestingly , the crystal structures of LeuT in the inward- and outward-facing conformation reveal that the relative orientation of H375 and E396 changes during the transport cycle [5] . The third zinc co-ordinating residue , H193 , is located in the EL2; thus , correct modeling of this loop is required to fully understand the effect of zinc on the transport cycle . Modeling studies of human NSS transporters have focused on the transmembrane helices and the substrate binding site [29]–[43] . Although these studies usually included the EL2 loop , they did not report an analysis of the loop geometry , the disulfide bond or the spatial proximity with residues in the EL4 . In addition , several molecular dynamics ( MD ) simulations of human NSS transporter have been carried out to date [36] , [37] , [41] , [44]–[48] . Analysis of the conformations and properties of EL2 were often not reported . Huang et al . [37] developed a DAT model and studied dopamine and cocaine binding using MD simulations . They included knowledge on the disulfide bond and spatial proximity of residues H193 , H375 and E396 in their model building process , but did not analyze the behavior of the EL2 in their simulations . Henry et al . [46] reported on a simulation of SERT which focused mainly on the co-transported ions . Gedeon et al [44] reported on 30 ns simulation studies of LeuT and DAT . They found stable transmembrane regions and observed in the DAT that the mobility of the EL2 loop exceeds that of the other loop regions by two to three fold . Koldso et al . [45] reported simulations of SERT in different conditions and observed a transition from the outward-facing to the inward-facing conformation; the authors reported per-residue mobility and found that the EL2 loop showed two to three times higher fluctuations than the other loops of the SERT . Residue H193 should be close to H375 and E396 to allow zinc to be in contact with all three residues . Hence , we addressed the possible conformation of the EL2 loop and its repercussion for the transport cycle by using the zinc binding site of DAT as a molecular ruler to calibrate the resulting model . We present a refined model of the entire DAT transmembrane domain including EL2 . The refined model was stable in a 200 ns long MD simulation . The mobility of the modeled EL2 was comparable to that of the other loops in DAT . Furthermore , our DAT model revealed that the zinc binding site consisted of four coordinating amino acid side chains rather than three that had been previously identified [18] , [20] , [49] . This prediction was confirmed by site-directed mutagenesis of D206 in EL2 thus providing an experimental validation of our refined DAT model .
Similar to comparing the transporter core , we tested the validity of our DAT model with regard to the substrate permeation pathway , including ( i ) the salt bridge in the outer vestibule , ( ii ) the accessibility of residues within the vestibule , ( iii ) the salt bridge found at the inner gate , and ( iv ) the mutation of Y335 , which impairs transport . A water mediated salt bridge has been reported to form between the conserved residues R85 and D476 ( residue R30 and D404 in LeuT ) in the occluded state of LeuT . However , in the open-outward conformation , the distance is increased between these two residues as the bundle domain rotates by ∼20 degrees relative to the hash domain [5] , [9] . Our model was based upon the occluded state of LeuT . We found a stable ionic interaction between R85 and D476 as shown in Fig . 2A which was either mono-dentated of bi-dentated . We did not observe water molecules stably inserted as evident in the crystal structure of LeuT . The salt bridge stabilized the distance between H1 and H10 and thereby restricted the relative motion between hash and bundle domain . We consistently found that water molecules occupied the S1 binding site , as indicated by the average water density shown as black grid in Fig . 2C–E . The water molecules in the S1 binding site form a continuous hydrogen bonded network that connects to the bulk solution in the extracellular space , which was occasionally interrupted: Fig . 2C–E displays snapshots from the simulations overlaid by the average water density . The constriction zone is formed by the outer gate , which we observed to consist of residues R85 , D476 , W84 , F320 , F155 and Y156 . The salt bridge between R85 and D476 form the first layer followed by the hydrophobic layer consisting of W84 , F320 , F155 and Y156 . We observed the charged side chain of D79 to be well hydrated . The sodium ions remained firmly bound to their binding site; they directly interacted with only one or two water molecules . However , no water density is visible next to the chloride ion . Interestingly , sodium ion 2 becomes increasingly hydrated from the cytosolic site in the second of the 200 ns simulations ( Fig . 2D ) . Similar hydration from the cell interior was previously observed for SERT [45] and DAT [47] . Once fully hydrated , the sodium starts moving , as described below ( in the next section ) . Residue R60 has previously been shown to interact with D436 in DAT [56] . The mutation of either residue resulted in a marked decrease in [3H]DA uptake . The resulting mutant transporters are thought to reside in an inward-facing conformation . However , transport function of the R60A mutant was partially restored with zinc [57] . We found in all simulations that the side chains of these two residues formed very stable salt bridges ( Fig . 2B ) . We observed only occasional opening for very brief time periods . Hence , their disruption would affect the stability of the outward-facing state . Residue Y335 is also important for transport . The mutation of Y335 to alanine completely abolishes [3H]DA uptake [28] and shifts the transporter into a channel-like mode [27] . [3H]DA uptake is partially restored by the application of extracellular zinc , suggesting that this mutant is deficient in the return step to the outward-facing conformation [28] . We found Y335 to be located in the center of the inner vestibule . Water penetrated into the closed inner vestibule until it reached Y335 , which suggests that this residue may play a dual role by ( i ) stabilizing the outward-facing conformation and ( ii ) forming the hydrophobic part of the inner gate . NSS transporters couple substrate transport to the ion gradients of both sodium and chloride . For example , the translocation of DAT substrates requires the sequential binding and co-transport of two sodium ions and one chloride ion . Both sodium binding sites are conserved between LeuT and DAT and have been modeled accordingly ( Fig . 3A ) . Sodium 1 remained stably bound in all simulations , as shown in Fig . 3B . Sodium 1 interacted with and oriented the side chain of residue D79 . This amino acid side chain interacts with the positively charged nitrogen of the monoamine substrates . Its mutation results in a non-functional transporter [54] . The residue corresponding to D79 is replaced with a glycine in all non-monoamine transporters , e . g . LeuT , GlyT and the GABA transporters . Substrates of these transporters are amino acids and thus supply a carboxyl group ( absent in the monoamines substrates of DAT , NET and SERT ) in trans . As observed in the LeuT crystal structures , this carboxyl group occupies the place of the side chain of D79 and directly interact with sodium 1 . Sodium 2 remained stably bound only in two simulations , while it started moving towards the cytosol in the second 200 ns long simulation . We observed in the first 50 ns an increasing number of water molecules interacting with sodium 2 which began oscillating its position after 50 ns . The motion of the sodium was closely followed by the side chain of D421 in helix 8 . In the next 100 ns , sodium 2 moved back and forth between its binding site and a position at the cytosolic oriented side of helix 8 . The water file connecting the S1 binding site with the extracellular bulk solvent became interrupted during this period . We observed in the last 50 ns an increased preference for occupying the cytosolic site of helix 8 . A similar behavior of sodium 2 was observed by Koldso et al [45] in simulations of SERT , but we did not observe complete opening of the R60-D436 salt bridge ( R79-D425 in SERT ) or transition to the inward-facing state . Transport of substrates by NSS depends on chloride , while LeuT-mediated transport does not require chloride . The evidence that chloride is required for transport is strong , as transport is strongly reduced in its absence [12] , [13] , [58] . It is however still not fully established if the chloride gradient is necessary for co-transport of neurotransmitters . While the classical stoichiometry of DAT transport proposes that substrate transport is chloride dependent [59] , Erreger et al . [58] have proposed that chloride plays a regulatory function , but its chemical gradient does not directly support transport , as they found that both internal and external chloride facilitate transport and that increasing intracellular chloride concentration did not affect transport associated currents . Previous modelling and mutational analyses [12] , [13] located the chloride in a hydrophilic pocket . Consistent with this notion , we found the chloride atom stably bound in this pocket ( Fig . 3B ) . The entire EL2 consists of several segments: it begins with a loop , that includes the disulfide-bridge between C180 and C189 as well as H193 and is followed by the EL2-helix: this helix in the center of the extracellular loop is conserved from the procariotic LeuT to the human NSS transporter family . This structural element is followed by another loop element that connects the EL2-helix with transmembrane helix 4 . LeuT serves as a template for both the EL2-helix and the second loop , while the first loop is in DAT by 21 residues longer than in the LeuT template . Our EL2 modeling focuses on creating this extended loop . Models of NSS transporters which include EL2 have already been published [31]–[33] , [35]–[37] , [39] , [41] , [42] . Large mobility of the EL2 loop was observed in those MD studies that reported on the stability of the loop [44] , [45] . This does not seem to be compatible with the structural requirements of the zinc binding site in DAT . RMSD values were reported to be larger than 0 . 4 nm , if reported . Our initial models were created while using the close proximity between residues H193 , H375 and E396 as the only restraint . These models suffered from the same high mobility upon rigorous testing of EL2 in MD simulations and we found a wide range ( 0 . 4 to 1 . 4 nm ) of different RMSD values between independent runs . The RMSD were calculated by first fitting the transporter to the hash domain and subsequently probing the mobility of EL2 by calculating the Cα RMSD value of residues 178 to 202 . We observed that residue H193 did not remain in close proximity of residues H375 and E396 . However , zinc binding induces a spatial constraint that requires immobility of the residues involved . We therefore refined our initial DAT homology model to include EL2 and accommodate the zinc binding site . Human NSS transporters possess a substantially longer EL2 than that found in the LeuT template ( Fig . 4 ) . We solved the conformational sampling problem by employing the high-affinity zinc binding site as a molecular ruler [18] , [20] . Residues H375 and E396 are both located in EL4 . They can be used to limit the possible spatial placement of H193 . In addition , EL2 contains a conserved cysteine disulfide bond between C180 and C189 . These two constraints allowed for a sharp reduction of the potential conformational phase space . The sequence alignment of all NSS transporters indicates that EL2 ( indicated by the red bar in Fig . 4 ) consists of two parts with different properties , divided at residue H193 ( indicated by a black arrow in Fig . 4 ) . The first part , which precedes H193 , is conserved in length and amino acid type and thus will most likely be structured . However , the second part , which is between H193 and the EL2-helix , is variable in length . It is also rich in glycine and serine and is therefore predicted to be largely unstructured . In an iterative approach , first 200 homology models were built and their quality was assessed by the MODELLER [60] energy function and the DOPE score [61] . The 10 best models were inserted into a POPC membrane and probed for stability by MD simulation ( duration 50 ns ) as described in “material and methods” . Structural restraints were imposed on loop modeling to reduce the search space during model building . These restraints were based on the following predictions: ( i ) the three N-glycosylation sites N181 , N188 , and N205 ought to be solvent exposed to allow for glycosylation [62] , [63]; ( ii ) C180 and C189 form a disulfide bond and removal of this disulfide-bridge ablates surface expression [64]; ( iii ) H193 must be in close proximity to H375 and E396 [18] , [20]: the zinc ion is coordinated by the side chains of all three residues , hence , H375 and E396 in EL4 served to constrain the position of H193 . Assuming that the geometry of the EL2-helix resides above E396 , two options were available to place H193: ( i ) placement above the two EL4 helices , or ( ii ) between H5 , H7 and H8 at the edge of the transporter . The latter , in addition , establishes the transporter-membrane interface . The first option could be ruled out: residue conservation analysis did not allow to predict any conserved region in the EL2-helix . If the conserved part of the EL2 loop ( from helix 3 to H193 ) would fold over and thereby interact with the EL2-helix , then the buried residues should be conserved in orthologous DAT sequences . Furthermore , residues with similar biophysical properties should be found in the closely related paralog NET , because the same zinc-binding site can readily be engineered onto NET [18] . In addition , a similar pattern would be expected in other members of the NSS family . We tested several models in which the loop was folded above the EL2-helix . In all these MD simulations , we observed an unstable loop structure . The zinc coordinating residue H193 moved away from the other two coordinating residues on the EL4 ( H375 and E396 ) and we did not observe events where it would re-establish the contact . This is not in accordance with the high degree of conservation observed in the first part of EL2 . If the loop was freely floating , there would be no evolutionary restrain that promoted the observed conservation . This would be incompatible with the requirements for zinc binding . The second option constrains the backbone of the EL2 behind the EL2-helix , in a similar manner to that seen in the recently published inward- and outward-facing structures of LeuT [5] . Here , H193 can be positioned between H375 , E396 and the membrane , and hence above H5 , H7 and H8 as shown in Fig . 5 . This positioning allowed for EL2 to cover the hydrophobic surface of H5 , H7 , H8 and EL4B . Furthermore , EL2 shielded this covered hydrophobic part from the charges of adjacent lipid head groups . In support of this notion , simulations that started from this conformation revealed a much higher stability and resulted in a stable conformation after several iterations of model creation and testing . The C180–C189 disulfide bond and the positioning of H193 greatly reduced the available phase space . Indeed , the sequence stretch before and after the disulfide bond had to be almost fully extended to reach from the end of helix H3 to residue H193 at the zinc binding site . The remaining amino acids between C180 and C189 form a loop . Its length is highly conserved within the NSS family ( see magenta arrows in Fig . 4 ) . Two residues in the center of this stretch ( W184 and N185 ) are almost fully conserved among all NSS sequences . The other 6 amino acids are not conserved by residue but rather by length and type: they are either polar or charged . Such a high degree of conservation indicates an evolutionary constraint: tryptophanes are found in membrane proteins with high frequency at the hydrophobic/hydrophilic interface of membranes [65] , [66] . A free energy minimum has been identified in this region for tryptophanes when they are moved from the water into the center of the membrane [67] . The tryptophan W184 could therefore act as a membrane anchor for the loop formed between C180 and C189 [68] ( Fig . 5 ) . In support of this notion , all simulations that started from a membrane-inserted W184 structure remained stable in the lipid-water interface . In contrary , this residue showed almost un-constrained movements in simulations where W184 was not inserted in the membrane . Hence , this membrane-association strongly restricts the movement of the entire loop . There is experimental evidence to support this model: if W184 is mutated to leucine , it abolishes cell surface expression of DAT consistent with the fact that it no longer shows a free energy minimum at the water-lipid interface [55] . Three models were challenged by 200 ns long MD simulations . The refined DAT model were stable over the entire length of the simulation as shown in Fig . 6 . The overall RMSD of the DAT reached a plateau at 0 . 24–0 . 26 nm . This value is expected for proteins of 500 to 600 residues . In contrast , EL2 alone was slightly more mobile and leveled off at 0 . 3–0 . 5 nm ( Fig . 6B ) . The increased flexibility of the EL2 loop reported here is to be expected , because loops are in general less restrained than the core of the transporter . We noted that the serine and glycine rich stretch of the EL2 loop between H193 and the EL2 helix ( residue G195 to G203 ) moved freely and showed large motional amplitudes . This structural mobility was expected according to the primary sequence . The ß-factors show the mobility of DAT at a per-residue level ( Fig . 6A ) . The pattern of higher and lower mobility mirrors the helical parts and the loop regions of the DAT structure ( Fig . 6A ) . The position of H193 is indicated by circles colored in magenta . The restricted mobility of H193 is clearly visible , as is the large mobility of the serine and glycine rich stretch ( residue G195 to G203 ) . The observed difference in motions of the glycine rich stretch between the three simulations can be attributed to limited sampling . We observed larger ß-factors in the EL4A helix ( residue K374 to D385 ) in two out of three simulation . We found a shift in the relative position of the helix giving rise to the large ß-factors , while the EL4A helix itself remained stable throughout the simulation . We observed stable zinc binding sites in all three simulations ( see Fig . 7 ) . Residue E396 shows a bi-dentate zinc coordination in two out of tree simulations , indicating a strong interactions between the bound zinc and the carboxyl group of the E396 side chain . The interaction of histidine with zinc has a chemical bond component and is geometrically restrained with a strong distance dependence . These quantum chemical effects are typically not correctly described by classical static forcefields including OPLS . We opted to maintain the full charge on the zinc ion and to not add any term to for histidine-zinc interaction . This choice was motivated by the aim of the study , as we intended to challenge the geometry of the zinc-binding site and not to enforce it . In this way , the structure can change , if it was unstable . The two histidine side chains of residues H193 and H375 do both show a larger distance to the zinc ion as compared to the charge-charge interaction between E396 and zinc , but the local geometry remains stable . The interaction of zinc with the histidine side chains is found to be a direct interaction or water bridged . The reason for this behavior can be found in the full charge of +2 on the zinc and the much smaller partial charge of the Nε atom of the histidine side chain . The zinc does therefore present a strong attraction force for solvent and water penetration must be expected . The crystal structures of zinc containing proteins reveal average zinc-to-nitrogen distances of ∼0 . 2 nm [69] , [70] . This would cause an atomic overlap and strongly contribute to repulsion according to the Lennard-Jones non-bonding interaction term . A σ value equal to 0 . 252 nm marks the distance beyond which the Lennard-Jones potential of the OPLS force field of the zinc-to-nitrogen non-bonded interaction becomes attractive; the minimum of the potential is found at 0 . 33 nm . This strongly supports the nature of the zinc-histidine interaction as chemical bond . Despite this shortcoming , both histidine residues H193 and H375 remained firmly located in the vicinity of zinc . We expected thermal motions and water penetration to be a destabilizing force for the structure; therefore , it is remarkable that our models remain stable over the entire 200 ns period , further supporting the correctness of our model . We re-parameterized the charges of zinc and the side chains of the coordinating residues H193 , D206 , H375 and E396 using “R . E . D . server” [71] , [72] in order to correctly define the chemistry and test the model . “R . E . D . server” was originally developed to create OPLS type charges by fitting partial charges to quantum chemical calculations . We applied the same OPLS bonded parameter as used in a recent study of the zinc containing enzyme human carbonic anhydrase [73] . The distance between zinc and the Nε of the histidine side chain was maintained as parameterized in a 100 ns long simulation . The trajectory revealed that the distance to the two negatively charged residues D206 and E396 was unchanged since both residues remained in contact with the zinc ion ( See insert in Fig . 7 ) . RMSD as well as RMSF revealed that the addition of the chemical bonds did not affect the structure of the model or its dynamic behavior . In particular , the RMSD of the DAT reached the same level , while we observed that the RMSD of the EL2 loop became smaller , leveling off at 0 . 15–0 . 25 nm as compared to 0 , 2–0 . 3 nm observed without the zinc-nitrogen chemical bond . Analysis of the endogenous high-affinity zinc binding site in DAT revealed that the first coordination sphere of zinc includes a previously unrecognised fourth residue: D206 ( Fig . 5 ) . This aspartate is present in all orthologous DAT sequences , which contain H193 . In our simulations , D206 consistently interacted with zinc via its carboxyl moiety , thereby completing the first coordination shell of zinc . We found that the D206 – zinc distance displayed a stable time dependent behavior similar to the interaction of zinc with E396 . The main difference to E396 is the coordination geometry . The carboxyl group of E396 mainly formed a bi-dentate coordination with both of its oxygens . In contrary , D206 coordinated zinc typically with only one oxygen atom , while the second oxygen of the carboxyl group interacted with the surrounding bulk water . If this model were true , then we would expect that modification of this residue should alter the affinity of extracellular zinc for DAT . We therefore tested this hypothesis by mutating D206 to lysine ( DAT-D206K ) , to the zinc coordinating residues cysteine ( DAT-D206C ) , histidine ( DAT-D206H ) as well as to glutamate ( DAT-D206E ) and alanine ( DAT-D206A ) . HEK293 cells were transiently transfected with plasmids encoding either the wild-type or mutant versions of DAT . Mutants were expressed on the cell surface and were thus indistinguishable from YFP-DAT when examined by confocal microscopy , with the only exeption of the histidine mutant . The large , rigid and ingombruent size of the histidine side chain is probably responsible for a folding problem , ER retention and subsequent degradation . For clarity reasons we focus in the discussion of the results on the two mutants DAT-D206K and DAT-D206C and summarize transport inhibition data for all mutants in Table 1 . The confocal microscopy images of wild type DAT and of the two mutants DAT-D206K and DAT-D206C are shown in Fig . 8A–C , indicating similar surface expression . The two mutants also transported the substrate [3H]MPP+ with rates ( 5 . 86±0 . 8 and 8 . 39±1 . 6 pmol/min/well for DAT-D206C and DAT-D206K , respectively ) that were comparable to that of wild-type DAT ( 7 . 67±1 . 8 pmol/min/well ) . These values are within the range of previously published uptake rates for DAT expressed in heterologous cell systems [18] , [21] . We assessed the ability of zinc to inhibit substrate uptake by these mutants and used wild-type DAT and DAT-H193K as reference: in wild-type DAT ( black symbols in Fig . 8D ) , zinc exerted a biphasic inhibition on substrate uptake . The first component ( IC50 = 1 µM , see Table 1 ) is due to interaction of zinc with its high-affinity binding site . The second component refects an action on low-affinity sites [18] , [21] . Accordingly , in DAT-H193K , the affinity of zinc to the high-affinity site was lowered so much that it was not possible ot resolve the two components resulting in a homogeneous inhibition curve ( Table 1 ) . Substituting D206 by lysine reduced the inhibitory potency of zinc on the high-affinity component by approximately three fold ( green symbols in Fig . 8D; Table 1 ) . This reduction in inhibitory potency of zinc is not as large as that observed for the H193K mutant . Substitution of D206 by cysteine , which is known to be a zinc coordinating residue , also led to an apparent reduction in zinc binding affinity for DAT ( Table 1 ) . However , in DAT-D206C , zinc was a more effective blocker than in any other version of DAT ( blue symbols in Fig . 8D ) . This resulted in almost complete inhibition of transport upon saturation of the high affinity site ( 99% occupancy predicted at 250 µM ) . Thus , inhibition by non-specific binding could no longer be observed . Mutation of D206 of glutamate or alanine did not result in any significant change in the inhibitory potency of zinc ( see Table 1 ) . We created models of the D206K and the D206A mutants to investigate the effects of these mutations in more detail . The models included the zinc-nitrogen interactions defined as a chemical bond ( see above ) . Simulations were carried out for 20 ns and remained stable for both mutants: the RMSD to the starting structure was 0 . 15 nm and we did not observe any conformational changes . The side chain of E396 remained in direct contact with the zinc ion as observed for wild type DAT . In the mutant D206A , a water molecule takes the place of the carboxyl group of aspartate 206 ( Fig . 9 ) that interacts with zinc: the side chain of alanine is uncharged and small enough to leave the space . A water molecule can be observed in the same position in the D206K mutant: the long side chain of D206K is observed to extend into the solvent . Thereby , it offers similar space opportunities next to zinc as seen in D206A ( Fig . 9 ) . The positive charge on the lysine side chain does nevertheless interact with the zinc ion by long ranged electrostatic interactions . This repulsive force reduced the affinity for zinc as was observed in the uptake inhibition experiments ( see Fig . 7 ) .
Analysis of the human genome predicted that approximately 3000 proteins are zinc binding proteins [74] . These can be classified into two main groups based on the functional role of zinc: either enzymatic or structural [69] . Zinc accepts 4 to 6 ligands in its first coordination shell [70] and interacts with nitrogens provided by the imidazol ring of histidine , carboxyl oxygens supplied by aspartate or glutamate and sulfur atoms from the sufhydrdyl group of cysteine . The binding affinity of zinc is also controlled by the protein environment , with affinities in the picomolar range for intracellular proteins and micromolar for extracellular proteins . However , the binding affinity of zinc does not appear to depend on the specific nature of the interacting atoms , as very similar affinities have been observed with varying types of protein side chain ligands [70] . In almost all cases , if zinc is found in the active side of an enzyme , one of the coordination sites is not from a protein side chain: this allows the substrate to directly interact with the zinc atom of the enzyme . In contrast , structural zinc binding sites are characterized by a completed first coordination shell of zinc , with all coordinating atoms originating from protein side chains . Three zinc coordinating residues ( H193 , H375 and E396 ) have already been characterized in DAT [18] , [20] . We identified a fourth residue ( D206 ) in the first coordination shell of zinc: this is in line with the structural-regulatory and non-enzymatic function of the zinc binding site . The mutation of D206 to lysine reduced the affinity of DAT for zinc , but not to the same extent as seen in the H193K mutant . The positively charged Nζ atom of the H193K mutant side chain is expected to retain the same orientation in the mutant protein . It can therefore be assumed to be located in the center of the zinc binding site and to directly take the position of the zinc ion . In contrast , the positively charged Nζ atom of the D206K mutant should be oriented towards the solvent and does therefore not compete to the same extend with zinc for its interaction site . The substitution of the zinc coordinating residue D206 with the zinc ligand cysteine had a very different effect: it induced a change in the regulatory effect of zinc binding and had a only modest effect on the binding affinity of zinc . Thus , a complete inhibition of substrate uptake was observed in DAT-D206C upon zinc binding . A similar effect was observed for the DAT mutants E396H and T400C [20] . The residual transport activity of the wild-type DAT after zinc binding can be explained by the specific properties of the carboxyl side chain of D206 and E496 . The carboxyl moiety of aspartate and glutamate side chains can coordinate zinc by one or both oxygens and this interaction is entirely electrostatic in nature . Both factors allow for a larger range of possible amino acid-zinc distances and orientations , which enables them to be structurally promiscuous . In contrast , the interaction between the cysteine sulfur and zinc is predominantly a charge-transfer interaction and restricts the possible distances to a narrow window . This strongly reduces the distance promiscuity of the cysteine mutant and also explains the complete zinc inhibition of dopamine transport seen with DAT-D206C , as compared to the partial zinc inhibition of transport seen in wild-type DAT . We observed lower affinity of zinc to the DAT-D206C mutant as compared to wild type . It is conceivable that the geometry at the zinc binding site is optimal for aspartate , but less so for cysteine . Side chain solvent exposure and reduced geometrical promiscuity of cysteine may therefore be responsible for the lower binding affinity . The zinc inhibition curve of the D206E mutant was virtually identical with wild type . This was an expected result , as structural analysis showed that D206 coordinates zinc laterally and some room is available for structural adaptation . The extention of the side chain of residue 206 by one methylen group in the D206E mutant does therefore not have any significant impact on this interaction . The D206A mutation was phenotypically silent . Mutations of residues known to be in contact with zinc , but without accompanying affinity-changes , have been described previously for several proteins , including enzymes [75] , zinc finger proteins [76] , and receptors [77] . The finding is therefore not without precedent that the D206A mutation does not affect zinc binding within the error bars of our experiment . The mutation of aspartate to alanine reduces the size of the side chain of residue 206 to an extend that is large enough for a water molecule to take the place of the 206 side chain and cooridinate zinc , as observed in zinc-based enzymes . The correct modeling of EL2 , which harbors the zinc coordinating residue H193 , is required to fully understand the functional impact of zinc on the DAT transport cycle . Up to now , molecular models of this extracellular loop have been established [31]–[35] , [41] , [44] , [45] , [47] , but they have been rarely scrutinized . The EL2 of the NSS is 21 amino acids longer than EL2 in LeuT and thus the potential conformational space is prohibitively large for ab initio modeling . The dopamine transporter , however , provides an opportunity to reduce the number of possible configurations , as the loop can be restrained by the coordinates of the high-affinity zinc binding site . We traced this loop behind the EL2-helix , where it interfaces with the membrane . We observed that the loop is most restrained in its flexibility at position H193 . This feature is very likely to be important for the transport reaction , because this region shows structural changes during the transport cycle , highlighted in recent structures of LeuT in the inward- and outward-facing conformations [5] . Here , helix H8 is part of the hash domain and H7 is part of the bundle , while helix EL4A and H2 partially follow the movement of the bundle . The mobility of the EL2-helix is facilitated by the conserved residue P213 within the EL2-helix that allows for helix bending . We observed that the sequence stretch between H193 and the helix of EL2 is very flexible , as indicated by initial analysis of NSS sequences . This high flexibility is most likely necessary to avoid any energetic barrier for transport . Partial digestion experiments of rDAT , in which the second part of the EL2 loop ( R218 in rDAT , located at the end of the EL2 helix and potentially R227 in the loop following the 2EL helix ) is cleaved by trypsin [78] showed no difference in trypsin digestion upon zinc or substrate binding , while binding of different inhibitors , including cocaine and CFT , restrained the transporter in a state that showed decreased protease sensitivity . Identical proteolysis behavior with and without zinc suggests that zinc binding per se does not induce major changes in conformation of the EL2 loop . We can only speculate on the structural origin of the change in sensitivity to trypsin in light of the new inward- and outward-facing template LeuT structure: the LeuT structures show that the EL2 helix partially follows the movement of the bundle domain during the transport cycle . The main trypsin cleavage site was observed at the remote end of this helix . Inhibitors restrain the DAT in a single conformation , while in other conditions this was not necessarily the case . It is therefore conceivably that the trypsin sensitive conformation is not accessible in the inhibitor bound state . In functional terms , it has been shown that zinc binding promotes the population of the outward-facing conformation [79] . Structural analyses of the residues coordinating zinc revealed that H193 and E396 can be assigned to the hash domain . H375 is found on top of helix 7 and is therefore part of the bundle domain , while D206 is located on the helix in EL2 which partially follows the motion of the bundle . The model of substrate transport by NSS [5] , [9] proposes that the bundle domain changes its conformation during transport: this movement closes the outer vestibule at the extracellular face of the transporter and opens the inner vestibule . Fig . 10 shows a model of the DAT zinc binding site , built by combining our EL2 loop model with the recent open-outward- ( Fig . 10A ) or inward-facing conformations ( Fig . 10B ) of the LeuT [5] . These models visualize the expected conformational change in the DAT and display the change in the first coordination shell of zinc upon transition from the outward- to the inward-facing conformation . The models uncovered that the rotational-translational movement of the bundle domain alters the geometry of the zinc binding site . The position of H375 was thereby displaced by 0 . 85 nm from the tetrahedral zinc coordinating geometry and was moved almost behind D206 . Hence , the first zinc coordination shell was disrupted . These observations allowed us to propose a two-step model of the mode of action of zinc on DAT: ( i ) the zinc ion is attracted to the binding site by the two negative charges of D206 and E396 and ( ii ) the tetrahedral coordination is completed by H193 and H375 . Hence , binding of zinc selects for the outward-facing conformation , as the coordination by H375 is only possible in this conformation . The strong phenotypes observed for the H193 and H375 mutants and the weaker effects of the D206 mutants can be rationalized in the context of this conformational change . Inhibition of transport by zinc is observed , because the bound zinc ion puts a restraint on the distance between H375 on the moving bundle domain and H193 plus E396 on the hash or scaffold domain . A mutation on either side abrogates this tight restraint that reduces the transport rate of DAT by ∼50% upon zinc binding . As a consequence , inhibition of transport cannot be observed in the experimental assay even if zinc still binds: this is the result of the mutation of the essential interaction site on one of the two domains . The situation for D206 is different: residue D206 is located within the helix of the second extracellular loop . This helix does partially follow the motion of the bundle domain ( see Fig . 9 ) . Because the helix is not strictly associated with either domain , it is not directly involved in the essential interaction that changes turnover number of DAT upon zinc-binding . In this sense , D206 has a supportive role , while H193 , H375 and E396 are essential for controlling transport rates .
The alignment was created using muscle [80] and is based on the alignment published by Beuming et al . [40] . The alignment was modified in EL4 by closing the gaps before and after the EL4A helix ( See Fig . S1 ) . We thereby obtained improved clustal quality scores . The structure of LeuT with the PDB ID: 2A65 [7] was used as the reference template for creating the homology model of the human dopamine transporter . In addition to the LeuT template , parts of the best structure from the previous model building interaction were used as templates in subsequent iterations of model building , optimization and testing . MODELLER version 9 . 8 [81] was used to create 200 structures using the automodel procedure . The structures were evaluated using the MODELLER energy score and the DOPE score [61] . The best models were further evaluated for compactness , accessibility of N-glycosylation site and geometry of the zinc binding site . The positions of the sodium ions in the LeuT structure were maintained in the DAT model . The chloride ion was placed as proposed in the literature [11]–[14] . The 10 best models were inserted into a system consisting of a pre-equilibrated membrane created to harbor the dopamine transporter , plus water and counter ions . In order to prevent atom overlaps , the g_membed method [82] was used to insert the human DAT model . After equilibration of the surrounding environment for 2 . 5 ns , position restraints on DAT were slowly reduced in 4 steps , applying 1000 , 100 , 10 , and 1 kJ/mol , respectively , each time simulating for 2 . 5 ns . Distance restraints designed to maintain the secondary structure were in addition to the position restraints applied using a force constant of 100 kJ/mol . An additional 20 ns equilibration simulation was carried out , where distance restraints on the secondary structure were maintained while position restraints were removed . The stability of the model was further challenged in a final 20 ns unconstrained MD . In total 15 iterations were necessary in order to identify good models that were stable in MD simulations . The best model was further challenged in a 200 ns simulation . MD simulations were carried out using the GROMACS 4 . 5 . 3 MD package [83] , [84] , applying the OPLS force field [85] , [86] . The 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine ( POPC ) lipids of the membrane were represented by Berger lipids , [87] converted into the format of the OPLS all atom force field by following the procedure proposed by Neale ( http://www . pomeslab . com/files/lipidCombinationRules . pdf ) . The water was represented as SPC water [88] . The simulations were carried out at a constant temperature of 310 K , using the v-rescale ( τ = 0 . 1 ps ) thermostat [89] , while coupling the protein , the membrane , and the water/ions separately . The pressure was maintained at 1 bar using the weak coupling algorithm [90] with a coupling constant of 1 . 0 ps and a compressibility of 4 . 5×10−5 bar-1 . The electrostatic interactions were evaluated using the smooth particle mesh Ewald method [91] , with a cutoff of 1 . 0 nm . The long-range electrostatic interactions were calculated with fourth-order B-spline interpolation and a Fourier spacing of 0 . 14 nm . The Lennard-Jones interactions were evaluated using a cutoff of 1 . 0 nm with the neighbor search list updated every ten steps . Long range correction for energy and pressure were applied . Bonds and angles of the water molecules were constrained using the SETTLE algorithm [92] , while all other bonds were constrained using LINCS [93] . The coordinates of zinc and the side chains of the four coordinating residues ( the imidazol rings of the two histidines , and the carboxyl groups of aspartate and glutamate ) were extracted from our homology model . A methyl group was added where the chemical bonds were truncated . The geometry was first optimized at the semi-empirical level and then at the quantum-chemical level using Gaussian through the R . E . D Server [71] , [72] . Partial charges are subsequently derived by the R . E . D Server that are tailored for the OPLS force field based on the quantum chemical calculations . The partial charges were then adjusted to account for the already present partial charges that were already present on these amino acids to obtain an overall unit charge . [3H]1-methyl-4-phenylpyridinium ( [3H]MPP+; 85 Ci/mmol ) was supplied by American Radiolabeled Chemicals ( St . Louis , MO ) . Chemicals at analytical grade were obtained from Sigma Aldrich . Cell culture media , and antibiotics were obtained from Invitrogen . Wild-type human DAT was generously donated by Marc G . Caron [94]; DAT H193K was a generous gift from Ulrik Gether [18] . Wild-type and mutant DAT were YFP tagged at their N-terminus as described in Egana et al . [95] . Mutagenesis was performed using the Quickchange Lightning Kit by Agilent Technologies . Primers were designed using the “quickchange primer design tool” by Agilent . Primers used were: D206K: ( 5′-3′ ) : CAGCTCGGGCCTCAACAAGACTTTTGGGACCACAC; D206C: ( 5′-3′ ) : CAGCTCGGGCCTCAACTGCACTTTTGGGACCACA . HEK293 cells were cultured in Dulbecco's modified Eagle's medium ( DMEM ) with high glucose ( 4 . 5 g/liter ) and L-glutamine ( 584 mg/liter ) , supplemented with 10% fetal calf serum ( FCS ) , 100 units/ml penicillin and 100 µg/ml streptomycin . The cells were maintained at 37°C in a humidified atmosphere of 5% CO2/95% air on standard plastic culture ware . The cells were transiently transfected with 2–10 µg of plasmid DNA as required , using the calcium phosphate precipitation method . Cells were seeded onto poly-D-lysine coated 15 mm coverslips for confocal microscopy twenty-four hours after calcium phosphate transfection . Forty-eight hours after transfection , the cells were analysed by confocal microscopy . The plasma membrane was identified using 0 . 025% trypan blue as previously described [96] . All images were acquired using a Zeiss Axiovert LSM510 confocal laser-scanning microscope . Cells were seeded at 0 . 5×105 cells/ml into poly-D-lysine coated 48 well plates twenty-four hours after calcium phosphate transfection with either wild-type or mutant DAT . Uptakes were performed as described previously [21] . In brief , the cell medium was aspirated and the cells were washed once with Krebs-HEPES buffer at room temperature . The washed cells were pre-incubated with Krebs-HEPES buffer in the presence of 0–10 mM ZnCl2 for 5 min at room temperature . In the first step of the assay , this buffer was replaced with Krebs-Hepes buffer containing the appropriate ZnCl2 concentration and 0 . 02 µM [3H]MPP+ . After three minutes substrate uptake was stopped by exchange of the substrate containing buffer with ice-cold Krebs-Hepes buffer . The cells were lysed in 1% SDS and transferred to scintillation vials . Scintillation cocktail was added and the vials were assayed for [3H] content by liquid scintillation counting . Non-specific uptake was determined in the presence of 10 µM mazindol . Uptake data are given by mean values ± S . E , obtained from n = 6–8 experiments . Total uptake data were corrected for non-specific uptake and expressed as a percentage of 0 mM ZnCl2 for each experiment . IC50 values were calculated for each mutant by performing non-linear regression analysis using PRISM version 4 . 0 ( GraphPad Software , Inc . , San Diego , CA ) .
|
The dopamine transporter ( DAT ) regulates dopaminergic neurotransmission in the brain and is implicated in numerous human disease states . DAT is unique among the monoamine neurotransmitter transporter family because its substrate transport is inhibited by extracellular zinc . DAT homology models rely upon the crystal structure of LeuT solved in 2005 . LeuT and DAT share a relatively low overall sequence identity of 22% . In addition , the length of the second extracellular loop of DAT exceeds that of LeuT by 21 residues . The zinc binding site cannot be directly modeled from the LeuT template alone because of these differences . Current available homology models of DAT focused on substrate or inhibitor binding rather than on the second extracellular loop . We exploited the specificity of the zinc binding site to build and calibrate a DAT homology model of the complete transmembrane domain . Our model predicted that the zinc binding site in DAT consists of four zinc co-ordinating residues rather than three that had been previously identified . We verified this hypothesis by site-directed mutagenesis and uptake inhibition studies .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"neuropharmacology",
"drugs",
"and",
"devices",
"drug",
"dependence",
"neuroscience",
"behavioral",
"pharmacology",
"protein",
"structure",
"neurotransmitters",
"pharmacology",
"psychopharmacology",
"biology",
"biochemical",
"simulations",
"biophysic",
"al",
"simulations",
"neurological",
"disorders",
"neurology",
"parkinson",
"disease",
"computational",
"biology",
"recreational",
"drug",
"use",
"macromolecular",
"structure",
"analysis"
] |
2013
|
Mutational Analysis of the High-Affinity Zinc Binding Site Validates a Refined Human Dopamine Transporter Homology Model
|
We previously used a single nucleotide polymorphism ( SNP ) in the CHRNA5-A3-B4 gene cluster associated with heaviness of smoking within smokers to confirm the causal effect of smoking in reducing body mass index ( BMI ) in a Mendelian randomisation analysis . While seeking to extend these findings in a larger sample we found that this SNP is associated with 0 . 74% lower body mass index ( BMI ) per minor allele in current smokers ( 95% CI -0 . 97 to -0 . 51 , P = 2 . 00×10−10 ) , but also unexpectedly found that it was associated with 0 . 35% higher BMI in never smokers ( 95% CI +0 . 18 to +0 . 52 , P = 6 . 38×10−5 ) . An interaction test confirmed that these estimates differed from each other ( P = 4 . 95×10−13 ) . This difference in effects suggests the variant influences BMI both via pathways unrelated to smoking , and via the weight-reducing effects of smoking . It would therefore be essentially undetectable in an unstratified genome-wide association study of BMI , given the opposite association with BMI in never and current smokers . This demonstrates that novel associations may be obscured by hidden population sub-structure . Stratification on well-characterized environmental factors known to impact on health outcomes may therefore reveal novel genetic associations .
As obesity represents a substantial and growing threat to public health , efforts to identify the determinants of obesity are of considerable scientific and societal importance . Genome-wide association studies ( GWAS ) have identified numerous variants associated with body mass index ( BMI ) [1] , but a substantial proportion of the estimated heritability remains to be accounted for . At the same time , a number of modifiable environmental factors have been identified that influence BMI , with cigarette smoking a strong lifestyle influence on BMI [2] . In a previous Mendelian randomisation analysis , we used a single nucleotide polymorphism in the CHRNA5-A3–B4 gene cluster associated with heaviness of smoking within smokers [3] to confirm the causal effect of smoking in reducing BMI [4] . We sought to extend these findings in a larger sample drawn from the Causal Analysis Research in Tobacco and Alcohol ( CARTA ) consortium ( http://www . bris . ac . uk/expsych/research/brain/targ/research/collaborations/carta/ ) . We used the same genetic variant , characterised by two SNPs ( rs16969968 and rs1051730 ) which are in perfect linkage disequilibrium ( LD ) in samples of European ancestry , and therefore reflect the same genetic signal ( hereafter rs16969968-rs1051730 ) . This variant is associated with approximately 1% phenotypic variance in cigarettes per day and approximately 4% variance in cotinine levels ( the primary metabolite of nicotine , and a more precise measure of exposure ) [5] , [6] . Mendelian randomisation analyses of the causal effects of smoking heaviness require stratification according to smoking status – any causal effects of the exposure ( i . e . , smoking heaviness ) should be reflected in an association of the instrument ( i . e . , genotype ) among current smokers only , and not never smokers ( former smokers might be expected to be intermediate between current and never smokers ) [7] . The never smoking group therefore enables a test of the specificity of the instrument ( i . e . , that the variant only affects the outcome through the exposure of interest ) [8] . Critically , the rs16969968-rs1051730 variant has not been shown to be associated with smoking initiation ( i . e . , it does not influence risk of being an ever versus a never smoker ) in previous GWAS of smoking behaviour [9] , which reduces the risk of introducing collider bias when stratifying on smoking status . In the course of these analyses , we observed an unexpected finding , which we report here . Specifically , we observed an association of rs16969968-rs1051730 with higher BMI in never smokers . This association has not previously been reported in GWAS of BMI published to date . We therefore focus on the implications of this novel finding , and not the Mendelian randomisation analysis of the causal effects of smoking on BMI .
Our total sample size comprised 148 , 730 never smokers , former smokers and current smokers . In the 66 , 809 never smokers , we observed positive association of rs16969968-rs1051730 with BMI ( Table 1 ) , indicating an association operating via pathways other than smoking ( percentage change per minor allele +0 . 35 , 95% CI +0 . 18 to +0 . 52 , P = 6 . 38×10−5 ) . We also confirmed the expected inverse association of rs16969968-rs1051730 with BMI in the 38 , 913 current smokers ( percentage change −0 . 74 , 95% CI −0 . 97 to −0 . 51 , P = 2 . 00×10−10 ) , consistent with a causal , weight-reducing effect of cigarette smoking on BMI . There was no evidence of association in the 43 , 009 former smokers ( percentage change −0 . 14 , 95% CI −0 . 34 to +0 . 07 , P = 0 . 19 ) . An interaction test indicated that these estimates differed from each other ( P = 4 . 95×10−13 ) . Similar associations were observed for weight ( Table 1 ) and waist circumference ( data available on request ) , but not height ( Ps ≥0 . 27 for all smoking categories ) . Between-study heterogeneity was low ( I2 values ≤36% ) , and there was no evidence for effect modification by sex . Critically , when data were examined without stratification by smoking status no clear evidence of association with BMI was observed ( P = 0 . 22 ) , indicating that a conventional GWAS would have failed to detect this signal . The 0 . 35% per minor allele BMI increase in never smokers represents a change of approximately 0 . 09 kg/m2 . This is smaller than the effect of rs9939609 in FTO ( ∼0 . 4 kg/m2 ) [10] but is comparable in terms of variance explained to the other variants identified by Speliotes and colleagues [1] . As noted above , the rs16969968-rs1051730 variant has not been shown to be associated with smoking initiation in previous GWAS of smoking behaviour [9] . This is also true in our data ( ever smoker versus never smoker: OR per minor allele 1 . 01 , 95% CI 0 . 99 to 1 . 03 , P = 0 . 50 ) , although we observed an association with smoking cessation ( current smoker versus former smoker: OR per minor allele 1 . 08 , 95% CI 1 . 06 to 1 . 10 , P = 1 . 44×10−12 ) , consistent with previous studies [11] . Therefore , we do not believe that these findings are due to collider bias , whereby stratifying on the exposure measure can induce associations between instrument and outcome [12] .
Our results indicate that rs16969968-rs1051730 may be associated with BMI in never smokers , via pathways other than smoking , as well as with heaviness of smoking among current smokers . At this stage we can only speculate as to the mechanism through which rs16969968-rs1051730 may exert a positive effect on BMI in never smokers . In GWAS , the CHRNA5-A3-B4 gene cluster was confirmed to be associated with heaviness of smoking , and downstream health outcomes including lung cancer and peripheral arterial disease [9] , [13] , [14] . It has been shown that the rs16969968 variant is functional and leads to an amino acid change ( D398N ) in the α5 nicotinic acetylcholine receptor ( nAChR ) subunit protein [15] . Animal models indicate that this subunit modulates tolerance to high doses of nicotine [16] . Candidate gene studies have suggested an association of rs16969968-rs1051730 with other substance use phenotypes , such as cocaine use [17] , while other variants in this region have been reported to be associated with alcohol consumption [18] , although the evidence for these associations is currently weak . Therefore , one possibility is that nAChRs play a role in central mechanisms mediating responding to rewarding stimuli in general , which could include natural rewards such as food . It is also notable that rs3743075 , located within the CHRNA3 gene and correlated with rs16969968-rs1051730 ( r2 = 0 . 34 , D′ = 1 . 00 ) , shows association ( N = 974 , P = 9 . 06×10−5 ) with BMI ( defined as <30 kg/m2 vs ≥30 kg/m2 ) ( dbGaP Study Accession: pha003015 . 1 ) . There is evidence from animal models that activation of hypothalamic α3β4 nAChRs leads to activation of pro-opiomelanocortin neurons , and subsequent activation of melanocortin 4 receptors , which have been shown to be critical for nicotine-induced decreases in food intake [19] . Therefore , another possibility is that nAChR sub-units play a role specifically in mediating food intake , through as yet undescribed mechanisms . In other words , the effects we have observed operate via other nAChRs , and other genes in this region ( namely CHRNA3 and CHRNB4 ) may contribute to our finding . Clearly further work is required to explore this possibility . The use of more detailed body composition measures such as percent body fat and its distribution may also serve to refine the nature of the association . Our results , if confirmed , have important implications for the design of future GWAS . The association we observed in never smokers would essentially be undetectable in an unstratified sample , since the effect size observed in the combined sample would require approximately 791 , 000 participants to detect even at an uncorrected P-value of 0 . 05 , and even then would indicate an inaccurate effect size . This is essentially because the effect of rs16969968-rs1051730 on BMI that operates via pathways other than smoking is countered by the weight-reducing effect of smoking . Therefore , since there are roughly twice as many never smokers as current smokers on average across our sample , these two effects negate each other . On the other hand , a sample of approximately 160 , 000 never smokers would be required to detect the effect we observed with genome-wide significance . Assuming the proportions of never , former and current smokers in our sample , this would imply a total sample size of around 350 , 000 . While this is larger than published GWAS of BMI [1] , it is achievable . Therefore , although we cannot say how frequent a scenario such as the one we observed here will be , additional variants may be identified in GWAS stratified by environmental exposures known to have pronounced effects on the phenotype of interest , such as cigarette smoking or physical activity on BMI . The pleiotropic effect of rs16969968-rs1051730 ( or LD of this variant with another variant causally influencing BMI ) , if shown to be robust via replication , has important implications for Mendelian randomisation studies assessing the causal effects of smoking . In this case , we can be reasonably confident that the BMI-reducing effect of the variant operates through smoking because the association with BMI in current smokers is in the opposite direction to the association in never smokers . Furthermore , if the effects on BMI that operate via pathways other than smoking and the effects that operate via the weight-reducing effects of smoking are independent , then the true causal estimate of the magnitude of effect of smoking in reducing BMI is likely to be larger than estimated with this variant . However , some caution must be exercised in conducting and interpreting the results of other Mendelian randomisation analyses using this variant because rs16969968-rs1051730 may influence outcomes through its effects on BMI , instead of or in addition to smoking heaviness . One possible solution is to use genetic variants for BMI as a method of reciprocal randomization to determine the direction of causation within inter-correlated networks of mechanistic pathways ( i . e . , network Mendelian randomisation ) [20] . A limitation to our analysis is that we were only able to control for potential population stratification indirectly in most samples , by restricting analyses to participants of self-reported European ancestry . We were not able to use other methods , such as adjustment for principal components , given that not all contributing studies hold the necessary genetic data . However , we note that the minor allele frequency of the rs16969968-rs1051730 differed only slightly across studies ( between 0 . 30 and 0 . 36 ) . Testing for gene-environment interaction in GWAS is not novel [21] , and examples exist which incorporate smoking status as an environmental factor [22] . However , this remains relatively uncommon , due to methodological challenges ( e . g . , introducing collider bias ) and sample size constraints . A key challenge is the identification of suitable environmental variables on which to stratify GWAS analyses , from the multitude available . We suggest that focusing on environmental factors that are most strongly associated with the phenotype of interest , are likely to have profound biological effects , and which can be characterised in a relatively consistent way across studies , is likely to be the best strategy . Smoking status meets all of these criteria , and the data presented here demonstrate how stratification on well-characterized environmental factors known to impact on health outcomes ( such as smoking status ) may reveal novel genetic associations with health outcomes . As our data indicate , these associations may operate through genetic influences on the environmental factors themselves , or through new pathways which are masked by the environmental factors .
We used data on individuals ( ≥16 years ) of European ancestry ( ascertained via self report , or based on the genome-wide genotype data where available ) from 29 studies in the Causal Analysis Research in Tobacco and Alcohol ( CARTA ) consortium ( http://www . bris . ac . uk/expsych/research/brain/targ/research/collaborations/carta/ ) : the 1958 Birth Cohort ( 1958 BC ) , the Avon Longitudinal Study of Parents and Children ( ALSPAC , including both mothers and children ) , the British Regional Heart Study ( BRHS ) , the British Women's Heart and Health Study ( BWHHS ) , the Caerphilly Prospective Study ( CaPS ) , the Christchurch Health and Development Study ( CHDS ) , the Cohorte Lausannoise ( CoLaus ) study , the Exeter Family Study of Child Health ( EFSOCH ) , the English Longitudinal Study of Ageing ( ELSA ) , FINRISK , the Danish GEMINAKAR twin study , Generation Scotland , the Genomics of Overweight Young Adults ( GOYA ) females , GOYA males , the Helsinki Birth Cohort Study ( HBCS ) , Health2006 , Health2008 , the Nord-Trøndelag health study ( HUNT ) , Inter99 , the Northern Finland Birth Cohorts ( NFBC 1966 and NFBC 1986 ) , MIDSPAN , the Danish MONICA study , the National Health and Nutrition Examination Survey ( NHANES ) , the MRC National Survey of Health & Development ( NSHD ) , the Netherlands Twin Registry ( NTR ) , the Prospective Study of Pravastatin in the Elderly at Risk ( PROSPER ) and Whitehall II . References to these individual studies are available on request . All studies received ethics approval from local research ethics committees ( see Text S1 for full details ) . Within each study , individuals were genotyped for one of two single nucleotide polymorphisms ( SNPs ) in the CHRNA5-A3-B4 nicotinic receptor subunit gene cluster , rs16969968 or rs1051730 . These single nucleotide polymorphisms are in perfect linkage disequilibrium with each other in Europeans ( R2 = 1 . 00 in HapMap 3 , http://hapmap . ncbi . nlm . nih . gov/ ) and therefore represent the same genetic signal . Where studies had data available for both SNPs , we used the SNP that was genotyped in the largest number of individuals . Height ( m ) , weight ( kg ) and waist circumference ( cm ) were assessed within each study , directly measured for 99% of participants , and self-reported for GOYA females ( N = 1 , 015 ) and a sub-set of NTR ( N = 602 ) . Body mass index ( BMI ) was calculated as weight/height2 . Smoking status was self-reported ( either by questionnaire or interview ) . Individuals were classified as current , former , or never cigarette smokers . Where information on smoking frequency was available , current smokers were restricted to individuals who smoked regularly ( typically at least one cigarette per day ) . Where information on pipe and cigar smoking was available , individuals reporting being current or former smokers of pipes or cigars but not cigarettes were excluded from all analyses . For studies with adolescent populations ( ALSPAC children and NFBC 1986 ) , analyses were restricted to current daily smokers who reported smoking at least one cigarette per day ( current smokers ) and individuals who had never tried smoking ( never smokers ) . Descriptive characteristics of smoking frequency data are provided in Text S2 . Analyses were conducted within each contributing study using Stata and R software , following the same analysis plan . Analyses were restricted to individuals with full data on smoking status and rs16969968-rs1051730 genotype . Within each study , genotype frequencies were tested for deviation from Hardy Weinberg Equilibrium ( HWE ) using a chi-squared test . Mendelian randomisation analyses of the association between rs16969968-rs1051730 and BMI were performed using linear regression , stratified by smoking status ( never , former and current ) and sex , and adjusted for age . BMI was log transformed prior to analysis . An additive genetic model was assumed on log values , so that each effect size could be exponentiated to represent the percentage increase in BMI per minor ( risk ) allele . For NHANES , which has a survey design , Taylor series linearization was implemented to estimate variances . For studies including related family members appropriate methods were used to adjust standard errors: in GEMINAKAR , twin pair identity was included as a cluster variable in the model , in MIDSPAN linear mixed effects regression models fitted using restricted maximum likelihood were used to account for related individuals . ALSPAC mothers and children were analysed as separate samples; as there are related individuals across these samples , sensitivity analyses were performed excluding each of these studies in turn . Results from individual studies were meta-analysed in Stata ( version 13 ) using the “metan” command . As I2 values were all equal to or below 36% ( indicating low to moderate heterogeneity ) , fixed effects meta-analyses were performed . The “metareg” command was used to examine whether SNP effects varied by sex and estimates were combined as there was no evidence for effect modification by sex . Evidence for interaction between genotype and smoking status was assessed using the Cochran Q statistic . Data are available from the Institutional Data Access/Ethics Committees of the individual studies that contributed to this analysis , for researchers who meet the criteria for access to confidential data . Full details are provided in Text S3 . Sample size calculations were performed using Quanto software ( http://biostats . usc . edu/Quanto . html ) . The following parameters were used: 80% power to detect associations , minor allele frequency of 0 . 33 , mean and standard deviation for BMI of 25 kg/m2 and 3 . 8 kg/m2 respectively , alpha values of 0 . 05 and 5×10−8 .
|
We found that a single nucleotide polymorphism in the CHRNA5-A3-B4 gene cluster , which is known to influence smoking heaviness , is associated with lower body mass index ( BMI ) in current smokers , but higher BMI in never smokers . This difference in effects suggests that the variant influences BMI both via pathways other than smoking , and via the weight-reducing effects of smoking , in opposite directions . The overall effect on BMI would therefore be undetectable in an unstratified genome-wide association study , indicating that novel associations may be obscured by hidden population sub-structure .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"genetics",
"biology",
"and",
"life",
"sciences",
"human",
"genetics"
] |
2014
|
Stratification by Smoking Status Reveals an Association of CHRNA5-A3-B4 Genotype with Body Mass Index in Never Smokers
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In plants , RNA silencing-based antiviral defense is mediated by Dicer-like ( DCL ) proteins producing short interfering ( si ) RNAs . In Arabidopsis infected with the bipartite circular DNA geminivirus Cabbage leaf curl virus ( CaLCuV ) , four distinct DCLs produce 21 , 22 and 24 nt viral siRNAs . Using deep sequencing and blot hybridization , we found that viral siRNAs of each size-class densely cover the entire viral genome sequences in both polarities , but highly abundant siRNAs correspond primarily to the leftward and rightward transcription units . Double-stranded RNA precursors of viral siRNAs can potentially be generated by host RDR-dependent RNA polymerase ( RDR ) . However , genetic evidence revealed that CaLCuV siRNA biogenesis does not require RDR1 , RDR2 , or RDR6 . By contrast , CaLCuV derivatives engineered to target 30 nt sequences of a GFP transgene by primary viral siRNAs trigger RDR6-dependent production of secondary siRNAs . Viral siRNAs targeting upstream of the GFP stop codon induce secondary siRNAs almost exclusively from sequences downstream of the target site . Conversely , viral siRNAs targeting the GFP 3′-untranslated region ( UTR ) induce secondary siRNAs mostly upstream of the target site . RDR6-dependent siRNA production is not necessary for robust GFP silencing , except when viral siRNAs targeted GFP 5′-UTR . Furthermore , viral siRNAs targeting the transgene enhancer region cause GFP silencing without secondary siRNA production . We conclude that the majority of viral siRNAs accumulating during geminiviral infection are RDR1/2/6-independent primary siRNAs . Double-stranded RNA precursors of these siRNAs are likely generated by bidirectional readthrough transcription of circular viral DNA by RNA polymerase II . Unlike transgenic mRNA , geminiviral mRNAs appear to be poor templates for RDR-dependent production of secondary siRNAs .
RNA silencing directed by miRNAs , short interfering ( si ) RNAs and PIWI-interacting RNAs is involved in regulation of gene expression and chromatin states and in defense against invasive nucleic acids such as transposons , transgenes and viruses [1]–[3] . Virus-infected plants accumulate high levels of viral siRNAs ( vsRNAs ) of three major size-classes: 21-nt , 22-nt and 24-nt [4] , [5] . In Arabidopsis thaliana infected with DNA viruses , all four Dicer-like ( DCL ) enzymes are involved in processing of vsRNA duplexes from longer double-stranded RNA ( dsRNA ) precursors: DCL4 and DCL1 generate 21-nt class , DCL2 generates 22-nt class and DCL3 generates 24-nt class; 21-nt and 24-nt vsRNAs accumulate at higher levels than 22-nt vsRNAs [6]–[8] . By contrast , in RNA virus-infected Arabidopsis , DCL4-dependent 21-nt vsRNAs and/or DCL2-dependent 22-nt vsRNAs are the most abundant species , whereas DCL3-dependent 24-nt vsRNAs accumulate at much lower levels [7] , [9] , [10] . This reflects the difference in viral life cycles: DNA viruses transcribe their genomes in the nucleus , whereas RNA viruses are generally restricted to the cytoplasm . Likewise , plant endogenous genes and transgenes that undergo transcriptional silencing spawn predominantly DCL3-dependent 24-nt siRNAs , whereas those that undergo post-transcriptional silencing spawn predominantly DCL4-dependent 21-nt siRNAs and , in certain cases , DCL2-dependent siRNAs [1] , [11] , [12] . In endogenous and transgene-induced silencing pathways , dsRNA precursors of siRNAs can be generated by RNA-dependent RNA-polymerase ( RDR ) . The Arabidopsis thaliana genome encodes six RDRs , three of which have been implicated in siRNA biogenesis [13] . RDR2 is required for biogenesis of 24-nt heterochromatic siRNAs ( hcsiRNAs ) mainly originating from repetitive DNA loci including transposons . RDR6 is required for biogenesis of trans-acting siRNAs ( tasiRNAs ) , natural antisense transcript siRNAs and siRNAs derived from posttranscriptionally-silenced transgenes [1] . RDR6 is also involved in production of secondary siRNAs from some protein-coding genes targeted by miRNAs [14] , [15] . RDR1 has so far been implicated in viral siRNA biogenesis ( see below ) and its function in endogenous or transgene-induced silencing is not known . Presumptive single-stranded RNA templates for RDR2 are produced by plant-specific RNA polymerases Pol IV and/or Pol V , but little is known about Pol IV and Pol V transcripts and RDR2-dependent dsRNAs [16] . dsRNA precursors of tasiRNAs originate from Pol II transcripts of TAS genes , which are cleaved by a miRNA::Argonaute ( AGO ) protein complex [17]–[20] . Either the 3′ cleavage product or the 5′ cleavage product is converted by RDR6 to dsRNA: RDR6 recruitment to only one of the two cleavage products is determined by 22-nt size of the initiator miRNA produced from a bulged hairpin precursor [21]–[23] or a second binding site of the miRNA::AGO complex [17] , [19] , respectively . The possible role of RDRs in vsRNA biogenesis has been extensively studied using A . thaliana single , double and triple null mutants for RDR1 , RDR2 and RDR6 [8] , [24]–[28] . These studies produced rather conflicting results , but in many cases , wild type viruses were shown to predominantly spawn RDR-independent vsRNAs [29] . However , mutant RNA viruses with deletion or point mutation in the viral silencing suppressor gene spawn RDR6- and/or RDR1-dependent vsRNAs [26]–[28] . As a consequence the suppressor-deficient RNA viruses could establish systemic infection only on A . thaliana mutant plants lacking RDR6 and/or RDR1 activity . Nevertheless , suppressor-deficient RNA viruses spawn substantial amounts of RDR-independent vsRNAs . Thus , one of the major precursors of RNA virus-derived vsRNAs is likely a double-stranded replicative intermediate , transiently produced by viral RNA-dependent RNA-polymerase ( vRdRP ) . Primary vsRNAs generated from such precursors may trigger RDR-dependent production of secondary siRNAs . Plant DNA viruses do not encode a vRdRP . However , the biogenesis of DNA virus-derived vsRNAs does not appear to involve host RDRs . Thus , Cauliflower mosaic virus ( CaMV ) -derived vsRNAs of all major classes accumulate at comparable high levels in A . thaliana wild-type and rdr1 rdr2 rdr6 triple mutant plants and their long dsRNA precursors are likely generated by Pol II [8] . The lack of RDR-dependent vsRNAs can be explained by the ability of a CaMV silencing suppressor protein to interfere with DCL4-mediated processing of dsRNAs produced by RDR6 [30] , [31] . Silencing suppressor proteins of DNA geminiviruses have not been reported to interfere with RDR activity or DCL-mediated processing of RDR-dependent dsRNAs . In A . thaliana null mutants for Pol IV , RDR2 , or RDR6 activity , the biogenesis of vsRNAs from Cabbage leaf curl virus ( CaLCuV; a member of genus Begomovirus of the family Geminiviridae ) was not affected , suggesting that RDR2 and RDR6 are not involved in production of dsRNA precursors of vsRNAs [7] . However , involvement of RDR1 in this process or possible redundancy in activities of distinct RDRs were not investigated so far . Geminiviruses encapsidate circular single-stranded ( ss ) DNA of ca . 2 . 5-to-2 . 7 kb in geminate virions and accumulate in the nucleus as multiple circular dsDNA minichromosomes . The minichromosomes are both the intermediates of rolling circle replication and the templates for Pol II-mediated bidirectional transcription [32] . Like many members of the genus Begomovirus , CaLCuV has a bipartite genome comprising 2 . 6 kb DNA-A and 2 . 5 kb DNA-B [33] . The DNA-A encodes proteins involved in replication ( AC1 and AC3 ) , transcription ( AC2 ) and encapsidation ( AV1 ) , while the DNA-B encodes BC1 and BV1 proteins with movement functions . A large intergenic region on DNA-A and DNA-B contains a 192 bp common region of nearly identical sequence with the origin of replication and bidirectional promoter elements . By analogy with other begomoviruses [34] , the bidirectional promoter is expected to drive Pol II transcription of the leftward ( AC1/AC4/AC2/AC3 and BC1 ) and rightward ( AV1 and BV1 ) genes . In addition , a monodirectional promoter is expected to drive Pol II transcription of a short AC2/AC3 transcript , which is co-terminal with the long AC1/AC4/AC2/AC3 transcript . On both DNAs , the leftward and rightward transcription is terminated by poly ( A ) signals located in a close vicinity on the virion ( sense ) and complementary ( antisense ) strands , respectively . In CaLCuV DNA-A , this juxtaposition of the poly ( A ) signals creates a ca . 25-nt overlap of the sense and antisense transcripts . Such overlap was proposed to form a dsRNA precursor of primary vsRNAs [35] , which may initiate RDR-dependent production of vsRNAs from other regions of the viral transcripts . Such phenomenon of transitivity has been described for posttranscriptional and transcriptional silencing of a transgene targeted by vsRNAs ( virus-induced gene silencing; VIGS ) or by primary siRNAs derived from an inverted-repeat transgene . In these cases , RDR6- or RDR2-dependent production of secondary siRNAs outside of the target region was detected , respectively [36] , [37] . Notably , posttranscriptional silencing of endogenous plant genes by virus- or transgene-derived primary siRNAs was not associated with secondary siRNA production [36] , [38] , [39] , suggesting that endogenous mRNAs are not good templates for RDRs . In this study , we used Illumina deep sequencing of short RNAs , combined with blot hybridization and genetic analysis , to investigate the biogenesis of primary and secondary siRNAs . To this end , Arabidopsis wild-type , RDR-mutant and transgenic plants were infected with CaLCuV or its derivatives carrying fragments of an endogenous gene or a transgene . We found that , like most endogenous plant mRNAs , viral mRNAs are not prone to transitivity: the majority of vsRNAs are RDR1- , RDR2- and RDR6-independent primary siRNAs . By contrast , a transgene mRNA targeted by primary vsRNAs is subject to RDR6-dependent production of secondary siRNAs . We also found that silencing of the transgene driven by a CaMV 35S promoter can be triggered by primary vsRNAs targeting an enhancer ( but not core promoter ) region and this , presumably transcriptional , silencing was not associated with accumulation of secondary siRNAs .
To analyze begomovirus interactions with the host small RNA ( sRNA ) -generating silencing pathways , we deep-sequenced sRNA populations from mock-inoculated and CaLCuV-infected A . thaliana wild-type ( Col-0 ) plants and CaLCuV-infected rdr1 rdr2 rdr6 triple null mutant plants ( rdr1/2/6 in Col-0 background; [8] ) . The protocol was designed to sequence short RNAs with 5′-phosphate and 3′-hydroxyl groups , which include DCL products . Samples of total RNA extracted from pools of three plants were processed in parallel and the resulting cDNA libraries sequenced in one channel of an Illumina Genome Analyzer , thus allowing quantitative comparison of changes in the profile of host sRNAs upon virus infection and the profile of vsRNAs in wild-type versus mutant plants . A total number of reads in the high-coverage libraries was ranging from 9 . 3 to 10 . 4 million , of which 7 . 3 million ( ‘Col-0 mock’ ) , 5 . 3 million ( ‘Col-0 CaLCuV’ ) and 5 . 0 million ( ‘rdr1/2/6 CaLCuV’ ) of 20–25 nt reads mapped to the Arabidopsis thaliana Col-0 or CaLCuV genomes with zero mismatches ( Table S1A ) . Two additional low-coverage libraries with 0 . 45 million ( ‘Col-0 mock*’ ) and 0 . 43 million ( ‘Col-0 CaLCuV*’ ) of 20–25 nt reads with zero mismatches ( Table S1A ) were obtained in an independent experiment . In mock-inoculated plants , most of the 20–25 nt sRNAs mapped to the A . thaliana genome ( Figure 1A; Table S1A ) . The 24-nt and 21-nt classes were predominant ( 35% and 28% , respectively ) , whereas other size-classes were less abundant ( 23-nt – 19%; 22-nt – 8%; 20-nt – 7%; 25-nt – 3% ) ( Figure 1B ) . This is consistent with the previous studies showing that 24-nt hcsiRNAs and 21-nt miRNAs are the most abundant sRNA classes in A . thaliana [40] , [41] . Upon CaLCuV infection , the host sRNA profile was slightly altered in that the 21-nt class became the largest ( 32% ) and the 24-nt class the second largest ( 28% ) ( Figure 1B; Table S1A ) . A similar shift in the host sRNA profile was also detected in the low coverage experiment ( Table S1A ) . By contrast , A . thaliana infection with the pararetrovirus CaMV results in overaccumulation of 24-nt host sRNAs [8] . The biological significance of the opposite effects of geminivirus and pararetrovirus infections on host sRNAs remains to be investigated . In CaLCuV-infected Col-0 plants , a large fraction of 20–25 nt reads mapped to the virus genome with zero mismatches ( ca . 32% and 62% in the high- and low-coverage libraries , respectively; Figure 1A and Table S1A ) . Notably , the viral DNA-B was the major source of vsRNAs ( 70% and 85% of 20–25 nt viral reads , respectively; Table S1A ) . On both DNA-A and DNA-B , vsRNA reads were almost equally distributed between the virion and complementary strands ( Table S1A; Figures 2 and S1 ) . Similar to the host sRNAs in infected plants , 21-nt and 24-nt vsRNAs represent the first ( 42% ) and the second ( 31% ) largest fractions of 20–25 nt viral reads , respectively . But unlike the host sRNAs , 22-nt viral reads represent the third largest fraction ( 18% ) , while 20-nt , 23-nt and 25-nt classes are significantly underrepresented ( Figure 1C ) . This size-class profile of CaLCuV vsRNAs agrees with our blot hybridization analysis using short probes and confirms the involvement of distinct DCLs in vsRNA biogenesis ( Figure S2; [7] ) . Interestingly , the host sRNAs of 21-nt and 24-nt classes exhibit a strong bias to 5′-terminal uridine ( 5′U; 69% ) and 5′-terminal adenosine ( 5′A; 52% ) , respectively ( Table S1A ) , owing to the preferential association of miRNAs with AGO1 and hcsiRNAs with AGO4 [17] , [42]–[44] . By contrast , vsRNAs of 21-nt and 24-nt classes are less strongly enriched in 5′U ( 46% ) and 5′A ( 32% ) , respectively , and the second most dominant nucleotide is 5′A for 21-nt class ( 25% ) and 5′U for 24-nt class ( 32% ) ( Table S1A ) . Both the diversity in nucleotide composition and size of CaLCuV vsRNAs and the lack of any strong 5′-nucleotide bias imply the involvement of multiple AGOs in sorting vsRNAs . Inspection of single-nucleotide resolution maps of 20–25 nt vsRNAs revealed that unique vsRNA species of each major class ( 21-nt , 22-nt and 24-nt ) cover the entire genome of CaLCuV in both sense and antisense polarity as dense tiling arrays without gaps on the circular sequences of 2583 bp DNA-A and 2513 bp DNA-B ( Tables S2 and S3 ) . Hence , dsRNA precursors of vsRNAs of each class should cover the entire circular viral DNAs . However , the relative abundance of vsRNAs varies drastically: several large regions of DNA-A and DNA-B are densely covered in both polarities with vsRNA hotspots ( defined here arbitrarily as short sequence segments spawning several vsRNA species with more than 300 reads each ) ( Figure 2 and Figure S1 ) . This implies the existence of several overlapping dsRNA precursors that accumulate at high and low levels . Interestingly , vsRNA hotspots on both virion and complementary strands are interrupted with short sequences that spawn vsRNAs of lower abundance ( Figure 2 and Figure S1; Table S2 and Table S3 ) . This implies differential stability of vsRNA duplexes processed consequently from ends of long dsRNA precursors or , alternatively , preferential internal excisions of vsRNA duplexes from certain regions of a long dsRNA . We also found that most vsRNA hotspots contain all the three major size-classes of vsRNAs ( Figure S1; Table S2 and Table S3 ) , indicating that same dsRNA precursors are processed by different DCLs . This conclusion is consistent with our genetic analysis coupled with blot-hybridization of DNA virus-derived sRNAs [6] , [7] ( Figure S2 ) and sRNA deep-sequencing studies of other viruses [8] , [45]–[48] . In DNA-A , the most abundant vsRNAs of both sense and antisense polarities , which include those with more than 1000 reads , originate from the AV1 ORF ( Figure 2A and Figure S1A ) . The left border of this vsRNA hotspot region is at position 331 ( Table S2 ) , where the transcription start site can be predicted , i . e . at an optimal distance downstream of the TATA box ( TATATAA at positions 228–305 ) and 9 nts upstream of the AV1 start codon ( 339–341 ) . The right border of this vsRNA hotspot is at around position 1060 ( Table S2 ) , i . e . just upstream of the AV1 stop codon ( 1092–1094 ) . After a short gap of 55 bp ( 1061–1116 ) lacking highly abundant vsRNAs , a large region spanning all the leftward ORFs is also covered with vsRNA hotspots , albeit at lower density than in the AV1 region . In this region , the most abundant vsRNAs originate from the large portion of the AC1 ORF including the nested AC4 ORF and less abundant vsRNAs from the AC2 ORF ( Figure 2A; Table S2 ) . Notably , the 25 nt region ( 1089–1113 ) , in which the rightward ( AV1 ) and the leftward ( AC1/AC4/AC2/AC3 and AC2/AC3 ) viral mRNAs are expected to overlap and potentially form a dsRNA substrate for DCL , is not a vsRNA hotspot . Likewise , the 240 bp intergenic region between the predicted leftward and rightward transcription start sites ( at positions 93 and 331 , respectively ) , which contains the bidirectional promoter elements and overlaps the common region ( 22–213 ) , is also devoid of vsRNA hotspots: it has only two islands covered with vsRNAs of 100–250 reads . Furthermore , the promoter region in front of the predicted transcription start site of AC2/AC3 mRNA ( position 1651 , downstream of TATATAA at 1683–1677 ) does not contain any prominent vsRNA hotspots ( Figure 2A and Figure S1A; Table S2 ) . Taken together , the promoter and terminator regions of CaLCuV DNA-A are devoid of highly abundant vsRNAs . Thus , the virus may have evolved a mechanism to evade transcriptional silencing which could potentially be directed by vsRNAs . In DNA-B , two large regions are covered with extreme hotspots containing multiple vsRNA species with more than 1000 reads on both sense and antisense strands . The first is located downstream of the common region and it spans a large portion of the BV1 ORF . The second is located upstream of the common region and it spans a large portion of the BC1 ORF ( Figure 2B and Figure S1B; Table S3 ) . Like in DNA-A , the terminator region of rightward ( BV1 ) and leftward ( BC1 ) genes is devoid of vsRNA hotspots . Note that the DNA-B poly ( A ) signals AATAAA are located at positions 1305–1310 and 1356–1361 of the virion and complementary stands , respectively , and therefore the BV1 and BC1 mRNAs are not expected to overlap . A predicted BC1 promoter region with the TATA-box at positions 2471–2463 ( TATATAA ) is devoid of vsRNA hotspots and the border of the vsRNA hotspot region corresponds to the predicted transcription start site at 2439 . Thus , BC1 mRNA can form one of the strands of a vsRNA precursor . In contrast , a predicted BV1 promoter region with the TATA-box at position 442–447 ( TATATAA ) is covered with vsRNA hotspots on both strands . This suggests that the region upstream of the BV1 ORF might be actively transcribed . Interestingly , it contains an ORF at positions 319 to 471 ( Figure 2B ) . Such active transcription could in turn lead to production of abundant vsRNAs that can potentially direct transcriptional silencing of the BV1 promoter . This may represent either a host antiviral defense or a viral strategy of gene regulation . Based on close inspection of cold versus hot spots of viral siRNAs , AU-rich sequences can generally be considered as a poor source of siRNAs , possibly owing to relatively low stability of AU-rich siRNA duplexes processed by DCLs from long dsRNA precursors . Other features of RNA primary or secondary structure which might potentially influence siRNA biogenesis or stability remain to be further investigated . The Arabidopsis sRNA profile is drastically altered in rdr1/2/6 triple mutant compared to wild-type plants: 24-nt and 23-nt classes are selectively and strongly reduced , mainly owing to the loss of RDR2-dependent hcsiRNAs [40] . Thus , 21-nt class becomes the most predominant , followed by 20-nt and 22-nt classes ( Table S1A ) : these three classes are mainly populated with RDR-independent miRNAs , whereas RDR6-dependent tasiRNAs and secondary siRNAs are much less abundant [41] . By contrast , the CaLCuV vsRNA profile was only slightly altered in rdr1/2/6 compared to wild-type ( Figure 1C ) . The overall accumulation level of 20–25 nt vsRNAs was higher in rdr1/2/6 than wild-type plants . If normalized by the levels of 21-nt host sRNAs ( 1 . 22 million in ‘Col-0 CaLCuV’ versus 1 . 21 million in ‘rdr1/2/6 CaLCuV’ ) , this ca . 1 . 5-fold increase is mainly owing to higher accumulation of DNA-B vsRNAs of all the major classes ( Table S1A; Figure 1A ) . The single-nucleotide resolution maps of vsRNAs from Col-0 and rdr1/2/6 are remarkably similar . The vsRNA hotspots occur in the same regions and the relative abundance of vsRNA species is very similar within most hotspots ( Figure 2 and Figure S1; Table S2 and Table S3 ) . For DNA-A , the levels of 20–25 nt vsRNAs derived from the AC2 hotspot region are relatively lower in rdr1/2/6 than in Col-0 , whereas those derived from the AV1 region are generally similar in rdr1/2/6 and Col-0 ( Figure 2A ) , with an exception of 24-nt vsRNAs that accumulate at relatively higher levels in rdr1/2/6 ( Figure S1A; Table S1A ) . For DNA-B , the levels of 20–25 nt vsRNAs in most hotspots are 1 . 5- to 2 . 5-fold higher in rdr1/2/6 than in Col-0 , with an exception of the middle part and the 3′ part of BV1 ORF , in which vsRNA levels are generally similar in rdr1/2/6 and Col-0 or , at some locations in the 3′ part , lower in rdr1/2/6 ( Figure 2B ) . No drastic difference in the relative abundance of vsRNA size-classes along the DNA-B sequence was observed ( Figure S2B; Table S3 ) . Analysis of 5′-terminal nucleotides of vsRNAs revealed no substantial difference between Col-0 and rdr1/2/6 ( Table S1A ) , further supporting that vsRNA biogenesis is not drastically affected by null mutations in RDR1 , RDR2 and RDR6 . The above-described deep sequencing findings for vsRNA size-classes , relative abundance and distribution along the viral genome and RDR1/2/6-independence of vsRNA biogenesis were confirmed by blot hybridization analysis of sRNAs from CaLCuV-infected wild-type and rdr1/2/6 mutant plants using several short probes specific to DNA-A or DNA-B ( Figure S2 and Figure 3B ) . In addition , analysis of CaLCuV-infected dcl1 dcl2 dcl3 dcl4 quadruple mutant plants ( dcl1/2/3/4 ) confirmed our previous findings that the majority of vsRNAs are generated by four DCLs [7] . We further established that a mutant DCL1 protein produced from the dcl1-9/caf1 allele in dcl1/2/3/4 plants [8] appears to be capable of generating 21-nt vsRNA from dsRNA precursors derived from vsRNA hotspot regions of DNA-B ( Figure S2 ) . Likewise , a major fraction of 21-nt vsRNAs derived from the leader region of CaMV , which is an extreme hotspot of 21-24 nt vsRNA production , requires DCL1 for their biogenesis and residual accumulation of 21-nt vsRNAs was observed in dcl1/2/3/4 [8] . Taken together , our findings indicate that CaLCuV vsRNA biogenesis does not require RDR1 , RDR2 , or RDR6 . However , there appears to be a quantitative difference in relative abundance of dsRNA precursors derived from the vsRNA hotspot regions of DNA-A and DNA-B in wild-type versus rdr1/2/6 plants . To test if the observed differences in relative abundance of vsRNAs correlate with relative levels of viral transcripts and/or viral DNA , we measured the accumulation of viral long nucleic acids in wild-type and rdr1/2/6 plants by RNA and DNA blot hybridization as well as real time PCR ( Figure 3 ) . The results of total RNA ( Figure 3A ) and polyadenylated mRNA ( Figure 3D ) analyses revealed that the relative accumulation of viral transcripts positively correlates the relative abundance of vsRNAs in the major hot spot regions . Indeed , AV1 mRNA , the most readily detectable viral transcript , accumulated at slightly higher levels in rdr1/2/6 than wild type plants , whereas accumulation of the less abundant AC2/AC3 mRNA was slightly reduced in rdr1/2/6 . This resembles the profile of DNA-A derived vsRNAs and its alteration in rdr1/2/6 . Furthermore , accumulation of BC1 and BV1 polyadenylated mRNAs was increased ca . 1 . 2- and 1 . 4-fold , respectively , in rdr1/2/6 compared to wild type plants , which correlates with slightly increased accumulation of DNA-B derived vsRNAs in rdr1/2/6 . Notably , in addition to viral mRNAs , shorter viral transcripts also accumulate at high levels and appear as a smear on the total RNA blot ( Figure 3A ) . These aberrant RNAs may represent degradation products of viral mRNAs or prematurely terminated viral transcripts . In the case of DNA-B , the aberrant RNAs appear to be much more abundant than BV1 and BC1 mRNAs , since the latter are barely detectable ( Figure 3A ) . This correlates with much higher accumulation of vsRNAs from DNA-B than DNA-A ( Figure 1A ) . The higher abundance of aberrant RNAs transcribed from DNA-B can be explained by higher accumulation of total DNA-B compared to total DNA-A as estimated by Southern ( Figure 3C ) . Real time PCR analysis ( Figure 3D ) revealed that total viral DNA accumulates at higher levels in rdr1/2/6 compared to wild type plants ( ca . 1 . 4- and 2-fold increase for DNA-A and DNA-B , respectively ) . However , Southern blot hybridization analysis ( Figure 3C ) showed that this increase is mainly owing to increased accumulation of viral single-stranded DNA ( ssDNA ) . By contrast , the levels of viral dsDNA , which serves as a template for both transcription and replication , are similar in wild type and rdr1/2/6 plants . Thus , rolling circle and/or recombination-dependent replication mechanisms [32] produce increased levels of viral ssDNA ( but not dsDNA ) in the absence of RDR1 , RDR2 and RDR6 . This finding implicates an RDR activity in the regulation of geminiviral DNA replication . Interestingly , homologous recombination-dependent , double-stranded DNA brake ( DSB ) repair in Arabidopsis involves DSB-induced small RNAs ( diRNAs ) [49] . RDR2 and RDR6 play redundant roles in the biogenesis of diRNAs , implicating RDR activity in DSB repair . Our above-described results suggested that CaLCuV vsRNAs are primary siRNAs ( i . e . RDR-independent ) and that secondary siRNAs ( i . e . RDR-dependent ) may comprise only a small fraction of vsRNAs ( if any ) . To investigate if primary vsRNAs are capable of triggering production of secondary siRNAs in CaLCuV-infected plants , we used a virus-induced gene silencing ( VIGS ) vector based on the CaLCuV DNA-A derivative lacking most of the AV1 ORF sequence ( positions 350–1032 ) [50] . When a 354 bp fragment of the A . thaliana Chlorata I ( ChlI/CH42; At4g18480 ) gene ORF is inserted in place of the AV1 ORF , the resulting recombinant virus CaLCuV::Chl knocks down ChlI mRNA levels in all tissues of CaLCuV::Chl-infected A . thaliana plants [7] and causes whitening of newly growing tissues due to the loss of chlorophyll ( “chlorata” phenotype; [50] ) . The recombinant virus spawns abundant 21 , 22 , and 24 nt siRNAs from the ChlI insert , whose biogenesis does not require RDR6 or RDR2 . However , an extensive chlorata phenotype is nearly abolished in rdr6 and dcl4 null mutant plants [7] , suggesting that RDR6-/DCL4-dependent secondary siRNAs might be involved in total silencing the ChlI gene . To test this hypothesis we deep-sequenced sRNAs from CaLCuV::Chl-infected Col-0 plants exhibiting an extensive chlorata phenotype . Of 2 . 28 million total 20–25 nt reads , 1 . 58 million mapped to the A . thaliana genome and 0 . 61 million to CaLCuV::Chl genome ( A+B ) with zero mismatches . Of the latter reads , 0 . 45 million originate from the circular CaLCuV::Chl DNA and 0 . 16 million from DNA-B ( Table S1B ) . This is in contrast to our above observation for wild-type CaLCuV which spawns more abundant vsRNAs from DNA-B . Inspection of the single-nucleotide resolution map of 20–25 nt sRNAs perfectly matching to a 3298 bp region of the A . thaliana genome , which contains the ChlI gene , revealed that of the 109′098 redundant reads , 109′002 originate from the 354 bp segment ( positions 1192–1545 ) that corresponds exactly to the ChlI segment inserted in CaLCuV::Chl . The remaining sRNAs ( 91 reads ) originate mostly from the ChlI sequence downstream of this segment ( Figure 4; Table S1B and Table S4 ) . We conclude that accumulation of secondary siRNAs outside of the vsRNA target region is negligible compared to primary siRNAs . This is consistent with the previous studies that detected no transitivity when endogenous plant genes were knocked down by RNA virus- or transgene-induced silencing [36] , [38] , [39] . Within the ChlI target region the sRNA profile resembles the global profile of CaLCuV vsRNAs in that the three size-classes are predominant ( 21-nt – 30%; 22-nt – 25%; 24-nt – 38% ) . However , the distribution of sRNAs is unequal between the strands: 80% of 20–25 nt reads map to the coding strand , and 21-nt and 22-nt classes derived from the coding strand are equally abundant ( 28% each ) . This strong bias is due to a bigger number of sRNA hotspots and higher accumulation levels of sRNA species within the hotspots on the coding strand ( Figure 4; Table S4 ) . The significance of this bias for ChlI silencing remains to be investigated . In A . thaliana , the ChlI gene has a close homolog ChlI-2 ( At5g45930 ) , silencing of which is likely required for the chlorata phenotype . To address if potential silencing of ChlI-2 is associated with secondary siRNA production we created a map of ChlI-2 sRNAs ( Figure S3A ) . Of 3′093 reads of 20–25 nt sRNAs matching the ChlI-2 genomic locus with zero mismatches in CaLCuV::Chl-infected plants , 2′987 reads map within the 354 bp VIGS-target sequence and only 104 ( ca . 3% ) map downstream of the target . Moreover , within the target sequence almost all the reads ( 2′977 ) match two sequence stretches of >20 nts in length which are identical in ChlI and ChlI-2 ( Figure S3A; Table S4 ) . Thus , similar to ChlI , only small amounts of secondary siRNAs are generated on ChlI-2 target gene . Presently , we cannot exclude that these small amounts of secondary siRNAs are required for total chlorata silencing . As we hypothesized earlier [7] , total Chl silencing is likely established in newly emerging leaves by mobile RDR6- and DCL4-dependent Chl siRNAs . Recent studies indicate that 21–24 nt siRNAs act as mobile silencing signals and can direct mRNA cleavage and DNA methylation in recipient cells , even though they accumulate in recipient tissues at much lower levels than in source tissues [51] , [52] . Notably , vsRNAs targeting ChlI-2 mRNA at two potentially cleavable sites separated by ca . 100 nts do not trigger any robust secondary siRNA production from the intervening region . This indicates that a two-hit model for the RDR6-dependent biogenesis of tasiRNAs and other secondary siRNAs [14] , [19] , [53] does not apply for ChlI-2 and ChlI . Like in the wild-type DNA-A , vsRNAs cover the entire circular CaLCuV::Chl DNA in both orientations without gaps ( Table S4 ) . However , vsRNA hotspots are more evenly distributed along the CaLCuV::Chl sequence compared to the wild-type DNA-A: in fact , new hotspots appear in the intergenic region between the transcription start sites as well as in the terminator region ( Figure S3; Table S4 ) . This finding was confirmed by blot hybridization ( Figure S2 , compare CaLCuV wt and CaLCuV::Chl ) . Furthermore , genetic analysis revealed that production of vsRNAs from any region of CaLCuV::Chl including the ChlI insert does not require RDR6 or RDR2 , since vsRNAs of all classes accumulated at similar levels in wild type and rdr2 rdr6 double mutant plants ( rdr2/6; Figure S2 ) . The latter finding indicates that RDR6-dependent secondary siRNA production does not occur within the VIGS target region and that potential cleavage of endogenous ( ChlI or ChlI-2 ) and CaLCuV mRNAs at two sites is not sufficient to attract RDR6 activity . Taken together , our findings for both wild-type and CaLCuV::Chl viruses suggest that dsRNA precursors of vsRNAs originate from the entire circular viral DNAs including “non-transcribed” intergenic regions . Therefore , these precursors might be produced by Pol II-mediated readthrough transcription far beyond the poly ( A ) signals , thus encircling the viral DNA in sense and antisense orientation . It can be further suggested that such readthrough transcription is more efficient on CaLCuV::Chl DNA-A than wild-type DNA-A , owing to the smaller size and the chimeric configuration of the rightward transcription unit carrying the ChlI segment . This would explain prominent hotspots in the promoter and terminator regions and also much higher production of vsRNAs from CaLCuV::Chl DNA-A than DNA-B , which is not the case for wild-type CaLCuV . Notably , CaLCuV::Chl is an attenuated virus which produces much less severe symptoms than wild type CaLCuV [49] . Whether vsRNA-directed silencing contributes to the attenuated symptom development of this recombinant virus remains to be investigated . The apparent paucity of secondary siRNAs derived from CaLCuV mRNAs or ChlI and ChlI-2 mRNAs could be explained by two scenarios . In the first scenario , the products of potential vsRNA-directed cleavage of host and viral mRNAs are not optimal templates for RDR activity . In the second one , CaLCuV infection blocks RDR activity and thereby prevents RDR-dependent amplification of siRNAs . To distinguish between these scenarios , we used the CaLCuV VIGS vector for targeting a transgene in the A . thaliana line L2 expressing green fluorescence protein ( GFP ) under the control of the CaMV 35S promoter and terminator ( 35S::GFP; [54]; Figure 5 ) . Like other transgenes , 35S promoter-driven GFP transgenes in A . thaliana and N . benthamiana are prone to transitivity in which secondary siRNAs are generated outside of the region targeted by primary sRNAs [36] , [38] , [55] . An aberrant nature of transgenic transcripts appears to attract RDR activity . We inserted in the CaLCuV vector a full-length ( FL ) , 771 bp GFP coding sequence ( designated ‘CodFL’ ) or 30-bp sequences of the GFP transgene transcribed region . The latter is defined here as the GFP mRNA region from the transcription start site to the mRNA processing/poly ( A ) addition site . As depicted in Figure 5 , the short inserts included the sequences from within the 5′-untranslated region ( 5′UTR ) ( designated ‘Lead’ ) , the beginning , middle and end of the coding sequence ( ‘CodB’ , ‘CodM’ and ‘CodE’ ) , and the 3′UTR ( ‘Trail’ and ‘PolyA’ ) and the sequences surrounding the ATG start codon ( ‘Start’ ) or the TAA stop codon ( ‘Stop’ ) . Inoculation of L2 plants with the resulting recombinant viruses by biolistic delivery of viral DNA led to development of local GFP silencing on inoculated leaves followed by systemic GFP silencing on newly-emerging infected tissues ( both leaves and inflorescence; Figure S4B ) . GFP silencing in infected tissues , which was manifested under UV light as red fluorescence areas on otherwise green fluorescent tissues ( Figure 5B and Figure S4B ) , well correlated with knockdown of GFP mRNA levels as measured by real time PCR ( Figure S4D ) . All the recombinant viruses carrying an insert from the GFP transcribed region induced systemic GFP silencing , although to various degrees ( Figure 5B ) . Furthermore , in all these cases , GFP silencing correlated with accumulation of GFP siRNAs derived from both the short insert/target sequences and the GFP mRNA sequences outside of the target sequence ( Figure 5C and Figure S4C ) . Notably , the 30 bp GFP insert/target sequences generally gave rise to abundant siRNAs of 21-nt , 22-nt and 24-nt classes , resembling those derived from the virus genome and therefore likely originating from the replicating virus carrying the insert rather than from the transgene . By contrast , secondary siRNAs derived from non-target sequences of the GFP transgene were generally represented by a dominant 21-nt class , although 22-nt and 24-nt classes were also detected ( Figure 5C; also see below ) . Furthermore , targeting the GFP sequences upstream of the translation stop codon ( Lead , Start , CodB , CodM and CodE ) induced the production of abundant secondary siRNAs exclusively from sequences downstream of the target site , whereas targeting the 3′UTR sequences ( Stop , Trail and PolyA ) resulted in secondary siRNAs from the sequences upstream and downstream of the target site ( Figure 5C ) . Such directionality in secondary siRNA biogenesis resembles that in RDR6-/DCL4-dependent biogenesis of tasiRNAs [17] , [18] . Our findings further suggest that , following vsRNA-directed cleavage of GFP mRNA , the 5′-cleavage product might be protected by translating ribosomes from being converted to dsRNA precursor of secondary siRNAs . However , if it contains the translation stop codon , the ribosomes can terminate translation and be released . Thus , following vsRNA-directed cleavage downstream of the stop codon , both 5′ and 3′ cleavage products of GFP mRNA enter the secondary siRNA-generating pathway . The above findings based on blot hybridization analysis ( Figure 5C ) were fully validated by Illumina sequencing of sRNAs from L2 plants infected with Lead , CodM , Trail and polyA viruses ( Figure 6 and Figure S5; Table S5 and Table S6 ) . In addition , analysis of the deep sequencing data showed that vsRNAs targeting the 3′UTR induce production of much more abundant secondary siRNAs from the region upstream of the target site than from downstream sequences ( Figure 6 ) . Interestingly , secondary siRNA hotspots are non-randomly distributed along the GFP transcribed region: in all the four cases the siRNA hotspots occur in the region comprising the 3′ portion of the GFP ORF and the beginning of the 3′UTR . The size-class profile and relative abundance of siRNA species in this siRNA hotspot region are very similar . In the case of Lead and polyA viruses , additional siRNA hotspots occur in the middle of GFP ORF and the 3′UTR , respectively ( Figure 6 and Figure S5 ) . Interestingly , vsRNAs targeting the 5′UTR does not induce abundant secondary siRNA production from the region immediately downstream of the target site , which contains the 5′ portion of GFP ORF . This region also appears to be a poor source/target of primary vsRNAs ( see CodB in Figure 5 ) . Furthermore , robust production of secondary siRNAs does not appear to depend on the accumulation levels of any major size-class of primary vsRNAs of antisense polarity that have the potential to cleave GFP mRNA and initiate secondary siRNA biogenesis ( Figure S5; Table S1 , Table S5 and Table S6 ) . We assume that , once initiated by primary vsRNAs , secondary siRNA biogenesis might be reinforced by feedback loops in which certain secondary siRNAs of antisense polarity target the GFP mRNA . Such feedback loops regulate tasiRNA production from TAS1c gene , in which certain tasiRNAs cleave its own precursor transcript to initiate RDR6-dependent production of additional dsRNAs [20] , and potentially occur in transgene-induced silencing systems [56] , [57] . Contrary to what we observed for the transcribed region , targeting of the GFP non-transcribed regions with short sequences inserted into the CaLCuV VIGS vector did not lead to GFP silencing or secondary siRNA production in systemically-infected L2 plants ( Figure 7 and Figure S4 ) . The 30-bp sequences which surround the 35S core promoter elements including the CAAT and TATA boxes ( ‘CAAT’ and ‘TATA’ ) and the transcription start site ( ‘Plus1’ ) , or sequences that occur in a distal region of the 35S enhancer ( ‘EnhSh’ ) and just downstream of the mRNA processing/poly ( A ) addition site ( ‘Post’ ) gave rise to abundant siRNAs of the three major classes but no secondary siRNAs were detected outside of the target sequence . Furthermore , insertion of the 90-bp 35S core promoter region ( ‘Core’ ) did not result in GFP silencing or secondary siRNA production , despite abundant primary siRNAs targeting this region . However , insertions of the entire 35S enhancer region of 272 bp ( ‘Enh’ ) or the full-length promoter of 382 bp ( ‘ProFL’ ) resulted in systemic GFP silencing . But also in these two cases no secondary siRNAs were detected outside of the target region ( Figure 7 ) . These findings were confirmed by Illumina sequencing of sRNAs from L2 plants systemically infected with Core , Enh and ProFL viruses ( Figures 8 and Figure S6; Table S5 and Table S6 ) . In addition , the deep sequencing revealed that , besides extremely low levels of secondary siRNA accumulation outside of the target region , there appear to be almost no secondary siRNA amplification within the target region . Thus , the duplicated 273-bp Enhancer* region shares 94% nucleotide identity with the target Enhancer region , since these sequences originate from two different strains of CaMV , and we found only negligible numbers of reads in the three stretches of the Enhancer* sequence that have mismatches to corresponding stretches of the Enhancer sequence ( Figure 8; Table S5 , see positions 760–781 , 803–837 and 869–905 ) . Taken together , we conclude that production of abundant secondary siRNAs can be triggered by primary virus-derived siRNAs that target GFP mRNA . Hence , CaLCuV infection does not block amplification of secondary siRNAs likely mediated by RDR activities ( see below ) . This is also supported by our blot hybridization analysis showing that accumulation of RDR6-dependent tasiRNAs is not significantly affected by CaLCuV infection ( Figure S2; siR255 ) . Both primary ( virus-derived ) and secondary siRNAs correlate with efficient GFP silencing . However , targeting of the non-transcribed , 35S enhancer region by primary siRNAs induces efficient GFP silencing without any substantial production of secondary siRNAs . Hence , secondary siRNAs do not appear to be necessary for silencing GFP transgene , at least at the transcriptional level . Previously , transcriptional VIGS through targeting the 35S promoter region of 35S::GFP transgene was observed but its dependence on primary or secondary siRNAs was not tested in that case [58] . To investigate genetic requirements for the biogenesis of GFP secondary siRNAs , the L2 transgenic line was crossed with the Col-0 mutant lines carrying point mutations in RDR6 ( rdr6-14; [59] ) and DCL4 ( dcl4-2; [60] ) . The resulting homozygous mutant lines L2 x rdr6 and L2 x dcl4 expressed high levels of GFP , similar to those of the parental L2 plants ( not shown ) . Systemic infection of L2 x rdr6 and L2 x dcl4 plants with the recombinant viruses Lead , CodM and Trail resulted in GFP silencing in all cases , except L2 x rdr6 plants infected with the Lead virus . Consistent with our findings for wild-type CaLCuV ( Figure S2 ) and CaLCuV::Chl ( [7]; Figure S2 ) , blot hybridization analysis revealed that the biogenesis of 21 , 22 and 24 nt vsRNAs derived from the AC4 ORF region of the three recombinant viruses was not affected in L2 x rdr6 plants lacking RDR6 ( Figure 9 ) . By contrast , probes specific for the target transgene revealed a major contribution of RDR6 in secondary siRNA production . In fact , production of secondary siRNAs of all size-classes outside of the target region was nearly abolished in L2 x rdr6 plants infected with Lead , CodM and Trail viruses ( Figure 9 ) . For the latter two viruses , accumulation of siRNAs from the insert/target sequence was also reduced: interestingly , the reduced accumulation was observed for siRNAs of sense but not antisense polarity in CodM virus , while siRNAs of both polarities were strongly reduced in Trail virus . By contrast , accumulation of siRNAs from the Lead insert/target sequence was not altered in L2 x rdr6 plants infected with Lead virus ( Figure 9 ) . We conclude that RDR6-independent primary vsRNAs represent the majority of siRNAs derived from the Lead sequence , whereas the CodM and Trail sequences also spawn RDR6-dependent secondary siRNAs in addition to primary vsRNAs . These secondary siRNAs could potentially be produced from the transgene and/or the viral insert . We therefore used the probes specific to the viral sequence located just downstream of the insert ( CbA1063_s and CbA1063_as ) , i . e . present in the chimeric rightward viral transcript . The results revealed that , in the case of Lead and CodM viruses , RDR6 is not involved in production of vsRNAs from this region ( Figure 9 ) . Thus , the contribution of RDR6 to siRNA production from the CodM insert/target sequence of antisense polarity can be explained by RDR6-dependent siRNA production from the target gene rather than the chimeric virus . However , accumulation of vsRNAs derived from the chimeric transcript region of Trail virus was substantially reduced ( 24-nt ) or nearly abolished ( 21-nt and 22-nt ) in L2 x rdr6 plants . This indicates that , in addition to the transgenic mRNA , the chimeric viral transcript can also be used for RDR6-dependent production of secondary siRNAs . But the insert sequence itself appears to regulate relative contribution of RDR6 . Notably , the ChlI insert sequence does not make the chimeric viral transcript prone to RDR6-dependent vsRNA production ( Figure S2 ) . It remains to be further investigated why the Trail ( but not Lead , CodM or ChlI ) sequence makes the viral chimeric transcript prone to RDR6-dependent amplification of secondary siRNAs . Interestingly , this sequence originates from the CaMV terminator/leader region and contains two stretches of AG-repeats ( Protocol S1 ) . It is puzzling that , in the absence of RDR6-dependent secondary siRNAs in L2 x rdr6 plants , the GFP silencing is efficiently triggered by CodM and Trail viruses but not by Lead virus . We speculate that GFP mRNA cleaved by primary siRNAs within its 5′UTR can still be translated , unless it enters the RDR6 pathway converting the coding and 3′UTR sequences to secondary siRNAs . By contrast , primary siRNA-directed cleavage within the coding sequence or 3′UTR would block productive translation and could therefore be sufficient for GFP silencing . In L2 x dcl4 plants , we detected reduced accumulation of 21-nt primary siRNAs from the viral AC4 region and 21-nt primary and secondary siRNAs from the GFP sequences . Unexpectedly , accumulation of 22-nt and 24-nt primary and secondary siRNAs was increased: this increase was more prominent for secondary GFP siRNAs ( Figure 9 ) . This resembles the shift in the profile of RDR6-dependent 21-nt tasiRNAs in this particular mutant background ( [60]; Figure 9 , see tasiRNA siR255 ) . Thus , a mutated DCL4 protein expressed from the dcl4-2 allele appears to promote processing of RDR6-dependent dsRNAs by alternate DCLs that generate longer siRNAs ( i . e . DCL2 and DCL3 ) . Taken together , our findings confirm a major role of DCL4 in processing 21-nt secondary siRNAs from RDR6-dependent dsRNA precursors derived from the transgene and 21-nt primary vsRNAs from RDR6-independent viral dsRNA precursors . In addition , our results reveal that RDR6-dependent dsRNA can be efficiently processed by alternate DCL activities if the DCL4 protein is mutated by an amino acid substitution in the helicase domain . These alternate DCLs produce primary and secondary siRNAs which are equally potent in GFP silencing , since we did not observe any substantial difference in systemic silencing phenotypes between wild-type and dcl4-2 plants infected with any of the recombinant viruses . This is in line with our previous findings for CaLCuV::Chl-derived primary vsRNAs of distinct classes produced in single , double and triple dcl mutant plants , which could efficiently knockdown ChlI mRNA [7] . Previously , a major role of DCL2 was established for production of secondary siRNAs in a transgene targeted by primary siRNAs from another transgene [11] . Here , in addition to DCL2 , we find the apparent involvement of DCL3 which normally generates 24-nt nuclear siRNAs in secondary siRNA production . Thus , a fraction of dsRNA precursors of the GFP transgene-derived secondary siRNAs might be localized in the nucleus . Alternatively , a fraction of DCL3 protein might also be cytoplasmic . Secondary siRNAs are involved in various silencing pathways in plants , fungi and some animals . In C . elegans , RDR-dependent amplification of secondary siRNAs appears to reinforce silencing triggered by primary siRNAs which are processed by dicer from endogenous or exogenous dsRNA [61] , [62] . In plants , some of the endogenous mRNAs targeted by miRNAs spawn RDR6-dependent secondary RNAs , a contribution of which to miRNA-directed gene silencing is not fully clarified [14] , [15] . In most cases , plant miRNA-directed cleavage or translational repression is sufficient for robust gene silencing without production of secondary siRNAs [14] . Likewise , most plant mRNAs silenced by transgene- or virus-derived primary siRNAs do not spawn secondary siRNAs . This suggests that plant mRNAs could have evolved to be poor templates for RDR activity . Our study supports this notion by demonstrating that Arabidopsis ChlI and ChlI-2 mRNAs that undergo robust VIGS spawn only small amounts of secondary siRNAs . Furthermore , we demonstrate that geminiviral mRNAs , which can potentially be targeted by highly abundant vsRNAs of antisense polarity ( Figure 2 ) , are not templates for RDR1- , RDR2- , or RDR6-dependent siRNA amplification . By contrast , the transgenic GFP mRNA targeted by primary viral siRNAs spawns massive amounts of secondary siRNAs whose production requires RDR6 . Our findings suggest that some aberrant feature ( s ) of the transgenic GFP mRNA possessing non-self UTR sequences may attract RDR6 activity . Notably , the involvement of RDR6 and RDR1 in production of viral siRNAs in RNA virus-infected plants was revealed only by using the mutant RNA viruses carrying deletions or point mutations in viral silencing suppressor genes: unlike wild-type RNA , the mutated viral RNA spawned RDR-dependent vsRNAs . What makes mutant/chimeric viral mRNAs and transgenic mRNAs good templates for RDR activity remains unclear . One possibility is that viral and plant mRNAs could have evolved primary sequence or secondary structure elements that block RDR activity . Such elements may accidentally be disrupted by mutations in the suppressor-deficient RNA viruses . Likewise , transgene transcripts might lack some of the naturally evolved sequence or structure elements . Our findings suggest that the precursors of geminiviral siRNAs are most likely produced by Pol II-mediated bidirectional readthrough transcription in both sense and antisense orientations on the circular viral DNA . Such transcripts ( or their degradation products ) can potentially pair viral mRNAs and thus form perfect dsRNAs to be processed by multiple DCLs into vsRNAs . Readthrough transcription far beyond a poly ( A ) signal is a known property of Pol II . In pararetroviruses , it represents an obligatory mechanism by which a pregenomic RNA covering the entire circular genome is generated . The poly ( A ) signal of plant pararetroviruses is located at a relatively short distance ( e . g . 180 bp in CaMV ) downstream of the pregenomic RNA promoter: this allows efficient readthrough transcription at the first encounter by the Pol II complex and termination of transcription at the second encounter [63] , [64] . Thus , substantial readthrough transcription can also be expected in geminiviruses which possess relatively short transcription units . Evidence for the existence of readthrough transcripts was obtained earlier for a related geminivirus [34] and is also provided here by deep sequencing showing that vsRNAs of both sense and antisense polarities densely tile along the entire CaLCuV genome including “non-transcribed” intergenic region of both DNA-A and DNA-B . Pol II readthrough transcription downstream of a canonical poly ( A ) signal of the endogenous A . thaliana gene FCA was recently shown to be repressed by a DCL4-dependent mechanism [12] . In a dcl4 mutant , the increased transcriptional readthrough far beyond the FCA poly ( A ) signal triggered silencing of a transgene containing the same 3′ region . Notably , the transgene silencing was caused by RDR6-dependent production of very abundant 22-nt siRNAs by DCL2 and less abundant 24-nt siRNAs by DCL3 . This siRNA pattern resembles the pattern of GFP transgene-derived secondary siRNAs that we observed in L2 x dcl4 plants ( Figure 9 ) . Also in line with our observations , robust siRNA-directed silencing of the transgene and FCA did not spread to a converging gene that overlaps with the FCA readthrough transcript [12] , further supporting the notion that most endogenous genes are not prone to RDR6-dependent transitivity .
Arabidopsis thaliana wild-type ( Col-0 ) and rdr2/6 , rdr1/2/6 and dcl1/2/3/4 mutant lines used in this study , their growth conditions and infection with wild-type CaLCuV ( the DNA-A clone ‘CLCV-A dimer’ [33] and the DNA-B clone pCPCbLCVB . 002 [50] ) and CaLCuV::Chl ( pMTCbLCVA::CH42 and pCPCbLCVB . 002 [50] ) using biolistic delivery of viral DNA have been described earlier [7] , [8] . Using the same protocols , L2 transgenic plants ( Line 2; [54] ) were grown and inoculated with CaLCuV::GFP viruses . L2 plants [54] were crossed with the dcl4-2 and rdr6-14 mutants [59] , [60] . L2 homozygosity was determined by PCR in the F2 populations using 5′-TTGCTGCAACTCTCTCAGGGCC-3′ and 5′-GATAAATGTGGAGGAGAAGACTGCC-3′ for detecting the presence of the T-DNA and 5′-ACACTCTCTCTCCTTCATTTTCA-3′ and 5′-TCTGCAACACTCTGTCATTGG-3′ for detecting the absence of intact genomic region . RDR6-14 homozygosity was determined by visual observation of the typical epinastic leaf phenotype of the rdr6 mutants and was further confirmed using a dCAPS marker consisting of NcoI digestion of the PCR product obtained using 5′-AAGATTTGATCCCTGAGcCAT-3′ and 5′-GTTCGCCTTGTTTCTTGCTT-3′ . DCL4-2 homozygosity was determined by the typical epinastic leaf phenotype of the dcl4 mutants . Homozygosity for L2 and the respective mutations were confirmed in F3 plants following the same procedures . The CaLCuV::GFP viruses EnhSh , CAAT , TATA , Plus1 , Lead , Start , CodB , CodM , CodE , Stop , Trail , PolyA and Post were generated by cloning preannealed sense and antisense oligonucleotides ( listed in Protocol S1 ) into XbaI and XhoI sites of the CaLCuV VIGS vector pCPCbLCVA . 007 [50] . The CaLCuV::GFP viruses Enh , Core and ProFL were generated by subcloning into XbaI and XhoI sites of pCPCbLCVA . 007 the corresponding regions of the L2 T-DNA 35S promoter using PCR with primers listed in Protocol S1 on total DNA isolated from L2 transgenic plants . In all the above derivatives of the CaLCuV VIGS vector the insert sequences are in antisense orientation with respect of the AV1 gene promoter . For both blot hybridization and Illumina deep-sequencing , aerial tissues of three virus-infected ( or mock-inoculated ) plants were harvested one month post-inoculation and pooled for total RNA preparation using a Trizol method [7] . sRNA blot hybridization analysis was performed as in Blevins et al . [7] using short DNA oligonucleotide probes listed in Protocol S1 . cDNA libraries of the 19–30 nt RNA fraction of total RNA samples were prepared as we described previously [8] . The high-coverage libraries of wild-type CaLCuV were sequenced on an Illumina Genome Analyzer ( GA ) Hi-Seq 2000 using a TruSeq v5 kit , while the low coverage libraries on a GA-II using Chrysalis v2 . The libraries of CaLCuV::Chl and CaLCuV::GFP viruses were sequenced on a GA-IIx using Chrysalis v4 and TruSeq v5 , respectively . After trimming the adaptor sequences , the datasets of reads were mapped to the reference genomes of Arabidopsis thaliana Col-0 ( TAIR9 ) , CaLCuV ( U65529 . 2 for DNA-A and U65530 . 2 for DNA-B ) and other references using a Burrows-Wheeler Alignment Tool ( BWA version 0 . 5 . 9 ) [65] with zero mismatches to the reference sequence . The reference sequences of CaLCuV DNA-A and its derivatives , CaLCuV DNA-B , L2 T-DNA and ChlI/CH42 and ChlI-2 genomic loci are given in Protocol S1 . Reads mapping to several positions on the references were attributed at random to one of them . To account for the circular virus genome the first 50 bases of the viral sequence were added to its 3′-end . For each reference genome/sequence and each sRNA size-class ( 20 to 25 nt ) , we counted total number of reads , reads in forward and reverse orientation , and reads starting with A , C , G and T ( Table S1 ) . In the single-base resolution maps of 20 , 21 , 22 , 23 , 24 and 25 nt vsRNA ( Tables S2 , S3 , S4 , S5 , S6 and S7 ) , for each position on the sequence ( starting from the 5′ end of the reference sequence ) , the number of matches starting at this position in forward ( first base of the read ) and reverse ( last base of the read ) orientation for each read length is given . Note that the reads mapped to the last 50 bases of the extended viral sequence were added to the reads mapped to the first 50 bases . The detailed protocol for high-resolution analysis of long RNA using total RNA and 5% PAGE followed by blot hybridization was described previously [30] . To detect the viral mRNAs AV1 , AC2/AC3 , BV1 and BC1 ( Figure 3A ) , the membrane was successively hybridized with mixtures of DNA oligonucleotides complementary to each given mRNA ( for sequences , see Protocol S1 ) . Southern blot analysis was performed as in [66] . In short , total DNA from the plants were extracted by CTAB-based protocol . Five µg of total DNA was electrophoresed in 1% agarose gel prepared in 1× Tris-sodium acetate-EDTA buffer . Full-length linear DNA of CaLCuV was loaded as a positive control for Southern hybridization . After EtBr staining , the DNA in the gel was alkali-denatured and transferred to the Hybond N+ nylon membrane ( GE healthcare lifesciences ) . PCR fragments of DNA-A ( 900 bp obtained with the primers Cb_AV1_qPCR_s and Cb_AC3_qPCR_as ) and DNA-B ( 862 bp Cb_BV1_qPCR_s and Cb_BC1_qPCR_as ) , which do not contain the common region of the virus , were labeled with [α-32P]dCTP using Rediprime II DNA labeling system ( GE healthcare lifesciences ) and used as probes . Hybridization with the labeled probe was performed at 65°C for 16–20 hours using PerfectHyb Plus Hybridization Buffer ( Sigma-Aldrich ) and the membrane was washed thrice at 65°C with 2× SSC/0 . 5% SDS . The signal was detected after 5 days exposure to a phosphor screen using a Molecular Imager ( Typhoon FLA 7000 , GE healthcare lifesciences ) . Relative accumulation of polyadenylated viral mRNAs and total viral DNA in wild type versus rdr1/2/6 ( Figure 3D ) was measured using real time PCR as in [8] . For polyadenylated RNA , cDNA was synthesized from 5 µg of total RNA using 100 pmoles of oligo d ( T ) 16 primer . The RNA-primer mixture was heated to 70°C for 10 min and chilled on ice for 5 min . 4 µl of 5× first-strand synthesis buffer ( 250 mM Tris-HCl [pH 8 . 3] , 375 mM KCl , 15 mM MgCl2 , 0 . 1 M DTT ) , 2 µl 0 . 1 M DTT , 1 µl 10 mM deoxynucleoside triphosphate mix and 1 µl ( 200 U ) of Superscript III reverse transcriptase ( Invitrogen ) were added and incubated at 50°C for 60 min . The reaction was stopped by heating the mixture to 95°C for 5 min . 2 µl of the 10 times diluted reverse transcription reaction mix or 2 µl of total DNA ( 2 ng ) were taken for PCR in LightCycler 480 Real-Time PCR System ( Roche applied sciences ) using FastStart Universal SYBR Green Master ( Rox ) mix ( Roche ) and primers designed using Beacon designer 2 software ( PREMIER Biosoft International ) . PCR primers specific for viral DNAs A and B and each viral mRNA as well as internal controls ( 18S rDNA and ACT2 mRNA ) are given in Protocol S1 . Cycling parameters were 95°C for 10 min , followed by 45 cycles: 95°C for 10 s , 56°C for 10 s , 72°C for 20 s . Amplification efficiency of primers was determined by means of a calibration curve ( Ct value vs . log of input cDNA/DNA ) prepared in triplicate . The Ct values obtained for viral genes were normalized with internal control values and the delta Ct values were obtained . The normalized values for CaLuCV-infected wild type Col-0 were set to 1 . To quantify the L2 GFP mRNA levels , poly-dT cDNAs were made as described above . Real-time PCR was performed in 96-well titer plates on an ABI PRISM 7000 SDS apparatus with SYBR GREEN PCR Master Mix ( ABI ) following manufacturers' recommendations ( 95°C for 5 min . , followed by 40 cycles: 95°C for 30 s , 60°C for 45 s ) . Primers are given in Protocol S1 . Uncertainties were propagated from standard errors for triplicate measurements of cDNA pools ( derived from column-purified RNA of 3–4 plants ) .
|
RNA silencing directed by small RNAs ( sRNAs ) regulates gene expression and mediates defense against invasive nucleic acids such as transposons , transgenes and viruses . In plants and some animals , RNA-dependent RNA polymerase ( RDR ) generates precursors of secondary sRNAs that reinforce silencing . Most plant mRNAs silenced by miRNAs or primary siRNAs do not spawn secondary siRNAs , suggesting that they may have evolved to be poor templates for RDR . By contrast , silenced transgenes often produce RDR-dependent secondary siRNAs . Here we demonstrate that massive production of 21 , 22 and 24 nt viral siRNAs in DNA geminivirus-infected Arabidopsis does not require the functional RDRs RDR1 , RDR2 , or RDR6 . Deep sequencing analysis indicates that dsRNA precursors of these primary viral siRNAs are likely generated by RNA polymerase II-mediated bidirectional readthrough transcription on the circular viral DNA . Primary viral siRNAs engineered to target a GFP transgene trigger robust , RDR6-dependent production of secondary siRNAs , indicating that geminivirus infection does not suppress RDR6 activity . We conclude that geminiviral mRNAs , which can potentially be cleaved by primary viral siRNAs , are resistant to RDR-dependent amplification of secondary siRNAs . We speculate that , like most plant mRNAs , geminiviral mRNAs may have evolved to evade RDR activity .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"plant",
"science",
"plant",
"biology",
"plant",
"pathogens",
"plant",
"pathology",
"biology"
] |
2012
|
Primary and Secondary siRNAs in Geminivirus-induced Gene Silencing
|
Chagas disease results from infection with the diploid protozoan parasite Trypanosoma cruzi . T . cruzi is highly genetically diverse , and multiclonal infections in individual hosts are common , but little studied . In this study , we explore T . cruzi infection multiclonality in the context of age , sex and clinical profile among a cohort of chronic patients , as well as paired congenital cases from Cochabamba , Bolivia and Goias , Brazil using amplicon deep sequencing technology . A 450bp fragment of the trypomastigote TcGP63I surface protease gene was amplified and sequenced across 70 chronic and 22 congenital cases on the Illumina MiSeq platform . In addition , a second , mitochondrial target—ND5—was sequenced across the same cohort of cases . Several million reads were generated , and sequencing read depths were normalized within patient cohorts ( Goias chronic , n = 43 , Goias congenital n = 2 , Bolivia chronic , n = 27; Bolivia congenital , n = 20 ) , Among chronic cases , analyses of variance indicated no clear correlation between intra-host sequence diversity and age , sex or symptoms , while principal coordinate analyses showed no clustering by symptoms between patients . Between congenital pairs , we found evidence for the transmission of multiple sequence types from mother to infant , as well as widespread instances of novel genotypes in infants . Finally , non-synonymous to synonymous ( dn:ds ) nucleotide substitution ratios among sequences of TcGP63Ia and TcGP63Ib subfamilies within each cohort provided powerful evidence of strong diversifying selection at this locus . Our results shed light on the diversity of parasite DTUs within each patient , as well as the extent to which parasite strains pass between mother and foetus in congenital cases . Although we were unable to find any evidence that parasite diversity accumulates with age in our study cohorts , putative diversifying selection within members of the TcGP63I gene family suggests a link between genetic diversity within this gene family and survival in the mammalian host .
Trypanosoma cruzi is a kinetoplastid parasite and the causative agent of Chagas disease ( CD ) in Latin America . T . cruzi infects approximately 8 million people throughout its distribution and causes some 13 , 000 deaths annually [1] . Chagas disease follows a complex course . Infection , often acquired in childhood , is generally lifelong but progression from the indetermined ( asymptomatic ) to symptomatic stage occurs in only 30% of cases [2] . A broad pathological spectrum is associated with clinical CD including potentially fatal cardiological and gastrointestinal abnormalities [3] . The relative contributions of parasite and host immunity in driving disease pathology are a matter of continuing debate [4] . Recently , for example , bioluminescent parasite infections in BALB/c mouse models have suggested that heart disease can progress in the absence of detectable local parasite load [5] . It is widely recognized that natural parasitic infections are often comprised of several parasite clones [6] . Malariologists use the term ‘multiplicity of infection’ ( MOI ) to describe when multiple Plasmodium sp . genotypes occur within the same host [7 , 8] . A similar phenomenon has been observed in T . cruzi in vectors ( e . g . [9] ) , as well as mammalian reservoir hosts ( e . g [10] ) and humans hosts ( e . g . [11] ) using solid phase plating and cell sorting techniques . The occurrence of multi-genotype infections has fundamental implications for host immunity [12] , as well as for accurate evaluation of pathogen drug resistance [13] , transmission rate , epidemiology and population structure ( e . g . [7 , 11] ) . The efficiency with which it is possible to sample pathogen clonal diversity from biological samples has soared in recent years with the advent of next generation sequencing . Deep sequencing approaches have long been applied to study the dynamics of HIV anti-viral therapy escape mutations . As a result amplicon sequencing increasingly features in a clinical diagnostic context [14] . Plasmodium falciparum MOI can be resolved at merozoite surface protein loci at far greater depths than possible by standard PCR approaches [15] . Furthermore , targeting low copy number antigens in parasite populations via amplicon sequencing can provide important clues to frequency-dependent selection pressures within hosts , between hosts and between host populations [16] . T . cruzi can persist for several decades within an individual host . Unsurprisingly perhaps , therefore , T . cruzi shows significant antigenic complexity . T . cruzi surface proteins are encoded by several large , repetitive gene families that are distributed throughout the parasite genome [17] . Among these gene families the mucins , transialidases , ‘dispersed gene families’ ( DGFs ) , mucin-associated surface proteins ( MASPs ) and GP63 surface proteases comprise the vast majority of sequences—10–15% of the total genome size [17 , 18] . Whilst the role of some of the proteins encoded by surface gene families in host cell recognition and invasion is relatively well understood ( e . g . the transialidases [19] ) , the role of others ( e . g . the MASPs , DGFs ) is not . Furthermore , the role each plays in evading an effective host response remains largely unknown . The GP63 surface proteases are found in a wide variety of organisms , including parasitic trypanosomatids [20] . In Leishmania spp . GP63 proteases are the most common component of the parasite cell surface with crucial roles in pathogenicity , innate immune evasion , interaction with the host extracellular matrix and ensuring effective phagocytosis by macrophages [21] . In T . brucei subspp . the role of GP63 proteins is less well defined , although some protein classes are thought to be involved with variant surface glycoprotein processing between different life cycle stages [22] . In T . cruzi at least four classes of GP63 gene are recognized [20] . Like many GP63 proteases in Leishmania spp . , surface expressed T . cruzi GP63 ( TcGP63 ) genes are anchored to the cell membrane via glycosyl phosphatidylinositol moieties [23 , 24] . Among these are the TcGP63 Ia & Ib genes ( collectively TcGP63I ) . TcGP63 Ia & Ib encode 78kDa 543 amino acid proteins , are expressed in all life cycle stages and are implicated in the successful invasion of mammalian cells in vitro [23 , 24] . In the current study we target TcGP63I genes as markers of antigenic diversity among three cohorts of Chagas disease patients: two in Cochabamba , Bolivia and one in Goias , Brazil . We also targeted a maxicircle gene for the NADH dehydrogenase subunit 5 to provide basic T . cruzi genotypic information for each case . Diversity at each of the two T . cruzi loci within each patient was characterized using a deep amplicon sequencing approach , generating several million sequence reads . Our results shed light on the diversity of parasite DTUs within each patient , as well as the extent to which parasite strains pass between mother and foetus in congenital cases . We were unable to find any evidence that parasite diversity accumulates with age in our study cohorts , or to detect a link between parasite diversity and clinical profile . However , we were able to detect evidence of putative diversifying selection within members of the TcGP63 gene family , suggesting a link between genetic diversity within this gene family and survival in the mammalian host .
Ethical permissions were in place at the two centres where human sample collections were made , as well as at the London School of Hygiene and Tropical Medicine ( LSHTM ) . Local ethical approval for the project was given at the Plataforma de Chagas , Facultad de Medicina , UMSS , Cochabamba , Bolivia by the Comite de Bioetica , Facultad de Medcina , UMSS . Local ethical permission for the project was given at the Hospital das Clínicas da Universidade Federal de Goias ( UFG ) , Goias , Brazil by the Comite de Etica em Pesquisa Médica Humana e Animal , protocol number 5659 . Ethical approval for sample collection at the LSHTM was given for the overall study , “Comparative epidemiology of genetic lineages of Trypanosoma cruzi” protocol number 5483 . Samples were collected with written informed consent from the patient and/or their legal guardian . Parasite isolation protocols were different between centres . At the UMSS , 0 . 5 mL of whole venous blood was taken from chronic patients and inoculated directly into biphasic blood agar culture . T . cruzi positive samples were minimally repassaged and cryopreserved at log phase ( precise repassage history unavailable ) . For infants , 0 . 5 mL of chord blood was taken at birth and inoculated into culture . Again , positive samples were cryopreserved at log phase after minimal repassage ( precise repassage history unavailable ) . DNA extractions , using a Roche High-Pure Template Kit , were made directly from the cryopreserved stabilate . At the UFG , 17 mL of whole blood was collected into EDTA , centrifuged for 10 minutes at 1200g at 4°C and the plasma replaced with 8mL Liver Infusion Tryptone ( LIT ) medium . After a further 10 minutes at 1200g ( 4°C ) , the supernatant was again removed . Two mL of packed red blood cells were subsequently transferred to 3 mL of LIT medium and checked periodically for signs of epimastigote growth by light microscopy . Positive cultures were not repassaged . Instead primary cultures were stabilized by the addition of guanidine 6 M-EDTA 0 . 2 M ( Sigma-Aldrich , UK ) . DNA extractions were made from the full volume using the QIAamp DNA Blood Maxi Kit ( Qiagen , UK ) according to the manufacturer’s instructions . Among Bolivian strains , DNA concentrations submitted to PCR were standardized after quantitation using a PicoGreen assay . In view of presence of human genetic material in Goias samples , parasite DNA concentrations were standardized to within the same order of magnitude via qPCR as previously described [25] . All samples collected for in this study are listed in Table 1 . The two areas studied have dissimilar histories in terms of Chagas disease transmission intensity . Vector-borne T . cruzi transmission in Goias and its surrounding states ( where samples were collected—Table 1 ) was interrupted approximately 20 years before the sampling detailed in this study [26 , 27] . In the sub-Andean semi-arid valleys of Cochabamba and its environs , however , vector-borne domestic transmission is still a likely source of new infections , albeit at a reduced rate since intensive spraying campaigns in the mid 2000s [28] . Clinical data collected in this study were categorised simply into symptomatic and asymptomatic classes for statistical tests in view of samples sizes . Sub-categories within symptoms were defined as 1 ) Cardiopathy ( including any electrocardiographic and/ or echocardiographic abnormalities , X-ray with cardiac enlargement . Patients with atypical cardiac abnormalities i . e . those not exclusively associated with Chagas disease , were included in the symptomatic class in the context of this study . ) 2 ) Megaesophagous ( including achalasia and barium swallow abnormalities ) 3 ) Megacolon ( constipation associated with dilation as by barium enema ) and 4 ) Normal ( no symptoms or signs on examination and a normal electrocardiogram ) ( Table 1 ) Degenerate primers for a 450bp fragment of the maxi-circle NADH dehydrogenase 5 were designed as described in Messenger et al . 2012 [29] . Degenerate primer design for the TcGP63I family surface proteases ( including Ia and Ib sublaclasses ) [24] was achieved by reference to sequences retrieved from EuPathDB for Esmeraldo ( TcII ) , CL Brener ( TcVI ) , Silvio ( TcI ) and JR ( TcI ) ( http://eupathdb . org/ ) . Primer biding site positions in relation to TcGP63I putative functional domains are displayed in S1 Fig . Homologs were identified by BLAST similarity to a complete TcGP63I sequence ( bit score ( S ) ≥ 1000 ) . Alignments of resulting sequences were made in MUSCLE [30] and primers were designed manually to target a variable region within and between individual strains with a final size of 450bp . ND5b primer sequences were ND5b_F ARAGTACACAGTTTGGRYTRCAYA; ND5b_R CTTGCYAARATACAACCACAA . The final TcGP63 primers were TcGP63_F RGAACCGATGTCATGGGGCAA and TcGP63_R CCAGYTGGTGTAATRCTGCYGCC . Amplification was undertaken using the Fluidigm platform and a reduction of the manufacturer’s recommended number of cycles to total of 26 was made in an attempt to minimise PCR amplification bias . Thus , the manufacturer’s recommended conditions were adapted to the following protocol: one cycle of 50°C for 2 minutes , 70°C for 20 minutes , and 95°C for 10 minutes; six cycles of 95°C for 15 seconds , 60°C for 30 seconds , 72°C for 60 seconds; two cycles of 95°C for 15 seconds , 80°C for 30 seconds , 60°C for 30 seconds and 72°C for 60s; five cycles of 95°C for 15 seconds , 60°C for 30 seconds , 72°C for 60 seconds; two cycles of 95°C for 15 seconds , 80°C for 30 seconds , 60°C for 30 seconds and 72°C for 60 seconds; five cycles of 95°C for 15 seconds , 60°C for 30 seconds , 72°C for 60 seconds , and finally five cycles of 95°C for 15 seconds , 80°C for 30 seconds , 60°C for 30 seconds and 72°C for 60 seconds . Amplifications were performed using the FastStart High Fidelity PCR System ( Roche ) . Three PCR reactions were pooled per sample prior to sequencing in an attempt to further reduce amplification biases [31] . Equimolar concentrations of ND5 and TcGP63I amplicons from 96 DNA samples were multiplexed on Illumina runs using dual index sequence tags ( Illumina Inc ) . Sequencing was undertaken using a MiSeq platform using a 2 x 250 bp ( Reagent Kit version 2 ) according to the manufacturer’s protocol . In addition to the clinical samples , we included a dilution series of control samples . The controls comprised artificially mixes of DTUs I-VI genomic DNA at equimolar concentrations . At the ND5 locus , comparison between the expected DTU abundance ratios and diversity of artificial control mixes and that defined via amplicon sequencing was made ( S2 Fig . ) . De-multiplexed paired-end sequences were submitted to quality control and trimming in Sickle [32] and mate pairs trimmed in FASTX Toolkit ( http://hannonlab . cshl . edu/fastx_toolkit/ ) . ND5 , TcGP63 and contaminating sequences were then sorted against a reference using BOWTIE2 [33] . Individual paired reads were found to be overlapping in only a minority of cases . Thus we chose to proceed with analysis of a sequence fragment with a truncated central section for both targets . Further sequence manipulations were undertaken using FASTX Toolkit and custom awk scripts to parse files and concatenate each mate pair into a single sequence for downstream analysis . MUSCLE [30] was used for alignment of amplicon sequences in each patient sample . Next , analysis was undertaken in the Mothur software package [34] for the elimination of putative PCR chimeras and individual sequence clustering . The Shannon index of diversity was calculated at the intra-patient level based on sequence types ( STs ) defined at 97% and 99% identity in Mothur [34] . Comparisons of Shannon diversity were made between patients in each cohort ( Bolivia chronic , Bolivia congenital , Goias chronic ) via analyses of covariance and linear regression in the R package ( http://CRAN . R-project . org ) . TcGP63I sequence datasets for patients from each cohort were then merged and analyses conducted using 97% and 99% STs defined with UPARSE [35] across patients . Weighted UniFrac distances between TcGP63I STs among samples were generated and subsequently clustered via a principal coordinates analysis in QIIME [36] . Significance of association between UniFrac clustering , disease status and age was tested in the vegan package in R [37] . Estimates of diversifying selection among TcGP63I STs were made in KaKs Calculator [38] using Yang and Neilson’s 2000 approximate method [39] and tested for significance using a Fisher’s exact test . Prior to selection calculations , sequences were clustered into 99% identity STs and singletons excluded in an attempt to exclude SNPs introduced as PCR artefacts . To test for diversifying selection across putative TcGP63I gene families ( TcGP63Ia & Ib—97% cut-off as defined by Cuevas and colleagues [24] ) , 99% identity STs from each patient cohort were pooled ( Table 2 ) . To test for selection within TcGP63I gene families , STs within each 97% category ( corresponding to TcGP63Ia & b respectively ) were examined separately per cohort ( Table 2 ) . Amplicon sequences analysed in this study are available in the data appendix in supplementary information ( S1 Appendix ) .
After quality filtering , trimming , decontamination and removal of unpaired reads , 6 , 736 , 749 reads were assigned to the ND5 mitochondrial marker and 871 , 855 to TcGP63I marker across the 92 clinical samples , perhaps reflecting higher copy number in the former than the latter . After trimming , the overlap between individual mate pairs was marginally too short to be assembled into a single read . Thus paired reads were first aligned against a full-length reference fragment and the central portion excised to remove any gaps and ensure correct alignment . Sequence depth thresholds per sample for inclusion were set for each dataset ( Goias—ND5 & TcGP63–10 , 000; Cochabamba—ND5: 30 , 000; TcGP63 10 , 000; see Fig . 1 ) . Reads from samples in excess of this threshold were discarded and samples with read counts below this threshold excluded . Our aim in setting the threshold was: 1 ) To include as many samples as possible while maintaining a good depth of coverage; 2 ) To standardise sampling intensity across individuals and thus facilitate comparisons between them . The ND5 mitochondrial target was sequenced to provide DTU I-VI identification of parasites circulating within and among patients by comparison to existing data [29] . However , with reference to the results from the control samples—and due the necessary truncation of the sequence fragment—only three groups could be reliably distinguished , corresponding to the three major T . cruzi maxicircle sequence classes [40] . The three groups corresponded to TcI , TcII and TcIII-VI respectively . Furthermore , in reference to the control mixes , we found evidence that amplification bias dramatically skewed the recovery of sequence types ( STs ) towards the TcIII-VI group . Some skew is expected , as these four DTUs ( TcIII-VI ) share the same maxicircle sequence class , and this class is thus more abundant in the control mix . However , TcI and TcII—which should have in theory been present as 16% ( 1/6 ) of all sequences in the controls respectively—were in fact present ( on average ) at only 2 . 9% and 0 . 03% among the four samples where all three STs were recovered ( S2 Fig . ) . Amplicon sequencing from the two most concentrated controls ( 57 ng/uL and 125 ng/uL genomic DNA respectively ) resulted in poor sequence yields and a failure to recover all three STs . Unsurprisingly perhaps in the light of the control data , most clinical samples were dominated by sequences from a single group , with minor contributions from others ( Fig . 2 ) . Indeed sequences recovered from many strains were monomorphic at the 97% identity level—especially in Cochabamba . As such , comparisons based on ND5 are necessarily descriptive and meaningful alpha ( within sample ) and beta ( between sample ) diversity statistics were not calculated . Fig . 2 shows the distribution of DTUs among samples as defined by the ND5 locus . Most Cochabamba chronic cases samples were assigned to a single sequence within the TcIII-VI group ( likely to be TcV , as we defined with standard genotyping assays [41] with the exception to two TcI cases—PCC 240 and PCC 289 ( Fig . 2 , Panel B ) . Sequence-type diversity in Goias was considerably higher ( Fig . 2 , Panel A ) . In this case the TcII group , rather than the TcIII-VI group , predominated . Unlike in Bolivia , sequences from other groups were present alongside TcII in multiple patients but at frequencies two orders of magnitude lower . Congenital pairs that originated from Cochabamba resembled chronic cases from the same region in their DTU composition ( TcIII-VI group predominant , Fig . 2 , Panel C ) . Strikingly , mother/child pair CIUF65 ( B5 ) and CIUF75 ( M5 ) share similar mixed infection profiles ( TcI/ TcIII-VI ) at similar relative abundances ( c . 1:1000 ) , consistent with the minor to major genotype abundance ratios observed in Goias . The same is also true for the Goias congenital pair ( Fig . 1 ) which both showed TcII/TcI mixes . Finally , sequential isolates taken from the same Goias chronic patient at different time points suggest that minor abundance genotypes are not always consistently detectable in the blood ( Fig . 2 ) : TcI is absent at first sampling of patient y , but present at the second sampling . For patient z , the TcIII-VI genotype is only present in the first of the two sample points . For both Cochabamba and Goias , reference to the control data suggests that ‘minor genotypes’ could be substantially more abundant in the patients than the amplicon sequence data suggest . Alpha diversity measurements aim to summarise the diversity of species ( in this case STs ) , within an ecological unit ( in this case a host ) . We summarized the number of STs and their relative abundance in each of our samples , using the Shannon Index ( SI ) [42] . Among non-congenital cases , our aim was to evaluate possible associations between TcGP63I antigenic diversity and several epidemiological and clinical parameters—age , sex and disease status . We used analyses of covariance ( ANCOVA ) to test for the effect of these parameters on intra-host antigenic diversity ( STs defined both at 97% and 99% for comparison ) , combining continuous ( age ) and categorical ( sex , clinical forms ) data . In Cochabamba , regardless of the order in which parameters were included as factors in the model , there was no evidence for a main effect of age , sex or symptoms on alpha diversity ( SI ) at either ST divergence level ( 97% ST Age: p = 0 . 734; Sex: p = 0 . 298; clinical form: p = 0 . 136 . 99% ST—Age: p = 0 . 854; Sex: p = 0 . 169; clinical form = 0 . 0988 ) . Similarly , ANCOVAs were non-significant for an association between the SI and age , sex or symptoms in Goias ( 97% ST—Age: p = 0 . 382; Sex: p = 0 . 535; clinical form: p = 0 . 486 . 99% ST—Age: p = 0 . 319; Sex: p = 0 . 696; clinical form: p = 0 . 697 ) . Finally , we undertook linear regressions of SI with age in each population . As one might expect from previous ANCOVAs , no significant correlation was detected ( Goias R2 = 0 . 0233 , p = 0 . 340 ( 97% ST ) ; R2 = 0 . 0256 , p = 0 . 3049 ( 99% ST ) Cochabamba R2 = 0 . 0287 , p = 0 . 429 ( 97% ST ) ; R2 = 0 . 0230 p = 0 . 479 ( 99% ST ) ) . Congenital comparisons were made pairwise between mother and infant at 99% ST similarity . In addition to the ten matched isolate pairs from Cochabamba , a single pair from Goias was also included ( 6718 & 6720 ) in the comparisons . The results of the alpha diversity comparisons are shown in Fig . 3 , and read depths were balanced between samples . In terms of the absolute number of STs identified , infants exceeded mothers in most instances ( pairs 2 , 3 , 4 , 5 , 6 , 8 & 9 ) . In the remaining cases however ( 4/11 ) , the number of antigenic sequence types was greater in the mother . Shannon diversity index comparisons between mothers and infants , which also takes ST abundance into account , suggested that some differences ( e . g . pairs 4 , 5 &6 ) might be marginal ( Fig . 3 ) . Individual sample sequence datasets within each of the different study cohorts ( Cochabamba congenital , Cochabamba non-congenital and Goias ) were merged to facilitate analysis of the distribution of antigen 99% STs among individuals ( i . e . beta-diversity comparisons ) . Pairwise weighted Unifrac distances were calculated within cohorts of chronic cases from Cochabamba and Goias to examine whether the sequence diversity of the TcGP63I antigenic repertoire present in each patient could be associated with disease outcome . Principal coordinate analyses of the resulting matrices are displayed in Fig . 4 . Among cases from Goias , repertoires varied considerably among cases , with several outliers . However , repertoires from symptomatic and asymptomatic cases were broadly overlapping in terms of sequence identity , and no clustering was noted among different symptom classes either ( Fig . 4 , Plot B ) . Permutational multivariate analysis confirmed the absence of a link between ST clustering and symptoms as well as symptom classes ( p = 0 . 77 & 0 . 74 respectively ) . However , ST clustering and age were weakly associated ( p = 0 . 049 ) , consistent perhaps with exposure of individuals among different age groups to different circulating parasite genotypes at their time of infection . TcGP63I read yields permitted comparisons for only two pairs of sequential isolates from the sample patients—x and y ( see Table 1 ) —both of which showed closely clustering , although non-identical , profiles . TcGP63I diversity between Cochabamba chronic cases was arguably lower , with the exception of two outliers unambiguously identified as TcI with reference to the ND5 locus ( all others were classified as TcIII-VI—likely TcV ) . Again , however , symptomatic and asymptomatic cases were broadly overlapping . Sequence type profile comparisons among Cochabamba congenital cases were made for 99% STs and are displayed in heatmap format in Fig . 5 . There are two key features of interest . The first is that profiles in mother an infant can match very closely ( e . g . pairs 2&6 ) . The second is that novel STs were present in the infant sample with respect to the mother in half of the cases . Indeed , in pair 9 , the infant profile was radically different to that of the mother . Trimmed TcGP63 reads , pre-filtered for quality and PCR errors , were pooled within each study site ( Bolivia , Goias ) . To further reduce minority SNPs and PCR errors , STs were defined at 99% with each site in UPARSE [35] . Ka/Ks ratio estimates within each study area indicated a significant excess of synonymous mutations among STs ( Goias = 0 . 8354 , Bolivia = 0 . 7515 ) averaged across sites ( Table 2 ) . However , when calculations were based on diversity present among well represented STs of each gene family member ( TcGP63Ia and TcGP63Ib , 97% cut-off [24] ) a powerful and significant excess of non-synonymous substitutions was noted within each study area ( Ka/Ks , Goias , ST1 = 2 . 6436 , ST4 = 6 . 3415; Bolivia ST3 = 2 . 8059; Table 2 ) . Again , calculations were based not on individual sequences , but rather 99% STs within predefined 97% clusters . The position of the 97% STs in question is shown in the tree in S3 Fig . , with clear similarity between those clusters under apparent diversifying selection ( Goias ST1 & 2 , and Bolivia ST3 ) with TcGP63Ia and TcGP63Ib references respectively [24] .
In this study our aim was to collect a cohort of T . cruzi samples from clinical CD cases , representative of different endemic regions and of different ages and disease presentations , to explore links between CD epidemiology and multiplicity of infection . To provide a robust , sensitive and quantifiable means of assessing intra-host parasite diversity we first implemented standardized parasite isolation ( and enrichment ) strategies within each study cohort . Latterly , we developed an amplicon sequencing approach to profile parasite diversity within each patient . Given the relatively short ( 400–500bp ) read lengths generated by next generation sequencing platforms ( at the time of experimentation ) , we chose a rapidly evolving maxicircle gene ( ND5 ) in an attempt to resolve DTU level diversity ( [29] ) . Current multilocus nuclear targets are generally too long ( 500bp+ ) to meet our selection criteria [43] ) . To explore antigenic diversity , we chose a putatively low ( 5–10 ) copy number gene family member TcGP63I , expressed on the parasite surface during the amastigote and trypomastigote lifecycle stage and thus exposed to the human immune system [24] . Given that both ND5 and TcGP63I are present as several copies per parasite genome ( and potentially show inter-strain copy number variation e . g . [44] ) , one cannot presume a 1:1 relationship between ST and parasite individual , even if we were able to account for the PCR amplification bias we detected . The identification of a genetically , variable , single copy , surface expressed antigen locus is a major challenge in T . cruzi—antigen genes are by their nature highly repetitive [17 , 18] . TcGP63I , with its relatively low copy number represents the closest currently available fit , and , as we have shown , provides a useful target for revealing intra-host antigenic diversity . Merozoite surface proteins ( MSP ) 1 and 2 have traditionally provided useful targets for detecting MOI in P . falciparum ( e . g . [45 , 46] . Furthermore , amplicon sequencing of the MSP locus has been successfully proven to reveal as many as six-fold more variants than traditional PCR-based approaches [15] . The substantial historical interest in defining MOI among P . falciparum owes itself to the strong correlation between MOI and rate of parasite transmission [47] . As such , fluctuations in transmission intensity can be tracked to evaluate the efficiency of vector eradication campaigns , drug treatments , the introduction of insecticide-treated nets etc—without the need to directly estimate the entomological inoculation rate . Evaluation of CD transmission intensity has its own challenges . The presence of infected individuals , triatomine vectors in domestic buildings , incrimination of vectors via human blood meal identification ( e . g . [48] ) can all help to build the overall picture . However , parasite transmission is likely to occur in only a tiny proportion of blood meals [49 , 50] , and vector efficiency is thought to vary considerably between triatomine species [51]—thus the presence of vectors is no guarantee of transmission . Infection with T . cruzi is lifelong , thus positive patient serology is not a reliable indicator of active parasite transmission either . Traditionally , active T . cruzi transmission has been implied from positive serology among younger age classes . Especially in hyperendemic areas of Bolivia , Paraguay and Argentina the proportion of seroprevalent individuals increases with age [52 , 53] . MOI in T . cruzi patients should follow a similar trend given a stable force of infection . Furthermore MOI comparisons between disease foci could , controlling for age , facilitate an appreciation of relative transmission intensities—a useful tool for those who wish to track the efficacy of interventions . In the current study , however , we were unable to identify a correlation between MOI and age , even once patient sex and clinical form had been corrected for . Our inability to validate this fundamental prediction has many possible causes . First , patients in each cohort originate from different communities within each study area ( Table 1 ) . Micro-geographic variation in T . cruzi genetic diversity is commonly observed ( e . g . [11 , 54 , 55] , and the same is likely to be true for infection intensity . Thus , if patients from different sites share dissimilar histories in the intensity and diversity of exposure to T . cruzi clones , comparisons between them are difficult to make . Secondly , the relationship between MOI and age is not necessarily linear . If a degree of cross-genotype immunity accumulates with exposure , one might expect a slower increase in intra-host antigenic diversity in older age groups . However , this was not the case in our dataset and neither a linear , nor a unimodal relationship could be established . Amplicon sequencing approaches to the study of transmission patterns in human parasites have so far been restricted to those species that replicate and reach high parasitemias in peripheral blood ( i . e . T . brucei [56] and P . falciparum [13 , 15] ) . T . cruzi trypomastigote circulating parasitemias , as measured by qPCR , are thought to vary considerably between acute ( 400 parasites/ml ) , newborn ( 150–12000 parasites/ml ) and chronic ( 3–16 parasites/ml ) cases [25 , 57] . Nonetheless , they remain several orders of magnitude lower than those that occur during T . brucei or P . falciparum infections . Low circulating T . cruzi parasitemia presents major problems to studies that aim to achieve molecular diagnosis of CD in chronic cases and ours is no exception . One problem is that much of the parasite diversity present in the host is likely to be sequestered in the tissues at any give time [58] , as our sequential samples from Goias also suggest . Thus blood stage parasite genetic diversity may be a poor representation of that actually present in the host . Another confounder is culture bias , by which differential growth of clones in culture , as well as loss of clonal diversity during repassage can both influence diversity estimates . Attempts to generate amplicon sequence data directly from clinical blood samples would likely to be thwarted by low circulating parasitemia [25 , 56] . Instead we elected to enrich for parasite DNA via culture—in Goias without further repassage , but in Bolivia with at least one repassage before cryopreservation . Low circulating parasitemia in Chagas patients also means it is possible that amplicon-sequencing strategies might rapidly ‘bottom out , ’ if few parasites are present within a sample . In our dataset , for example , at the ND5 locus , minority DTUs at 97% divergence can be present as a proportion of < 1 in 1000 ( Fig . 1 ) , with the implication that several thousand parasites must be present in the sample . In both Goias and Bolivia matched instances occurred in congenital cases where TcI exists in mother and infant as the minor DTU at similar relative abundance ( i . e . 1 in 1000 , Fig . 1 ) . It is highly unlikely that these data directly reflect chronic CD parasitemia levels . Instead , with reference to the data we obtained from the controls , PCR amplification bias is a more likely source of unrealistic major to minor genotype ratios . As such , the fourfold over-representation of a ST in the original sample , for example , can result in 100–1000 fold over-representation after PCR . However , while the relative abundance of sequence types recovered using the amplicon approach may be an inaccurate reflection of those present for both ND5 and TcGP63 , similar profiles between mother and infant suggests that this bias is likely to be consistent across samples . Thus comparisons between samples are still valid . Furthermore for ND5 at least it seems that T . cruzi frequently exchanges mitochondrial ( maxicircle ) genomes with little apparent evidence of nuclear exchange [11 , 29] . Fusion of maxicircle genomes occurs transiently during T . brucei genetic exchange events [59] , and may also do so in T . cruzi . Even though standard maxicircle genotyping of progeny only ever reveals a single parent in both species , it is possible that heterologous maxicircle sequences may persist at low abundance in parasite clones . Such a phenomenon could explain the DTU sequence type ratios observed , and this study is the first to sequence a maxicircle gene to this depth . There is general consensus in the literature is that the likelihood of congenital CD transmission is not strongly influenced by the genotype of the parasite infecting the mother [60–62] . Nonetheless , the majority of cases are reported in the Southern Cone region of South America , providing a circumstantial link with major human-associated T . cruzi genotypes TcV TcII , and TcVI . In this study , in the one mixed infection we found , major and minor DTUs ( TcVI / TcI ) detected in the mother at the ND5 locus were recovered from the infant in similar proportions . TcGP63I beta diversity comparisons of STs defined at 99% showed substantial sharing of between mother and infant ( Fig . 5 ) . However , both beta diversity comparisons ( Fig . 5 ) and total ST diversity ( alpha ) comparisons ( Fig . 3 ) at 99% indicate that while maternal diversity sometimes exceeds that of the infant ( explicable perhaps by sequestration in the mother and selective or stochastic trans-placental transfer ) , the reverse is frequently true . The occurrence of STs in the infant , not present in the mother , has several possible explanations . The infants sampled in this study were neonates , thus superinfection can be ruled out as a source of further parasite clonal diversity . A recent study of infected neonates in Argentina estimated mean infant parasitemia at 1 , 789 parasites/ml via qPCR—far in excess of that one might expect in the mother [57] . Thus the parasite sample size discrepancy between mother and infant perhaps explains the unexpected levels of diversity in the infant . Even though the TcGP63I gene family is apparently under intense diversifying selection , it seems unlikely that point mutation could generate novel variants over such a short time scale to explain genetic diversity in the infant . Structural variants and homologous recombination are a potential source of diversity , although most , if not all of recombinants should have been excluded in the quality filtering stages , and would be hard to distinguish from PCR chimeras in any case . Many important T . cruzi surface genes belong to large , recently expanded paralogous multigene families [17] . The abundance of these gene copies highlights their likely adaptive significance in terms of infectivity and host immune evasion , especially because trypansomatids exert so little control of gene expression at the level of transcription [63] . In Leishmania major , for example , it has been recently shown that gene amplification may rapidly duplicate segments of the genome in response to environmental stress [64] . As well as expansion , adaptive change is also likely to occur at the amino acid level among members of paralogous gene families , as has been suggested for T . brucei [65] . Despite the relatively small size of the TcGP63I gene family , the amplicon sequencing approach we employed allowed us to explore selection at the level of the gene within the population , i . e . within and between parasite genomes within and between hosts at the population level . Highly elevated non-synonymous substitutions suggest intense diversifying selection within TcGP63Ia and TcGP63Ia STs respectively for those assigned to TcII or TcI . STs from patients infected with TcIII-TcVI ( putative TcV ) showed few apparent substitutions ( Table 2 ) , perhaps consistent with the recent origin of this DTU [66] . The sequence fragment we studied was outside the zinc binding domain of this metalloprotease , indicating selective forces can act on this protein independent of its core proteolyic function , perhaps through repeated exposure to host immunity . It is important not to overlook the potential importance of multiclonal infections for parasitic disease , both as markers of population level factors such as parasite transmission , but also at the host level , including immunity and disease progression . In this study we have developed an amplicon sequencing approach to probe parasite genetic diversity within and among clinical CD cases to unprecedented depth . While our approach shows the power of this amplicon-seq to resolve diversity in clinical and congenital CD cases , it also highlights the potential biases that might be introduced with the addition of a PCR step . A tool that allows the accurate evaluation MOI would be valuable for tracking transmission rates at restricted disease foci ( i . e . villages , outbreaks ) in the context of measuring the success of intervention strategies . A similar tool could provide a powerful means of longitudinal tracking of T . cruzi infections in terms of disease progression , treatment failure and immunosuppression . Here we demonstrate that amplicon sequencing could have a role to play in this context . However , as sequencing costs decline and reference genome assemblies improve , whole genome deep sequencing , perhaps even of individual parasite cells , becomes and increasingly viable option as it already has for Plasmodium sp . [7 , 67] .
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Trypanosoma cruzi , the causal agent of Chagas disease in Latin America , infects several million people in some of the most economically deprived regions of Latin America . T . cruzi infection is lifelong and has a variable prognosis: some patients never exhibit symptoms while others experience debilitating and fatal complications . Available data suggest that parasite genetic diversity within and among disease foci can be exceedingly high . However , little is know about the frequency of multiple genotype infections in humans , as well as their distribution among different age classes and possible impact on disease outcome . In this study we develop a next generation amplicon deep sequencing approach to profile parasite diversity within chronic Chagas Disease patients from Bolivia and Brazil . We were also able to compare parasite genetic diversity present in eleven congenitally infants with parasite genetic diversity present in their mothers . We did not detect any specific association between the number and diversity of parasite genotypes in each patient with their age , sex or disease status . We were , however , able to detect the transmission of multiple parasite genotypes between mother and foetus . Furthermore , we also detected powerful evidence for natural selection at the antigenic locus we targeted , suggesting a possible interaction with the host immune system .
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[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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Deep Sequencing of the Trypanosoma cruzi GP63 Surface Proteases Reveals Diversity and Diversifying Selection among Chronic and Congenital Chagas Disease Patients
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Glycosylphosphatidylinositol ( GPI ) is a post-translational modification resulting in the attachment of modified proteins to the outer leaflet of the plasma membrane . Tissue culture experiments have shown GPI-anchored proteins ( GPI-APs ) to be targeted to the apical membrane of epithelial cells . However , the in vivo importance of this targeting has not been investigated since null mutations in GPI biosynthesis enzymes in mice result in very early embryonic lethality . Missense mutations in the human GPI biosynthesis enzyme pigv are associated with a multiple congenital malformation syndrome with a high frequency of Hirschsprung disease and renal anomalies . However , it is currently unknown how these phenotypes are linked to PIGV function . Here , we identify a temperature-sensitive hypomorphic allele of PIGV in Caenorhabditis elegans , pigv-1 ( qm34 ) , enabling us to study the role of GPI-APs in development . At the restrictive temperature we found a 75% reduction in GPI-APs at the surface of embryonic cells . Consequently , ~80% of pigv-1 ( qm34 ) embryos arrested development during the elongation phase of morphogenesis , exhibiting internal cysts and/or surface ruptures . Closer examination of the defects revealed them all to be the result of breaches in epithelial tissues: cysts formed in the intestine and excretory canal , and ruptures occurred through epidermal cells , suggesting weakening of the epithelial membrane or membrane-cortex connection . Knockdown of piga-1 , another GPI biosynthesis enzymes resulted in similar phenotypes . Importantly , fortifying the link between the apical membrane and actin cortex by overexpression of the ezrin/radixin/moesin ortholog ERM-1 , significantly rescued cyst formation and ruptures in the pigv-1 ( qm34 ) mutant . In conclusion , we discovered GPI-APs play a critical role in maintaining the integrity of the epithelial tissues , allowing them to withstand the pressure and stresses of morphogenesis . Our findings may help to explain some of the phenotypes observed in human syndromes associated with pigv mutations .
Proteins can attach to the plasma membrane by intrinsic transmembrane domains or by post-translational modifications with lipid moieties . One such lipid modification , tethering proteins to the outer leaflet of the plasma membrane ( PM ) , is a glycosylphospatidylinositol ( GPI ) anchor , whose synthesis and attachment to proteins in the endoplasmic reticulum ( ER ) is a multi-step process involving >30 enzymes [1] . Proteins subjected to GPI anchor modification harbor two signal peptides , an N terminal signal peptide that targets them to the ER and a C terminal signal peptide that serves as a marker for GPI attachment [2] . The basic structure of a GPI anchor consists of a phosphoethanolamine linker , a glycan core and a phospholipid tail . The glycan core of GPI can be modified by other phosphoethanolamine or other sugar groups , giving rise to diverse GPI anchor structures [3] . From the ER , GPI-anchor proteins ( GPI-APs ) are transported to the Golgi , where the phospholipid tail of GPI anchor undergoes lipid remodeling to increase the efficiency of membrane binding . GPI-AP are then sorted and subsequently delivered to the outer leaflet of the PM through the trans-Golgi network [4] . GPI-APs are mostly localized to the apical membrane of polarized cells and are enriched in domains known as lipid rafts [5 , 6] . Extraction of lipid rafts using weak non-ionic detergent pulls down GPI-APs along with the rafts [7] . Apical polarization of GPI-APs has also been observed in vivo in epithelial cells of pancreas , intestine and urinary bladder in GFP-GPI-expressing mice . GPI-APs are also present in non-polarized tissues with equal distribution across the membrane [8] . GPI-APs have very diverse functions in various cells across species . They are required for viability and cell wall biosynthesis in yeast , act as defense against host immune system in trypanosome , mediate cell-cell interactions , signal transduction , and perform enzymatic activity in mammalian cells [1 , 3 , 9] . At the tissue level , GPI-APs were shown to be important for germline and oocyte development in the nematode Caenorhabditis elegans ( C . elegans ) . Mutation in piga-1 ( ortholog of mammalian PIGA ) , the catalytic subunit of phosphatidylinositol N-acetylglucosaminyltransferase complex , the first enzyme playing a role in GPI biosynthesis , decreases the number of germline mitotic cells and compromises oocyte formation and maturation [10] . At the organism level , GPI-APs were shown to be essential for mouse and human embryogenesis . A complete PIGA knockout mouse could never be obtained and this may be explained by the fact that mouse embryonic stem cells depleted of PIGA form embryoid bodies that are arrested at an early stage of differentiation [11 , 12] . While each individual GPI-AP has a unique function that depends on the protein itself , there is evidence to suggest that GPI anchors themselves , independent of the proteins they anchor , play a role in organizing the PM . Moreover , despite the fact that GPI-anchors are positioned in the outer leaflet of the PM , they have been shown to be affected by the organization of the actin cortex underlying the PM [13 , 14] . Mounting evidence supporting essential roles for GPI-APs during human embryogenesis comes from human genetic studies conducted in the past decade . Missense mutations in genes encoding enzymes catalyzing various steps of GPI anchor biosynthesis , such as PIGW that catalyzes attachment of acyl group to phosphatidylinositiol [15 , 16] , PIGV that catalyzes transfer of second mannose to GPI intermediate [17 , 18] , PIGT that attaches GPI to proteins [19] and PGAP2 that modifies the phospholipid tail of PI [20] result in congenital diseases known as hyperphosphatasia mental retardation syndrome ( HPMRS ) , Hirschprung disease , morphological malformation and renal anomalies [21 , 22 , 23 , 24] . Studies on the roles of GPI-APs during embryogenesis have been hindered by the difficulties in obtaining viable mutants for GPI biosynthesis enzymes . In this study , we exploit a hypomorphic temperature-sensitive allele of pigv-1 ( human PIGV ortholog ) in C . elegans to investigate the role of GPI-APs during embryogenesis . We found that GPI-APs are vital for the integrity of epithelial tissues during morphogenesis , suggesting an essential role for GPI-APs in stabilizing the apical membrane of epithelial tissues under stress .
In the course of our whole genome sequencing of maternal-effect morphologically abnormal ( mal ) mutants isolated by Hekimi et al . [25] in an ethyl methanesulfonate ( EMS ) mutagenesis screen , we discovered that mal-3 ( qm34 ) ( Fig . 1A ) has a missense mutation at amino acid 361 of previously unassigned gene T09B4 . 1 , converting glycine to glutamate ( Fig . 1B ) . BLAST analysis of the T09B4 . 1 protein sequence suggested that it is an ortholog of human GPI mannosyltransferase 2 , which is known as PIGV ( S1A–B Fig . ) . The mutation was verified by conventional sequencing , and from this point onwards we refer to mal-3 ( qm34 ) as pigv-1 ( qm34 ) . Sometimes , EMS mutagenesis results in hypomorphic alleles that are temperature-sensitive . We investigated this possibility by growing pigv-1 ( qm34 ) worms at 15 , 20 and 25°C and measuring their viability at each temperature . We found that pigv-1 ( qm34 ) is a heat-sensitive allele , with more than 80% embryonic lethality at 25°C ( Fig . 1C , S1 Table ) . We followed embryogenesis by time-lapse differential interference contrast ( DIC ) microscopy and observed phenotypes resulting from pigv-1 inactivation at 25°C . At this temperature C . elegans embryogenesis takes 10 . 5 hours from the first division till hatching ( S2 Fig . ) . The first 3 hours of embryogenesis are characterized by formation of the founder cells , rapid cell division and gastrulation . At around 3 hours the epidermis is born on the dorsal side of the embryo and the next 3 . 5 hours are dominated by epidermal morphogenesis , a three step process made up of intercalation , enclosure , and elongation [26] . Loss of pigv-1 resulted in defects appearing during elongation with cysts forming inside the embryo and/or cells leaking out from the embryo body , resulting in elongation arrest and embryonic lethality ( Fig . 1D ) . Quantification of 176 pigv-1 ( qm34 ) embryos showed that over 80% displayed ruptures and/or cyst formation and arrested in elongation ( Fig . 1E ) . Few escapers hatched and became L1 larva with body shape defects ( Fig . 1A ) . Utilizing the heat sensitivity of pigv-1 ( qm34 ) , we determined the developmental period when pigv-1 activity is required through reciprocal temperature shift experiments . We found that pigv-1 activity is essential from the one cell embryo stage until elongation . Once elongation was underway inactivation of PIGV-1 had less effect on embryogenesis ( Fig . 1F , S3 Table ) . We confirmed that these phenotypes are caused by the mutation in pigv-1 by rescue experiments . Transformation of pigv-1 ( qm34 ) worms with a fosmid that contains a wild-type allele of the pigv-1 gene significantly rescued embryonic lethality ( P<0 . 01 ) ( Fig . 1G , S4 Table ) . Expression of a gfp-tagged pigv-1 under the control of 2 . 4 kb upstream of the pigv-1 start codon failed to rescue embryonic lethality in pigv-1 ( qm34 ) mutant worms , most likely due to low expression . On the other hand , expression of pigv-1 under the control of the erm-1 promoter , which resulted in 3 fold stronger expression , successfully rescued embryonic lethality of pigv-1 ( qm34 ) ( Fig . 1G , S4 Table ) , confirming that the mutated gene causing lethality in the pigv-1 ( qm34 ) strain is pigv-1 . To visualize GPI-AP distribution during embryogenesis , we used Alexa-488 labeled proaerolysin ( FLAER ) , a bacterial toxin that binds specifically to GPI-AP [27] , to label embryos at different stages of development ( Fig . 2 ) . In the one-cell embryo , GPI-APs accumulated at perinuclear areas and were enriched in the anterior cytoplasm ( Fig . 2 , first row ) . As soon as new membrane was delivered to the cell surface , during cell division , GPI-APs accumulated on the plasma membrane ( Fig . 2 , second row ) . During gastrulation we observed GPI-APs accumulated at the membrane of all cells ( Fig . 2 , fourth row ) . While being uniformly localized on membrane of all cells in the early embryo , non-uniform GPI-AP distribution was observed upon tissue differentiation . For example , during dorsal intercalation , GPI-APs were highly enriched on pharyngeal cell membranes in a non-polarized manner , whereas later on , during elongation , they became apically enriched ( Fig . 2 , fifth to seventh rows ) . To gain insight into the spatial and temporal activity of the PIGV-1 enzyme during embryogenesis , we visualized an N-terminally GFP-tagged PIGV-1 driven by its endogenous promoter in an extrachromosomal array . We could not detect GFP::PIGV-1 in the early embryo , possibly due to silencing of the transgenes in the germline . Later in development the expression level was low . Nevertheless , we observed GFP::PIGV-1 to be prominent in the epidermis , pharynx , intestine , rectum and excretory cell ( Fig . 3A ) , all tissues with epithelial character . At the subcellular level , PIGV-1 localized to intracellular structures that appear to be ER [28 , 29] . Using FLAER staining as readout for GPI-anchor biosynthesis , we compared the intensity of FLAER staining in pigv-1 ( qm34 ) at the permissive ( 15°C ) and restrictive ( 25°C ) temperatures . At 15°C , pigv-1 ( qm34 ) embryos exhibited FLAER levels similar to wild type , whereas at 25°C , abrogation of PIGV-1 activity led to a 4-fold reduction in the FLAER signal ( Fig . 3B , second and third rows ) . FLAER staining was restored to wild-type levels in pigv-1 ( qm34 ) embryos at 25°C when pigv-1 was expressed in all epithelial tissues by the erm-1 promoter ( Fig . 3B , fourth row ) . Taken together these data show that GPI-APs are enriched in epithelial tissues and the abundance of GPI-APs at the cell membrane is dependent on the activity of PIGV-1 . In mammalian cells , more than 30 enzymes are known to regulate the GPI anchor biosynthesis pathway . Many of these enzymes have orthologs in C . elegans ( S1B Fig . ) . A previous study has shown that RNAi-mediated knockdown of most C . elegans GPI anchor biosynthesis enzymes does not lead to any phenotype and two of them , namely pigk and pigo resulted in sterility [10] . We scanned a range of feeding RNAi conditions for pigk and pigo , with the rationale that partial loss of function might bypass their requirement for germline development , and expose a possible role in embryogenesis . However , we observed either sterility or no phenotype when each of the two enzymes was depleted . Thus , we turned our attention towards piga-1 ( tm2939 ) mutant worms characterized in the previous study [10] . Progeny of homozygous piga-1 ( tm2939 ) worms are embryonic lethal , and they display a deformed eggshell due to increased osmotic sensitivity during germline development . To uncouple the functions of PIGA-1 during germline development and embryogenesis , we used piga-1 ( tm2939 ) worms rescued by piga-1 expression under the control of lag-2 , a distal tip cell promoter . First , we examined whether lag-2 drives piga-1 expression during embryogenesis and found piga-1 expressed ubiquitously during embryogenesis ( Fig . 4A ) . Since the plag-2::piga-1::gfp construct is expressed as an extrachromosomal array , some embryos lose piga-1 expression during embryogenesis . We identified which embryos lost the extrachromosomal array and followed their embryonic phenotypes . While all the embryos retaining piga-1 expression during embryogenesis hatched , ~50% of the embryos devoid of piga-1 expression were arrested during elongation . In one-third of arrested embryos , internal cells leaked out from the embryo body ( Fig . 4B ) , a phenotype reminiscent of pigv-1 ( qm34 ) embryos , suggesting that weakening of epithelial tissue integrity is not a specific phenotype of pigv-1 loss of function , but rather a general consequence of disruption of the GPI biosynthesis pathway . The elongation phase of C . elegans embryogenesis is characterized by the formation of circumferential actin bundles ( CFB ) in the dorsal and ventral epidermal cells and actomyosin contraction in the lateral epidermal cells [30] . Contractility of the muscle tissues is known to be required for elongation beyond the 2-fold length [31] . We tested whether the elongation arrest occurring upon pigv-1 inactivation is caused by defective CFB and/or muscle organization . We examined CFB in pigv-1 ( qm34 ) embryos using an F-actin reporter ( VAB-10 actin binding domain tagged with GFP ) and found that CFB structure is indistinguishable from that of wild type embryo ( S3A Fig . ) . Myotactin antibodies were utilized to examine muscle organization and we observed no difference between muscle organization in wild type and in pigv-1 ( qm34 ) embryos ( S3B Fig . ) . Moreover , some pigv-1 ( qm34 ) embryos elongated beyond two-fold stage . These results suggest that elongation arrest in pigv-1 ( qm34 ) embryos is not caused by defects in CFB or muscle structure . We then set out to characterize the embryonic phenotypes resulting from pigv-1 inactivation in more detail . We employed several cell junction and membrane markers expressed in specific tissues to pinpoint the location of the defects . Using AJM-1::GFP and HMP-1::GFP as a marker for epidermal apical junctions , we observed gaps between epidermal cells through which internal cells leaked out , most often from the embryo anterior ( Fig . 5A and S1–S4 Movies ) . In some embryos , the gap is created by misalignment of leading ventral epidermal cells coming from opposite ends to enclose the embryo at the ventral midline ( Fig . 5A ) . Using a plasma membrane marker specifically expressed in the pharynx and intestine , we identified cysts to be located at the basal side of the intestine , and using CED-10::GFP , which highlights plasma membrane of all cells , we observed cysts to be located between the intestine and its surrounding basal lamina ( Fig . 5B-C , S4 Fig . ) . Using AJM-1::GFP to highlight the apical junctions of intestinal cells we observed widening of the lumen in pigv-1 ( qm34 ) embryos ( Fig . 5D ) . We measured intestinal lumen width of wild type and pigv-1 ( qm34 ) embryos in early ( 2–2 . 5 fold ) and later ( 3–3 . 5 fold ) stages of elongation and found that the lumen width of pigv-1 ( qm34 ) embryos was significantly wider ( P<0 . 05 ) than that of wild type embryos at late elongation ( Fig . 5D ) . Furthermore , we noticed that the intestine in pigv-1 ( qm34 ) embryos was often twisted ( S6C Fig . ) . Using mCherry-tagged AQP-8 , a water channel specifically localized to the excretory canal , expressed at a low level which maintains a normal translumenal flux , we found the excretory canal to be another location where cysts formed in pigv-1 ( qm34 ) embryos ( Fig . 5E ) . In contrast with the intestinal cysts that formed in extracellular space the excretory canal cysts formed within the cell . Few embryos that survived embryogenesis hatched with excretory canal cysts ( S5 Fig . ) . The excretory canals in larvae with excretory canal cysts were usually very short . Not only the length , but the branching of the excretory canal is also affected in pigv-1 ( qm34 ) embryo . In wild-type worms the excretory canal extends four tubules shaped like an H: a pair towards anterior and another pair towards posterior from the cell body . However , the excretory canal in pigv-1 ( qm34 ) embryo often has one or two more tubules extending from the cell body or branching from the original tubules ( S7 Fig . ) . GPI-APs are known to be targeted to apical membranes in polarized epithelial cells [5 , 6] . We therefore examined whether the apicobasal polarity of epithelial cells is affected in pigv-1 ( qm34 ) embryos . We observed that the apical markers PAR-6 and PKC-3 were correctly localized on the apical intestinal and excretory cell membranes in pigv-1 ( qm34 ) embryos ( S6A Fig . ) , and AJM-1 was localized at the apical side of epidermal and intestinal cell-cell junctions ( S6B–C Fig . ) . Conversely , the basolateral marker LET-413 was localized to the basolateral membranes in epidermal and intestinal cells in pigv-1 ( qm34 ) embryos , indistinguishable from wild type ( S6B Fig . ) . Similarly , the intermediate filament IFB-2 was correctly localized beneath the apical membrane in intestinal tissue in pigv-1 ( qm34 ) embryos ( S6C Fig ) . Altogether , these results rule out a polarity defect as the underlying cause for the pigv-1 ( qm34 ) mutant phenotypes . We observed pigv-1 loss of function to affect the integrity of three epithelial tissues: epidermis , intestine and excretory canal . However , it was not immediately evident which defective tissue was responsible for the embryonic lethality . To address this question we restored pigv-1 expression specifically in each epithelial tissue or in all epithelial tissues of pigv-1 ( qm34 ) worms and determined their embryonic viability . We employed the lin-26 promoter to drive expression in the epidermis , the pha-4 promoter to drive expression in the pharynx and intestine , the aqp-8 promoter to drive expression in the excretory canal , and the erm-1 promoter to drive expression in all epithelial tissues ( Fig . 6A ) . All promoters drove pigv-1 expression at comparable levels . While restoring pigv-1 expression in the pharynx-intestine or in the excretory canal partially reduced pigv-1 ( qm34 ) embryonic lethality , restoring pigv-1 expression in the epidermis did not significantly reduce pigv-1 ( qm34 ) embryonic lethality ( Fig . 6B , S4 Table ) . The most significant rescue of embryonic lethality achieved by expression of pigv-1 in a single tissue was a 17% reduction in lethality . In contrast , expressing pigv-1 in all epithelial tissues using the erm-1 promoter sharply decreased pigv-1 ( qm34 ) embryonic lethality down by 62% , comparable to the sum of the embryonic rescue of each epithelial tissue ( Fig . 6B , S4 Table ) . Thus , it appears that pigv-1 function is required in all epithelial tissues for embryonic viability . The cytoskeletal cortex underlying the plasma membrane provides it with structural support and protects the membrane from mechanical stress . Depletion of spectrin in erythrocytes changes membrane rigidity and subsequently leads to cell fragmentation [32] . Thus , we hypothesized that strengthening the actin cortex in pigv-1 ( qm34 ) embryos might positively affect membrane integrity . First , we examined whether providing more actin has any impact on epithelial membrane integrity . We examined pigv-1 ( qm34 ) embryos overexpressing YFP::ACT-5 in the epidermis and intestine and found that embryonic lethality in these worms is indistinguishable from that of pigv-1 ( qm34 ) ( Fig . 7A , S5 Table ) . We then explored whether strengthening the link between the actin cortex and the cell membrane might influence membrane integrity . We chose worms overexpressing ERM-1::GFP at a level which does not cause any phenotypic defect since a previous study showed that at high levels of expression ERM-1 leads to formation of excretory canal cysts [33] . We crossed the ERM-1::GFP-overexpressing worms with pigv-1 ( qm34 ) and found that embryonic lethality was significantly reduced in the pigv-1 ( qm34 ) ;ERM-1::GFP strain . Depletion of overexpressed ERM-1 by gfp ( RNAi ) in this stain reverted embryonic lethality back to pigv-1 ( qm34 ) level , confirming ERM-1 overexpression is responsible for rescuing pigv-1-associated embryonic lethality ( Fig . 7A , S5 Table ) . Careful examination of embryogenesis in pigv-1 ( qm34 ) embryos overexpressing ERM-1::GFP revealed strong suppression of pigv-1 phenotypes , and a significant portion of embryos ( 36% ) hatched without any visible defects ( Fig . 7B , S2 Table ) . Considering ERM-1 localization at intestine and excretory canal apical membranes , we reasoned that ERM-1 overexpression could rescue apical-associated phenotypes in these tissues . Measuring the width of intestinal lumen we found that it was reduced to the wild type dimension ( Fig . 7C ) . To gain insight into the mechanism of pigv-1-phenotype rescue by ERM-1 overexpression , we examined whether endogenous ERM-1 distribution and level were altered in pigv-1 ( qm34 ) embryos . Immunolabeling with ERM-1 antibodies showed no difference in ERM-1 distribution or level between wild type and pigv-1 ( qm34 ) embryos ( Fig . 8A ) . We then asked whether ERM-1 might rescue pigv-1 mutant by enhancing the residual pigv-1 activity and restoring the level of GPI-APs . Using FLAER as the probe for GPI-APs , we found that GPI-AP level in pigv-1 ( qm34 ) embryos overexpressing ERM-1 is similar to pigv-1 ( qm34 ) embryos alone , suggesting that ERM-1 overexpression does not rescue pigv-1 embryonic lethality by restoring GPI-APs ( Fig . 8B ) .
GPI anchor is an important post-translational protein modification whose functions and mechanisms have been widely studied using unicellular organisms and mammalian cells in culture [1 , 6 , 9] . However , the role of GPI biosynthesis in animals remains poorly understood . In humans , somatic mutations in PIGA gene loci lead to paroxysmal nocturnal hemaglobinuria , a disease characterized by increased susceptibility of erythrocytes to lysis by the complement immune system [34] . No heritable mutation in piga gene in human has been identified , suggesting that PIGA function is required during embryogenesis . Indeed , deletion of PIGA gene in mice , which completely abrogates GPI biosynthesis , resulted in early embryogenesis defects [11 , 35] . However , this condition precludes the study of GPI function throughout embryogenesis . Also in C . elegans , a null mutation in piga-1 results in germline defects and early embryonic lethality . In this study , we circumvented the early requirements for GPI-APs by using a temperature sensitive hypomorphic allele of pigv-1 . The amount of GPI-APs remaining upon pigv-1 inactivation was sufficient for normal germline development , thus enabling us to uncover their requirement during embryogenesis . We showed that GPI-APs are present and function throughout embryogenesis . Interestingly , the phenotypes of pigv-1 inactivation , i . e . , weakened epithelial tissues , are manifested only late in embryogenesis during the elongation stage of epidermal morphogenesis . This may be due to increased mechanical forces generated by actomyosin in muscle and epidermis tissues at that stage . Although present at the membrane of all cells in the C . elegans embryo , pigv-1 loss of function exhibits no defect in early development events , such as gastrulation or tissue differentiation . This is in contrast to mammalian embryogenesis , in which complete PIGA depletion results in defects in tissue differentiation [35] . One possible explanation for this difference is that the residual GPI-APs in pigv-1 animals are sufficient for normal differentiation . Another reason could be differences in the proteins regulating differentiation . Tissue differentiation in mammals is regulated by BMP/ TGF-β signaling whose activation requires GPI-anchored co-receptors , Dragon and Cripto-1 [35 , 36] . Although present in C . elegans , BMP/TGF-β signaling is not required during embryogenesis , but operates during postembryonic development , regulating body size [37 , 38] . Inactivation of pigv-1 in C . elegans embryos resulted mainly in epithelial defects . Failures in epidermal enclosure and intestinal cyst formation are consistent with weaker cell-cell adhesion . In the epidermis , improper cell-cell adhesion creates gaps between ventral epidermal cells from which internal tissues leak out during elongation . Compromised cell-cell junctions in the intestine , which has higher osmotic pressure than the surrounding tissues , would allow passage of low molecular weight substances , such as water molecules , from the intestinal lumen to the intestine basal side . The presence of a basal lamina separating the intestine from the pseudocoelom results in accumulation of these substances in the form of cysts . One possible explanation of these results is that the reduction in the amount of one or more specific cell adhesion proteins that are GPI-anchored causes the observed defects . However , amongst the GPI-APs that have been experimentally identified in C . elegans none are known to mediate cell-cell adhesion [7 , 10] . While we do not rule out the involvement of yet unknown GPI-anchored adhesion proteins , we propose another mechanism to explain the observed epithelial phenotypes that does not depend on a specific protein , but rather on the GPI anchors themselves . Goswami et . al . have shown that cortical actin affects the organization of GPI-AP in the membrane [13] . We propose that GPI-APs are enriched in apical membranes of polarized epithelial cells where they play a role in organizing the membrane into domains that interact with the actin cortex within the cell and through these interactions stabilize the apical membrane . According to this model , a decrease in GPI-APs will lead to fewer membrane-cortex connections and thus to a weaker apical membrane . In support of this idea , we observed a widening of the intestinal lumen in pigv-1 mutant embryos , as would be expected if the apical membrane of the intestine is weakened and thereby cannot resist as well the osmotic pressure from inside the lumen . Further support for this model comes from the finding that overexpression of ERM-1 rescues lumen width and overall embryonic lethality of pigv-1 mutant embryos . ERM-1 , the sole C . elegans ortholog of ezrin , radixin and moesin , is a linker protein that has an actin-binding domain and attaches to the PM through its FERM domain , serving to connect the PM with the actin cortex [39 , 40] . ERM-1 overexpression did not increase the levels of GPI-APs in pigv-1 embryos and hence the reduction in lethality associated with it is most likely due to its membrane-cortex cross-linking function . From this we deduce that loss of GPI-APs leads to a weakening of apical membranes in epithelial cells , irrespective of the proteins attached to the GPI-anchor . Another epithelial tissue affected by pigv-1 loss of function is the excretory canal . Down regulation of GPI-APs in the excretory canal leads to cysts formation and this cystic excretory canal is usually short , consistent with apical membrane weakening upon the loss of GPI-APs . Unlike the intestine , which is a multicellular tubule , the excretory canal is a unicellular tubule that extends actively during embryo elongation . It has been demonstrated that a balance between membrane-actin cortex recruitment and translumenal flux is essential for the excretory canal extension [33] . Weakened apical membrane upon down regulation of GPI-APs in pigv-1 mutant embryo may prevent further recruitment of membrane components and actin undercoat to extend the canal , creating an imbalance between the two forces . Consequently , the dominant force , the translumenal flux is transmitted to enlarge the canal diameter , resulting in cysts formation . Another phenotype we observed in the excretory canal of pigv-1 mutants is ectopic branching . To our knowledge such a phenotype has not been associated with loss of function of any gene so far , opening a new avenue to study the regulation of tubular branching . Besides epithelial tissues , loss of GPI-APs in C . elegans may also affects neuronal and/or muscle tissues , suggested by the lethargic phenotype of pigv-1 ( qm34 ) worms , although the GPI-APs responsible for this phenotype remains to be identified . The short excretory canal that has been observed occasionally in pigv-1 ( qm34 ) could also result from the loss of GPI-APs from neuronal membrane . The neuronal cell adhesion molecules ( NCAM ) that are essential for axon outgrowth and pathfinding have been demonstrated to regulate excretory canal extension [41 , 42 , 43] . In the absence of NCAM , the excretory canal does not grow to full extent . Supporting this view , the in vitro and the in silico experiments found several NCAMs ( rig-3 , rig-6 , rig-7 and wrk-1 ) to be potentially GPI-modified [7 , 44] . Not all epithelial tissues displayed abnormal phenotypes in pigv-1 mutants . The pharynx and rectum are two epithelial tissues that do not seem to be affected by down regulation of GPI-APs . High enrichment of GPI-APs at pharyngeal membranes compared to other tissues could provide an explanation for the absence of weakened membrane phenotypes . However , this reason does not hold for the rectum , as GPI-APs at rectal membranes are not more abundant than other tissues that display weakened membrane . Since both pharynx and rectum are covered by a cuticle , the most likely explanation for the absence of visible phenotypes is that the cuticle protects both tissues from potential damage resulting from weakened membranes . Restoring PIGV-1 expression individually in the epidermis , intestine and excretory canal in pigv-1 ( qm34 ) embryos revealed that the defects in these epithelial tissues do not contribute equally to the embryonic lethality . The intestine and the excretory canal defects have higher contribution to embryonic lethality as compared to the epidermal defects . This is somewhat unexpected because 56% of pigv-1 ( qm34 ) embryos die due to tissues leakage from the embryo interior , indicating that a gap between epidermal cells is present from where the tissues pass through . However , uncontained high pressure built in the intestinal and excretory canal due to cell adhesion defects and membrane weakening may be sufficient to open epidermal junction and push the internal tissues out of embryo interior . Mutations in the human ortholog of C . elegans pigv-1 , PIGV , have been associated in genetic studies with hyperphosphatasia-mental retardation syndrome ( a . k . a Mabry syndrome ) . This autosomal recessive syndrome has a wide spectrum of phenotypes including intellectual disabilities , facial anomalies , hyperphosphatasia , vesicoureteral and renal anomalies , and anorectal anomalies [21] . With the exception of hyperphosphatasia , which is known to be the result of loss of GPI-anchored complement inhibitors in blood cells [34] , the proteins and cellular functions that are affected in humans with PIGV mutations are unknown . Although our findings in C . elegans cannot possibly fully explain the cellular physiology of the human disease , it does point to a basic mechanism , i . e . , weakening of apical membranes in epithelial cells , that may be playing a role in some of the manifestations of the disease . Furthermore , if it will be discovered that epithelial membrane integrity is affected in human patients then our work also suggests a promising avenue for therapy , i . e . , strengthening of the membrane-cortex connection , based on our ERM-1 overexpression results .
Strains were grown and maintained at 20°C under standard conditions [45] . Wild type strain N2 was used as a control . The pigv-1 ( qm34 ) was retrieved from an EMS screening conducted by Hekimi et al . [25] . For analysis using GFP fusions , F2 progeny exhibiting pigv-1 phenotypes and carrying the markers were selected from crosses between pigv-1 ( qm34 ) and the following strains: SU93 jcIs1[ajm-1::gfp , unc-29 ( + ) , rol-6p::rol-6 ( su1006 ) ] [46] , SU265 jcIs17[hmp-1p::hmp-1::gfp , dlg-1p::dlg-1::dsRed , rol-6p::rol-6 ( su1006 ) ] [47] , SU467 pIs7[pha-4p::pm::gfp , rol-6p::rol-6 ( su1006 ) ] [48] , FT17 xnIs3[par-6p::par-6::gfp , unc-119 ( + ) ]; unc-119 ( ed3 ) III , MOT63 temIs59[pIC26::pkc-3]; unc-119 ( ed3 ) III , WS4918 opIS310[ced-1p::yfp::act-5::let-858 3'UTR , unc-119 ( + ) ] [49] , VJ402 fgEx1[erm-1p::erm-1::gfp , rol-6p::rol-6 ( su1006 ) ] [33] , ML1735 mcIs50[lin-26p::vab-10 ( actin-binding domain ) ::gfp , myo-2p::GFP] [50] , plag-2p::piga-1::egfp-expressing strain was generated by Murata et al [10] . All plasmids generated in this study were constructed in a modified pPD95 . 75 backbone . For tissue-specific rescue of pigv-1 loss of function , GFP position was changed to be at the N terminal instead of at the C terminal of the multiple cloning sites ( MCS ) , whereas for AQP-8-expressing plasmid , GFP at C terminal was replaced with mCherry . To construct pigv-1p::gfp::pigv-1 plasmid , pigv-1 promoter ( 2 . 4 kb sequence upstream of pigv-1 start codon ) and coding sequence were amplified and inserted into SbfI and AgeI sites upstream of gfp in original pPD95 . 75 vector . Circular PCR was performed to amplify the whole plasmid , but the gfp region using a pair of primers harboring XhoI sites at their 5’ ends . PCR product was then ligated to produce a circular plasmid containing pigv-1 promoter and coding sequence , but without gfp . Second circular PCR was conducted to insert two new restriction sites , i . e . : NotI and BglII between pigv-1 promoter and coding sequence . PCR product was then subjected to digestion using NotI and BglII . gfp coding sequence was amplified from original pPD95 . 75 and subcloned into pJET ( Thermo Scientific ) . The recombinant plasmid was digested using NotI and BglII and gfp sequence-containing product was ligated to pigv-1-containing pPD95 . 75 , resulting in a plasmid expressing gfp::pigv-1 driven by pigv-1 promoter . Four different promoters were used to rescue pigv-1 ( qm34 ) in different tissues: 4 . 1 kb sequence of lin-26 promoter to drive pigv-1 expression in epidermis , 7 . 1 kb of pha-4 promoter for expression in pharynx and intestine , 2 . 2 kb of aqp-8 promoter for expression in excretory canal and 3 kb of erm-1 promoter for expression in all epithelial tissues . They are inserted into modified pPD95 . 75 at SbfI/NotI sites replacing pigv-1 promoter . Transgenic animals generated by injecting the constructs into the gonad of hermaphrodite animals resulted in the following strains: RZB40 ( pigv-1 ( qm34 ) ; msnEx40[lin-26p::gfp::pigv-1; rol-6 ( su1006 ) ] ) , RZB41 ( pigv-1 ( qm34 ) ; msnEx41[pha-4p::gfp::pigv-1; rol-6 ( su1006 ) ] ) , RZB129 ( pigv-1 ( qm34 ) ; msnEx129[aqp-8p::gfp::pigv-1; rol-6 ( su1006 ) ] ) and RZB128 ( pigv-1 ( qm34 ) ; msnEx128[erm-1p::gfp::pigv-1; rol-6 ( su1006 ) ] ) . To construct aqp-8::mCherry-expressing plasmid , mCherry coding sequence was amplified from pAA64 and ligated to circularly amplified pPD95 . 75 devoid of gfp sequence using Gibson assembly ( NEB ) . Subsequently , 2 . 2 kb aqp-8 promoter together with aqp-8 genomic sequence were inserted at SbfI/BamHI sites in modified pPD95 . 75 . Injection of this construct resulted in strain RZB221 ( pigv-1 ( qm34 ) ; msnEx221[aqp-8p::aqp-8::mCherry; rol-6 ( su1006 ) ] ) . Microinjection was performed as described by Mello and Fire [51] . Injection mix includes 100 μg/μl salmon sperm DNA digested with PvuII , 20 μg/μl rol-6 ( su1006 ) digested with SbfI and 5–10 μg/μl each construct digested with SbfI . Genomic DNA was extracted from pigv-1 ( qm34 ) mutant worms using standard method and subjected to whole genome sequencing using Illumina platform and annotated using MAQGene [52] . The whole genome sequencing and its annotation were performed by Hobert lab ( Columbia University ) . Candidate genes altered in pigv-1 ( qm34 ) were narrowed down using genetic mapping results done by Hekimi et al . [25] . Point mutation in pigv-1 gene was confirmed by amplification of pigv-1 gene in pigv-1 ( qm34 ) mutant worms , subcloning into pJET vector ( Thermo Scientific ) and followed by conventional sequencing ( First Base ) . Further validation of pigv-1 missense mutation as the phenotype-causing gene in pigv-1 ( qm34 ) worms was done by injection of 100 μg/μl fosmid WRM063BcC08 , which contains pigv-1 gene , together with the co-transformation marker rol-6 ( su1006 ) into the gonad of pigv-1 ( qm34 ) hermaphrodites . F2 rollers were upshifted to 25°C and examined for embryonic lethality . Ten to fifteen gravid hermaphrodites were placed on the plate and incubated for several hours to lay more than 100 eggs . Hermaphrodites were then removed and the number of eggs laid was counted . Twenty-four hours later , the number of larvae hatched was determined . Each experiment was done in duplicate and repeated five times . Beside experiments determining temperature sensitivity that are conducted at three different temperatures ( 15°C , 20°C and 25°C ) , the remaining experiments were conducted solely at 25°C to get the highest extent of pigv-1 inactivation . In this case , L4 larvae were upshifted from 20°C to 25°C for 20 to 24 hours prior to the test . For upshift experiment , embryos were dissected from gravid pigv-1 ( qm34 ) worms grown at 15°C and incubated at 25°C for the duration of embryogenesis . Each embryo was staged and scored for hatching . For downshift experiment , similar procedure was performed , except that pigv-1 ( qm34 ) worms were kept at 25°C for 24 hours before downshifted to 15°C . Embryos that do not hatch at the end of embryogenesis were considered as lethal . Larvae or embryos collected from gravid hermaphrodite , mounted onto 3% agarose padded-glass slide , closed with coverslip and sealed with wax . Normaski images shown in Fig . 1A , B and S2B were captured using a Nikon Ti Eclipse widefield microscope equipped with DIC 1 . 40NA oil condenser and a charged-coupled device camera Cool Snap HQ2 ( Photometrics ) . All other imaging were done using spinning disk confocal system composed of a Nikon Ti Eclipse microscope with a CSU-X1 spinning disk confocal head ( Yokogawa ) , DPSS-Laser ( Roper Scientific ) at 491 and 568 nm excitation wavelength and an Evolve Rapid-Cal electron multiplying charged-coupled device camera ( Photometrics ) . For both microscopes , Metamorph software ( Molecular Devices ) was used to control acquisition . Projected images were created using Fiji . After 24 hour DIC recording , wild type , pigv-1 ( qm34 ) and pigv-1 ( qm34 ) embryos expressing ERM-1::GFP were scored as viable or lethal and each category is further classified into four subcategories; i . e . : without visible defects , with cysts and rupture , with cyst only and with rupture only . IPTG plate used for gfp ( RNAi ) feeding was prepared as described [53] . Wild type and pigv-1 ( qm34 ) L1 larvae expressing ERM-1::GFP were fed using bacterial-feeding strain of gfp for 3 days at 15°C till they become L4 and then upshifted to 25°C for overnight . The absence of GFP signal was verified by using fluorescent stereomicroscope and only those devoid of the signal were subjected for embryonic lethality test . Fixation and indirect immunofluorescence were performed essentially as described [54] . The following primary mouse antibodies were used: ERM-1 ( DSHB; 1/20 ) , AJM-1 ( MH27 , DSHB; 1/10 ) , myotactin ( MH46 , DSHB; 1/5 ) and LET-413 ( DSHB; 1/2 ) and IFB-2 ( MH33 , DSHB; 1/5 ) . Donkey anti-mouse coupled to Alexa 647 ( 1/500 ) ( Life technologies ) was used as secondary antibodies and proaerolysin coupled to Alexa 488 ( FLAER , Protox Biotech ) was used to detect GPI-APs . Images were taken on a Nikon Ti Eclipse spinning disk microscope with 100x objective and processed further using Fiji . To measure lumen width in wild type and pigv-1 ( qm34 ) mutant embryos , N2 and pigv-1 ( qm34 ) embryos expressing AJM-1::GFP were fixed , maximum intensity projection of embryonic intestine in GFP channel was constructed and the widest section of intestinal lumen was determined . The same procedure was done to measure lumen width in pigv-1 ( qm34 ) embryos expressing ERM-1::GFP , except that AJM-1 antibodies were used instead of AJM-1::GFP expression . Statistical analyses were done using Microsoft Excel . Two-tailed Student’s t-test was applied to compare the values .
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Cell surface proteins , such as receptors , either integrate into the plasma membrane through a transmembrane domain or are tethered to it by an accessory glycosylated phospholipid ( GPI ) anchor that is attached to them after they are made . The GPI-anchor biosynthesis pathway is highly conserved from yeast to humans and null mutations in any of the key enzymes are lethal at early developmental stages . Point mutations in several genes encoding for GPI-anchor biosynthesis enzymes have been linked to human disease . Specifically , mutations in PIGV are associated with multiple congenital malformations , including renal and anorectal malformation and mental retardation . It is currently not known how the mutations in PIGV lead to these diseases . Here we describe a point mutation in the PIGV ortholog of the nematode Caenorhabditis elegans , pigv-1 , which is found to cause a high degree of embryonic lethality . We documented a substantial reduction in the level of GPI-anchors in the mutant . Importantly , following its development using 4D microscopy and employing tissue-specific rescue , we identified loss of epithelial integrity as the primary cause of developmental arrest . Our results highlight the importance of GPI-anchored proteins for epithelial integrity in vivo and suggest a possible etiology for human diseases associated with PIGV mutations .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Glycosyl Phosphatidylinositol Anchor Biosynthesis Is Essential for Maintaining Epithelial Integrity during Caenorhabditis elegans Embryogenesis
|
Rickettsia ( R . ) typhi is the causative agent of endemic typhus , an emerging febrile disease that is associated with complications such as pneumonia , encephalitis and liver dysfunction . To elucidate how innate immune mechanisms contribute to defense and pathology we here analyzed R . typhi infection of CB17 SCID mice that are congenic to BALB/c mice but lack adaptive immunity . CB17 SCID mice succumbed to R . typhi infection within 21 days and showed high bacterial load in spleen , brain , lung , and liver . Most evident pathological changes in R . typhi-infected CB17 SCID mice were massive liver necrosis and splenomegaly due to the disproportionate accumulation of neutrophils and macrophages ( MΦ ) . Both neutrophils and MΦ infiltrated the liver and harbored R . typhi . Both cell populations expressed iNOS and produced reactive oxygen species ( ROS ) and , thus , exhibited an inflammatory and bactericidal phenotype . Surprisingly , depletion of neutrophils completely prevented liver necrosis but neither altered bacterial load nor protected CB17 SCID mice from death . Furthermore , the absence of neutrophils had no impact on the overwhelming systemic inflammatory response in these mice . This response was predominantly driven by activated MΦ and NK cells both of which expressed IFNγ and is considered as the reason of death . Finally , we observed that iNOS expression by MΦ and neutrophils did not correlate with R . typhi uptake in vivo . Moreover , we demonstrate that MΦ hardly respond to R . typhi in vitro . These findings indicate that R . typhi enters MΦ and also neutrophils unrecognized and that activation of these cells is mediated by other mechanisms in the context of tissue damage in vivo .
Rickettsioses are emerging febrile diseases that can be fatal . Causative agents are intracellular bacteria of the family of Rickettsiaceae that are transmitted to humans by arthropods . The family Rickettsiaceae is subdivided into the genera Rickettsia and Orientia . While the genus Orientia has only one member , Orientia tsutsugamushi which is the causative agent of scrub typhus , the genus Rickettsia is further subdivided into four major groups: The spotted fever group ( SFG ) , the typhus group ( TG ) , the transitional and the ancestral group . The majority of rickettsiae belong to the SFG . Prominent members of this group are Rickettsia ( R . ) rickettsii , the causative agent of Rocky Mountain Spotted Fever ( RMSF ) , and R . conorii that causes Mediterranean Spotted Fever ( MSF ) . R . prowazekii and R . typhi constitute the typhus group ( TG ) of rickettsiae [1 , 2] . The transitional group consists of R . felis , R . akari and R . australis and members of the non-pathogenic ancestral group are R . bellii and R . canadensis [2 , 3] . R . prowazekii and R . typhi are the causative agents of epidemic and endemic typhus , respectively . These diseases appear with similar symptoms . After an incubation period of 10–14 days the disease starts with the sudden onset of high fever that lasts for several days . Patients further suffer from diverse symptoms including headache , muscle and joint pain , nausea and vomiting . In addition , neurological symptoms such as confusion and stupor are common [4] . As endothelial cells belong to the main target cells of rickettsiae [5] , rickettsial infections result in local blood vessel lesions and inflammatory responses . For that reason the majority of patients develop a characteristic hemorrhagic rash as rickettsiae first enter the skin [2] . Systemic infection can result in fatal multi-organ pathology and complications such as pneumonia , myocarditis , nephritis , encephalitis or meningitis [4 , 6] . In addition , splenomegaly and liver dysfunction are common [7] . The course of disease of endemic typhus is generally milder than that of epidemic typhus . The lethality of R . typhi infection is estimated to be <5% [8 , 9] while the lethality of R . prowazekii infection is up to 20–30% [6 , 9 , 10] if untreated with effective antibiotics such as tetracyclins or chloramphenicol . Mouse models for rickettsial infections are rare . Immunologically useful strains such as C57BL/6 and BALB/c mice were found to be resistant to various rickettsiae while C3H/HeN mice have been shown to be susceptible [11–15] . Infection of C3H/HeN mice revealed some insight into immune response against rickettsiae in recent years . It has been shown that cytotoxic CD8+ T cells in addition to IFNγ are critical for protection against SFG rickettsiae such as R . rickettsii and R . conorii in C3H/HeN mice [16–19] while generally little is known about immune response against TG rickettsiae . Mice of the C57BL/6 strain that lack adaptive immunity ( C57BL/6 RAG1-/- mice ) mount a robust innate immune response that is sufficient to prevent rickettsial disease , at least for a long period of time . C57BL/6 RAG1-/- mice survive the infection with R . conorii as well as with R . typhi for at least 20 days [20 , 21] . R . typhi , however , persists in these animals , causing lethal central nervous system inflammation months after infection [21] . In the present study we analyzed CB17 SCID mice in R . typhi infection . These mice resemble C57BL/6 RAG1-/- mice as they also lack T and B cells [22 , 23] . However , whereas C57BL/6 RAG1-/- mice are capable to control the infection for more than 80 days before R . typhi reappears in the central nervous system , infection of CB17 SCID mice with R . typhi leads to a complete different outcome . CB17 SCID mice succumbed to R . typhi infection within 20 days . At the time of death R . typhi was detectable at high amounts in various organs with the highest bacterial load in the spleen followed by the brain , lung and liver . The most striking pathological changes in CB17 SCID mice were a dramatic enlargement of the spleen and severe liver necrosis . Splenomegaly was mainly due to massive accumulation of MΦ and neutrophils . Both cell types were found to harbor R . typhi and exhibited an inflammatory and bactericidal phenotype , indicated by the production of reactive oxygen species ( ROS ) and the expression of inducible nitric oxide synthase ( iNOS ) . We further show that neutrophil-depletion completely prevents liver necrosis in R . typhi-infected CB17 SCID mice , demonstrating that neutrophil activity is responsible for liver damage in these animals . The absence of neutrophils , however , did not alter bacterial load nor prevent the mice from death . In addition , neutrophil depletion did not influence the strong systemic inflammatory response observed in these mice . This response was dominated by IFNγ , TNFα and IL-6 and mainly driven by MΦ and NK cells . We finally show that MΦ and also neutrophils , although the cells take up R . typhi , hardly respond to the bacteria in a direct way . iNOS expression by these cells in vivo did not correlate with R . typhi uptake . Moreover , bone marrow-derived MΦ ( bmMΦ ) were uncapable to kill ingested bacteria and neither released inflammatory mediators nor bactericidal nitric oxide ( NO ) upon infection with R . typhi in vitro . These data show that R . typhi does not activate MΦ in a classical manner although the cells upregulated the expression of major histocompatibility complex class I ( MHCI ) and CD80 . We therefore suggest that MΦ activation in R . typhi-infected CB17 SCID mice is largely mediated by indirect mechanisms in the context of cellular damage . Collectively , our data show that liver damage in CB17 SCID mice is due to the action of neutrophils and suggest that overwhelming systemic inflammation is responsible for death of these mice .
BALB/c , BALB/c RAG2-/- and congenic CB17 SCID ( CB17/lcr-PrkdcSCID/lcrlcoCrl ) mice that lack T and B cells due to a genetic autosomal recessive mutation in the PrkdcSCID allele on chromosome 16 [22 , 23] were bred and maintained in the animal facilities of the Bernhard Nocht Institute for Tropical Medicine , Hamburg , and housed in a biosafety level 3 facility for experimentation . The facilities are registered by the Public Health Authorities ( Behoerde für Gesundheit und Verbraucherschutz , Hamburg ) . All experimentations and procedures were approved by the Public Health Authorities ( Behoerde für Gesundheit und Verbraucherschutz , Hamburg: no 88/13 ) and performed according to the German Animal Welfare Act . R . typhi ( Wilmington strain ) was cultivated in L929 mouse fibroblasts ( ATCC CCL-1 ) in RPMI1640 ( PAA , Cölbe , Germany ) supplemented with 10% FCS ( PAA , Cölbe , Germany ) , 2 mM L-glutamine ( PAA , Cölbe , Germany ) and 10 mM HEPES ( PAA , Cölbe , Germany ) without antibiotics under biosafety level 3 conditions . 1×107 L929 cells were seeded in 175 cm2 culture flasks ( Greiner Bio-One , Frickenhausen , Germany ) and γ-irradiated ( 1966 rad at 560sec ) . One day later cells were infected with R . typhi and incubated for 5 to 7 days . Stocks of purified bacteria were prepared from L929 cell lysates . Therefore , cells were resuspended in 1 . 5 ml PBS and vortexed thoroughly for 1 min with 200 μl sterile siliceous particles ( 60/90 grit silicon carbite , Lortone inc . , Mukilteo USA ) in a 2 ml SafeSeal tube ( Sarstedt , Nümbrecht , Germany ) . The crude lysate was strained through a 2 μm cell strainer ( Puradisc 25 syringe filter 2 μm; GE Healthcare Life Sciences , Freiburg , Germany ) , mixed in a ratio of 1:1 with 2-fold concentrated storage medium ( FCS/15% DMSO ) and transferred into Cryo . S tubes ( Greiner Bio-One , Frickenhausen , Germany ) in liquid nitrogen . Thawed bacterial stocks were centrifuged at 7826xg for 5 min at room temperature , washed once with PBS and analyzed for bacterial content by quantitative real-time PCR ( qPCR ) . Spot forming units ( sfu ) as a measure for the amount of living bacteria in the preparation were determined by immunofocus assay . For this purpose , L929 cells were incubated with titrated amounts of R . typhi in 24well plates . After 4h of bacterial adherence the medium was exchange against semi-solid medium containing 1% methylcellulose and cells were further incubated for 8–10 days . For detection of R . typhi , cells were fixed in PBS/4% formaldehyde/0 . 1% TritonX100 ( Sigma-Aldrich , Deisenhofen , Germany ) for 20 minutes followed by permeabilization in PBS/0 . 5% TritonX100 for 20–60 minutes . Cells were blocked with 200 μl PBS/10% FCS for 1 hour . Monoclonal anti-R . typhi antibody ( BNI52 ) was added at 1 μg/ml in PBS/10% FCS overnight at 4°C . Cells were washed in H2O and with goat anti-mouse HRP ( Dako , Hamburg , Germany; 1:400 in PBS/10% FCS ) for 1-2h in the dark at RT . Finally , cells were washed and plates were developed with Immunoblot 3 , 3′ , 5 , 5′-tetramethylbenzidine ( TMB ) substrate solution ( Mikrogen , Neuried , Germany; 200 μl ) and analyzed with a BZ9000 Keyence microscope ( Keyence , Neu-Isenburg , Germany ) . Mice were subcutaneously ( s . c . ) infected into the base of the tail with 2×106 sfu R . typhi in 50 μl PBS . For neutrophil depletion , 200 μg anti-Ly6G were injected every 3 days intraperitoneally into CB17 SCID mice starting 6 days after infection with R . typhi . A control group of R . typhi-infected CB17 SCID received equal amounts of IgG2a isotype antibody . A second control group of animals was not infected and received anti-Ly-6G only . A third group of control mice was not infected and treated with PBS . Depletion of neutrophils was monitored by flow cytometry of blood cells . For flow cytometric detection of intracellular IFNγ and TNFα expression by different cell populations directly ex vivo 100 μg brefeldin A ( #B7651; Sigma , Deisenhofen , Germany ) were intravenously injected into R . typhi-infected CB17 SCID mice 12h prior to spleen cell isolation . Non-infected control animals that had received PBS instead of R . typhi were treated the same way . These analyses were performed on day 12 post infection or PBS treatment , respectively . Based on the findings described in the first part of the results section a clinical score was defined to monitor the health status of R . typhi-infected animals . The following five criteria were assessed: posture ( 0: normal , 1: temporarily curved , 2: curved ) , fur condition ( 0: normal , 1: staring in the neck , 2: overall staring ) , activity ( 0: normal , 1: reduced , 2: strongly reduced ) , weight loss ( 0: < 10% , 1: 10–14% , 2: > 15% ) and food and water uptake ( 0: normal , 1: reduced , 2: none ) . Mice were considered healthy with a score < 5 , moderately ill with a score of 5–7 and severely ill with a score of 8–10 . Mice were euthanized reaching a total score of ≥8 or showing weight loss of ≥20% . This was determined as the time of death . The state of health of the animals was assessed by clinical scoring every 2 days . Blood was taken submandibular or by cardiac puncture after euthanasia with CO2 . For plasma samples blood was collected in EDTA coated tubes ( KABE Labortechnik GmbH , Nümbrecht-Elsenroth , Germany ) and centrifuged at 5654×g . Serum samples were obtained by agglutination for 15–20 at RT followed by centrifugation for 10 min 5654×g . 10 mg tissue was homogenized in 500 μl PBS in Precellys ceramic Kit tubes ( Peqlab . Erlangen , Germany ) in a Precellys 24 homogenizer ( Peqlab . Erlangen , Germany ) with following cycle parameters: 6000 rpm two times for 45 sec with a 60 sec break . DNA was prepared from 80 μl homogenized organs or up to 1×106 L929 cells using the QIAamp DNA Mini Kit ( Qiagen , Hilden , Germany ) according to the manufacturer’s guide . R . typhi was quantified by amplification of a 137 bp fragment of the PrsA gene ( RT0565 ) with the forward primer 5´-ACA GCT TCA AAT GGT GGG GT-3´ and reverse primer 5´-TGC CAG CCG AAA TCT GTT TTG-3´ in a standard SYBR green real-time PCR . To determine R . typhi copy numbers a standard template plasmid ( pCR2 . 1-PrsA ) containing the same PrsA DNA fragment was used . Reactions were performed in a Rotor Gene 6000 ( Qiagen , Hilden , Germany ) in a total volume of 10 μl with 1×HotStar Taq DNA Polymerase Buffer comprising 1 . 5 mM MgCl2 , 0 . 175 mM dNTPs , 100 nM primers , 0 . 05x SYBR green I nucleic acid gel stain ( SIGMA Life Science , Deisenhofen , Germany ) and 0 . 25 U HotStar Taq DNA Polymerase ( Qiagen , Hilden , Germany ) under following conditions: 15 min pre-heating at 95°C followed by 40 cycles of denaturation ( 94°C for 20 sec ) , primer annealing ( 53°C , 30 sec ) and elongation ( 72°C for 20 sec ) . Anti-R . typhi ( BNI52 ) is a monoclonal mouse antibody that was generated at the Bernhard Nocht Institute for Tropical Medicine , Hamburg , Germany . It was used at 1 μg/ml for immunofluorescent stainings of infected cell cultures and flow cytometry . For flow cytometry the following antibodies were used at the indicated dilutions and concentrations: anti-NOS2 ( iNOS ) -PE ( clone CXNFT , 1:200 ) , anti-NOS2 ( iNOS ) -PE/Cy7 ( clone CXNFT , 1:300 ) , anti-MHCI ( H-2d ) -PE ( clone SF1-1 . 1 . 1 , 1:200 ) , rat IgG2a κ Isotype PerCp-Cy5 . 5 ( eBR2a ) and anti-mouse NKp46-PE ( clone 29A1 . 4 , 1:200 ) from eBioscience , Frankfurt , Germany; anti-CD11b-PerCp-Cy5 . 5 ( clone M1/70 , 1:200; 1:800 for bmMΦ ) from BD Bioscience , Heidelberg , Germany; anti-Ly6-C-PerCP/Cy5 . 5 ( clone HK1 . 4 , 1:200 ) , anti-Ly-6G-APC ( clone 1A8 , 1:166 , 7 ) , anti-GR1 ( L6G/Ly6C ) -APC ( clone GR-1/RB6-8C5 , 1:500 ) , anti-CD80-PE/Dazzle594 ( clone 16-10A1 , 1:100 ) , anti-CD11b-FITC ( clone M1/70 , 1:100 ) , rat IgG2a κ isotype PE ( RTK2758; 1:200 ) , rat IgG1 κ isotype PE-Cy7 ( RTK20711; 1:200 ) , anti-mouse IFNγ PE/Dazzle ( clone XMG1 . 2; 1:333 ) , anti-mouse TNFα BV510 ( clone MP-6-XT22; 1:80 ) and rat IgG1 κ isotype PE/Dazzle 594 ( RTK 2071; 1:200 ) from BioLegend ( London , UK ) ; unlabeled mouse IgG3 κ isotype ( clone B10; 1 μg/ml ) and anti-mouse-IgG3-FITC from SouthernBiotech ( #1100–02; Birmingham , USA; 1:200 ) . Histological stainings were performed with the following antibodies and reagents: R . typhi patient serum ( 1:100 ) from the diagnostics department of the Bernhard Nocht Institute for Tropical Medicine , Hamburg , Germany; anti-mouse iNOS ( ABIN373696 , 1:75 ) from Abcam , Cambridge , USA; anti-mouse IBA1 ( #019–19741; 1:500 ) from WAKO , Neuss , Germany; anti-mouse Ly-6G ( clone 1A8; 1:1000 ) from BD Biosciences , Heidelberg , Germany; anti-mouse-IgG3-FITC ( #1100–02; 1:200 ) from SouthernBiotech , Birmingham , USA; anti-human IgG-FITC ( #H10101C; 1:200 ) , anti-rabbit Alexa555 ( #A31572; 1:300 ) and anti-rat Alexa568 ( #A11077; 1:300 ) from Thermo Fisher Scientific , Braunschweig , Germany; anti-FITC-Alexa488 ( 1:1000 ) from LifeTechnologies , Darmstadt , Germany; DAPI ( 4´ , 6-diamidino-2-phenylindole dihydrochloride; 1:1000 ) and CohnII human IgG fraction ( 5% in PBS ) from Sigma , Deisenhofen , Germany . Isotype antibodies were used at concentrations corresponding to the respective staining antibodies . For neutrophil depletion anti-Ly-6G ( clone 1A8 ) and rat IgG2a ( clone 2A3 ) isotype control antibody ( BioXCell , New Hampshire , USA ) were used . Single cell suspensions were prepared from spleen , liver , blood samples or cell culture . Erythrocytes were eliminated from spleen , liver and blood samples by incubating the cells in erythrocyte lysis buffer ( 10 mM Tris , 144 mM NH4Cl , pH 7 . 5 ) for 5 minutes at room temperature . Afterwards , cells were washed twice with PBS . Fc receptors were blocked with 50 μl 5% CohnII human IgG fraction ( Sigma-Aldrich , Deisenhofen , Germany ) in PBS or Perm/Wash solution . BD Cytofix/Cytoperm and BD Perm/Wash solutions ( BD Biosciences , Heidelberg , Germany ) were used for intracellular staining of iNOS and R . typhi . Intracellular cytokines were detected employing the FoxP3/Transcription Factor Staining Buffer Set ( eBioscience , Frankfurt , Germany ) . Procedures were performed according to the manufacturer´s instructions . CD80 and MHCI on bmMΦ were first stained extracellularly followed by intracellular staining of iNOS and R . typhi . Antibodies were diluted in 50 μl of either PBS or Perm/Wash solution . Cytokines ( TNFα and IFNγ ) , NKp46 , CD11b and GR1 were stained simultaneously intracellularly in Permeabilization Buffer of the FoxP3/Transcription Factor Staining Buffer Set . After staining , cells were washed and resuspended in PBS/1% PFA or PBS/10% FCS prior to flow cytometry . Analyses were performed with a BD Accuri C6 or BD LSR II flow cytometer ( BD Biosciences , San José , USA ) and FlowJo single cell analysis software ( FlowJo LLC , Ashland , USA ) . ROS release was determined in blood cells of infected mice by the formation of the fluorescent compound rhodamine-123 from dihydrorhodamine-123 ( DHR-123 , AAT Bioquest , California , USA ) . Staining was performed with 30 μl EDTA blood samples after erythrocyte lysis . Surface markers were stained as described above prior to ROS detection . Cells were incubated with 30 μg/ml DHR-123 in PBS for 20 min at 37°C in the dark . After washing with 4 ml of cold PBS 40 μl of cell suspensions were immediately analyzed using BD Accuri C6 ( BD Biosciences , San José , USA ) and FlowJo single cell analysis software ( FlowJo LLC , Ashland , USA ) . Plasma cytokines were quantified by bead-based LEGENDplex immunoassay ( BioLegend , London , UK ) according to the manufacturer’s protocol using cluster tubes ( ThermoScientific , Loughborough UK ) . 12 . 5 μl of plasma from EDTA blood samples was used diluted 1:2 in PBS . Supernatants from bmMΦ were used non-diluted . Analyses were performed using a BD Accuri C6 ( BD Biosciences , San José , USA ) and LEGENDplex analysis software ( BioLegend , San Diego , USA ) . Serum levels of GPT were evaluated using Reflotron GPT ( ALT ) stripes and Reflotron Plus device ( Roche Diagnostics , Mannheim , Germany ) according to the manufacturer’s instructions . Serum samples were diluted 1:3 in PBS prior to analyses . Bone marrow was isolated from femur and tibia of BALB/c mice . 2×106 cells were differentiated in petri dishes for 12 days in IMDM ( PAA , Cölbe , Germany ) supplemented with 10% FCS , 2 mM L-glutamine , 5% horse serum ( Biochrom , Berlin , Germany ) and L929 fibroblast medium as a source of M-CSF . Fresh medium was applied every 3 days . After 12 days of differentiation bmMΦ were harvested and washed twice with PBS . For analysis of NO and cytokine release as well as flow cytometry , bmMΦ were seeded into 24-well tissue culture plates at 5×105 cells per well and infected in duplicates with 5 , 10 or 25 R . typhi particles as determined by qPCR per cell . Control cells were incubated with medium or stimulated with 0 . 5 μg/ml E . coli ( strain 055:B5 ) lipopolysaccharide ( LPS ) ( Sigma , Deisenhofen , Germany ) . After incubation of 24 and 48 hours cells were analyzed by qPCR and flow cytometric staining of R . typhi , MHCI , CD80 and iNOS . Cytokines and nitric oxide ( NO ) were quantified in the supernatants as described below . NO concentrations were determined by Griess reaction in supernatants of bmMΦ . Assays were performed in microtiter plates ( Greiner Bio-One , Frickenhausen , Germany ) . 100 μl of sample were mixed with 50 μl Griess 1 reagent ( 0 . 5 g sulfonamide in 50 ml 1M HCl ) and 50 μl Griess 2 reagent ( 0 . 15 g naphtylethylendiamine-dihydrochloride in 50 ml H2O ) . A serial dilution of sodium nitrite ( NaNO2 ) in culture medium was used as a standard ( cmax 125 μM ) . The absorbance was measured at 560 nm with a Dynex MRXII spectrophotometric microplate reader ( Dynex Technologies , Chantilly , USA ) . 5×104 bmMΦ were seeded into 8well Nunc Permanox chamber slides ( Sigma-Aldrich , Munich , Germany ) . Living R . typhi or heat-inactivated R . typhi particles ( 30 min , 56°C ) were added at 10 copies per cell . Control cells were not infected . Medium was exchanged after 4 h of bacterial adherence . Cells were further incubated for 48 h and permeabilized by addition of ice-cold acetone:methanol ( 1:3 ) for 10 minutes at -20°C . Cells were washed 3 times in PBS and staining procedures were then performed at 37°C . Fc receptors were blocked with 5% CohnII in PBS for 15 minutes and 1 μg/ml anti-R . typhi ( BNI52 ) was added for additional 30 minutes . After washing , cells were stained with anti-mouse IgG3-FITC ( 1:200 ) in PBS for 30 minutes followed by staining with anti-FITC-Alexa488 and DAPI ( both 1:1000 ) . Finally , cells were washed in PBS and slides were covered with Permafluor Mounting Medium and cover slips ( ThermoScientific , Loughborough UK ) . Images were taken with the Axioskop MC-80 microscope ( Zeiss , Oberkochen , Germany ) . For immunohistochemistry ( IHC ) tissues from infected mice were fixed in 4% formalin in PBS and embedded in paraffin . Deparaffinization of the sections was performed using standard methods . Sections were first heated at 63°C for 30 minutes in a heating cabinet followed by treatment with Xylol for 30 minutes and EtOH ( 3x 100% EtOH , 3x 96% EtOH , 80% EtOH , 70% EtOH ) . Each step was performed for 3–5 minutes . Slides were finally washed in H2O . Deparaffinized sections were boiled for 30 minutes in 10 mM citrate buffer ( 10 mM sodium citrate , 0 . 05% Tween20 , pH6 . 0 ) for antigen retrieval . Staining was performed using a Ventana Benchmark XT apparatus ( Ventana , Tuscon , USA ) . Antibodies were diluted in 5% goat serum ( Dianova , Hamburg , Germany ) in Tris-buffered saline pH7 . 6 ( TBS ) and 0 . 1% Triton X100 in antibody diluent solution ( Zytomed , Berlin , Germany ) . Rabbit anti-mouse IBA1 ( 1:500 ) , rabbit anti-mouse iNOS ( 1:75 ) and rat anti-mouse Ly-6G ( 1:1000 ) were used . R . typhi was detected employing serum from a R . typhi-patient ( 1:100 ) . Slides were incubated with primary antibodies for 1 h . Histofine Simple Stain MAX anti-human , anti-rabbit , anti-mouse or anti-rat peroxidase-coupled antibodies ( Nichirei Biosciences , Tokyo , Japan ) were used as secondary antibodies . Detection was performed with ultraview universal DAB detection kit ( Ventana , Tuscon , USA ) . For immunofluorescent stainings donkey anti-rabbit Alexa555 ( 1:300 ) , goat anti-rat Alexa568 ( 1:300 ) , goat anti-human IgG-FITC ( 1:200 ) and anti-Alexa488-FITC ( 1:1000 ) were used as secondary antibodies . Nuclei were stained with DAPI ( 1:1000 ) . Sections were covered with Tissue-Tek embedding medium ( Sakura Finetek , Staufen , Germany ) . Images were taken with a BZ9000 Keyence microscope ( Keyence , Neu-Isenburg , Germany ) . Statistical analyses were performed with GraphPad Prism 5 software ( GraphPad Software , Inc . , La Jolla , USA ) . The proportion of surviving animals was analyzed with the Log-rank Mantel Cox test . Normality test was performed with D'Agostino-Pearson normality test for n≥8 . For comparison between two groups two-tailed Students t-test for parametric samples or Mann-Whitney U test for non-parametric samples were applied . To assess differences between multiple groups Kruskal-Wallis test followed by Dunn´s post-test or Two way ANOVA followed by Tukey´s post- est were applied .
To determine the susceptibility of CB17 SCID mice to R . typhi infection , we infected the animals with titrated amounts of R . typhi ( 2×106 , 2×104 and 2×102 sfu ) s . c . into the base of the tail . A control group of CB17 SCID mice received PBS instead of R . typhi . Immunocompetent congenic BALB/c wild-type mice were infected with the highest dose of R . typhi as an additional control . As expected , BALB/c wild-type mice did not show clinical symptoms of disease at any point in time and all animals survived the infection ( Fig 1A and S3B Fig ) . In contrast , CB17 SCID mice were highly susceptible . 100% of the mice that received 2×106 sfu and 94% of the mice that were infected with 2×104 sfu succumbed to the infection while 60% of the mice that obtained 2×102 sfu survived the infection ( Fig 1A ) . The survival period was 16 . 93±3 . 75 days for mice that were infected with the highest dose , 22 . 07±2 . 74 days for mice infected with the median dose and 24 . 5±3 . 54 days for those that received the lowest dose . Staring fur was the first sign of illness and appeared around day 7–10 post infection in animals that received the highest dose of R . typhi ( 2×106 sfu ) while the onset of disease was later in mice that were infected with 2×104 ( day 12–14 ) . Disease then rapidly progressed and the animals showed hunchback appearance and inactivity . This correlated with body weight loss that further progressed until death while PBS-treated CB17 SCID control mice remained healthy and gained weight ( Fig 1A ) . Based on these findings the lethal dose of 2×106 sfu was used for all further experimentation . Next , bacterial dissemination was analyzed . Bacterial load was determined in liver , spleen , brain and lung by qPCR . High amounts of R . typhi were found in all organs in CB17 SCID mice at the time of death . The highest bacterial load was detected in spleen followed by the brain , lung and liver ( Fig 1B ) , demonstrating disseminated infection in these animals . These results show that CB17 SCID mice are highly susceptible to R . typhi infection and fail to control bacterial growth . We further investigated pathological changes in CB17 SCID mice . R . typhi-infected CB17 SCID mice showed a very strong increase in spleen size and weight ( 288 . 2±23 . 3 mg ) at the time of death compared to 33 . 1±2 . 6 mg in control CB17 SCID mice ( Fig 2A ) . The cellular composition of the spleen of R . typhi-infected CB17 SCID mice was further assessed by flow cytometric analysis . Cells were stained for CD11b and GR1 to distinguish CD11b+GR1hi neutrophils from CD11b+GR1low MΦ/monocytes as depicted in Fig 2B ( left ) . R . typhi-infected CB17 SCID mice showed a significantly increased frequency of MΦ/monocytes . At the time of death CD11b+GR1low MΦ/monocytes constituted 27 . 6±4 . 3% of the spleen cells compared to 12 . 1±1 . 1% in CB17 SCID control mice ( Fig 2B , middle ) . A similar trend was true for CD11b+GR1hi neutrophils that represented 9 . 5±1 . 9% of the cells in the spleen of control mice and 15±2 . 5% of the spleen cells in R . typhi-infected CB17 SCID mice ( Fig 2B , right ) . Thus , together MΦ/monocytes and neutrophils represented approximately 40% of the spleen cells . We further analyzed the absolute numbers of MΦ/monocytes and neutrophils in the spleen during the course of infection and compared CB17 SCID mice and BALB/c wild-type mice . In BALB/c wild-type mice numbers of CD11b+GR1low MΦ/monocytes remained unaltered during the course of infection ( Fig 2C , left ) while numbers of CD11b+GR1hi neutrophils were slightly enhanced early in infection on day 3 ( control: 7 . 22×105 , R . typhi-infected: 1 . 73×106 ) and returned to basal counts until day 7 ( Fig 2C , right ) . In R . typhi-infected CB17 SCID mice numbers of CD11b+GR1hi neutrophils and CD11b+GR1low MΦ/monocytes steadily increased during the course of infection beginning on day 3 and resulting in an approximately 30-fold increase of MΦ/monocytes ( control: 2 . 5×105 , R . typhi-infected: 8 . 2×106; Fig 2C , left ) and 50-fold increase of neutrophils immediately prior to death ( control: 1 . 18×105 , R . typhi-infected: 6 . 74×106; Fig 2C , right ) . These results demonstrate that splenomegaly in R . typhi-infected CB17 SCID mice is largely due to disproportionate increase of MΦ/monocytes and neutrophils . Next to the massive enlargement of the spleen R . typhi-infected CB17 SCID mice developed severe liver necrosis which was already visible by eye . In addition , the gall bladder of R . typhi-infected CB17 SCID mice was dark , indicating endothelial damage and bleedings in the organ ( Fig 3A , left ) . Liver damage was measurable by significantly elevated levels of GPT in the serum of R . typhi-infected CB17 SCID mice ( Fig 3A , middle ) . In addition , liver weight was enhanced in several animals at the time of death although these differences were not significant ( 1162±166 . 8 mg compared to 1035±11 . 7 mg in control mice; Fig 3A , right ) . Numerous necrotic areas were visible in histological stainings of the liver of R . typhi-infected CB17 SCID mice compared to control animals that received PBS instead of bacteria and several spots of infiltrating cells were detectable that were not present in the liver of healthy control mice ( Fig 3B ) . Cellular infiltration began around day 7 post infection when the bacteria were predominantly found in endothelial cells and necrotic lesions were still absent . Infiltrating cells further increased until death around day 15 . At this point in time the bacteria were detectable in foci of cellular infiltrates ( S1 Fig ) . Further flow cytometric analysis of cellular isolates from the liver at the time of death confirmed a significant increase of cellular infiltrates ( Fig 4A , left ) . Among these a significantly enhanced percentage of both CD11b+GR1low MΦ/monocytes ( 12 . 6±2 . 5% compared to 5 . 9±1 . 2% in control mice; Fig 4A , middle ) and CD11b+GR1hi neutrophils ( 16 . 9±2 . 4% compared to 3 . 7±0 . 7% in control mice; Fig 4A , right ) was observed , demonstrating that MΦ/monocytes as well as neutrophils infiltrate the liver to a comparable extent . We further performed serial histological sections to clarify the localization of these cells as well as of R . typhi in the liver . For this purpose sections were stained for IBA1 which is exclusively expressed by MΦ [24] and Ly-6G as a marker for granulocytes [25] . In addition , iNOS was stained as an indicator for cellular activation . Enhanced numbers of IBA1+ MΦ were found equally distributed in the liver parenchyma of R . typhi-infected CB17 SCID mice , indicating hyperplasia of Kupffer cells . IBA1+ MΦ accumulated around necrotic areas ( Fig 4B ) . In addition , several foci of infiltrating IBA1+ MΦ from the periphery were observed ( Fig 4C ) . In contrast to MΦ , infiltrating Ly-6G+ granulocytes almost exclusively clustered in foci often found nearby necrotic regions ( Fig 4B ) . Expression of iNOS was detectable in IBA1+ MΦ as well as in Ly-6G+ neutrophils ( Fig 4B ) , demonstrating an activated phenotype of both cell populations . R . typhi was detectable in clusters of infiltrating Ly-6G+ neutrophils as well as IBA1+ MΦ but not within necrotic tissue ( Fig 4B and 4D ) . Activated phagocytes that exert bactericidal functions release reactive oxygen species ( ROS ) and express iNOS to produce nitric oxide ( NO ) [26] . To further assess these functional properties of MΦ/monocytes and neutrophils in R . typhi infection we performed flow cytometric analyses . CD11b+GR1low MΦ/monocytes and CD11b+GR1hi neutrophils from R . typhi-infected CB17 SCID mice were analyzed at the time of death of the animals for ROS release , iNOS expression and bacterial uptake . Non-infected mice that received PBS instead of R . typhi were used as a control . Fig 5A ( left ) shows a representative flow cytometric analysis of ROS content in CD11b+GR1low MΦ/monocytes ( top ) and neutrophils ( bottom ) in the blood . ROS were detectable in around 7% of the CD11b+GR1low MΦ/monocyte population and 3% of the CD11b+GR1hi neutrophils in R . typhi-infected CB17 SCID mice ( Fig 5A ) . We further analyzed bacterial uptake and iNOS expression in CD11b+GR1low MΦ/monocytes and CD11b+GR1hi neutrophils in spleen and liver . Representative dot plots of intracellular staining of R . typhi and iNOS in cells from both organs are shown in Fig 5B and 5C ( top ) . R . typhi was detectable in a high proportion of CD11b+GR1low MΦ/monocytes ( 9 . 0±1 . 2% in the spleen and 2 . 1±0 . 7% in the liver ) and CD11b+GR1hi neutrophils ( 11 . 8±1 . 9% in the spleen and 2 . 1±0 . 5% in the liver ) , demonstrating ingestion of R . typhi by both cell populations ( Fig 5B and 5C ) . Furthermore , CD11b+GR1low MΦ/monocytes as well as CD11b+GR1hi neutrophils expressed iNOS in spleen ( 31 . 5±6 . 2% of CD11b+GR1low MΦ/monocytes and 2 . 4±0 . 3% of CD11b+GR1hi neutrophils ) and liver ( 11 . 1±2 . 9% of CD11b+GR1low MΦ/monocytes and 1 . 3±0 . 5% of CD11b+GR1hi neutrophils ) with MΦ representing the main iNOS-expressing cell population in both organs ( Fig 5B and 5C ) . Thus , MΦ and neutrophils exhibit a bactericidal phenotype . Recent data show that neutrophils largely contribute to bacterial elimination in the liver [27–30] . Having shown that neutrophils infiltrate the liver of R . typhi-infected CB17 SCID mice , we further elucidated the contribution of neutrophils to bacterial elimination and protection against R . typhi . For this purpose neutrophils were depleted in R . typhi-infected CB17 SCID mice by the application of anti-Ly-6G antibody beginning at day 6 post infection before neutrophils start to rise ( Fig 2B ) . Anti-Ly-6G treatment was repeated every 3 days . R . typhi-infected control mice received equal amounts of isotype antibody instead . Additional control groups of CB17 SCID mice were treated with either PBS or anti-Ly-6G but were non-infected . Success of neutrophil depletion was examined by flow cytometry of blood cells from infected CB17 SCID mice 1 day after the second antibody application . At this point in time ( day 10 post infection ) , CD11b+Ly-6Ghi neutrophils represented approximately 65% of the CD11b+ cells in the blood of R . typhi-infected control mice and were completely absent in R . typhi-infected CB17 SCID mice that received anti-Ly-6G antibody ( Fig 6A ) . However , neutrophil depletion did not alter the course of disease as monitored by clinical scoring ( Fig 6B , left ) and mice succumbed to the infection with similar kinetics as control mice ( Fig 6B , right ) . Furthermore , neutrophil-depleted animals showed comparable bacterial burden in spleen , liver , brain and lung as R . typhi-infected control animals that were treated with isotype antibody ( Fig 6C ) . R . typhi-infected CB17 SCID mice still developed splenomegaly in the absence of neutrophils that was comparable to R . typhi-infected mice that were treated with isotype antibody ( Fig 6B , insert ) . We further assessed the cellular composition of the spleen of all groups of mice including non-infected animals that received either PBS or anti-Ly-6G only . As expected , the CD11b+GR1hi neutrophil population was absent in all mice that received anti-Ly-6G , whether infected or not ( Fig 6D , left ) , while a reciprocally , although not significantly enhanced percentage , of CD11b+GR1low MΦ/monocytes was observed in R . typhi-infected CB17 SCID mice in the absence of neutrophils . 53 . 5±3 . 8% of the spleen cells in neutrophil-depleted mice were CD11b+GR1low MΦ/monocytes compared to 45 . 3±1 . 9% in control animals ( Fig 6D , right ) , indicating that the absence of neutrophils is in part compensated by increased accumulation of MΦ/monocytes . Although neutrophils are known to be crucial for pathogen elimination in bacterial infections [31] , an impact of these cells in bacterial control was not observed in R . typhi-infected CB17 SCID mice ( Fig 6C ) . However , activated neutrophils can also mediate harmful reactions and can be involved in hepatic injury [32 , 33] . We therefore analyzed liver pathology by measuring serum GPT and performing histological stainings . Indeed , neutrophil-depleted R . typhi-infected CB17 SCID mice were completely protected from liver damage . In the absence of neutrophils , R . typhi-infected CB17 SCID mice showed normal serum GPT levels . Livers from these mice appeared healthy and the gall bladders were clear ( Fig 6E ) . Moreover , necrotic lesions were not detectable anymore in histological stainings although still many foci of infiltrating cells were visible ( Fig 6F ) . These were positive for IBA1 and , thus , MΦ ( S2B Fig ) . These results clearly show that neutrophils are solely responsible for liver necrosis in R . typhi-infected CB17 SCID mice . Although neutrophil-depleted R . typhi-infected CB17 SCID did not show liver damage anymore the animals succumbed to the infection . Thus , liver damage is not the cause of death which must have other reasons . One of these might be an overwhelming immune response . To gain insight into the immune response of CB17 SCID and wild-type BALB/c mice upon R . typhi infection we next analyzed cytokines in the blood . R . typhi-infected CB17 SCID mice showed steadily increasing release of inflammatory cytokines during the course of disease . This response was clearly dominated by IFNγ that reached plasma levels of 1034±180 pg/ml prior to death . In addition , slightly enhanced plasma levels of IL-6 ( 217±105 pg/ml ) , IL-12p70 ( 15±3 pg/ml ) , TNFα ( 48±7 pg/ml ) and MCP-1 ( 160±25 pg/ml ) were present ( Fig 7A ) . GM-CSF was not significantly enhanced in R . typhi-infected CB17 SCID mice during the course of infection ( S3 Fig ) . These results show that CB17 SCID mice mount a very strong systemic inflammatory response . In contrast , immunocompetent BALB/c wild-type mice produced significantly increased levels of IFNγ ( 191±70 pg/ml ) in addition to MCP-1 ( 197±81 pg/ml ) exclusively at day 3 post infection while IL-12p70 , IL-6 and TNFα were not detectable at all in these mice ( Fig 7A ) and GM-CSF was not significantly elevated during the course of infection ( S3 Fig ) . We further clarified the impact of neutrophil-depletion on the inflammatory immune response in R . typhi-infected CB17 SCID mice . Serum levels of IFNγ , IL-12p70 , IL-6 , TNFα and MCP-1 were increased in all R . typhi-infected animals compared to control mice . Neutrophil-depletion , however , did not alter cytokine production compared to R . typhi-infected CB17 SCID mice that received isotype antibody ( Fig 7B ) , demonstrating minor contribution of neutrophils to systemic inflammation . Systemic inflammation in R . typhi-infected CB17 SCID mice was clearly dominated by IFNγ , a cytokine that is known to be predominantly produced by NK cells . Therefore , we further assessed the expansion of NK cells in addition to MΦ and neutrophils during the course of disease and cytokine expression by these cell populations . First , blood cells were stained for NKp46 , CD11b and GR1 and absolute cell counts of NK cells ( NKp46+ ) , MΦ ( CD11b+GR1low ) and neutrophils ( CD11b+GR1hi ) after pregating on NKp46- cells were determined . NK cells steadily increased during the course of infection and were enhanced approximately 3 . 5-fold on day 12 post infection in the blood ( Fig 8A ) . Significantly enhanced numbers of MΦ were observed in the blood rather late in infection on day 12 . The increase of these cells , however , was stronger ( 7-fold ) compared to NK cells ( 3 . 5-fold ) ( Fig 8A ) . In contrast to NK cells and MΦ , neutrophils only transiently increased in the blood from day 3 to day 7 post infection and declined again until day 12 ( Fig 8A ) when the experiment was terminated . We further analyzed cytokine expression by these cell populations and determined numbers of NK cells , MΦ and neutrophils in the spleen . For this purpose we prepreated the animals with brefeldin A 12 hours prior to the analysis to assess cytokine expression directly ex vivo . Spleen cells were then stained for NKp46 , CD11b and GR1 to distinguish NKp46+ NK cells and CD11b+GR1low MΦ and CD11b+GR1hi neutrophils among NKp46- as described above . In addition , cells were stained for intracellular IFNγ and TNFα . First , cell counts of NK cells , MΦ and neutrophils were determined . Numbers of both MΦ and neutrophils were strongly increased in the spleen of R . typhi-infected animals ( MΦ: 9 . 56±1 . 09×106; neutrophils: 5 . 00±1 . 08×106 ) compared to control mice ( MΦ: 0 . 48±0 . 13×106; neutrophils: 0 . 47±0 . 07×106 ) . Thus , MΦ and neutrophil numbers were approximately 20-fold and 10-fold enhanced at this point in time ( Fig 8B ) . Numbers of NK cells were generally higher compared to MΦ and neutrophils in CB17 SCID mice . 1 . 01±0 . 19×106 NK cells were detectable in non-infected CB17 SCID control mice . NK cells significantly increased approximately 4-fold in the spleen of R . typhi-infected mice ( 4 . 08±0 . 72×106 ) ( Fig 8B ) . This increase corresponds to that observed in the blood ( Fig 8A ) . TNFα was predominantly detectable in MΦ . 7 . 08±0 . 64% of the MΦ expressed this cytokine . A lower proportion of neutrophils also expressed TNFα ( 2 . 65±0 . 28% ) while TNFα expression by NK cells was negligible and not significantly enhanced ( 1 . 28±0 . 50% ) ( Fig 8C , left ) . However , 9 . 43±1 . 02% of the NK cells in the spleen expressed IFNγ . Surprisingly , IFNγ was also detectable in 4 . 04±1 . 02% of the MΦ while only 1 . 24±0 . 16% IFNγ-expressing cells were present among neutrophils ( Fig 8C , middle ) . The absolute number of IFNγ-producing MΦ and NK cells was comparable in R . typhi-infected mice ( Fig 8C ) . This is explained by the stronger increase of MΦ compared to NK cells ( Fig 8B ) . These results show that both NK cells and MΦ contribute to IFNγ production and that MΦ are a major source of TNFα in R . typhi-infected CB17 SCID mice . As MΦ and neutrophils seem to be the dominant cell populations rising in R . typhi-infected CB17 SCID mice and show an activated phenotype , we further clarified if and how these cells react to R . typhi . In the experiment depicted in Fig 5 , we first gated on iNOS+ cells among CD11b+GR1low MΦ/monocytes and CD11b+GR1hi neutrophils and analyzed the cells for R . typhi content . This analysis should demonstrate whether it is the R . typhi-harboring cells that express iNOS . Surprisingly , the vast majority of the iNOS-expressing CD11b+GR1low MΦ/monocytes was R . typhi-negative ( 87 . 7±2 . 3% in the spleen and 92 . 8±1 . 3% in the liver ( Fig 9A ) ) and the proportion of iNOS-expressing cells that contained bacteria was correspondingly small . Similar was also true for CD11b+GR1hi neutrophils . Here , 72 . 3±4 . 1% of the iNOS-expressing cells in the spleen and 64 . 4±8 . 1% of those in the liver were negative for R . typhi ( Fig 9A ) . Thus , activation of these cells does not correlate with bacterial phagocytosis . Phagocytes such as MΦ usually recognize bacterial pathogens via pattern recognition receptors such as Toll-like receptors ( TLR ) . These induce a classically activated phenotype including iNOS expression as observed in R . typhi-infected CB17 SCID mice , the release of inflammatory cytokines and the upregulation of costimulatory cell surface molecules [34] . The observation that MΦ and neutrophil activation did not correlate with bacterial uptake in vivo ( Fig 9A ) , however , indicates that the cells may not directly react to the bacteria . To elucidate whether R . typhi activates MΦ , we generated bmMΦ from BALB/c mice and infected the cells with titrated amounts of R . typhi in vitro . Cells were analyzed for bacterial uptake and the expression of MHCI and CD80 by flow cytometry . In addition , NO , IL-6 , IL-12 and TNFα were quantified in the supernatant by Griess reaction and LegendPlex assay . Stimulation with E . coli LPS was used as a control . After 24h approximately 12% of the cells that were infected with 25 R . typhi copies per cell were positive for R . typhi as determined by flow cytometry ( Fig 9B ) . MΦ upregulated the expression of MHCI and CD80 48h after infection ( Fig 9B ) . However , the cells neither released detectable amounts of inflammatory cytokines nor NO as it was observed upon stimulation with LPS ( Fig 9B ) . These results show that MΦ do not react to R . typhi in a classical manner and further led to the question whether MΦ are capable to kill R . typhi . To clarify this issue we incubated bmMΦ with either living R . typhi or heat-killed R . typhi to be able to distinguish between living/replicating and degrading bacteria by immunofluorescence microscopy . As expected , fragments of degrading R . typhi particles were detectable after 48h in bmMΦ that received heat-killed bacteria ( Fig 9C ) . In contrast , bmMΦ that were incubated with living R . typhi clearly contained intact and replicating bacterial particles at this point in time . In several cells proliferating bacteria clustered in rosette-like structures while other cells showed a more equal distribution of R . typhi in the cytosol . Interestingly , free R . typhi antigen not bound to particles was also observed in some cells in the cytosol ( Fig 9C ) . Bacterial growth in bmMΦ in vitro was further confirmed by qPCR showing exponential increase of bacterial DNA in the cell culture within 96h ( Fig 9D ) . Collectively these results show that R . typhi does not activate MΦ in a classical manner and that MΦ are incapable to kill the bacteria in vitro . The results presented so far show that activated MΦ and neutrophils accumulate in immunodeficient CB17 SCID mice upon R . typhi infection and infiltrate the liver . Moreover , neutrophils revealed to be responsible for liver damage in these animals . To finally show whether these processes may also take place in immunocompetent mice , we again infected BALB/c wild-type mice . Although BALB/c wild-type mice do not show clinical symptoms of disease , histological analyses revealed that R . typhi infection affects the liver . Cellular infiltrates were visible in HE stainings of liver sections beginning on day 3 post infection , peaking on day 7 and declining until day 14 again ( Fig 10A ) . At the peak of cellular infiltration on day 7 , necrotic lesions were also visible in the livers of R . typhi-infected BALB/c mice ( Fig 10A ) . Further stainings revealed that enhanced numbers of IBA1+ MΦ , Ly-6G+ granulocytes as well as T cells were detectable in the liver of R . typhi-infected animals compared to control BALB/c mice that were treated with PBS ( Fig 10B ) . These cells were mainly found in the liver parenchyma . In addition , IBA1+ MΦ also accumulated around blood vessels ( Fig 10B , below middle ) . The bacteria and/or bacterial antigen were detectable in endothelial cells ( Fig 10B , below right ) and in IBA+ MΦ ( Fig 10B , below left ) but not in the liver parenchyma . Liver damage in BALB/c wild-type mice , however , was generally mild . Necrotic lesions were small and rare and enhanced levels of serum GPT were not detectable ( S3 Fig ) .
Immune competent BALB/c wild-type mice do not show symptoms of disease upon R . typhi infection , and the bacteria are quickly eliminated . Nonetheless , these mice show temporary liver damage . Liver dysfunction and hepatosplenomegaly are complications that frequently occur in patients with severe outcome of murine typhus [7] . In the current study we describe a murine model of R . typhi infection that reflects this pathology . T and B cell-deficient CB17 SCID mice succumb to the infection within approximately 3 weeks . The bacteria enter all analyzed organs , demonstrating systemic distribution . The most evident pathological changes , however , are splenomegaly and massive liver necrosis . The same observations were made in T and B cell-deficient BALB/c RAG2-/- mice . These animals showed a comparable course and outcome of disease ( liver necrosis , splenomegaly ) as well as a similar bacterial distribution in the organs ( S3 Fig ) . We therefore conclude that this outcome of disease is due to the lack of adaptive immunity in CB17 SCID mice rather than potential other effects of the mutation of the Prkdc gene that is responsible for the lack of T and B lymphocytes . Thus , CB17 SCID mice show a complete different outcome of disease than T and B cell-deficient C57BL/6 RAG1-/- mice that do not show splenomegaly and liver pathology but develop brain inflammation months after R . typhi infection[21] . These observations suggest that the different genetic background that may influence the innate immune status of these mouse strains determines the outcome of disease . Splenomegaly in CB17 SCID mice was mainly caused by the disproportionate accumulation of neutrophils and MΦ compared to other cells such as NK cells that showed comparatively moderate expansion . Transient increase of neutrophils in the blood and steady increase in the spleen may be a result of increasing exhaustion of the neutrophil reservoir in the bone marrow . Similar has been observed in high dose infection of mice with Listeria ( L . ) monocytogenes which led to neutrophil depletion in the bone marrow [35] . The factors that drive this massive MΦ and neutrophil expansion in R . typhi-infected CB17 SCID mice remain elusive . One important factor that is involved in myelopoiesis is the granulocyte/macrophage colony stimulating factor ( GM-CSF ) . As a part of the emergency response to infection , GM-CSF induces the production and mobilization of granulocytes and MΦ from the bone marrow [36 , 37] . GM-CSF together with macrophage colony stimulating factor ( M-CSF ) further promotes the maintenance , survival and functional activation of these cells at sites of injury [38–41] . GM-CSF , however , was not enhanced in the sera of R . typhi-infected CB17 SCID mice at any point in time ( S3 Fig ) . CB17 SCID mice produced enhanced levels of IL-6 , a cytokine that can directly stimulate granulopoiesis [42] , upon R . typhi infection . IL-6 has been shown to be crucial for efficient neutrophil response against bacterial infections such as L . monocytogenes [43] . Thus , IL-6 may play a role in the generation and mobilization of neutrophils in R . typhi-infected CB17 SCID mice . Enhanced numbers of both MΦ and neutrophils were detectable in the liver in several foci suggesting infiltration of these cells from the periphery . These cells were also found in association with necrotic lesion . In addition , large numbers of IBA1+ MΦ were equally distributed in the liver parenchyma . These cells may represent Kupffer cells , the resident MΦ of the liver , that are known to expand upon liver injury [44] . Thus , hyperplasia of Kupffer cells may also take place in R . typhi-infected CB17 SCID mice . Both MΦ and neutrophils ingested R . typhi in vivo . Infiltrating neutrophils constitute the first line of defense against most invading pathogens and are involved in the clearance of bacterial infections [31] . Upon systemic application the majority of pathogens is cleared in the liver early in the course of infection . Furthermore , recent data show that neutrophils rather than Kupffer cells account for bactericidal activity and bacterial elimination in the liver . This is evidenced by the fact that neutrophil-depleted mice show reduced capability to kill gram-positive as well as gram-negative bacteria in the liver [27–30] . For example , mice that were not able to mobilize neutrophils showed increased replication of the intracellular bacterium L . monocytogenes and died from the infection [45–47] . Here , neutrophils were essential in early defense against L . monocytogenes in the liver but not in the spleen or peritoneal cavity [48] . Neutrophil-depletion in R . typhi-infected CB17 SCID mice , however , did not result in increased bacterial load in the liver or other organs . This observation indicates a minor contribution of neutrophils to bacterial elimination and inefficient killing of ingested R . typhi although the cells exerted effector functions including the production of ROS , the expression of iNOS and subsequent NO release that are involved in bacterial killing [49] . These neutrophil effector functions are usually induced by the recognition of pathogen in addition to cytokines that are released during infection [50 , 51] . Neutrophil activation , however , did not correlate with the uptake of R . typhi , indicating that neutrophils may not directly recognize the bacteria . Endothelial cells are considered the main target cells of rickettsiae [5] . In concordance , R . typhi particles were detectable in endothelial cells in histological stainings of the livers from BALB/c wild-type and CB17 SCID mice . However , also hepatocytes may represent target cells . For example , R . conorii directly infects human hepatocytes inducing iNOS expression in these cells [52] . However , neither R . typhi particles nor R . typhi antigen were detectable in the liver parenchyma or in necrotic lesions in histological stainings of the liver from CB17 SCID mice but within infiltrating IBA1+ MΦ and Ly-6G+ granulocytes . Similar was also true for C . burnetii that was found in expanded MΦ in CB17 SCID mice and also causes hepatosplenomegaly [53] . Surprisingly , depletion of neutrophils did not alter bacterial load in the liver and other organs . Nonetheless , neutrophil-depletion completely prevented liver necrosis in R . typhi-infected CB17 SCID mice . Thus , liver damage in R . typhi infection is a result of immunopathological activity of neutrophils rather than direct hepatocyte damage by the bacteria themselves . In concordance with these observations neutrophil effector functions have been shown to exert cytotoxic effects and can cause severe hepatic injury [32 , 33] . Furthermore , depletion of neutrophils as well as the application of antioxidants or protease inhibitors can prevent liver dysfunction in animal models of sepsis [54–56] . Depletion of neutrophils , however , did not protect R . typhi-infected CB17 SCID mice from death . This can be ascribed to overwhelming systemic inflammation that was unaltered in neutrophil-depleted animals . Thus , there is only minor contribution of neutrophils to this response that was characterized by the release of MCP-1 and inflammatory cytokines including IFNγ , TNFα , IL-6 and IL-12 that are important for defense against intracellular pathogens . MΦ represent the major cellular source of TNFα , IL-6 and IL-12 [57–60] while MCP-1 , a chemoattractant protein for monocytes , is produced by various types of cells including endothelial cells , MΦ and fibroblasts upon oxidative stress or exposure to cytokines [61] . In concordance , TNFα was mainly produced by MΦ in R . typhi-infected CB17 SCID mice . IL-6 and TNFα are critical for rapid response to tissue injury and infections and induce the production of acute phase reactants in the liver [62 , 63] whereas IL-12 is the main inducer of IFNγ in NK cells and T cells [64 , 65] . This cytokine assists in bacterial killing by activating MΦ bactericidal functions [66 , 67] . Apart from NK cells we identified MΦ as a cellular source of IFNγ in R . typhi-infected CB17 SCID mice . MΦ have been demonstrated to be capable to produce this cytokine [68 , 69] and intracellular pathogens such as Mycobacterium tuberculosis can directly induce its production in MΦ [70–72] . In addition , IFNγ production in MΦ is induced by IL-12 [73 , 74] which was also enhanced in R . typhi-infected CB17 SCID mice . Interestingly , IL-12 and intracellular bacteria such as mycobacteria synergize in the induction of IFNγ in in vitro infected MΦ [72] . Finally , IFNγ induces its own expression in MΦ [75] . In this way , IL-12 and IFNγ can activate MΦ in an autocrine manner and further accelerate macrophage-driven inflammatory response . The observation that absolute cell counts of IFNγ-expressing NK cells and MΦ were equal strongly suggests that MΦ substantially contribute to IFNγ release in R . typhi-infected CB17 SCID mice . Expression of additional cytokines such as TNFα by MΦ further suggests that these cells play a dominant role in overall inflammation . Upon bacterial infection MΦ usually get activated by the recognition of common bacterial components , so-called pathogen-associated molecular pattern ( PAMP ) , that are detected by pattern recognition receptors ( PRR ) such as Toll-like receptors ( TLR ) . TLR engagement generally leads to a classically activated phenotype of MΦ . This is characterized by the production of inflammatory cytokines including IL-6 , IL-12 and TNFα , the expression of iNOS and subsequent release of NO [34 , 76 , 77] which is required for effective killing of intracellular bacteria such as mycobacteria [78–80] . In addition , classically TLR-activated MΦ upregulate cell surface molecules that are involved in antigen presentation including MHCI and II and costimulatory molecules such as CD80 and CD86 [81] . Indeed , high amounts of iNOS-expressing MΦ were detectable in R . typhi-infected CB17 SCID mice . As a gram-negative bacterium R . typhi possesses LPS [82 , 83] and other PAMPs suggesting that R . typhi activates MΦ via TLR like TLR4 . A role of TLR4 in the activation of innate immunity has been shown for example for R . conorii , a member of the SFG [84] . However , bmMΦ did not react to R . typhi with the production of NO and inflammatory cytokines but only upregulated MHCI and CD80 expression upon infection in vitro . Moreover , we observed that the majority of iNOS-expressing MΦ in vivo did not harbor R . typhi . These results strongly suggest that R . typhi does not activate MΦ in a classical manner via TLR . R . typhi probably enters these cells more or less unrecognized by PRR or may even specifically inhibit MΦ activation . Inhibition of MΦ activation by TG rickettsiae , however , has not been described in the literature . In concordance with the non-activated status of MΦ upon R . typhi infection in vitro , we further observed that the bacteria survive and replicate in bmMΦ in vitro . R . typhi has been shown before to infect murine as well as human MΦ [85 , 86] which is also true for other rickettsiae such as O . tsutsugamushi [12 , 13] and R . akari [87 , 88] . The observation that MΦ are incapable to efficiently kill R . typhi suggests that these cells likely represent general target cells of R . typhi and maybe other rickettsial species . However , differences in MΦ activity may exist between susceptible and non-susceptible mouse strains . A comparative analysis of the bactericidal activity of MΦ from mice of different genetic background and different susceptibility to rickettsial infections has been described in one study . Here , neither peritoneal MΦ from susceptible C3H/HeN mice nor resistant BALB/c and C57BL/6 mice were capable to kill R . akari in vitro unless the cells were activated with lymphokines . If treated with lymphokines , MΦ from all of these strains were comparably competent in killing R . akari [88] . These findings argue against major differences in macrophage activity against rickettsiae although differences may exist with regard to different rickettsial species . Our observations indicate that MΦ as well as neutrophils must become activated by other factors than recognition of the bacteria themselves via signaling receptors . As T cell-derived lymphokines are missing in C57BL/6 RAG1-/- and CB17 SCID mice , we suggest that such activating signals may be released in the context of cellular damage that can be induced by R . typhi infection of various cell types in different organs and tissues in the beginning of disease . These signals may include endogenous danger signals such as heat shock proteins ( HSP ) and ATP that can be released into the environment under circumstances of cellular damage [89] . Endogenous danger signals can activate neutrophils [31 , 90] and induce inflammatory responses including the release of IL-12 in MΦ [89 , 91–93] . Cytokines like IL-12 and IFNγ may then further accelerate the inflammatory response as described above . Prolonged and deregulated release of mediators such as TNFα , IL-6 and NO has non-beneficial effects . For example , TNFα acts cytotoxic and both TNFα and IL-6 are involved in pathological conditions including septic shock and cachexia [63 , 94] which is also true for NO [95] . Collectively we conclude that death of R . typhi-infected CB17 SCID mice is most likely due to overwhelming systemic inflammation driven by MΦ and other cells such as NK cells . Liver damage , however , is clearly an immunopathological effect mediated by neutrophil activity rather than direct destruction of hepatocytes by R . typhi itself . Since liver damage is also seen in R . typhi-infected BALB/c wild-type mice and in human R . typhi infection [7] , this mechanism might also be operating in immune competent individuals . Here , an unbalanced immune state and impaired functionality of adaptive immunity , especially T cells , may foster these processes and this outcome of disease .
|
Rickettsia typhi causes a relatively mild disease in humans and in immunocompetent mice the bacterium does not cause clinical symptoms as it is easily controlled by the adaptive T cell response . To analyze the role of innate immune mechanisms we here infected mice deficient in T and B cells and find that these mice die within 21 days from a systemic inflammatory response . In addition to splenomegaly due to the accumulation of macrophages and neutrophils , they also show severe liver necrosis that is caused by a massive influx of neutrophils but not the cause of death . The systemic inflammatory response is remarkable , because R . typhi does not directly activate macrophages and neutrophils . Our study demonstrates a strong immunopathological role of cells of the innate immune system in this infection that may also operate in patients as liver damage is a common symptom of the human disease .
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2016
|
Liver Necrosis and Lethal Systemic Inflammation in a Murine Model of Rickettsia typhi Infection: Role of Neutrophils, Macrophages and NK Cells
|
Functional inactivation of the Retinoblastoma ( pRB ) pathway is an early and obligatory event in tumorigenesis . The importance of pRB is usually explained by its ability to promote cell cycle exit . Here , we demonstrate that , independently of cell cycle exit control , in cooperation with the Hippo tumor suppressor pathway , pRB functions to maintain the terminally differentiated state . We show that mutations in the Hippo signaling pathway , wts or hpo , trigger widespread dedifferentiation of rbf mutant cells in the Drosophila eye . Initially , rbf wts or rbf hpo double mutant cells are morphologically indistinguishable from their wild-type counterparts as they properly differentiate into photoreceptors , form axonal projections , and express late neuronal markers . However , the double mutant cells cannot maintain their neuronal identity , dedifferentiate , and thus become uncommitted eye specific cells . Surprisingly , this dedifferentiation is fully independent of cell cycle exit defects and occurs even when inappropriate proliferation is fully blocked by a de2f1 mutation . Thus , our results reveal the novel involvement of the pRB pathway during the maintenance of a differentiated state and suggest that terminally differentiated Rb mutant cells are intrinsically prone to dedifferentiation , can be converted to progenitor cells , and thus contribute to cancer advancement .
Almost all growth inhibitory signals ultimately act through the Retinoblastoma tumor suppressor protein ( pRB ) family [1] . In its active , hypophosphorylated form , pRB blocks cell proliferation by limiting the activity of the family of E2F transcription factors that control the expression of a large cohort of genes , including those that are essential for the G1 to S transition [2] . E2F activity is rate-limiting for S phase entry , as forced expression of E2F is sufficient to overcome the growth-inhibitory signals and drive quiescent or postmitotic cells into S phase [3]–[6] . Inactivation of pRB relieves the critical constraint from E2F , thus , rendering cells insensitive to antiproliferative signals , one of the acquired traits of a cancer cell . Indeed , the functional inactivation of the pRB pathway is believed to be an obligatory early step in the majority of human cancers [7] . Thus , the current paradigm posits that the tumor suppressive function of pRB is defined by its ability to promote cell cycle exit . The view that pRB operates primarily during cell cycle exit is consistent with gene targeting studies in mice . Inactivation of the Rb gene family in mice resulted in ectopic proliferation and apoptosis [8] , [9]; while the loss of Rb in quiescent or even in terminally differentiated cells led to inappropriate cell cycle re-entry [10] , [11] . Interestingly , Rb knockout mice also exhibit reduced differentiation in multiple tissues suggesting that in addition to promoting cell cycle exit pRB may possess more specialized functions . In support of this idea , pRB was shown to directly interact with , and modulate activity of , cell-type specific transcription factors . For example , pRB interacts with the osteoblast transcription factor CBFA1/Runx2 and acts as a direct transcriptional co-activator of the CBFA1/Runx2 target genes required for the later stages of terminal differentiation [12] . This is particularly intriguing given the strong correlation between Rb mutations and the occurrence of osteosarcoma [13] . However , there is little support for the importance of these types of interactions in vivo . Further complicating the issue , several studies have demonstrated that some of the differentiation defects in Rb knockout mice are an indirect consequence of ectopic proliferation and apoptosis [14]–[16] . These results highlight the necessity to determine the bona fide role of Rb in promoting differentiation in vivo . Drosophila represents a powerful alternative model system to study the in vivo function of the pRB pathway , since the homologous E2F and pRB ( termed RBF ) gene families are smaller in flies than in mammals , yet their involvement in cell cycle control is remarkably conserved [17] . Curiously , the consequences of the loss of rbf in somatic tissues such as the larval eye imaginal disc are rather subtle [18]–[20] . One possibility is that other pathways may mask otherwise critical functions of rbf and thus compensate for its loss . This is an important conceptual point , since in addition to the inactivation of the pRB pathway , a cancer cell acquires mutations in multiple tumor suppressors and oncogenes; and the collective outcome of these alterations eventually determines the malignancy of the cancer cell [7] . The recently identified Hippo tumor suppressor pathway represents an attractive candidate for such a role in compensation , since like the pRB pathway it regulates cell cycle exit ( for review see: [21]–[23] ) . In the center of the Hippo pathway is a kinase cascade that contains Hippo ( Hpo ) and Warts ( Wts ) . Wts is the most downstream kinase of the cascade; and additionally the Fat pathway controls the level and activity of Wts . A well-known function of Wts in both pathways is to negatively regulate the transcriptional co-activator , Yorkie ( Yki ) . Inactivation of the Hippo kinase cascade by mutations of hpo or wts , or overexpression of yki , increases the rate of cell duplication during the growth phase of imaginal discs , protects cells from apoptosis , and delays the cell cycle exit of the uncommitted interommatidial cells of the larval eye imaginal disc . Although the Hippo pathway is best known for its role in regulation of cell proliferation , there is increasing evidence of its functions in postmitotic cells [24]–[26] . Classically , the Drosophila eye imaginal disc has been used to study the results following the inactivation of the Hippo and pRB pathways in vivo . A key reason is that in the eye disc cell proliferation and differentiation occur in highly reproducible patterns which are established through the developmentally regulated movement of the morphogenetic furrow ( MF ) [27] . In this model system even small perturbations in terminal cell cycle exit or differentiation can dramatically alter eye development and can therefore be unambiguously characterized . The adult eye is composed of a regular array of identical units termed ommatidia . Each individual ommatidium contains a cluster of eight photoreceptors , termed R1 through R8 . The passage of the MF results in specification of the pre-R8 photoreceptors that act as the founder cell of each ommatidium ( Figure 1A ) . Once an R8 is selected , the recruitment and selection of all other photoreceptors occurs in a strict procession through reiterative use of the epidermal growth factor receptor ( EGFR ) pathway [28] . As each R cell is specified it undergoes terminal differentiation , develops an axonal projection , and through expression of cell type specific factors eventually becomes a fully mature photoreceptor . Since the selection , specification , and ensuing maturation of all R cells occurs continuously with respect to the position of the MF , then the photoreceptors that are in the earliest stages of differentiation are always found within and immediately posterior to the MF ( Figure 1A ) . It then follows that the very first photoreceptors to completely differentiate can be found in the most posterior regions of the disc ( Figure 1A ) . This regimented developmental program provides a unique spatiotemporal model to visualize all steps of photoreceptor recruitment and subsequent differentiation in the same eye disc . We therefore utilized the Drosophila eye imaginal disc to examine the impact of the combined inactivation of the pRB and Hippo pathways . We found that rbf wts or rbf hpo double mutant cells initiate and progress through the neuronal differentiation program . However , double mutant cells failed to maintain their neuronal identity , dedifferentiated , and became uncommitted eye specific cells . Dedifferentiation of rbf wts double mutant photoreceptors was accompanied by widespread inappropriate proliferation . Yet , the two defects were independent of each other as rbf wts mutant photoreceptors dedifferentiated even when inappropriate proliferation was fully blocked by a de2f1 mutation . Thus , our findings suggest that the pRB pathway in cooperation with the Hippo pathway plays a specific role in maintenance of the differentiated state that is distinct from the pRB function to promote cell cycle exit .
As described above , the Drosophila eye provides a unique experimental system in which differentiation and proliferation during development can be readily studied ( Figure 1A ) . We took advantage of this well-characterized spatiotemporal model and carefully examined the properties of rbf mutant cells following inactivation of the Hippo pathway . We began our analysis by examining neuronal differentiation of R8 photoreceptors . Because R8 is the founder cell for each ommatidium , its recruitment is independent of the correct specification of the remaining photoreceptors in the ommatidium . In contrast , other photoreceptor recruitment occurs progressively in a stepwise manner ( R2/R5 followed by R3/R4 , R1/R6 and finally R7 ) and is dependent upon the presence of the previously recruited pair of R cells [28] . R8 photoreceptors can be uniquely identified by the expression of the transcription factor Senseless ( Sens ) [29] ( Figure 1B ) that is first detected immediately posterior to the MF . As photoreceptors progressively differentiate , they begin to express a late neuronal marker , Elav , several columns posterior to the onset of Sens expression ( Figure 1B ) . Unlike Sens , Elav is expressed in all R cells . Therefore in a wild-type disc , each cluster of Elav positive cells contains a single Sens positive cell ( Figure 1B ) . As previously reported [19] , the pattern of Sens and Elav expression was relatively normal in an rbf mutant disc , although there were slight abnormalities of Sens expression within cells immediately adjacent to the MF ( Figure 1C ) . To examine the expression of these differentiation markers in Hippo pathway mutant cells , we employed the FLP-FRT technique to generate clones of homozygous wts mutant cells . In this technique , homozygous wild-type cells are marked with GFP , while homozygous wts mutant cells are distinguished by the lack of GFP . In spite of increased spacing between adjacent ommatidia in wts mutant clones , each ommatidium ( marked by Elav ) still contained a single R8 cell ( marked by Sens ) ( Figure 1D ) . The increased spacing between ommatidia is due to inappropriate proliferation of non-neuronal , interommatidial cells that have failed to exit the cell cycle . Thus , consistent with previous reports ( for example see: [18] , [19] , [30]–[32] ) , neither the loss of rbf nor the loss of Hippo pathway signaling affected photoreceptor differentiation . To determine the effect of inactivation of Hippo pathway signaling in rbf mutant cells , we examined clones of wts mutant cells generated in hemizygous rbf120a mutant eye discs . Expression of Sens was properly initiated as rbf wts double mutant cells emerged from the MF . However , the number of Sens positive cells was severely decreased toward the posterior of the mutant clones ( Figure 1E ) . Additionally , we noted that approximately one third of the ommatidial clusters , as visualized by Elav expression , were missing Sens positive R8 cells ( examples are pointed to by arrows in Figure 1E and quantification is presented in Figure 1Ei ) . To exclude the possibility of allele specific effects , we confirmed our findings with a hpoMGH4 mutant allele ( Figure S1 ) and with an rbf14 allele ( Figure S2 ) . We note , that the phenotype of the rbf14 wtsx1 double mutant cells was more severe than that in the rbf120a wtsx1 double mutant tissue . Since rbf14 is a null allele , while a small amount of the RBF protein is produced from the rbf120a allele [19] , this suggests that the double mutant phenotype is highly sensitive to the dosage of RBF . Thus , we concluded that following specification mature R8 cells were gradually lost as neuronal differentiation proceeded . Importantly , the progressive loss of Sens expression in rbf mutant cells is specific to inactivation of Hippo signaling since a mutation in another tumor suppressor , tsc1 [33] , has no effect on R8 differentiation in rbf tsc1 double mutant cells ( Figure 1F and 1G and data not shown ) . Consistently with the larval eye disc analysis , in the adult eye , the rbf wts mutant clones had a characteristic glossy appearance that is indicative of a lack of differentiated photoreceptors ( Figure 1H ) . The loss of Sens expression in rbf wts double mutant tissue could be due to a failure to properly specify R8 cells . Therefore we examined expression of the proneural gene atonal ( ato ) since its expression pattern defines the pre-R8 cell recruitment and early specification of a mature R8 cell . In a wild-type disc , Ato is initially expressed in all cells of the MF . Later , Ato expression is resolved to a single pre-R8 cell via proneural enhancement and lateral inhibition [34] ( Figure 1I ) . In clones of rbf wts double mutant cells , Ato expression is initiated and refined to a single cell properly indicating that specification of R8 cells occurs normally ( Figure 1J ) . To further support this conclusion , we examined expression of the fibrinogen-related protein Scabrous ( Sca ) , another useful marker of R8 cell development . Sca is required for the restriction of Ato expression during the process of lateral inhibition that occurs in the resolution of a mature R8 cell [35] . As shown in Figure 1K and 1L , the pattern of Sca expression remains largely unaffected in the rbf wts double mutant tissue . We concluded that following developmental specification and refinement , mature R8 cells are progressively lost in rbf wts double mutant tissue . This is in striking contrast to the phenotypes of rbf , hpo , or wts single mutants , in which following specification and refinement , differentiation of photoreceptors remains normal . A simple explanation for the progressive reduction in the number of Sens positive cells within the rbf wts double mutant tissue is that these cells are eliminated through apoptosis . To test this idea , we used an antibody that recognizes a cleaved form of caspase 3 ( C3 ) to visualize apoptotic cells . The loss of rbf leads to a significant level of apoptosis immediately posterior to the MF ( Figure 2A ) [19] . Strikingly , a wts mutation protects rbf deficient cells from apoptosis as no C3 positive cells were found within rbf wts double mutant tissue including the region posterior to the MF , where differentiation occurs ( Figure 2B ) . The lack of apoptotic cells in rbf wts double mutant tissue is consistent with the known ability of mutations in the Hippo pathway to protect cells from several types of apoptosis [31] , [32] , [36] . To further confirm that apoptosis does not contribute to the loss of Sens expressing rbf wts mutant cells we overexpressed the baculovirus protein p35 in all cells posterior to the MF . p35 is a caspase inhibitor that potently blocks most cell death in Drosophila [37] . As shown in Figure 2C , the number of R8 cells , visualized by the expression of Sens , were progressively lost in the posterior region of the rbf wts double mutant clone even when p35 was overexpressed . We therefore concluded that a progressive reduction in the number of Sens positive cells is because rbf wts double mutant cells failed to maintain the neuronal differentiated state . Because defects in R8 differentiation are known to prevent development of other photoreceptors , we examined the differentiation of other R cells in rbf wts double mutant tissue . R2/R5 are recruited following R8 specification and can be identified by the high level of expression of the transcription factor Rough ( Ro ) ; that is also expressed at a lower level in R3/R4 , which develop following R2/R5 ( Figure 3A and 3Ai ) . Despite the stochastic disappearance of R8 cells in rbf wts double mutant tissue , one could find mutant ommatidia containing the correct number of two cells per cluster highly expressing Ro , thus indicating that recruitment of R2/R5 cells can occur properly ( pointed to by arrows in Figure 3Bi ) . However , there were ommatidia that had either only a single or no Ro expressing cells . Furthermore , the number of Ro positive cells was generally reduced in the posterior region of the clone ( Figure 3B and 3Bi and Figure S3 ) . These results suggested that R2/R5 development could occur normally , but that like the defects seen in R8 cells , following specification could not always be maintained as mature photoreceptors . Consistent with the notion that mature R cells were being lost we found that the total number of photoreceptors per ommatidium was highly variable in the rbf wts double mutant tissue as revealed by expression of Elav , which visualizes all photoreceptors in the ommatidium ( Figure 3B and 3C ) . Quantification supported the conclusion that there was not a stage in recruitment and specification of R cells that appeared to be completely inhibited ( Figure 3D ) suggesting that the defects seen were not directly due to developmental signaling being affected . In spite of the stochastic loss of neuronal markers , the cellular program of terminal neuronal differentiation was not blocked , as rbf wts double mutant photoreceptors retained the ability to complete neuronal differentiation . In wild-type discs , as photoreceptors differentiate they begin to express the neuron specific form of neuroglian ( Nrg ) along axonal projections which can be detected with the BP104 antibody ( Figure 3E ) [38] . These axonal projections migrate to connect with the optic lobe to form functional light sensory cells . We observed that rbf wts double mutant cells express Nrg in the anterior region of mutant clones ( Figure 3F ) ; indicating that as rbf wts mutant photoreceptors differentiate they exhibit characteristic morphological features of normal photoreceptors at this stage of development . However , similar to the expression of Elav , Ro , and Sens , expression of Nrg largely disappeared in the posterior region of the mutant clone . To determine if the defects in larval eye differentiation could be corrected later in development , we examined mosaic pupal eye discs at a stage when all cells of a mature ommatidium ( including pigment , cone , and bristle cells ) have developed . We found that there were fewer ommatidia , as revealed by Elav expression , in the rbf wts double mutant tissue than in the adjacent wild-type tissue and that mutant ommatidia contained a reduced number of photoreceptors ( Figure 3G and 3H ) . We concluded that the failure of rbf wts double mutant cells to maintain a differentiated state was not limited to R8 cells , appeared to occur stochastically , and therefore reflects a general requirement of the pRB and Hippo pathways in maintenance of neuronal differentiation . To further characterize the progressive loss of differentiated cells in the rbf wts double mutant tissue we examined the expression of the eye determination gene eyes absent ( eya ) . Eya promotes differentiation and plays a major role in the transcription factor network that controls eye development [39] . In wild-type eye discs , Eya is expressed at a high level in differentiating photoreceptors while uncommitted interommatidial cells express Eya at a lower level ( Figure 4A and 4Ai ) [39] . This difference in the levels of Eya is especially evident in clones of wts mutant cells in which the population of interommatidial cells is expanded ( Figure 4B and 4Bi ) . Eya remains to be expressed throughout the rbf wts double mutant tissue even in the most posterior regions , where loss of differentiation markers was most often observed ( Figure 4C and 4Ci ) . As shown in Figure 4Ci , Eya was highly expressed in rbf wts double mutant photoreceptors while interommatidial cells had a low level of Eya . Interestingly , we observed numerous examples of Elav negative rbf wts double mutant cells with a high level of Eya ( pointed to by arrows in Figure 4Ci ) . Since these cells were found immediately adjacent to ommatidial clusters it is attractive to speculate that these cells are undergoing dedifferentiation . However , this could not be directly tested due to the lack of markers of dedifferentiated cells . Nevertheless , given that the eye determination gene Eya was expressed in all cells within the rbf wts double mutant tissue we concluded that cells no longer expressing differentiation specific proteins did not change their identity and remained eye specific cells . To determine whether dedifferentiated rbf wts double mutant photoreceptors eventually differentiate into different cell types such as cone cells we examined expression of the cone cell marker Cut in mosaic pupal eye discs . At 48 hr after puparium formation , four cone cells per ommatidium were present in wild-type tissue ( Figure 4D ) . In contrast , the number of cone cells per ommatidium was reduced in rbf wts double mutant tissue . In general , we observed one to three cone cells , although one could also find ommatidia containing precisely four cone cells per ommatidium ( Figure 4D ) . However , we did not find any indication that cone cells overpopulate the mutant tissue suggesting that rbf wts double mutant cells do not transdifferentiate into cone cells . Taken together these data suggest that once recruited and specified rbf wts double mutant photoreceptors properly initiate and progress through the neuronal differentiation program . However , over time rbf wts double mutant photoreceptors stochastically lose their morphological features and become undifferentiated , eye specific cells . Therefore , we concluded that rbf wts double mutant photoreceptors undergo dedifferentiation . In normal cells proliferation and differentiation are tightly coordinated and are generally incompatible with each other . Dedifferentiation in rbf wts double mutant tissue prompted us to examine the impact of the combined loss of rbf and wts during cell cycle exit . We used BrdU labeling to mark cells in S phase . In the larval eye disc , the pattern of cell proliferation is linked to the MF , where cells are arrested in G1 and therefore do not incorporate BrdU ( Figure 5A ) . Directly posterior to the MF , uncommitted cells undergo a synchronous round of the cell cycle called the second mitotic wave ( SMW ) . No proliferation occurs posterior to the SMW as all cells withdraw from the cell cycle . rbf mutant eye discs exhibit only minor perturbations in cell cycle exit ( for example: [19] and data not shown ) . Inactivation of the Hippo pathway leads to inappropriate proliferation of interommatidial cells posterior to the SMW while photoreceptors exit the cell cycle properly ( [31] , [32] , [36] and data not shown ) . Not surprisingly , the precise pattern of cell proliferation was completely lost in rbf wts double mutant tissue . rbf14 wtsx1 double mutant cells were found to be inappropriately undergoing S phases and subsequent mitoses within the MF and posterior to the SMW ( Figure 5B–5D ) . Unexpectedly , we found that in addition to interommatidial cells , these inappropriate cell divisions were taking place in fully differentiated cells , marked by Elav and Sens expression ( Figure 5C and 5D ) , a phenotype that is distinct from either the loss of rbf or wts alone [19] , [31] , [32] , [36] . At least some of these differentiated cells continued to proliferate during early pupal development as revealed by the occurrence of lone Elav positive cells which expressed the mitotic marker phosphorylated histone H3 ( pH 3 ) in confocal images ( Figure 5E ) . In summary , these results show widespread inappropriate proliferation of differentiated rbf wts double mutant photoreceptors . In several experimental systems , when a differentiated cell reenters the cell cycle it undergoes dedifferentiation . Thus , dedifferentiation in rbf wts double mutant clones could be induced by inappropriate reentry into the cell cycle . To test this idea , we examined the procession of differentiation in rbf wts double mutant tissue when inappropriate proliferation of these cells was blocked by a de2f1 mutation . In agreement with our previous findings that de2f1 is specifically required during inappropriate proliferation wts mutant cells [40] , rbf wts de2f1 triple mutant cells failed to incorporate BrdU posterior to the SMW , but not in the anterior compartment when cells are normally cycling asynchronously ( Figure 6A ) . However , even in the complete absence of inappropriate proliferation we observed a widespread dedifferentiation in the rbf wts de2f1 triple mutant tissue as evidenced by the progressive loss of Sens positive cells in the posterior region ( Figure 6B ) . As in the rbf wts double mutant clones , cell death that might account for the loss of Sens positive cells was not detected in rbf wts de2f1 triple mutant tissue posterior to the MF ( Figure S4 ) . Additionally , wts mutant cells are intrinsically protected from apoptosis due to Yki induced upregulation of the Drosophila inhibitor of apoptosis , diap1; indeed , diap1 remained induced in the triple mutant cells ( Figure S4 ) . Thus , inappropriate proliferation of rbf wts double mutant photoreceptors does not induce their dedifferentiation . Furthermore , since the loss of de2f1 had no effect on the rbf wts mutant phenotype this suggests that dedifferentiation occurs in a dE2F1 independent manner and , thus , reflects a dE2F1 independent function of RBF . Yki represents a critical effector of the Hippo pathway and mediates its growth output . In wts or hpo mutants , Yki inappropriately translocates to the nucleus and activates Hippo pathway target genes that promote cell proliferation and block apoptosis [41] . Therefore we examined the subcellular localization of Yki in rbf wts double mutant cells . Yki is mostly cytoplasmic in wild-type cells , while it becomes more nuclear in wts mutant cells [42] , [43] . In the posterior region of developing larval eye imaginal disc , Yki was largely present in interommatidial cells and was undetected in differentiated photoreceptors ( Figure 7A ) . In contrast , Yki was localized to both the cytoplasm and nucleus in rbf wts double mutant cells ( Figure 7B ) . This was not a result of inappropriate proliferation , since Yki remained primarily nuclear in rbf wts de2f1 triple mutant cells ( Figure 7C ) that did not proliferate posterior to the SMW ( Figure 6A ) . Thus , we concluded that Yki is inappropriately localized to the nucleus in both rbf wts double mutant cells and in rbf wts de2f1 triple mutant cells , which along with dIAP1 upregulation ( Figure S4 ) , is a hallmark of Yki activation . Next , we tested whether activation of Yki is sufficient to trigger dedifferentiation of rbf mutant photoreceptors . We overexpressed a hyperactive form of YkiS168A using a GMR-Gal4 driver in cells posterior to the MF in the rbf120a mutant eye disc and analyzed the expression of Sens and Elav . The GMR-Gal4 driver has been previously validated in experiments to assess the function of Yki and its mammalian homolog YAP ( for example see: [44] ) . YkiS168A is resistant to an inhibitory phosphorylation by the Wts kinase and therefore more efficiently translocates to the nucleus [42] , [43] . Overexpression of Yki resulted in excessive proliferation in the posterior part of both the wild-type and rbf mutant eye disc ( Figure 7D and 7E ) . This led to an increased spacing between adjacent ommatidial clusters . Surprisingly , in contrast to rbf wts or rbf hpo double mutant cells , overexpression of Yki did not induce dedifferentiation of rbf mutant cells , as there was no reduction in the number of Elav and Sens positive cells even in the most posterior region ( Figure 7E ) . We note however that there is a spatial difference in Yki activation in these two settings . In rbf wts and in rbf hpo double mutant clones activation of Yki occurred prior to the MF while the GMR-Gal4 driver induced Yki expression in cells within and posterior to the MF . Nevertheless , it seems highly unlikely that this spatial difference accounts for the inability of Yki to induce dedifferentiation in rbf mutant cells since photoreceptor recruitment and specification within the MF is not affected in rbf wts double mutant tissue . Therefore , we concluded that although overexpression of Yki recapitulates the tissue overgrowth phenotype of the Hippo pathway mutants , it is insufficient to mimic the dedifferentiation defects of rbf wts mutant photoreceptors .
The normal process of differentiation is accompanied by a declining plasticity of cells that commit to lineage-specific fates . In non-pathological conditions , this eventually culminates in an irreversible state of terminal differentiation . We found that in rbf wts double mutant cells this irreversibility is lost . It is widely acknowledged that inactivation of the pRB pathway is an obligatory early event in tumorigenesis , while the tumor suppressive function of pRB is usually attributed to its role in promoting cell cycle exit [7] . Surprisingly , we found that dedifferentiation of rbf wts double mutant cells is not due to a failure to exit the cell cycle . Thus , our results illuminate a novel function of pRB , guarding the differentiated state of a cell , and suggest that it is separable and distinct from the cell cycle exit control . Dedifferentiation is an important topic in cancer biology . It is well known that tumors containing cells with the morphological features of progenitor cells are generally more malignant than those resembling differentiated cells . Thus , tumor aggressiveness often correlates inversely with the extent of differentiation within a tumor . One implication of this work is that the loss of Rb may sensitize cells to dedifferentiation . More broadly , our results suggest that the concomitant loss of both the pRB and Hippo pathways allows cells to revert back to a progenitor-like state and therefore to have an increased potential to contribute to tumor growth . In this work we employed the Drosophila retina to study the role of the pRB and Hippo pathways in differentiation . In the Drosophila retina , the developmental specification and recruitment of uncommitted cells is required for terminal neuronal differentiation . We found that both cell type specific ( Sen and Ro ) and more general ( Elav and Nrg ) neuronal markers are continuously lost over time in the rbf wts mutant tissue . Since improper recruitment impacts terminal differentiation then the loss of neuronal markers could be an indirect consequence of defects in recruitment . However , our analysis of R8 cell recruitment in rbf wts double mutant clones strongly argues against such an explanation . Specifically the expression of Atonal , a pro-neural gene that determines specification of the pre-R8 cell , and Scabrous , a secreted protein required for proper pattern formation of ommatidia to occur [35] , were initiated and correctly resolved in rbf wts double mutant clones . Additionally , our data are distinct from previously reported R8 specific differentiation defects . For example , a reduction in the number of Sens positive cells towards the posterior has been previously described in egfr mutant clones . However , the egfr mutant phenotype can be rescued by overexpression of p35 suggesting that in this setting R8 cells are eliminated by apoptosis [45] . In contrast , there is no apoptosis in rbf wts double mutant tissue and the loss of R8 cells occurred even in the presence of p35 . In another example , a pre-R8 cell forms in sens mutant ommatidia , but never a mature R8 cell . As a result , the pre-R8 cell switches fate to become an R2/R5 cell [46] . This is clearly not the case in rbf wts double mutant clones as mature R8 cells expressing the late neuronal marker Elav were present . This previous work further suggested that R-cell type specific signaling events are mutually exclusive from R-cell recruitment and resolution [46] . Our work expands upon this idea to suggest that following R-cell recruitment the pRB and Hippo pathways play a key role in maintaining the pro-neural program innate to each cell type in order to prevent the cell from dedifferentiating . The fact that an rbf mutation leads to the loss of differentiation markers itself is not unexpected , since , for instance , Rb-/- mouse embryos display a variety of differentiation defects [47]–[49] . However , what constitutes a novel finding is that a progressive loss of differentiation markers as seen in rbf wts double mutant cells has not been previously reported in Rb-/- mouse knockouts . Similarly , tissue specific ablation of Rb in terminally differentiated cells in vivo is not accompanied by dedifferentiation . For example , during mouse inner ear development , Rb-/- hair cells undergo inappropriate cell divisions while remaining fully differentiated [11] . In Drosophila , cells that are double mutant for rbf and dacapo , a p21 homolog , differentiate into photoreceptors and , at the same time , undergo further cell divisions without the loss of the late neuronal marker Elav [18] . Even in tumorigenic settings Rb-/- cells do not undergo dedifferentiation , as has been demonstrated by analysis of Rb-/- p130-/- p107+/- horizontal interneurons . These cells inappropriately re-enter the cell cycle , clonally expand , and form metastatic retinoblastoma in mice , yet they remain highly differentiated cells [50] . These studies concluded that pRB operates in vivo at the point of terminal cell cycle exit . Our results suggest that , additionally , the pRB pathway , in cooperation with the Hippo pathway , has an important function in maintenance of a differentiated state . One question that particularly interested us was whether the inappropriate proliferation of rbf wts double mutant photoreceptors triggers dedifferentiation . Earlier studies showed that inappropriate proliferation interferes with differentiation in cultured cells; and that the majority of differentiation defects in Rb-/- mouse knockouts appear to be an indirect consequence of defects in cell cycle exit and apoptosis or are a reflection of an extraembryonic function of Rb [14]–[16] , [51] , [52] . Therefore it was surprising that the rbf wts double mutant photoreceptors dedifferentiate in the complete absence of cell proliferation indicating that inappropriate cell cycle re-entry by itself is not sufficient to cause dedifferentiation . Consistently , driving rbf mutant photoreceptors into the cell cycle by overexpression of yki ( this study ) or by a concomitant loss of dacapo [18] does not cause dedifferentiation . Thus , the function of rbf in the maintenance of a differentiated state is unrelated and independent of the role of rbf during the cell cycle exit . Why combined inactivation of the Hippo and pRB pathways causes dedifferentiation is not known . We disfavor an explanation that this is merely a cumulative effect of inactivation of two negative regulators of cell proliferation . Although we haven't extensively tested other tumor suppressor genes , at least the loss of tsc1 failed to induce dedifferentiation of rbf mutant cells . Intriguingly , it has been previously shown that hpo and wts function in differentiated photoreceptors to regulate stable fate choice of the R8 cell subtypes [24] . Thus , dedifferentiation of rbf wts double mutant cells may reflect a specific functional overlap between pRB and Hippo pathways in neuronal cells . The idea that the Hippo pathway has a postmitotic function is further supported by the fact that while yki expression readily drives differentiated rbf mutant cells into the cell cycle , the presence of a functional Warts kinase in these cells protects them from dedifferentiating . One implication of this result is that other effector ( s ) of the Hippo pathway may cause dedifferentiation of rbf mutant cells . Several studies have described Yki independent functions of Wts , such as the regulation of dendritic tiling and maintenance [25] and control of autophagic cell death in salivary glands [26] . It is worth noting that in contrast to rbf wts double mutants , photoreceptor differentiation occurs normally in wts de2f1 de2f2 triple mutants [40] . This suggests that the differentiation phenotype observed in rbf wts double mutants is likely to reflect an E2F independent function of rbf . Although the analysis of differentiation in rbf wts de2f1 de2f2 quadruple mutant cells will be needed to confirm this point , our data raise an intriguing possibility that the convergence of the pRB and Hippo pathways in maintaining a differentiated state lies outside of their conventional roles to restrain the activities of E2F and Yki respectively . The process of cell-specific lineage commitment and terminal differentiation is accompanied by stabilization and maintenance of each cell-type specific transcription program . This is achieved by a progressive restriction of chromatin accessibility to genes that promote proliferation and , conversely , increasing chromatin accessibility to tissue-specific genes . It is well established that the Polycomb group ( PcG ) genes play key roles in “locking” the chromatin state during cell specification and differentiation [53] , [54] . Intriguingly , both the pRB and Hippo pathways were linked to the regulation of chromatin structure in Drosophila . For example , RBF was shown to directly regulate chromatin condensation [55] , while the Hpo and Wts kinases genetically and physically interact with Polycomb Group proteins ( PcG ) [25] . Thus , it is tempting to speculate that the dedifferentiation of photoreceptors in rbf wts double mutants could be the result of alterations in gene expression due to aberrant epigenetic changes in cells lacking functional pRB and Hippo pathways .
All crosses were done at room temperature unless otherwise stated . rbf1120a ey-FLP / Y; 82BFRT de2f1729 wtsX1 / 82B FRT [Ubi-GFP] rbf1120a ey-FLP / Y; 82BFRT wtsX1 / 82B FRT [Ubi-GFP] rbf1120a ey-FLP / Y; 42DFRT hpoMGH4 / 42DFRT [Ubi-GFP] rbf1120a ey-FLP / Y; GMR-Gal4 , UAS-p35 / UAS-YkiS168A rbf1120a ey-FLP / +; GMR-Gal4 , UAS-p35 / UAS-YkiS168A rbf1120a ey-FLP / Y; GMR-Gal4 , UAS-p35 / +; 82BFRT wtsX1 / 82B FRT [Ubi-GFP] rbf114 FRT19A / [Ubi-GFP] FRT 19A; ey-FLP / +; 82BFRT wtsX1 / 82B FRT [Ubi-GFP] rbf114 FRT19A / [Ubi-GFP] FRT 19A; ey-FLP / + ey-FLP / +; 82BFRT wtsX1 / 82B FRT [Ubi-GFP] rbf1120a hs-FLP / Y; 82BFRT wtsX1 / 82B FRT [Ubi-GFP] rbf1120a hs-FLP / Y; 82BFRT tscf01910 / 82B FRT [Ubi-GFP] rbf1120a hs-FLP / Y; 82BFRT tsc3 / 82B FRT [Ubi-GFP] hs-FLP / Y; 82BFRT tscf01910 / 82B FRT [Ubi-GFP] hs-FLP / Y; 82BFRT tsc3 / 82B FRT [Ubi-GFP] hs-FLP / Y; 82BFRT wtsX1 / 82B FRT [Ubi-GFP] To generate adult and larval rbf wts and rbf tsc double mutant tissue , and wts or tsc single mutant tissue , clones were induced 48 hr AED for 20 minutes at 37°C , and then larvae were grown at 25°C . Antibodies used were as follows: guinea pig anti-Senseless 1∶2000 ( from H . Bellen ) , rabbit anti-Yki 1∶800 ( from K . Irvine ) , rat anti-ELAV 1∶200 ( DSHB ) , mouse anti-Nrg 1∶100 ( DSHB ) , mouse anti-Eya 1∶100 ( DSHB ) , mouse anti-Scabrous 1∶30 ( DSHB ) , mouse anti-Rough 1∶100 ( DSHB ) , mouse anti-Cut 1∶200 ( DSHB ) , rabbit anti-Atonal 1∶2000 ( from Y . Jan ) , rabbit anti-C3 ( Cleaved Caspase3 ) 1∶100 ( Cell Signaling ) , mouse anti-BrdU 1∶50 ( Beckton Dickinson ) , rabbit anti-phosH3 1∶175 ( Upstate ) , mouse anti-RBF1 1∶20 , and Cy3 , Cy5 conjugated anti-mouse , anti-rabbit , anti-rat , and anti-guinea pig secondary antibodies ( Jackson Immunolaboratories ) . Larval and pupal tissues were fixed in 4% formaldehyde +1X phosphate-buffered saline for 35 minutes on ice , washed in 1X phosphate-buffered saline two times for 5 min on ice , then permeabilized in 1X phosphate-buffered saline +0 . 3% Triton-X100 three times for 5 minutes each , and then incubated with antibodies overnight at 4°C in phosphate-buffered saline , 10% normal goat serum , and 0 . 3% Triton-X100 . After the overnight incubation , samples were washed in 1X phosphate-buffered saline + 0 . 1% Triton-X100 three times for 5 minutes each at room temperature . Samples were then incubated with appropriate conjugated secondary antibodies for 1 hour at room temperature in phosphate-buffered saline , 10% normal goat serum , and 0 . 3% Triton-X100 . Finally , samples were washed five times for 5 minutes each at room temperature in 1X phosphate-buffered saline + 0 . 1% Triton-X100 before being stored in glycerol + antifade reagents and then mounted on glass slides . To detect S phases dissected larval eye discs were labeled with BrdU for 2 hrs at room temperature and then the eye discs were fixed overnight in 1 . 5% formaldehyde + 1X phosphate-buffered saline + 0 . 2% Tween−20 at 4°C . Samples were then digested with DNAase ( Promega ) treatment for 30 minutes at 37°C . Samples were then treated with primary and secondary antibodies as described above . All immunoflourescence was done on a Zeis Confocal microscope and images were prepared using Adobe Photoshop CS4 . All images are confocal single plane images unless otherwise stated as projection images .
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The inability to respond to growth inhibitory cues is one acquired trait of a cancer cell . Almost all such signals are eventually routed through the Retinoblastoma ( pRB ) tumor suppressor pathway . Therefore , inactivation of the pRB pathway is considered to be an early and obligatory event during transformation of a normal cell into a malignant cancer cell . In this study , we found that inactivation of the Hippo pathway makes Rb mutant cells prone to undergo morphological changes and to become less differentiated , progenitor-like cells . Furthermore , we show that this was independent of the failure of Rb mutant cells to properly respond to cell cycle exit cues . These results are significant since , in general , tumors containing progenitor-like cells have a higher potential to progress through later stages of tumorigenesis and to become more aggressive and more deadly . Thus , the inactivation of Rb not only renders cells insensitive to growth inhibitory signals , but also sensitizes cells to revert to a progenitor-like state .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology/cell",
"differentiation",
"cell",
"biology/cell",
"growth",
"and",
"division"
] |
2010
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Combined Inactivation of pRB and Hippo Pathways Induces Dedifferentiation in the Drosophila Retina
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The Dobzhansky and Muller ( D-M ) model explains the evolution of hybrid incompatibility ( HI ) through the interaction between lineage-specific derived alleles at two or more loci . In agreement with the expectation that HI results from functional divergence , many protein-coding genes that contribute to incompatibilities between species show signatures of adaptive evolution , including Lhr , which encodes a heterochromatin protein whose amino acid sequence has diverged extensively between Drosophila melanogaster and D . simulans by natural selection . The lethality of D . melanogaster/D . simulans F1 hybrid sons is rescued by removing D . simulans Lhr , but not D . melanogaster Lhr , suggesting that the lethal effect results from adaptive evolution in the D . simulans lineage . It has been proposed that adaptive protein divergence in Lhr reflects antagonistic coevolution with species-specific heterochromatin sequences and that defects in LHR protein localization cause hybrid lethality . Here we present surprising results that are inconsistent with this coding-sequence-based model . Using Lhr transgenes expressed under native conditions , we find no evidence that LHR localization differs between D . melanogaster and D . simulans , nor do we find evidence that it mislocalizes in their interspecific hybrids . Rather , we demonstrate that Lhr orthologs are differentially expressed in the hybrid background , with the levels of D . simulans Lhr double that of D . melanogaster Lhr . We further show that this asymmetric expression is caused by cis-by-trans regulatory divergence of Lhr . Therefore , the non-equivalent hybrid lethal effects of Lhr orthologs can be explained by asymmetric expression of a molecular function that is shared by both orthologs and thus was presumably inherited from the ancestral allele of Lhr . We present a model whereby hybrid lethality occurs by the interaction between evolutionarily ancestral and derived alleles .
Species can be isolated from one another by a variety of reproductive barriers . One widely observed barrier is hybrid incompatibility ( HI ) , the inviability or sterility of interspecies offspring . The key premise of the Dobzhansky-Muller ( D-M ) model explaining the evolution of HI is that genetic changes fixed in one population need not be compatible with changes fixed in a different population [1] , [2] . This is most commonly illustrated as two independently evolving populations that each diverge from the ancestral state and fix new alleles . Hybridization between the two populations brings together the independently derived alleles , thereby generating a genotype unscreened by natural selection . This genotype may suffer from an incompatible interaction between the derived alleles , resulting in developmental breakdown of the hybrid progeny . A key feature of this model is that HI alleles have diverged in sequence and function ( perhaps extensively ) from their ancestral states . A second important prediction of the model is asymmetry: Gene “A” from species one may interact with gene “B” from species two to cause HI , but not vice-versa [3] . Questions fundamental to understanding speciation then are: What molecular divergence between the ancestral and derived alleles is causing HI ? Is this divergence at the level of regulatory or structural changes ? What are the evolutionary forces causing this divergence ? One unifying emerging trend is that HI loci often show high levels of divergence caused by natural selection [3] , [4] . These findings are exciting , because if molecular divergence created by selection is causing HI , then the phenotypic target of selection is , at least in part , the evolutionary basis of speciation . A major goal then is to understand the role of selection in the evolution of incompatible divergence . Interestingly , studies on several recently characterized HI genes implicate divergence of heterochromatin and heterochromatin-binding proteins as the cause of incompatibility [5] , [6] . As heterochromatin is the graveyard of selfish genetic elements , this functional divergence could be the legacy of genetic conflicts between the host species and the invasion of selfish DNAs such as transposable elements and satellite DNAs [7] , [8] . A variation of the D-M model suggests that HI can also be caused by interactions between alleles that have not diverged from the ancestral state and derived alleles that have diverged in only one lineage [9] . If an HI allele has not diverged from its ancestral state , then this model predicts that its HI effects will be symmetrical , with orthologs from both species contributing to HI . Several examples of ancestral-derived incompatibilities have been discovered , and consistent with expectations the HI genes , when known , have experienced limited sequence divergence [10]–[12] . On the other hand , the expectation of a strict dichotomy between ancestral and derived HI alleles may reflect an over-simplified view of HI . Hybrids are the sum of two independently evolving genomes and thus suffer from multiple suboptimal interactions [3] . For example , species-specific divergence at cis and trans-regulatory elements is associated with widespread transcriptional dysregulation in hybrids [13] , [14] . This creates a genetic background distinct from either parental species , and several well-studied HI genes have genetic properties in hybrids that are significantly different from or even opposite to their intraspecific roles [3] . Crosses between D . melanogaster females and D . simulans males produce inviable hybrid sons and sterile hybrid daughters [15] . The incompatible D-M interaction in hybrid males can in part be explained by the interaction between two genes , Hybrid male rescue ( Hmr ) on the D . melanogaster X-chromosome and Lhr on the D . simulans 2nd chromosome [16] . A loss of function mutation in either Hmr or Lhr alone is sufficient to suppress the lethality of hybrid sons [16]–[19] . Thus it is the activity of these genes that causes hybrid breakdown . Lhr ( also known as HP3 ) encodes a protein that localizes to heterochromatin by directly binding to Heterochromatin Protein 1 ( HP1 ) [16] , [20] , [21] . Population genetic analyses demonstrated that the Lhr protein coding sequence ( CDS ) has diverged extensively between D . melanogaster and D . simulans under positive selection , leading to the suggestion that Lhr has co-evolved with species-specific heterochromatin sequences [16] . If this co-evolution reflects a history of genetic conflict then one might predict that hybrid lethality is caused by defects in heterochromatin structure or maintenance , and that Lhr orthologs have functionally diverged in their heterochromatin localization properties such that they would mislocalize in the presence of heterochromatin from different species . The hybrid lethality gene Lhr appeared initially to be a clear example of a derived D-M hybrid incompatibility locus . Consistent with the expectation of functional divergence , we previously found that the rescue of hybrid lethality via Lhr is asymmetric; removal of D . simulans Lhr ( sim-Lhr ) rescues lethal hybrid sons but removal of D . melanogaster Lhr ( mel-Lhr ) does not [16] . Surprisingly , however , Lhr orthologs from D . melanogaster , D . simulans and the outgroup species D . yakuba all have hybrid lethal activity when overexpressed in hybrids [21] . LHR proteins from these species also retain heterochromatic localization when expressed in polytenized salivary-gland cells , demonstrating that natural selection has not caused a wholesale change in Lhr function . This set of results suggests either that functional divergence is not an all-or-none property , or that Lhr is an ancestral HI locus , rather than a derived one . To distinguish between these two possibilities , and to uncover the functional divergence underlying the asymmetric rescue properties of Lhr orthologs , we developed a native-promoter driven transgenic system that allows a sensitive comparison of the functions and localization properties of D . simulans and D . melanogaster Lhr orthologs . Using this system , we have compared Lhr function in both pure species and hybrids using three sets of experiments: ( 1 ) genetic tests for hybrid lethal activity and interaction with its D-M partner , Hmr; ( 2 ) detailed cytological mapping of the heterochromatic localization of LHR and its association with hybrid lethality , and ( 3 ) expression analysis comparing transcriptional levels of the Lhr orthologs .
We generated parallel strains of D . melanogaster containing either D . simulans Lhr ( sim-Lhr ) or D . melanogaster Lhr ( mel-Lhr ) transgenes using the φC31 site-specific integration system [22] . Each Lhr ortholog was C-terminally tagged with an HA epitope and was expressed under the control of its native regulatory sequences ( Figure 1 ) . The transgenic constructs contained the eye-color marker white+ and were each integrated into the attP2 site on the third chromosome . We tested the transgenes for wild type activity by assaying for complementation of the D . simulans Lhr1 hybrid rescue mutation . D . simulans Lhr1 is a loss-of-function mutation that acts as a dominant suppressor of hybrid lethality [16] , [18] . Complementation here means that the transgene provides sufficient wild type Lhr activity to suppress rescue by the Lhr1 mutation , thus causing hybrid male inviability . Complementation tests were performed by crossing D . melanogaster mothers heterozygous for an Lhr-HA transgene to D . simulans Lhr1 fathers . This cross generates two classes of hybrid sons: the control class that lacks the transgene and has white eyes , and the experimental class that inherits the transgene and has orange eyes . Complementation is detected as the lethality of orange-eyed sons . If hybrid lethal activity partitions discretely between Lhr orthologs , as expected from the functional divergence interpretation of genetic asymmetry , sons inheriting the φ{Dsim\Lhr-HA} transgene should be lethal , while those inheriting φ{Dmel\Lhr-HA} should be viable . Unexpectedly , both transgenes fully complemented the D . simulans Lhr1 mutation ( Table 1 , crosses 1 thru 4 ) , suggesting that both D . simulans and D . melanogaster Lhr orthologs have hybrid lethal activity . As this result was contrary to expectation we tested several possible causes of artifacts . First , the C-terminal HA-tag does not affect Lhr function because untagged versions of both mel-Lhr and sim-Lhr also complement Lhr1 ( Table 1 , crosses 5 and 6 ) . Second , the adjacent gene Bap55 present in these constructs is not responsible for complementation because a modified mel-Lhr-HA transgene , φ{ΔBap55 Dmel\ Lhr-HA} , in which the Bap55 CDS is interrupted by two stop codons and a frameshift mutation , also complements Lhr1 ( Table 1 , cross 7 ) . Third , the results are not caused by other unknown aspects of the strain background or by the attP2 site because the attP2 site itself without an integrated transgene does not complement Lhr1 ( Table 1 , cross 8 ) . Furthermore mel-Lhr-HA integrated into a different site ( attP86Fb ) also complements Lhr1 ( Table 1 , cross 4 ) . Fourth , these results are not due to an over-expression artifact because data presented below demonstrate that the mel-Lhr-HA transgene expresses Lhr at a level similar to the endogenous wild type locus ( see section “cis-by-trans regulatory divergence causes functional divergence of D . melanogaster and D . simulans Lhr” below ) . These results clearly show that D . melanogaster Lhr has hybrid lethal activity even when expressed at its wild type level . How can these results be reconciled with the original observation that only a mutation in D . simulans Lhr , and not the D . melanogaster ortholog , rescues hybrid sons ? Those experiments were done in hybrid genotypes that had only a single dose of either mel-Lhr or sim-Lhr [16] . In contrast , the experiments here were performed by adding a transgenic copy of either mel-Lhr or sim-Lhr to hybrids that also carried the endogenous chromosomal copy of mel-Lhr . Increased dosage of mel-Lhr in the current experiments may therefore explain why we have not observed a difference between the mel-Lhr and sim-Lhr transgenes . This hypothesis raises the question of whether the hybrid lethal activity of the mel-Lhr-HA transgene would be eliminated in a background lacking the chromosomal copy of mel-Lhr . To test this we crossed D . melanogaster mothers that were doubly heterozygous for the mel-Lhr-HA transgene and an Lhr− deficiency to D . simulans Lhr1 fathers . If transgenic mel-Lhr behaves identically to the endogenous locus , then hybrid sons inheriting the Lhr− deficiency along with the mel-Lhr transgene should be equivalent in Lhr dosage to rescued +/Lhr1 hybrid males and thus be viable . However , hybrid sons from this cross were also inviable ( Table S3 ) . This result indicates that the mel-Lhr-HA transgene does not precisely phenocopy the native chromosomal mel-Lhr locus . In the Discussion we consider possible causes of this difference . Because the complementation tests did not reveal a difference in the hybrid lethal effects of Lhr orthologs we used a more sensitive genetic assay to test for functional divergence between mel-Lhr and sim-Lhr . We previously demonstrated that Lhr-dependent hybrid lethality requires the presence of its D-M partner , the D . melanogaster gene Hmr [16] . We reasoned that the hypomorphic allele Hmr1 might exhibit different sensitivities to the HI effects of the different Lhr alleles , but that the null allele Df ( 1 ) Hmr− would not . We therefore introduced each of our Lhr transgenes into these Hmr mutant backgrounds and tested the effect of the transgenes on hybrid male viability in crosses to D . mauritiana and D . simulans . Crosses with the sim-Lhr-HA transgene recapitulated our previous experiments: Hmr1 hybrid males carrying sim-Lhr-HA were essentially inviable at room temperature and showed strongly reduced viability at 18°C , while Df ( 1 ) Hmr− hybrid males were equally viable with and without the transgene ( Table 2 ) . We then performed similar crosses with mel-Lhr-HA . This transgene had little effect on viability of males with the null mutation Df ( 1 ) Hmr− and the results were in general not significantly different compared to the crosses with sim-Lhr-HA ( Table 2 , sets 1 & 2 ) . In crosses with the hypomorphic mutation Hmr1 , hybrids carrying mel-Lhr-HA had reduced viability compared to their non-transgene carrying siblings , particularly at room temperature . Strikingly , we found that in all four cross conditions the magnitude of the viability reduction was significantly less for mel-Lhr-HA compared to sim-Lhr-HA ( Table 2 , sets 3 & 4 ) . These data demonstrate that sim-Lhr is more potent than mel-Lhr in creating the hybrid lethal interaction with Hmr , and that our Lhr transgenes thus do in fact reveal a significant degree of functional divergence . Having demonstrated that wild type mel-Lhr has hybrid lethal activity , we reinvestigated whether removal of mel-Lhr has any detectable hybrid rescue activity . We previously showed that deletion of mel-Lhr does not rescue hybrids with D . simulans [16] . We therefore looked for rescue in hybrids with D . mauritiana at 18°C , conditions that are maximally conducive for hybrid viability [17] . Unrescued hybrid males die as larvae [23] . We found that two D . melanogaster Lhr− deletions rescued 7–21% of males to the pharate adult stage ( Table 3 ) . This is clearly a modest rescuing effect and did not occur in one of the genetic backgrounds tested ( Df ( 2R ) BSC49 crossed to D . mauritiana W139 ) , but it is significant because crosses with 45 other deletions across chromosome 2R gave no rescue . A third Lhr− deletion , Df ( 2R ) BSC44 , did not rescue hybrids , demonstrating that hybrid viability is sensitive to genetic background effects . The difference in magnitude of rescue for deletion of mel-Lhr versus sim-Lhr further supports our conclusion using transgenes that sim-Lhr has greater hybrid lethality activity than mel-Lhr . We next set out to determine why sim-Lhr is more potent than mel-Lhr in causing hybrid lethality . Coding sequence evolution leading to different protein localization patterns is one possible cause of Lhr functional divergence . In order to test this hypothesis we examined the cellular localization of LHR orthologs in their wild type backgrounds using our Lhr transgenes . In D . melanogaster LHR protein is most abundant during embryogenesis ( Figure S1 ) . We therefore analyzed the distribution of LHR during early embryogenesis and found a cyclical on-off pattern through the cell cycle , with localization to chromatin mainly during interphase ( Figure S2 ) . This pattern is identical to its interaction partner , Heterochromatin Protein 1 ( HP1 ) [24] . Thus , we focused on interphase nuclei , and unless otherwise specified all images were taken at embryonic nuclear cycles 12–14 , when heterochromatin is first observed . Consistent with previous results , LHR-HA colocalized with HP1 at DAPI-rich heterochromatic foci on the apical surface of the nuclei ( Figure 2A ) . Unlike HP1 , however , which is found throughout the nuclear compartment including euchromatin , LHR is restricted to heterochromatin . Consistent with being localized to a sub-domain of HP1 , LHR strongly overlapped with Histone-3 lysine 9 dimethylation ( H3K9me2 ) , a histone modification specific to pericentric heterochromatin [25] , but not with Cid , a histone variant specific to the centromere . LHR was also observed in the embryonic germline precursors , the pole cells , and in the somatic and germline cells of the ovary ( Figure S3A ) , where it again colocalized with H3K9me2 ( Figure S3B ) . However , LHR was excluded from the nucleolus , a sub-compartment within heterochromatin consisting of rDNA repeats ( Figure S3B ) . This observation suggested that LHR has a specific distribution within heterochromatin . We therefore used immuno-FISH to investigate the localization pattern of LHR relative to various pericentric satellites in D . melanogaster . We observed no overlap between LHR and the 359 bp satellite , a 4–5 Mb block on the X-chromosome [26] , [27] , nor between LHR and the highly abundant AATAT satellite , which is distributed across multiple chromosomes [28] ( Figure 2C ) . In contrast , LHR consistently overlapped with dodeca , a G/C-rich pericentric satellite on the third chromosome [29] , although a substantial amount of LHR is also found in other heterochromatic regions that we have not mapped . During metaphase , however , four discrete foci of LHR were visible along the metaphase plate . Noticeably , each LHR focus corresponded to the pericentric region of the third chromosome , as identified by overlapping dodeca signal ( Figure 2D ) . We next tested whether LHR localization is conserved in D . simulans . We constructed transgenic lines of D . simulans using the sim-Lhr-HA construct described above . Like mel-LHR in D . melanogaster , sim-LHR in D . simulans also localized to apical heterochromatic foci , as marked by DAPI ( Figure 3C ) . We were particularly interested to determine whether sim-LHR associated with the dodeca satellite , because the distribution of dodeca varies among melanogaster subgroup species [30] . In particular , dodeca satellite is present only in the pericentric region of the third chromosome in D . melanogaster , but is present in the pericentric heterochromatin of both the second and the third chromosomes in D . simulans [30] . We confirmed this difference and found that the dominant dodeca signal is on the D . simulans second chromosome in mitotic brain squashes ( Figure 3A ) . We also noted significant differences in the interphase organization of dodeca between species . We quantified the number of dodeca foci per nucleus and the fraction of nuclear space occupied in interphase nuclei from wild type brains . The dodeca signal in D . simulans appeared fragmented into more foci and occupied a greater nuclear volume , indicating that dodeca-containing heterochromatin has evolved species-specific nuclear organization properties ( Figure 3B ) . Despite this divergence in both chromosomal location and structure of dodeca , immuno-FISH mapping in D . simulans showed that sim-LHR partially colocalized with dodeca in interphase nuclei ( Figure 3C ) . As with mel-LHR , a substantial amount of sim-LHR localizes to other regions of heterochromatin which we have not mapped . However , our results show that its association with dodeca is conserved between species . We were unable to detect sim-LHR on chromosomes during metaphase ( data not shown ) . We note , however , that only a small fraction of mel-LHR appears to be on metaphase chromosomes in D . melanogaster ( see Figure S2 ) and we have found that challenging to image . We are thus unable to determine whether the apparent absence of sim-LHR from metaphase chromosomes reflects a true difference between species or instead is due to technical limitations . It is unclear how LHR localizes to specific domains within heterochromatin , but it might require associations with other heterochromatin proteins , some of which are also rapidly evolving [21] . If LHR is co-evolving with other rapidly evolving proteins , then its heterochromatic localization might be altered when expressed in a foreign species . To test this possibility we examined the localization of sim-LHR-HA in D . melanogaster . We found that sim-LHR-HA localized to the H3K9me2-enriched heterochromatic regions ( Figure 3D ) , and colocalized with the dodeca satellite in a pattern identical to that seen for mel-LHR above ( see Figure 2C ) . In order to directly compare the localization of LHR orthologs within the same nucleus , we generated a recombinant transgenic line that expressed both YFP-tagged mel-LHR and HA-tagged sim-LHR . The two LHR orthologs showed complete overlap , demonstrating that the heterochromatic localization properties of LHR orthologs are conserved ( Figure 3D ) . To determine whether heterochromatin states are perturbed in hybrids we examined HP1 and H3K9me2 localization . Although hybrid embryos were not sexed in this experiment , the staining appeared uniformly wild type in all embryos ( Figure 4A ) . In order to specifically compare LHR and/or dodeca localization in hybrid males versus females , we developed a FISH probe that hybridized to the D . simulans Y-chromosome ( Figure S4 ) . We found that mel-LHR staining was enriched within apical heterochromatin in both sexes , and that it overlapped partially with dodeca ( Figure 4C ) . Importantly , we detected no difference in dodeca organization and LHR localization between lethal hybrid males and viable hybrid females . Since heterochromatin defects might become more apparent later in development we then looked at heterochromatin states in hybrid larval neuroblasts . Consistent with the embryo staining , we saw no defects in the organization of either dodeca or the 2L3L satellite in either inviable male or viable female larvae ( Figure 4D ) . Furthermore , despite differences in the pericentric heterochromatic sequences between homologous chromosomes , somatic pairing during interphase appeared unaffected in hybrid nuclei . In spite of the adaptive protein sequence divergence between D . melanogaster and D . simulans orthologs of Lhr , our results surprisingly suggest only a limited degree of functional divergence of Lhr , with both orthologs having significant hybrid lethal activity and similar patterns of protein localization within heterochromatin . We therefore asked if gene regulatory divergence of Lhr between D . melanogaster and D . simulans might instead be responsible for the asymmetry of the lethal effects of Lhr in hybrids . We first surveyed Lhr transcript levels using qRT-PCR in three strains from each of the two species , and found no significant difference between the two species ( Figure 5A ) . Consistent with this , we detected similar levels of LHR protein between the species ( Figure 5B ) . Expression levels of mel-Lhr-HA and sim-Lhr-HA transgenes were each at a wild type level in their own species background , as total Lhr transcript level was approximately double in strains homozygous for the transgenes compared to wild type controls ( Figure 5C ) . However , sim-Lhr was significantly overexpressed in D . melanogaster . The different expression levels of the sim-Lhr-HA and mel-Lhr-HA transgenes in the same D . melanogaster background indicate that cis-regulatory divergence has occurred at Lhr ( Figure 5C ) . Furthermore , the fact that wild type levels of Lhr are not significantly different between the species ( Figure 5A ) despite these cis-regulatory differences suggests that trans acting factors that regulate Lhr have diverged . Taken together these data demonstrate that Lhr has undergone cis-by-trans compensatory regulation , such that cis-regulatory regions and trans-factors have co-evolved within each species to maintain a constant level of gene expression [31] . The uncoupling of such species-specific compensatory changes in a foreign genetic background would explain why sim-Lhr is hyper-expressed in D . melanogaster . Given these results , we hypothesized that such a mechanism might cause asymmetric expression of Lhr orthologs in hybrids and by extension underlie the asymmetric rescue properties of Lhr orthologs . To test this hypothesis , we did allele-specific pyrosequencing to estimate the relative expression levels of the two Lhr orthologs in hybrids ( Figure 6 ) . We examined 3–5 day-old larvae because temperature shift experiments have shown that the L2/L3 stage is the critical phase of the lethality [17] . As expected Lhr transcript from the pure species parents was essentially 100% for their respective species-specific SNP . However , there was a significant overrepresentation of the D . simulans-specific SNP in both hybrid males and females , with ∼65% of Lhr transcripts deriving from the D . simulans ortholog in hybrid males and ∼60% in hybrid females . These data confirm our expectation that cis-by-trans divergence of Lhr regulation causes asymmetric expression in hybrids , and strongly suggests that a D . simulans mutation rescues hybrid sons because it removes a greater fraction of the total pool of Lhr , compared to a mutation in the D . melanogaster ortholog . We emphasize that this regulatory evolution leads to asymmetric expression of Lhr in hybrids but does not appear to cause an increase in total levels . The abundance of transgenic mel-LHR protein is not elevated in hybrids compared to pure species , as determined by Western blots ( Figure 5D ) . Moreover , because protein levels of LHR orthologs appear equivalent in hybrids , we infer that levels of D . simulans LHR are also not visibly elevated in hybrids ( Figure 5D ) . We therefore conclude that hybrid male lethality is not caused by Lhr over-expression . As we discuss below , lethality instead appears to result from hybrids becoming sensitive to Lhr activity due to its interaction with additional genes including Hmr .
We attempted to create transgenic constructs of Lhr that were functionally identical to the wild type locus . To achieve this we generated Lhr transgenes that were driven by their native cis-regulatory sequences ( Figure 1 ) . Although the boundary of the regulatory regions included in the constructs was arbitrary we did quantitative RT-PCR assays on the transgenes to confirm that they expressed at wild type levels in both D . melanogaster and D . simulans ( Figure 5C ) . Additionally , we infer from western blots that the abundance of transgenic LHR protein is similar in hybrids and pure species ( Figure 5D ) , suggesting comparable expression levels in both backgrounds . Nevertheless , we found that our mel-Lhr-HA transgene has greater activity than wild type Lhr when directly tested against an Lhr− deletion ( Table S3 ) . We consider two explanations: One possibility is that the construct has aberrant expression in a limited number of tissues or developmental stages that is beyond the resolution of detection in qRT-PCR assays of whole embryos or animals . Two , genetic assays for Lhr rescue are highly sensitive to genetic background effects; for example a large screen for suppression of Lhr rescue found a wide range of rescue even in the control balancer-chromosome classes [32] . We also observed here variable effects of D . melanogaster Lhr− deletions on hybrid viability ( Table 3 ) . Thus it is possible that this anomalous result results from an interaction with the multi-locus deficiency used and/or its genetic background . While the result in Table S3 remains unexplained , we emphasize that the major conclusions of this study are not affected . The inference that mel-Lhr has hybrid lethal activity is independently shown by the rescue activity of the mel-Lhr deletion ( Table 3 ) . That result also demonstrates the asymmetric lethal activity of mel-Lhr and sim-Lhr , as does pyrosequencing of cDNA from hybrids ( Figure 6 ) . Likewise , the inference from transgenic assays that Lhr has undergone cis-by-trans compensatory evolution ( Figure 5C ) is fully consistent with the quantification of Lhr transcription by qRT-PCR in pure species ( Figure 5A ) coupled with the pyrosequencing result in hybrids . Our first hypothesis to explain the differential effects of mel-Lhr versus sim-Lhr on hybrid viability was that their respective proteins might have different localization patterns . Previous studies found the LHR localizes to heterochromatin in D . melanogaster , but did not determine whether it is a general heterochromatin factor or instead has a specific localization within heterochromatin [16] , [20] , [21] . The heterochromatic landscape is dramatically different in closely related species [33] , which raises the question of whether rapid evolution of Lhr orthologs reflects functional divergence necessitated by its association with fast-evolving heterochromatic sequences . We addressed this question by ( 1 ) mapping LHR localization within D . melanogaster pericentric heterochromatin , ( 2 ) comparing its localization in D . simulans , and ( 3 ) examining sim-LHR localization in a D . melanogaster background . Within both species LHR localized to heterochromatic foci but was not ubiquitous ( Figure 2A ) . For example , mel-LHR does not overlap with the AATAT or the 359 bp satellites , two major components of D . melanogaster pericentric heterochromatin [28] . In contrast , a portion of LHR consistently colocalized with the dodeca satellite in both species during interphase . The conservation of this colocalization pattern was particularly striking , given that dodeca repeats are found only on chromosome III in D . melanogaster but on both chromosomes II and III in D . simulans ( see Figure 3A and reference [30] ) . Thus , the chromosomal distribution of LHR between the two species is different . However , despite this divergence in the genomic location of dodeca , sim-LHR when expressed in D . melanogaster colocalized perfectly with mel-LHR ( Figure 3D ) , demonstrating full conservation of LHR's heterochromatic localization properties . For three reasons , it is highly unlikely that this conserved pattern is because LHR orthologs share a DNA-binding activity specific to the dodeca sequence . First , LHR contains no recognizable DNA-binding domain . Second , LHR localization to heterochromatin is dependent on HP1 binding [20] , [21] . Finally , LHR signal is neither restricted to dodeca nor perfectly overlapping with it ( Figure 2C and Figure 3C ) . Thus , it is unclear what features of DNA or chromatin are configuring this localization pattern of LHR . Neither the structure of the dodeca satellite nor LHR localization differed between pure species and hybrids , nor between lethal male and viable female hybrids ( Figure 4C and 4D ) . These results set Lhr apart from two other well-characterized heterochromatin-associated HI genes . OdsH is a fast-evolving homeodomain protein that mislocalizes to the heterochromatic Y-chromosome in hybrids [5] . Zhr is a species-specific satellite DNA that causes hybrid lethality by improperly segregating during mitosis [6] . Such defects have been interpreted as support for the hypothesis that internal conflict with selfish heterochromatic elements is driving HI [3] , [4] , [7] , [8] . We cannot rule out the possibility that there are defects in heterochromatin undetectable by our cytological analyses , or that Lhr may have other functions related to telomeric [16] or euchromatic [20] localization that have been affected by genetic conflicts . Nevertheless , the observations that heterochromatin appears normal in hybrids and that LHR localizes normally in both hybrids and when expressed in foreign species are not consistent with straightforward expectations of genetic conflict theories involving satellite DNAs [3] . Further work will be required to understand how Lhr causes lethal hybrids to have defects in cell proliferation and abnormally few larval cells entering mitosis [34] , [35] . Having found that LHR orthologs have not diverged in their heterochromatin localization , we tested whether the asymmetric effects of mutations in mel-Lhr versus sim-Lhr on hybrid lethality reflect a history of regulatory sequence divergence rather than protein sequence divergence . In particular , we hypothesized that asymmetric expression of Lhr orthologs in hybrids could explain the aforementioned genetic asymmetry . We tested this hypothesis by measuring allele-specific expression of Lhr orthologs in hybrid larvae . Our results strongly support this hypothesis: we found that approximately 66% of the total Lhr transcripts in lethal hybrid male larvae originates from the D . simulans allele ( Figure 6 ) . Thus a mutation in D . simulans Lhr creates hybrid sons with only 1/3rd the wild type level of Lhr transcript , while hybrid sons with a mutation in the D . melanogaster ortholog have twice that amount . We conclude that only a loss-of-function mutation in D . simulans Lhr produces viable hybrids because it removes a greater proportion of the total Lhr gene product . The divergence leading to asymmetric expression does not , however , reflect species-specific divergence in expression levels , because Lhr expression is not significantly different between D . melanogaster and D . simulans ( Figure 5A ) . Instead asymmetric Lhr expression in hybrids is likely caused by the uncoupling of species-specific compensatory changes between cis-regulatory sequences and trans-factors . Interestingly , studies comparing the evolution of transcriptional networks between species have found that this type of regulatory divergence is frequently associated with gene mis-expression in interspecific hybrids [14] , [31] . Furthermore , Takahasi et al . recently found evidence that stabilization of expression levels within a species involves widespread cis- and trans-compensatory mutations that can be detected as incompatibilities between heterospecific regulatory elements in interspecific hybrids [36] . The authors also suggest that signatures of adaptive evolution might result from the rapid accumulation of compensatory changes , and thus reflect the maintenance of an existing function rather than the evolution of a novel one . To our knowledge Lhr is the first example of cis-by-trans compensatory evolution occurring at an adaptively evolving hybrid incompatibility gene . An intriguing possibility is that the rapid evolution of the protein coding region reflects compensatory changes required to maintain an existing regulatory function of Lhr , rather than to alter its protein function . We emphasize that cis-by-trans regulatory divergence explains the asymmetric effect of Lhr mutations on hybrid viability , but is not the direct cause of Lhr having hybrid lethal activity . Instead our data argue that the hybrid male genotype has evolved an acute sensitivity to Lhr dosage . Our genetic assays further suggest that the activity of Lhr that causes hybrid lethality was likely present in the ancestral state because it is shared by both mel-Lhr and sim-Lhr . This hypothesis is further supported by the observation that GAL4-UAS driven expression of Lhr from D . yakuba , an outgroup species , also kills hybrid sons [21] . Unlike Lhr , however , transgenic assays with its D-M partner , Hmr , showed that only the D . melanogaster ortholog but not the D . simulans ortholog is capable of causing hybrid lethality [37] . That result is consistent with the HI effect of Hmr being derived during evolution in the D . melanogaster lineage . HI involving ancestral gene function is compatible with the D-M model , and was first considered by Muller [9] . One model he proposed involves incompatibility between an ancestral and a derived allele , with loss of a suppressor allele being required to ‘release’ the incompatibility . Here , this would require a suppressor to evolve first and become fixed in the D . melanogaster lineage , before the incompatibility-causing substitutions evolved in Hmr ( Figure 7A ) . In the hybrid background , the suppressor is diluted or inactivated , exposing the lethal interaction . Alternatively , incompatibility could result from a complex epistatic interaction involving three or more loci . In the simplest case , changes at a single D . simulans locus , Sen* , cause the hybrid background to become sensitive to the dosage of Lhr in the presence of Hmr from the D . melanogaster lineage ( Figure 7B ) . We favor the latter model because in the first model over-expression of sim-Lhr in D . melanogaster might be expected to at least partially overcome the suppressor and create the incompatible interaction . However , GAL4-UAS over-expression of sim-Lhr has no effect in a D . melanogaster pure species background [16] , [21] . Although we diagram only a single sensitizing locus , a polygenic model involving multiple genes is equally possible , because available data only establish that Hmr and Lhr are insufficient to cause hybrid lethality [16] . If many additional genes are involved , then the distinction between ancestral and derived alleles may become blurred . For example , interacting genes may co-evolve , and have high evolutionary rates that maintain interactions rather than alter molecular functions . Other examples of ancestral-derived incompatibilities have been discovered , such as the inter-allelic incompatibility at the S5 locus in rice , and the bi-locus incompatibility between the derived S . cerevisiae splicing factor MRS1 and the ancestral COX1 mRNA [11] , [12] . However , unlike the incompatible S5 alleles which differ by only two amino acid substitutions , and COX1 which retains the ancestral intron that causes HI , Lhr orthologs have diverged rapidly under selection [16] . It is therefore remarkable that despite extensive protein sequence divergence between the hybridizing species , hybrid lethality has evolved as sensitivity to the dosage of an ancestral function . The key mechanistic implication is that instead of searching for a process or function that differentiates Lhr orthologs as the source of hybrid lethality , we now know that the sensitivity to Lhr in hybrids is based on a function and/or interaction that is common to both orthologs . There are least 6 HI genes known that are rapidly diverging under selection [3] . With the exception of OdsH and Prdm9 , where the signature of selection is restricted to a single functional domain [38] , [39] , in the other HI genes peaks of nonsynonymous substitutions do not coincide with a specific functional domain within the protein coding sequence . In these cases , it has been assumed that changes derived under selection have led to functional divergence , in turn causing incompatibility . However , it remains to be tested if that is truly the case . We have assayed the hybrid lethal activity of both Lhr orthologs and found that despite extensive selection-driven divergence of the protein sequence , hybrid lethal activity is a shared ancestral function . We do not rule out the possibility that protein divergence makes some minor difference in hybrid lethal activity . However , our results suggest that the asymmetric effect of Lhr in causing hybrid lethality is explained by regulatory divergence . This finding demonstrates the need to consider regulatory divergence when interpreting interspecies experiments . Our results also highlight the complexity of the interspecific background and emphasize that hybrids are far from being the stoichiometric sum of two parental genomes . We suggest that while positive selection of protein-coding sequences remains a characteristic of HI genes , the phenotypic target of selection and its connection to HI are in some cases much less direct than expected .
All crosses were done at room temperature , or at 18°C where explicitly stated . At least 2 replicates were done for each cross . Each interspecific cross was initiated with ∼15–20 1-day-old D . melanogaster virgin females and ∼30–40 3–4-day-old sibling-species males . The nomenclature used for the transgenic lines and a complete description of the constructs used to generate them are included in Table S1 . Genetic markers , deficiencies , and balancer chromosomes are described on FlyBase [40] . We previously showed that the D . melanogaster stock y1 , w67c23; P{w+mC = lacW}l ( 2 ) k01209[k08901a]/CyO , used here in Table 3 and Table S3 , is deleted for Lhr ( see Fig . S4 in ref . [16] ) . To make a modified pCasper4 containing the attB site , we PCR amplified a 280 bp fragment using the pTA plasmid ( gift from Michele Calos ) as the template [22] . This PCR product , along with flanking SalI sites was cloned into the compatible XhoI site of pCasper4 to create the plasmid pCasper4\attB . In order to construct Lhr transgenes with Lhr under the control of its native regulatory sequences , we used a 4 . 8 kb genomic fragment that spans 2 . 7 kb upstream and 1 kb downstream of the Lhr CDS . This fragment includes the complete CDS of the adjacent gene Bap55 ( Figure 1 ) . To generate the p{sim-Lhr} construct we amplified this fragment from D . simulans w501 genomic DNA , using primer pairs 691/664 ( see Table S2 for primer sequences ) . This PCR product was gel purified and cloned into the pCR-BluntII TOPO vector ( Invitrogen ) , according to manufacturer's directions . The insert was sequenced completely and subcloned into pCasper4\attB using NotI and KpnI restriction enzymes . Note that this transgene contains more upstream DNA than the sim-Lhr transgene used by Prigent et . al . [41] , which was also functional . The p{mel-Lhr} construct was generated similarly , a 4 . 8 kb fragment was PCR amplified from wild type D . melanogaster ( strain Canton-S ) genomic DNA using primer pairs 597/598 , and TOPO cloned into pCR-BluntII vector . The forward primer contains a NotI site , allowing the insert to be released as a NotI fragment and cloned into the NotI site of pCasper4\attB . A clone was chosen with the same orientation as in p{sim-Lhr} . To construct p{sim-Lhr-HA} a triple-HA tag was added in-frame to the C-terminus of the Lhr CDS using a two-piece fusion PCR strategy . The two overlapping PCR products were amplified using p{sim-Lhr} as the template , with primer pairs 691/728 and 729/664 . These fragments were used as templates for the fusion PCR , and the gel-purified product was TOPO cloned into the pCRBluntII vector and sequenced completely . The insert was then subcloned into pCasper4\attB exactly as in p{sim-Lhr} . The construction of p{mel-Lhr-HA} followed the same logic , using the primer pairs 597/728 and 729/598 . To synthesize the p{mel-Lhr-YFP} construct a three-piece fusion PCR strategy was used , the first and last PCR products , containing upstream and downstream genomic regions respectively , were amplified using p{mel-Lhr} as the template , with primer pairs 597/730 and 733/598 . The central PCR product containing the YFP-tag was amplified from p{w+mC UAS-Lhr::Venus = UAS-Lhr::YFP} [16] , with primer pair 731/732 . The 3 overlapping PCR products were used as templates for the fusion PCR , and cloned into the pCR-BluntII vector and sequenced completely . The insert was subcloned into pCasper4\attB exactly as in p{mel-Lhr} . The p{ΔBap55 mel-Lhr-HA} construct is identical to p{mel-Lhr-HA} except that the Bap55 CDS is interrupted by the insertion of “TAA TGA C” , i . e . two stop codons and a frame shift mutation after the second methionine at position 6 . Two overlapping PCR products were amplified using p{mel-Lhr-HA} as template , with primer pairs 597/1171 and 1172/598 . The products were stitched together using fusion PCR and cloned into pCasper4\attB exactly as done in p{mel-Lhr} . φC31-mediated transformation of D . melanogaster was performed by Genetic Services Inc . The integration sites used were: i ) P{CaryP}attP2 and ii ) M{3xP3-RFP . attP}ZH-86Fb at cytological positions 68A4 and 86Fb , respectively [22] , [42] . P{CaryP}attP2 carries the body color marker yellow+ ( y+ ) . Site specificity of integration was tested using the PCR assays of ref . [43] . We also developed attP docking-site specific PCR assays , primer pairs1086/1087 for attP2 , and 949/1177 for ZH-86Fb . All D . melanogaster transformants were crossed into the strain w1118 . P-element mediated integration was used to transform the D . simulans w501 strain with P{sim-Lhr-HA} . Total RNA was isolated using the Trizol Reagent ( Invitrogen ) , followed by DNaseI ( Roche ) treatment and purification using RNeasy columns ( Qiagen ) . First strand cDNA was synthesized from 4 µg of total RNA using the SuperScriptIII first-strand synthesis system ( Invitrogen ) with the oligo ( dT ) 20 primer in a 20 µl reaction according to the manufacturer's instructions . Quantitative real time PCR ( qRT-PCR ) was performed on a Biorad MyiQ cycler with SYBR detection using the 2× supermix from Biorad . Relative concentrations of Lhr transcripts were calculated against rpl32 as the reference gene with rpl32 primers from reference [44] . The rpl32 gene sequence is 99% identical between the species . For Lhr primer pair 1147/1148 was developed to recognize conserved sequences and to amplify both D . melanogaster and D . simulans Lhr with equal and high efficiency . For each sample real-time PCR on test and reference genes was done in technical triplicates , and the standard curve method was used to estimate transcript abundance . For each genotype RNA was isolated from between 3 and 4 independent 6–10 hr-old embryo collections . For all genotypes except D . simulans P{sim-Lhr-HA} cDNA was synthesized twice from each RNA isolate . RNA was extracted from 3–5 day-old larvae collected from non-crowded vials . In hybrid crosses the D . melanogaster mothers carried the X-linked mutation y− allowing the sex of larvae to be determined by using mouth hook coloration ( daughters are y+ and sons y− ) . Total RNA and genomic DNA were simultaneously extracted from the same biological samples using the SV RNA system ( Promega ) . For the pure species control , RNA and genomic DNA were extracted once from a single biological collection , followed by a single round of cDNA synthesis . For the hybrid samples , RNA and genomic DNA were extracted from four independent biological samples . cDNA was synthesized twice from each independent RNA isolate . Pyrosequencing measurements were performed in triplicate on each cDNA and in duplicate on each genomic DNA . Whole cell extracts were obtained by grinding samples in ∼3 volumes of lysis buffer ( 50 mM Tris-HCl pH 7 . 5 , 10 mM EDTA , 1 . 25% TritonX-100 , 1× Roche protease inhibitor tablet ) . Extracts were cleared by centrifugation at 14 , 000 rpm for 10 min at 4°C . Total protein concentration of the cleared extracts was measured using Bradford assay ( Biorad ) and the samples were boiled in 0 . 5× volume of 4× SDS-Sample buffer . For most westerns 40 µg of total protein was loaded in each lane . Primary antibodies used were: rat anti-HA 3F10 ( Roche; 1∶1000 ) and mouse anti-tubulin T5168 ( Sigma; 1∶10 , 000 ) . HRP conjugated goat anti-rat and goat anti-mouse secondary antibodies ( Jackson; 1∶5 , 000 ) were used and detected with ECL Western blotting substrate ( Pierce ) . Embryo FISH and immuno-FISH were performed as in reference [6] and immunostaining of ovarioles was performed as in reference [45] with the following antibodies: Rat anti-HA 3F10 ( Roche; 1∶100 ) , mouse anti-HP1 C1A9 ( DSHB; 1∶100 ) , rabbit anti-histone H3 lysine 9 dimethylation ( Upstate 07-441; 1∶100 ) , rabbit anti-Cid ( a gift from S . Henikoff; 1∶1000 ) , rabbit anti-GFP ( Abcam ab6556; 1∶300 ) , mouse anti-Fibrillarin ( Cytoskeleton Inc . AFb01; 1∶400 ) and mouse anti-Hts 1B1 ( DSHB; 1∶4 ) . FISH probes are described in reference [6] . DNA was stained using TOPRO-3 iodide ( Molecular Probes ) or Vectashield containing DAPI ( Vector Laboratories ) . All imaging was conducted at the Cornell University Core Life Sciences Microscopy and Imaging Facility , using either a Leica DM IRB confocal microscope or an Olympus BX50 epifluorescent microscope , except for embryo images with a DAPI channel which were taken in the Plant Cell Imaging Center at the Boyce Thompson Institute , with a Leica TCS SP5 confocal microscope . Images were processed using Photoshop ( Adobe , version 7 . 0 ) . Contrast and brightness changes , when used , were applied globally across images . Quantification of dodeca signal in interphase larval brain tissue was done using ImageJ [46] . Watershed segmentation was applied on the DAPI-channel to generate a mask of nuclear territories . The Analyze Particle function was then used to identify individual nuclei as ROIs ( regions of interest ) and screened to exclude aberrant nuclear segmentations and non-nuclear entities . Each ROI was individually selected on the dodeca FISH channel of the same image and the FociPicker3D plug-in was used to identify regions of local maxima . We then calculated two measures to estimate the nuclear dispersion of dodeca satellite: ( 1 ) the total number of foci per nucleus and ( 2 ) the fraction of total nuclear area occupied by the dodeca signal .
|
When two different species mate , the hybrid progeny are often sterile or lethal . Such hybrid incompatibilities cause reproductive isolation between species and are an important mechanism for maintaining species as separate units . A gene called Lethal hybrid rescue ( Lhr ) is part of the cause of hybrid lethality between Drosophila species . Like many other hybrid incompatibility genes , Lhr protein sequences in the hybridizing species have diverged from one another by natural selection . This and other findings led to the hypotheses that the function of Lhr has changed between the two species , and this is what makes Lhr a hybrid lethality gene . Using a series of genetic , molecular , and cytological assays , we report evidence contrary to these hypotheses , that hybrid lethal activity is instead a function shared by both species and inherited from their common ancestor . This result is particularly surprising because the Lhr genes from the two species have different effects on hybrid viability . We discovered that these differential effects are caused by differences in expression levels of Lhr in hybrids rather than by changes in its protein-coding sequence . Our results demonstrate that , while natural selection may be important in evolving hybrid incompatibilities , how it does so in this case remains mysterious .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"gene",
"expression",
"genetics",
"population",
"genetics",
"biology",
"evolutionary",
"biology",
"evolutionary",
"processes",
"genetics",
"and",
"genomics"
] |
2012
|
Cis-by-Trans Regulatory Divergence Causes the Asymmetric Lethal Effects of an Ancestral Hybrid Incompatibility Gene
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Axis specification and segment determination in dipteran insects are an excellent model system for comparative analyses of gene network evolution . Antero-posterior polarity of the embryo is established through systems of maternal morphogen gradients . In Drosophila melanogaster , the anterior system acts through opposing gradients of Bicoid ( Bcd ) and Caudal ( Cad ) , while the posterior system involves Nanos ( Nos ) and Hunchback ( Hb ) protein . These systems act redundantly . Both Bcd and Hb need to be eliminated to cause a complete loss of polarity resulting in mirror-duplicated abdomens , so-called bicaudal phenotypes . In contrast , knock-down of bcd alone is sufficient to induce double abdomens in non-drosophilid cyclorrhaphan dipterans such as the hoverfly Episyrphus balteatus or the scuttle fly Megaselia abdita . We investigate conserved and divergent aspects of axis specification in the cyclorrhaphan lineage through a detailed study of the establishment and regulatory effect of maternal gradients in M . abdita . Our results show that the function of the anterior maternal system is highly conserved in this species , despite the loss of maternal cad expression . In contrast , hb does not activate gap genes in this species . The absence of this activatory role provides a precise genetic explanation for the loss of polarity upon bcd knock-down in M . abdita , and suggests a general scenario in which the posterior maternal system is increasingly replaced by the anterior one during the evolution of the cyclorrhaphan dipteran lineage .
Axis formation and segment determination in the vinegar fly Drosophila melanogaster are among the most thoroughly studied developmental processes today [1–5] . They offer an ideal starting point for the comparative study of development and the evolution of pattern-forming gene regulatory networks . Axis formation in flies is based on the graded distribution of morphogens established through a number of different maternal regulatory systems . In this study , we will be focusing on two of those in particular: the anterior and posterior systems [4] . In D . melanogaster , maternal protein gradients are either formed by localisation of mRNA at the anterior or posterior pole of the embryo , or by regionally specific translational repression of ubiquitous maternal transcripts [4 , 5] . The anterior system centres around the anterior determinant Bicoid ( Bcd ) . bcd mRNA is localised to the anterior pole of the embryo and an antero-posterior ( A–P ) protein gradient forms through diffusion from that source [6–8] . Bcd regulates the translation of uniformly distributed maternal mRNA of caudal ( cad ) [9 , 10] , which leads to a graded distribution of Cad protein with high concentration levels in the posterior [6 , 9 , 11–14] . In addition , Bcd acts as a concentration-dependent transcriptional regulator of zygotically expressed segmentation genes—such as gap or pair-rule genes [6 , 15–20] . In the case of the posterior maternal system , nanos ( nos ) mRNA is localised in the posterior pole region forming the source of the Nos protein gradient [21–23] . Unlike Bcd , Nos is not a transcriptional regulator: its only role is to translationally regulate ubiquitous maternal hunchback ( hb ) mRNA , leading to an anterior gradient of maternal Hb protein [24–26] . Evidence for the presence of localised determinants in dipterans goes back to early studies that utilised UV irradiation or RNAse treatment on embryos of chironomid midges ( Fig . 1 , Nematocera: Culicomorpha ) . These experiments produced mirror-duplicated abdomens , so-called bicaudal phenotypes , in which anterior structures are missing and replaced by duplicated organs usually found in the posterior [27–29] . The observed effects were attributed to the destruction of an anteriorly localised mRNA . However , the identity of the anterior determinant is still unknown in the majority of dipteran infraorders . The bcd gene arose through a duplication of the hox3 factor zerknüllt ( zen ) at the base of the cyclorrhapha ( Fig . 1 ) [30–33] . While its spatial distribution and role as transcriptional regulator are highly conserved among cyclorrhaphans [30–32 , 34–39] , it is not present in other flies . Interestingly , anterior UV irradiation of D . melanogaster embryos—or mutations to the bcd gene—never produce bicaudal phenotypes [40 , 41] . This hints at the presence of an additional non-localised factor . This factor is hb , which contributes to axis specification and A–P polarity in D . melanogaster . The ubiquitous distribution of its maternal mRNA may explain why it is resistant to localised UV irradiation . This interpretation is consistent with the fact that only embryos lacking both bcd and hb show bicaudal phenotypes in this species [24 , 42 , 43] . While the roles of bcd and hb in axis specification appear to be somewhat redundant in D . melanogaster , the situation is different in other cyclorrhaphan flies . The hoverfly Episyrphus balteatus , for example , has secondarily lost maternal hb expression ( Fig . 1 ) [38 , 44] . Consequently , knock-down of bcd by RNA interference ( RNAi ) leads to bicaudal phenotypes in this species [38] . In this paper , we study axis specification and maternal regulation of segmentation genes in another non-drosophilid cyclorrhaphan species , the scuttle fly Megaselia abdita ( Fig . 1 ) . M . abdita belongs to the most basally branching cyclorrhaphan lineage , the Phoridae [45 , 46] . While maternal cad expression has been lost in this species ( Fig . 1 ) [47] , hb retains its maternal contribution [31] . In light of this , it is surprising that knock-down of bcd does lead to bicaudal phenotypes . We investigate the regulatory causes of this phenomenon through a detailed study of the establishment and regulatory role of maternal gradients in M . abdtia . Our results reveal that the anterior and posterior systems are much less redundant compared to D . melanogaster . In particular , the difference between the two species can be explained by the loss of gap gene activation through maternal hb in M . abdita . Our results indicate that the role of the posterior system in axis specification has been lost in E . balteatus and M . abdita , while it still retains some of its ancestral functionality in D . melanogaster . In this general scenario , the anterior system is gradually replacing the posterior one during the evolution of the cyclorrhaphan flies .
The posterior maternal system is based on maternal gradients of Nos and Hb protein . In M . abdita , nos mRNA is localised posteriorly during early cleavage stages ( Fig . 2A ) becoming restricted to the pole cells by C10 ( Fig . 2B ) as in D . melanogaster . Previous reports have documented ubiquitous maternal hb mRNA [31] as well as conserved zygotic hb expression in an anterior and a posterior domain [48] . Antibody stainings reveal a distribution of Hb protein very similar to the zygotic mRNA pattern during the late blastoderm ( Fig . 2C , D ) . Furthermore , an anterior Hb protein gradient is present at cleavage and early blastoderm stages ( Fig . 2E ) . In order to investigate the role of the posterior system in the formation of this gradient , we treated M . abdita embryos with nos RNAi . These embryos show no effect on hb mRNA , while ectopic Hb protein is present in the posterior of the embryo ( effect detectable in 15 out of 16 RNAi-treated embryos; Fig . 2F ) . We conclude that the maternal Hb gradient is set up through translational repression by Nos in M . abdita as in D . melanogaster . The anterior maternal system of M . abdita is less conserved than the posterior one . Unlike D . melanogaster [9 , 10] and E . balteatus [44] , M . abdita lacks maternal cad transcripts [47] and consequently maternal Cad protein . Zygotic expression of cad , on the other hand , is qualitatively similar in D . melanogaster , E . balteatus , and M . abdita [9–12 , 14 , 37 , 42 , 47–49] . The only notable difference is that abdominal cad expression reaches further anterior in the latter two species compared to Drosophila [44 , 48] . In order to test how zygotic cad expression is regulated in M . abdita , we knocked down bcd , hb , and the head gap gene orthodenticle ( otd ) . In bcd RNAi-treated embryos , we observe a derepression of cad transcripts in the anterior ( 38/48; Fig . 3A–F ) . At cleavage cycle 13 ( C13 ) , cad expression appears uniform throughout the embryo ( Fig . 1D ) . During early C14A ( time class 2 , T2 ) , cad becomes expressed at higher levels in the anterior than in the posterior ( Fig . 3E ) . This effect is specifically confined to the region that is free of cad expression in wild-type embryos ( compare to Fig . 3B ) . At later stages , an ectopic domain resembling the posterior cad stripe forms in the anterior ( Fig . 3F ) . Similar ectopic cad stripes have been observed in the anterior of D . melanogaster bcd mutants [14] , cad reporter assays in D . melanogaster [47] , and E . balteatus embryos treated with bcd RNAi [38] . In hb knock-down embryos , we observe a small anterior expansion of cad expression in a minority of specimens ( 4/13; Fig . 3G–I; S1 File ) . Anterior derepression is much more subtle in this case than in bcd knock-downs ( Fig . 3D–F ) . This effect is similar to hb mutants of D . melanogaster [42] . Given the difference between bcd and hb knock-downs , we investigated potential additional contributions by otd , a factor known to act as a transcriptional repressor of cad in the jewel wasp Nasonia vitripennis [50] . otd expression is lost in bcd RNAi-treated embryos ( 12/16; S1 Fig ) . However , expression of cad appears normal in embryos treated with otd RNAi ( 25/25; Fig . 3J–L; S1 File ) . This indicates that otd is not involved in cad regulation , consistent with results from D . melanogaster [50] and E . balteatus [44] . In summary , anterior repression of cad in D . melanogaster is due mainly to a combination of translational repression by Bcd—acting on ubiquitous maternal cad mRNA—and transcriptional repression by hb—acting on the zygotic abdominal cad domain [14 , 42] . Transcriptional regulation of cad by Bcd plays a minor role , if any [47] . In contrast , repression of cad by Bcd occurs predominantly at the transcriptional rather than the translational level in M . abdita , similar to E . balteatus [38] . Our evidence does not conclusively establish whether this interaction is direct . However , we have shown that potential intermediate factors such as Otd and Hb are not involved in cad regulation , or show regulatory effects that are far too subtle to account for anterior repression in M . abdita . Previous work has shown that bcd mRNA is localised anteriorly in M . abdita [30–32 , 48] , and that it regulates hb transcription through the P2 promoter [31 , 37] . To assess the effect of bcd on gap gene regulation and embryo polarity in general , we characterised expression patterns of the trunk gap genes hb , giant ( gt ) , knirps ( kni ) , Krüppel ( Kr ) , and the pair-rule gene even-skipped ( eve ) in M . abdita embryos treated with bcd RNAi . We used single- and double-stained embryos to assess severity of the knock-down and spatial registration of expression patterns—between gap domains ( Fig . 4 ) as well as between Kr and the pair-rule gene eve ( Fig . 5 ) . We take advantage of the variable knock-down efficiency in RNAi experiments , which acts similar to an allelic series in classical genetics , to measure the sensitivity of specific gap domain boundaries towards decreasing levels of Bcd . In general , we find that all of these boundaries are highly sensitive to changes in Bcd concentration ( Figs . 4 and 5; see also S1 File ) . Wild-type embryos of M . abdita show a broad , bcd-dependent , anterior domain of zygotic hb expression , which gradually retracts from the pole ( Fig . 4B ) [31 , 37] . The posterior boundary of this domain shifts in anterior direction over time [48] , unlike its equivalent in D . melanogaster . In embryos treated with bcd RNAi , we observe an anterior cap of hb expression which never retracts from the pole ( 35/42; Fig . 4C–F; S1 File ) . It reduces in size with the severity of the bcd knock-down ( Fig . 4C–E ) indicating dependence on Bcd concentration . Similar anterior domains have been observed in embryos derived from bcd mutant mothers in D . melanogaster [51] and in bcd RNAi-treated embryos of E . balteatus [38] . In both of these cases , the anterior cap of hb expression has been interpreted as an anterior mirror duplication of the posterior hb domain [38 , 51] . The posterior hb domain is also conserved in M . abdita ( Fig . 4B ) [48] . It exhibits a slight anterior expansion in some embryos treated with bcd RNAi ( Fig . 4C–F; S1 File ) . In contrast , the posterior hb domain remains unaffected in D . melanogaster embryos lacking bcd [51] . Wild-type embryos of M . abdita have a broad anterior domain of gt , with a stationary posterior boundary , plus a posterior domain that shifts anteriorly over time ( Fig . 4H ) [48] . In embryos treated with bcd RNAi , we observe either loss ( 10/18 ) or strong reduction ( 8/18 ) of the anterior gt domain at early stages ( before T3 ) , while most embryos exhibit expression in a small anterior cap at later time points ( 14/15; Fig . 4I–L; S1 File ) . This anterior cap retracts from the pole around T8 ( 1/1 ) . As for hb , the extent of anterior gt expression decreases with increasing strength of the knock-down effect ( Fig . 4I–K ) . We interpret these observations as follows: delay and reduction of anterior gt expression are due to a lack of activation by Bcd , while the late anterior cap domain may be induced by ectopically expressed Cad ( see Fig . 3E , F ) . The effect of bcd knock-down on the posterior gt domain is more modest . This domain is always present in bcd RNAi embryos but exhibits some anterior displacement of both its boundaries ( Fig . 4I–L; S1 File ) . D . melanogaster embryos from bcd mutant mothers show a similar anterior displacement of the posterior gt domain , but no expression of gt in the anterior [52 , 53] . In contrast , E . balteatus embryos treated with bcd RNAi show broad derepression of gt , whose expression is only excluded from the anterior and posterior tip of the embryo [38] . In wild-type embryos of M . abdita , kni is expressed in an L-shaped anterior head domain , plus an abdominal domain that shifts to the anterior over time ( Fig . 4N ) [48] . In embryos treated with bcd RNAi , the head domain disappears , while the abdominal domain of kni expands and becomes displaced towards the anterior ( 38/38; Fig . 4O–R; S1 File ) . As in the case of hb and gt , the amount of expansion depends on the severity of the knock-down . This is qualitatively similar to embryos derived from bcd mutant mothers in D . melanogaster , but the effect is more severe in M . abdita and resembles kni expression in bcd mutants which are also heterozygous for maternal hb [24] . The effect of Bcd on kni is even more pronounced in E . balteatus where kni becomes drastically derepressed—showing ubiquitous expression in extreme cases—in embryos treated with bcd RNAi [38] . Wild-type M . abdita embryos have a central Kr domain , which is wider than its equivalent in D . melanogaster ( Fig . 4A , G , M ) [48] . As is the case for other gap domains , it shifts anteriorly and contracts over time . In embryos treated with bcd RNAi , the central domain of Kr expands towards the anterior ( 94/116; Fig . 4C–E , I–K , O–Q; Fig . 5B–F; S1 File ) . Yet again , the extent of the expansion is correlated with the strength of the knock-down . In the strongest cases , Kr expression is entirely missing ( 22/116; Fig . 4E , K , Q ) . A similar expansion of the central Kr domain has been observed in embryos from bcd mutant mothers in D . melanogaster [24] . However , these embryos never show a complete lack of Kr expression; it is only abolished by the additional removal of maternal hb [24 , 54] . Knock-down of bcd in E . balteatus , which lacks maternal hb expression altogether , leads to a complete absence of Kr expression in all RNAi-treated embryos [38] . In summary , our results suggest that Bcd is a concentration-dependent transcriptional regulator of gap genes in M . abdita . The observed effects of Bcd on gap gene expression are more severe than in D . melanogaster ( resembling gap gene patterns in mutants affecting both bcd and hb ) , but milder than in E . balteatus . M . abdita embryos treated with bcd RNAi can exhibit a bicaudal phenotype with complete axis polarity reversal and mirror-duplicated posterior structures in the anterior [31] . These severe knock-down phenotypes have their plane of symmetry at abdominal segment 5 ( A5 ) , and express four eve stripes—the two anterior ones probably being mirror-duplicated stripes 6 and 7 [31] . Such polarity reversal is never observed in embryos derived from bcd mutant mothers in D . melanogaster [41] , only in embryos that lack both bcd and maternal hb [24 , 43 , 54] . While the former still have a residual Kr domain , the latter lack Kr expression completely . Polarity reversal is also observed in E . balteatus embryos treated with bcd RNAi , which show no Kr expression at all [38] . We tested the relationship between the bicaudal phenotype and the presence or absence of Kr by co-staining bcd knock-down embryos for both eve and Kr ( Fig . 5 ) . The pair-rule gene eve is expressed in seven stripes in wild-type M . abdita embryos ( Fig . 5A ) [44 , 55 , 56] . Weak bcd knock-down phenotypes show a full complement of seven eve stripes that are displaced towards the anterior , with a correspondingly mild anterior displacement of Kr ( Fig . 5B; compare to Fig . 4C , I , O ) . Increasing severity of the knock-down results in the progressive loss of anterior eve stripes and more pronounced anterior displacement of the central Kr domain ( Fig . 5C–E; compare to Fig . 4D , J , P ) . In the strongest cases , we detect four eve stripes only ( as in [31] ) , and no or very little Kr expression ( Fig . 5F; compare to Fig . 4E , K , Q ) . This suggests that the absence of Kr expression is correlated with polarity reversal in bcd knock-down embryos . Why does lack of Bcd induce a bicaudal phenotype in M . abdita if it has a maternal Hb gradient very similar to D . melanogaster ? To answer this question , we compared the role of maternal Hb in gap gene regulation in both species . We have previously characterised the effect of Hb on Kr , kni , and gt in M . abdita [48] . Expression of kni and gt in embryos treated with hb RNAi is very similar to the corresponding patterns in hb mutants of D . melanogaster . In contrast , the effect of Hb on Kr differs between the two species: both show an anterior expansion of the central Kr domain ( 24 out of 53 RNAi-treated embryos in M . abdita ) , but only D . melanogaster embryos lacking maternal Hb exhibit a decrease in Kr expression levels [24 , 54] . We never observe such down-regulation in M . abdita embryos treated with hb RNAi ( S2 Fig ) [48] . Together with the absence of Kr expression in strong bcd knock-down phenotypes ( Fig . 4E , K , Q , Fig . 5E ) , this indicates that Hb is unable to activate Kr in M . abdita . In contrast , several authors have interpreted the reduced levels of Kr expression in hb mutants as evidence for activation of Kr by Hb in D . melanogaster [24 , 42] . However , it has never been shown whether this activating effect is direct or indirect—via repression of the repressor Kni by Hb ( see [5] , for a detailed discussion ) . To distinguish between these two possibilities , it is necessary to suppress kni in a background lacking maternal and zygotic hb . Direct activation is supported if levels of Kr expression remain low in embryos lacking both hb and kni , while an indirect effect via kni is supported if Kr levels are restored in these embryos compared to hb mutants alone . Unfortunately , it is not straightforward to create such double mutants , since both hb and kni are located on the same chromosome in the D . melanogaster genome , and germ line clones must be induced to eliminate both maternal and zygotic activities of hb . This may be the reason why this experiment has never been carried out . To overcome this challenge , we used RNAi-mediated double knock-down of hb and kni , and knock-down of hb in a kni mutant background . In D . melanogaster hb knock-down embryos , we observe anterior expansion and strong down-regulation of Kr ( 5/9; Fig . 6A , B; S2 File ) , as well as considerable anterior displacement of kni ( 3/5; S3 Fig; S2 File ) . These patterns correspond precisely to Kr and kni expression in embryos mutant for both maternal and zygotic hb [24] . Similarly , kni knock-down embryos show a Kr pattern which is identical to that observed in kni null mutants: we observe no posterior expansion of Kr ( Fig . 6E; S2 File ) , in accordance with a recent quantitative study [57] , but in disagreement with earlier qualitative reports [58–60] . These results indicate that our early embryonic RNAi knock-downs mimic strong null mutant phenotypes . In D . melanogaster hb/kni double knock-down embryos , we observe an anterior expansion of Kr , but no restoration of expression levels ( 12/18; Fig . 6C; S2 File ) . We confirm this result in kni mutant embryos treated with hb RNAi , which exhibit an identical anterior expansion of Kr and no restoration of expression levels ( 12/14; Fig . 6F; S2 File ) . Taken together , these results demonstrate that kni is not responsible for Kr down-regulation in D . melanogaster embryos lacking maternal and zygotic Hb . Therefore , activation of Kr by Hb is direct in this species . In contrast , this activatory role is absent in M . abdita where Hb acts as a repressor only , which leads to a lack of Kr expression and mirror symmetrical expression of the remaining gap genes in bcd knock-down embryos ( see also Conclusions ) . In D . melanogaster , maternal and zygotic Cad contribute to the activation of posterior gap domains [13 , 42] and—at least partially independently of gap gene regulation—activate posterior stripes of pair rule gene expression [11 , 50 , 61–64] . To investigate the exclusively zygotic contribution of Cad to gap and pair-rule gene expression in M . abdita , we characterised the expression patterns of hb , gt , Kr , kni , and eve ( Fig . 7A–L; S1 File ) as well as the cuticle phenotype ( Fig . 7O ) of embryos treated with cad RNAi . The cad knock-down phenotype of M . abita exhibits deletions of all segments posterior of T3 , and T3 itself is also disrupted in some embryos ( Fig . 7O ) . This phenotype is more similar to D . melanogaster than to E . balteatus . Embryos of the latter treated with cad RNAi exhibit a strongly reduced cephalopharyngeal skeleton , in addition to an almost complete loss of abdomen and thorax [44] . In contrast , D . melanogaster embryos mutant for both maternal and zygotic cad have an intact head and thorax and , although there is extensive loss of abdominal segments , often even retain some abdominal structures [11] . The fact that the M . abdita phenotype is stronger than that of D . melanogaster suggests that cad still plays an essential role in posterior segmentation in this species despite the loss of its maternal contribution . In light of this , it is surprising that knock-down of cad in M . abdita does not have a strong effect on gap gene expression . The only clearly detectable defect is a slightly reduced posterior hb domain ( 7/16; Fig . 7A–C ) . All other domains of hb , gt , Kr , and kni seem unaffected ( Fig . 7A–L; see also S1 File ) . Expression levels of Kr , kni , and gt appear similar to wild-type , although we cannot completely rule out a marginal decrease due to lack of sensitivity of our enzymatic detection method . This stands in contrast to D . melanogaster , where expression levels in the abdominal domain of kni and the posterior domain of gt are reduced in mutants lacking both zygotic and maternal cad ( while hb and Kr are expressed as in wild-type ) [13 , 42 , 50] . In E . balteatus cad knock-down embryos , anterior hb and Kr are normal , while the posterior kni , gt , and hb domains are absent or severely reduced [38 , 44] . To test if activation of gap genes by Cad is present but redundant with the complementary contribution by Bcd , we characterised the expression of kni and gt in embryos treated with RNAi against both bcd and cad ( Fig . 8; see also S1 File ) . We observe a large anterior displacement in the position of the abdominal kni domain ( 36/36 ) , as is seen in bcd RNAi-treated embryos . This was associated with a strong reduction in expression levels , particularly before T3 ( Fig . 8B; 14/15 ) , though after this stage levels of expression begin to resemble those in the wild-type . Embryos treated with bcd or cad RNAi alone , never show such reduction ( Fig . 4N–Q , Fig . 7J , K ) . Expression of gt is absent before T2 ( 6/10 ) , and only becomes detectable as a weak posterior domain at later stages ( Fig . 8D , F ) . In contrast to bcd RNAi-treated embryos ( Fig . 4H–L ) , we do not observe any anterior displacement of this domain ( see S1 File ) . In the anterior , we observe a cap of gt expression at the late blastoderm stage ( Fig . 8H ) , which closely resembles the anterior cap in embryos treated with RNAi against bcd alone ( Fig . 4I , J; S1 File ) . Our observations stand in contrast to those from D . melanogaster mutants lacking both maternal and zygotic cad and bcd . Such mutants show complete absence of both kni and gt expression [13] . Taken together , our results suggest that Cad contributes to early activation of both abdominal kni and posterior gt in M . abdita , in a way which is largely redundant with activation by Bcd . Surprisingly , late expression of both kni and gt in the posterior of the embryo seems to be at least partially independent of both Bcd and Cad activation . This suggests that a third , yet unknown , factor must contribute to gap gene activation in this species . Finally , we investigated the contribution of M . abdita cad to pair-rule expression . In embryos treated with cad RNAi , we observe a reduction in the number of eve stripes: 2 out of 12 embryos showed three , 5/12 four , and 5/12 five eve stripes ( Fig . 7M , N ) . Similarly , D . melanogaster embryos mutant for both maternal and zygotic cad have four eve stripes [50] . The most drastic effect of cad on pair-rule gene expression is observed in E . balteatus , where embryos treated with cad RNAi exhibit the loss of all but the first stripe of eve [44] . Taken together , our evidence demonstrates that zygotic cad still plays an important role in the determination of posterior segments of M . abdita . In contrast to D . melanogaster and E . balteatus , where eliminating cad has a clearly detectable effect on gap gene expression [13 , 42 , 44] , it is largely redundant for gap gene activation in M . abdita . This implies that cad performs its pattern-forming role mainly at the level of the pair-rule genes in this species . In this study , we have investigated the establishment of maternal gradients and their role in gap gene regulation in the scuttle fly M . abdita . We compare our results with the evidence from the vinegar fly D . melanogaster as well as the marmalade hoverfly E . balteatus ( Fig . 9 ) . On the one hand , we find that important aspects of maternal regulation are highly conserved among cyclorrhaphan flies . Bcd acts as a concentration-dependent transcriptional regulator , and Cad is involved in posterior patterning in all three species . On the other hand , we find a number of interesting differences between M . abdita , E . balteatus , and D . melanogaster . The first difference concerns the regulation of cad . Even though maternal cad expression can be detected in nematocerans , and basally branching non-cyclorrhaphan brachycerans ( Fig . 1 ) , maternal expression of cad has been lost in M . abdita [47] . Zygotic expression of cad is qualitatively similar between species , but reaches further anterior in M . abdita and E . balteatus than in D . melanogaster , creating a large overlap of cad and hb in these flies . Consistent with the absence of strong repression between these two genes , hb only weakly affects cad expression in M . abdita . In contrast , cad is completely de-repressed anteriorly in bcd knock-down embryos ( see Fig . 3 ) . There is some evidence from reporter assays that Bcd may regulate cad transcriptionally in D . melanogaster as well [47] . The situation is much less ambiguous in the case of E . balteatus , where cad is strongly up-regulated in the anterior upon bcd RNAi knock-down [38] . This similarity between M . abdita and E . balteatus suggests that transcriptional repression of cad by Bcd is much more prominent in these flies compared to D . melanogaster . Whether this interaction is direct in any of the three species remains to be shown . The second difference concerns the roles of bcd and hb in axis specification and gap gene patterning . Knock-down of bcd in M . abdita and E . balteatus leads to bicaudal phenotypes , as observed in bcd/hb double mutants but not in bcd mutants in D . melanogaster [24 , 41–43] . It is important to note that the situation in M . abdita is distinct from both D . melanogaster and E . balteatus ( Fig . 9 ) . More positional information is retained in bicaudal embryos , resulting in a more anterior ( A5 ) plane of symmetry , compared to A6 in the latter two species [24 , 31 , 38] . This difference is also reflected at the level of gap gene expression . Severe M . abdita knock-down phenotypes for bcd , which lack Kr expression , show a sequence of hb-gt-kni-gt-hb domains along the antero-posterior axis ( Fig . 9 ) ( this paper and [31] ) . D . melanogaster hb/bcd double mutants only have overlapping central gt and kni domains ( Fig . 9 ) [24 , 51 , 52 , 65] . E . balteatus knock-down embryos show an almost complete de-repression of gt and kni throughout the embryo ( Fig . 9 ) [38] . The anterior gradient of Bcd is an evolutionary innovation of the cyclorrhaphan lineage ( Fig . 1 ) [30–33] . The evidence suggests that it is completely sufficient for axis specification and embryo polarity in M . abdita and E . balteatus . In contrast , both maternal Bcd and Hb contribute synergistically to axis specification and gap gene patterning in D . melanogaster . While differences in the effect of Bcd between D . melanogaster and E . balteatus are easily explained by the absence of maternal hb in the latter [38] , it is less straightforward to pinpoint the cause for polarity reversal in bcd knock-down embryos of M . abdita . Our evidence suggests that this difference lies in the ability of maternal Hb to activate Kr in D . melanogaster , but not M . abdita ( see Fig . 4 , and [48] ) . Kr expression in the anterior of the embryo is correlated with the maintenance of polarity in D . melanogaster bcd mutants , and weak bcd knock-down phenotypes in M . abdita ( Figs . 4 and 5 ) . In D . melanogaster , maternal Hb is required for Kr expression in the absence of Bcd [24 , 42] , and we have shown here that this activating interaction is indeed direct and not caused by the indirect repression of the Kni repressor ( Fig . 6 ) . It remains unclear whether activation of Kr by maternal Hb has been gained in D . melanogaster or lost in M . abdita . However , there is some evidence that favours the latter scenario . Maternal hb expression is strongly conserved across arthropods far beyond the cyclorrhaphan lineage [66–74] , and hb is involved in axis patterning in many of the species where it has been studied [67 , 68 , 70–72 , 75 , 76] . Most interestingly in our context , Hb activates Kr in the flour beetle Tribolium castaneum [75] , the honeybee Apis mellifera [72] , the hemipteran milkweed bug Oncopeltus fasciatus [76] , and the cricket Gryllus bimaculatus [69] . The fact that this activating role of hb is conserved , and is only present in the one cyclorrhaphan species that retains some activity of maternal Hb in axis formation , seems to suggest that it may represent the ancestral state , and that activation of Kr by Hb has been lost in M . abdita and E . balteatus . We have previously demonstrated that the gap gene system of M . abdita compensates for the significant differences in the distribution of maternal factors compared to D . melanogaster , such that gap gene expression converges to equivalent patterns in both species by the onset of gastrulation [48] . Such compensatory evolution is called developmental system drift or phenogenetic drift [77–81] . At the level of the gap genes , this is achieved through quantitative changes in the strength of otherwise wholly conserved gap-gap interactions [48] . In contrast , our study shows that system drift at the level of maternal-to-gap interactions is mediated by both quantitative and qualitative differences in gene regulation . While inter-species differences in the effect of Bcd and Cad mainly consist in changes in activation strength , the activating role of Hb on Kr has changed in a qualitative way: while Hb activates Kr in D . melanogaster , this activating role is absent in both M . abdita and E . balteatus ( Fig . 9 ) . In summary , we observe a trend towards replacing the role of maternal Hb with activity of the anterior maternal system—Bcd and Cad—in non-drosophilid cyclorrhaphan lineages through the process of developmental system drift . This is reflected by the stronger phenotypes of bcd and cad knock-downs in both E . balteatus and M . abdita compared to D . melanogaster . In this view , axis formation and gap gene patterning in D . melanogaster retains more ancestral characteristics than these early-branching non-drosophilid cyclorrhaphans . Further corroboration of these insights will have to come from functional studies of axis specification and gap gene patterning in an appropriate outgroup ( Fig . 1 ) : non-cyclorrhaphan brachycerans or emerging nematoceran model systems such as the chironomid midge Chironomus riparius or the moth midge Clogmia albipunctata .
M . abdita fly culture , embryo collection and fixation were carried out as described in [82 , 83] . Enzymatic mRNA in situ hybridisation , image acquisition , and data processing were carried out as described in [84 , 85] . We use an embryonic staging scheme—homologous to the one already established for D . melanogaster [86]—which is described in detail in [56] . Embryo morphology and developmental timing are remarkably similar in both species . Embryos are classified into cleavages cycles C1–C14A according to nuclei number; C14A is further subdivided into eight time classes T1–8 based on nuclear and membrane morphology . Polyclonal antiserum was raised against M . abdita Hb protein expressed by means of a pET-DEST42 vector ( Invitrogen ) containing a full length cDNA insert . Purified Hb protein dissolved in 6M urea was used to raise rat antibodies by Primm Biotech ( primmbiotech . com ) using standard protocols . For antibody stains , wild-type blastoderm-stage embryos were collected after 4 hrs of egg laying and stained with a colorimetric protocol adapted from the in situ protocol published in [85] . In brief , fixed and dehydrated embryos were re-hydrated by washing 1x5min in PBT/methanol ( embryos were allowed to sink before the solution was removed ) , 2x in PBT , and 1x20 min in PBT . Embryos were washed 1x , then blocked with 2x30 min in western blocking reagent ( Roche ) in PBT followed by incubation with primary antibodies in blocking solution overnight . Unbound antibody was removed washing 3x in PBT followed by 4x15 min washes in PBT . Embryos were then re-blocked and incubated with secondary antibodies conjugated with alkaline phosphatase ( Roche ) at 1:3000 in blocking solution for 1 hr . Unbound antibody was removed as before . To prepare for staining , embryos were washed 2x5 min in AP buffer ( 100 mM NaCl , 50 mM MgCl , 100 mM Tris pH 9 . 5 , 0 . 1% tween-20 ) . Staining was carried out in the dark by the addition of AP buffer containing 0 . 1 mg/ml NBT and 0 . 05 mg/ml BCIP . Staining was stopped with 3x1 min followed by 3x10 min washes in PBT . Nuclei were counter-stained by a 10-min incubation in PBT containing 0 . 3 μM DAPI , followed by 3x washes and 3x10 min washes in PBT . Embryos were cleared through a series into 70% glycerol:PBS , of which 30 μl were mounted per slide . All washes were done on a nutator . We used RNAi knock-down protocols adapted from [31 , 37 , 87] . See [48] for further details . All expression boundaries plotted as graphs were extracted from NBT/BCIP stained embryos , except for Kr expression in M . abdita bcd RNAi-treated embryos , where boundaries were extracted from FastRed stains . Differences in expression levels in Fig . 6 and S2 Fig were assessed through simultaneous staining of wild-type and RNAi-treated embryos using NBT/BCIP to ensure a robust signal . Quantified expression data for M . abdita wild-type and RNAi knock-down embryos are available online through figshare ( http://dx . doi . org/10 . 6084/m9 . figshare . 1252195; [88] , and the SuperFly database ( http://superfly . crg . eu; [89] ) . Plots of gene expression boundaries from RNAi-treated or mutant embryos can be found in S1 File ( M . abdita ) and S2 File ( D . melanogaster ) . nos ( KP232978 ) was cloned from cDNA using data from our published early embryonic transcriptome ( http://diptex . crg . es; MAB_comp4961 ) [46] . All other genes were cloned as described in [48] . Embryo collection , fixation , RNAi treatment , and in situ hybridisation in D . melanogaster was carried out as for M . abdita [85 , 87] . D . melanogaster kni mutants correspond to deletion strain 3127 ( Bloomington Drosophila Stock Center ) with genotype Df ( 3L ) ri-79c/TM3 , Sb1 . Homozygous mutants were detected by an absence of FastRed kni staining during in situ hybridisation .
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The basic head-to-tail polarity of an animal is established very early in development . In dipteran insects ( flies , midges , and mosquitoes ) , polarity is established with the help of so-called morphogen gradients . Morphogens are regulatory proteins that are distributed as a concentration gradient , often involving diffusion from a localised source . This graded distribution then leads to the concentration-dependent activation of different target genes along the embryo’s axis . We examine this process , which differs to a surprising extent between dipteran species , in the scuttle fly Megaselia abdita , and compare our results to the model organism Drosophila melanogaster . In this way , we not only gain insights into how the mechanisms that establish polarity function differently in different species , but also how the system has evolved since these two flies shared a common ancestor . Specifically , we pin down the main difference between Drosophila and Megaselia in the altered function of the maternal Hunchback morphogen gradient , which activates target genes in the former , but not the latter species , where it has been completely replaced by the Bicoid morphogen during evolution .
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[
"Abstract",
"Introduction",
"Results",
"and",
"Discussion",
"Methods"
] |
[] |
2015
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Maternal Co-ordinate Gene Regulation and Axis Polarity in the Scuttle Fly Megaselia abdita
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During quiet resting behavior , involuntary movements are suppressed . Such movement control is attributed to cortico-basal ganglia loops , yet population dynamics within these loops during resting and their relation to involuntary movements are not well characterized . Here , we show by recording cortical and striatal ongoing population activity in awake rats during quiet resting that intrastriatal inhibition maintains a low-correlation striatal resting state in the presence of cortical neuronal avalanches . Involuntary movements arise from disturbed striatal resting activity through two different population dynamics . Nonselectively reducing intrastriatal γ-aminobutyric acid ( GABA ) receptor-A inhibition synchronizes striatal dynamics , leading to involuntary movements at low rate . In contrast , reducing striatal interneuron ( IN ) -mediated inhibition maintains decorrelation and induces intermittent involuntary movements at high rate . This latter scenario was highly effective in modulating cortical dynamics at a subsecond timescale . To distinguish intrastriatal processing from loop dynamics , cortex-striatum-midbrain cultures , which lack feedback to cortex , were used . Cortical avalanches in vitro were accompanied by low-correlated resting activity in the striatum and nonselective reduction in striatal inhibition synchronized striatal neurons similar to in vivo . Importantly , reduction of inhibition from striatal INs maintained low correlations in the striatum while reorganizing functional connectivities among striatal neurons . Our results demonstrate the importance of two major striatal microcircuits in distinctly regulating striatal and cortical resting state dynamics . These findings suggest that specific functional connectivities of the striatum that are maintained by local inhibition are important in movement control .
In the absence of specific sensory input or motor output , the brain nevertheless is highly active . In the cortex , such resting activity exhibits long-range spatial and temporal correlations [1–3] , with intermittent neuronal bursts described by power laws and defined as neuronal avalanches [4] . Neuronal avalanches have been identified in spontaneous activity in vitro in isolated cortex preparations [4–6] as well as in vivo in rodents [7–9] , nonhuman primates [10–13] and humans [2 , 14 , 15] , suggesting that , during resting , the cortex resides close to a critical state [16 , 17] at which numerous aspects of information processing are optimized [18] . The scale-free nature of cortical avalanches implies maximal variability in size and synchrony of neuronal events [19 , 20] . When monitored in motor cortical areas , avalanches unfold without the presence of apparent movements [10 , 13] , raising the question why even large avalanches during resting do not translate into sporadic or involuntary motor outputs . Here , we study this question in the context of forebrain loops that encompass cortex and basal ganglia and that are considered crucial for the initiation of voluntary as well as suppression of involuntary movements [21–25] . The main entry point from cortex to the basal ganglia is the striatum , which consists of more than 95% of γ-aminobutyric acid ( GABA ) -releasing spiny projection neurons ( SPNs ) and a small percentage of GABAergic interneurons ( INs ) , particularly parvalbumin-positive , fast-spiking INs [26 , 27] . Although changes in intrastriatal inhibition have long been identified to lie at the core of many movement disorders ( e . g . , [23 , 25] ) , the distinct roles of SPNs and INs remain unclear . SPNs form a sparse network of inhibitory recurrent connections with each other [28–30] , which theory and simulations suggest support competitive dynamics [31 , 32] that decorrelate networks [33] . In contrast , striatal fast-spiking INs provide a dense network of perisomatic inhibitory connections on SPNs , typically interpreted as cortical feedforward inhibition of SPNs [34–37] . Reducing striatal fast-spiking neuron activity induces involuntary movements in rodents [38] , in line with a reduced number of those neurons in humans suffering from Tourette syndrome [39 , 40] . However , how inhibition in striatal microcircuits relates to cortical avalanche dynamics at rest and suppresses involuntary movements is unclear . Here , we demonstrate in awake rats during quiet resting that cortical activity organizes as neuronal avalanches , whereas the striatum actively maintains a low-correlation state . Involuntary movements emerge from this dynamical profile through two distinct mechanisms . During nonselective reduction of inhibition in the striatum , movements emerged at low rate with little change in cortical avalanches but large increase in striatal synchrony . In contrast , when reducing inhibition from striatal INs only , movements emerged at high rate with corresponding large changes in cortical avalanches yet small change in relative striatal synchrony . In both scenarios , involuntary movements correlated with striatal and cortical bursts . To distinguish intrastriatal processing from loop dynamics , cortex-striatum-midbrain cultures , which lack feedback to cortex , were employed . Cortical avalanches in vitro were accompanied by low-correlated resting activity in the striatum and nonselective reduction in striatal inhibition synchronized striatal neurons , similar to in vivo . Importantly , reduction of inhibition from striatal INs maintained low correlations in the striatum while reorganizing functional connectivities among striatal neurons . Our findings demonstrate the importance of two major striatal microcircuits in distinctly regulating striatal and cortical resting state dynamics . We suggest that specific functional connectivities of the striatum that are maintained by local inhibition are important in movement control .
To study striatal resting activity during cortical avalanches and its change during involuntary movements , we exploited two dyskinesia models in rat . Involuntary movements in vivo have been induced either by nonselective reduction of intrastriatal inhibition using the GABAA-antagonist picrotoxin ( PTX ) [41–45] or selective reduction of striatal IN-mediated inhibition [38] using IEM-1460 [46 , 47] . Accordingly , we chronically implanted a cannula guide for local drug injection combined with a 16-channel microwire array ( MWA ) into the dorsal striatum ( Fig 1A and 1B; S1 Fig ) . Ongoing striatal local field potentials ( LFPs ) and multi-unit activity ( MUA ) were recorded before , during , and after local drug infusion in unrestrained awake rats not involved in any particular task . PTX ( 1 mM; n = 8 rats ) induced stereotypical movements at low rate ( 0 . 58 ± 0 . 06 s-1 ) in the contralateral front paw and/or neck region ( Fig 1C and 1D , left; S1 Movie ) . In contrast , IEM-1460 ( 5 mM ) induced more variable , intermittent movements at ~6 times higher rate ( 3 . 45 ± 0 . 44 s-1; S2 Movie; n = 7 rats; paired t test , t ( 10 ) = –7 . 9 , p < 0 . 001; PTX versus IEM ) in the contralateral front paw ( Fig 1C and 1D , left; S2 and S3 Figs ) . Involuntary movements correlated with positive LFP ( pLFP ) deflections in the striatum ( Fig 1C and 1D , right ) , which mirrored the significant increase in rate for IEM-1460- over PTX-induced movements ( Fig 1E and 1F , middle; rANOVA , F ( 2 , 12 ) = 51 . 84 , p < 0 . 001 ) . Importantly , the increased pLFP rate under IEM-1460 was not dose dependent , as a ten times lower concentration of IEM-1460 induced pLFPs at a similar rate as 5 mM ( S3 Fig; pLFP rate at 0 . 5 mM: 3 . 96 ± 0 . 76 s-1; 5 mM: 4 . 38 ± 0 . 53 s-1 ) . The change in pLFP rate was not paralleled by a corresponding change in cross-correlation ( CC ) between pLFPs , which was found to be relatively high at baseline and increased only weakly under PTX or IEM-1460 ( Fig 1F , right; 4 ms bin size; rANOVA , F ( 2 , 12 ) = 10 . 13 , p = 0 . 003; 1 . 16-fold increase ) . Because pLFPs could largely reflect synaptic input to the striatum , we additionally analyzed striatal MUA , which more directly reflects intrastriatal processing . Indeed , striatal MUA showed an increase in rate as well as an order of magnitude increase in spatial correlations for dyskinetic conditions . At baseline , spatial MUA correlations were low ( r = 0 . 02 ± 0 . 01; n = 5 rats , 20 ms bin size ) and increased 8-fold for IEM-1460 and even 11-fold for PTX ( Fig 1G , right; IEM-1460: r = 0 . 16 ± 0 . 05; n = 4 rats; PTX: r = 0 . 22 ± 0 . 03 , n = 4 rats; rANOVA , F ( 2 , 6 ) = 10 . 23 , p = 0 . 012; baseline versus PTX: p = 0 . 013 , baseline versus IEM-1460: p = 0 . 069 , Bonferroni-corrected ) . Similarly , the temporal correlation between MUA was also wider for PTX than IEM ( Fig 1G , right; PTX: 60 . 0 ± 6 . 63 ms; IEM-1460: 34 . 3 ± 9 . 5 ms; half-width in the CC function ) . The dissociation between pLFP- and MUA-based measures is supported by the weak correlation between striatal MUA and the LFP under baseline conditions ( Fig 1G , left; S4 Fig ) . Our findings so far suggest that striatal activity changes from a weakly correlated state during resting to a more correlated state under PTX- and IEM-1460-induced dyskinesia , with IN-mediated disinhibition causing involuntary movements at higher rate compared to nonselective striatal disinhibition . Changes in striatal MUA correlation could still reflect changes to striatal input rather than differences in local striatal processing . Specifically , the recruitment of cortico-basal ganglia loops during involuntary movements is supported by early reports on interrupting involuntary movements through cortical cooling in rodents and the emergence of synchronized cortical and striatal LFP deflections before movement onset [48] . Indeed , when recording ongoing LFP and MUA activity in cortex from up to 32 electrodes while repeating our local infusion of PTX or IEM-1460 into the striatum ( Fig 2A and 2B ) , the cortical LFP was found to change similar to the striatal LFP ( Fig 2C ) . In particular , the rate of negative LFP ( nLFP ) deflections in cortex was significantly higher during IEM-1460 than PTX ( Fig 2D , middle; see also Fig 1F ) . In contrast , spatial correlations in cortex were markedly increased for IEM-1460 but not for PTX compared to baseline ( Fig 2D , right; 4 ms bin size; rANOVA , F ( 2 , 6 ) = 12 . 0 , p = 0 . 008; baseline versus IEM-1460: p = 0 . 014; PTX versus IEM-1460: p = 0 . 019 , Bonferroni-corrected ) , which differed from what we found for the striatum ( see also Fig 1F , right ) . Given that cortical MUA strongly correlated with cortical nLFPs during all conditions ( S5 Fig ) , the CC for cortical MUA was also found to be the largest for IEM-1460 ( baseline: 0 . 02 ± 0 . 0 , n = 5; PTX: 0 . 07 ± 0 . 03 , n = 5; IEM-1460: 0 . 12 ± 0 . 05 , n = 2 ) . This increase in cortical synchronization for IEM-1460 compared to PTX suggests that synchronization of striatal activity under IEM-1460 might be largely explained by changes in cortical activity . To compare the striatal change in synchrony relative to that in cortex , we normalized the average spatial correlation in the striatum by that found in cortex . Indeed , PTX-induced movements revealed a strong increase in relative striatal synchrony , whereas IEM-1460–induced movements emerged from relatively decorrelated striatal conditions ( Fig 2E ) . This decorrelated striatal state under normal resting conditions and during IEM-1460–induced movements was confirmed whether using cortical LFP or cortical MUA , which strongly correlated with cortical LFP during all conditions ( S5 Fig ) . Taken together , these results establish two vastly different population scenarios for striatal induction of involuntary movements—a nonselective disinhibition , which induces movements at low rate in face of large relative striatal synchrony , and a selective reduction of IN-mediated inhibition , which induces movements at high rate with modest changes in relative striatal synchrony . We next demonstrated that the observed changes in striatal and cortical activity indeed arise from a resting state in cortex that organizes in the form of neuronal avalanches , and that , compared to PTX , IEM-1460–induced involuntary movements are more effective in introducing deviations from avalanche dynamics . Neuronal avalanches reflect spatiotemporal clusters of activity , which , besides pairwise correlations , also contain significant higher-order correlations that establish precise scale-invariant dynamics in space and time [12 , 13] . Cortical avalanches have been described in local populations of pyramidal neurons [7 , 9] and at the mesoscopic scale using nLFPs [4 , 8] as well as in humans using magnetoencephalography and functional magnetic resonance imaging [1 , 2 , 14 , 15] . In cortex , nLFPs are associated with increased firing in local synchronized neuronal populations [8 , 10 , 49] . We therefore used the nLFP ( S5 Fig ) to measure spatiotemporal activity clusters and quantify cortical dynamics . Fig 2F illustrates the definition of spatiotemporal avalanches using a given threshold for detection of nLFPs ( black dots ) and bin size , Δt , for concatenation of successive nLFPs into spatiotemporal clusters ( adjacent dark gray time bins ) . In line with previous reports on ongoing activity in vivo [8] , spatiotemporal clusters of cortical nLFPs during baseline distributed in size according to a power law with exponent α = –1 . 45 ± 0 . 08 and cut off at array size close to 32 , the defining characteristics of avalanche dynamics ( [50]; Fig 2G , baseline; threshold: −2 . 5 standard deviation ( SD ) , Δt = 4 ms; n = 5 rats; power law versus exponential: log-likelihood ratio ( LLR ) = 169 . 1 − 2738 . 1 , all p < 0 . 001 in favor of power law , see Materials and Methods ) . The power law barely changed during PTX ( Fig 2G , middle; same threshold as for baseline ) , whereas IEM-1460 increased the probability of large cortical clusters significantly compared to baseline and PTX ( Fig 2G , right ) , as measured by the Kolmogorov–Smirnov ( KS ) distance ( DKS ) , which here quantifies the deviation from a power law with exponent α = −1 . 5 ( Fig 2H , rANOVA , F ( 2 , 6 ) = 16 . 92 , p = 0 . 003; baseline versus IEM-1460: p = 0 . 004 , PTX versus IEM-1460: p = 0 . 019 , Bonferroni-corrected ) . In line with the observed increase in nLFP frequency , the rate of spatiotemporal clusters increased during both drug conditions and was highest under IEM-1460 ( baseline: 1 . 93 ± 0 . 75 s-1 , PTX: 7 . 27 ± 4 . 72 s-1 , IEM-1460: 12 . 3 ± 3 . 66 s-1 ) . Importantly , the average duration of spatiotemporal clusters was less than 10 ms under all conditions and thus approximately one order of magnitude shorter than the time between clusters , indicating that the increased probability of larger clusters under IEM-1460 did not result from coalescing clusters due to the chosen bin time , Δt . In summary , a striatal resting state , in which IN-mediated inhibition is reduced , is highly effective in entraining cortical dynamics away from neuronal avalanches . In order to dissociate changes in striatal dynamics due to intrastriatal processing versus cortico-basal ganglia-thalamic loops , we next studied striatal responses to cortical avalanches in organotypic cortex-striatum-midbrain cultures , which lack striatal feedback to cortex [51 , 52] . Cultures were grown on custom planar microelectrode arrays ( MEAs ) with two electrode fields , allowing for simultaneous recording from cortex ( 8×4 electrodes ) and striatum ( 6×5 electrodes ) ( Fig 3A ) . Recordings were performed between 13 to 28 days in vitro ( DIV ) when the striatum was innervated by corticostriatal projection neurons [53] and densely innervated by tyrosine-hydroxylase ( TH ) -positive fibers ( Fig 3B , left ) originating from substantia nigra neurons of the midbrain culture ( Fig 3B , right; 175 ± 33 TH-positive neurons , range: 37–385; n = 11 cultures; [51] ) . During that period , cortical and striatal population activities were highest ( Fig 3C ) [54] , showed stable activity profiles ( S6 Fig ) , and electrophysiological properties of striatal neurons had matured appropriately ( Figs 3E and 4B ) . This open-loop in vitro system confirmed our in vivo finding that cortical neuronal avalanches are accompanied by low-correlated periods in striatal activity . First , nLFP amplitudes , which correlate with MUA activity ( Fig 3D ) , as well as spatial correlations between nLFP or MUA activity were smaller in the striatum compared to cortex ( Fig 3F and 3G ) . Second , spatiotemporal nLFP clusters in cortex revealed avalanche signatures , i . e . , a power law in cluster size distribution with exponent α close to −1 . 5 ( Fig 3H , black , discrete: n = 8 , power law versus exponential: LLR = 1 , 564–27 , 090 , all p < 0 . 001 in favor of power law; α = −1 . 47 ± 0 . 02 , [4] ) . In contrast , striatal nLFP cluster size distributions , although consistent with a power law distribution ( Fig 3H , red; n = 8 , LLR = 123–3 , 225 , all p < 0 . 01; α = −3 . 04 ± 0 . 27 ) , showed a more negative exponent ( Fig 3I; paired t test , t ( 7 ) = −5 . 9 , p < 0 . 001 ) ; that is , the probability of large nLFP clusters was lower in striatum compared to cortex , in line with our finding of low spatial correlations in the striatum in vivo during resting activity . A similar relationship was observed when defining cluster size as the absolute sum of nLFP amplitudes ( Fig 3H , continuous ) . The difference between cortical and striatal cluster size distributions was of dynamical nature because it was significantly reduced by bath application of PTX ( 4 μM; DKS between cortical and striatal cluster size distributions , n = 8 , rANOVA , F ( 2 , 14 ) = 11 . 67 , p = 0 . 001 , S7 Fig ) . Our open-loop in vitro model confirms our in vivo finding that resting state activity in the form of cortical avalanches is associated with a low-correlation resting state in the striatum . To further study the differential effects of PTX and IEM-1460 on striatal dynamics observed in vivo , we first confirmed that IEM-1460 selectively suppressed firing in striatal INs in our in vitro system . Whole-cell current-clamp recordings ( Fig 4A ) of electrophysiologically identified INs ( Fig 4B and 4C ) showed that spontaneous action potential firing was significantly reduced in response to local application of 500 μM IEM-1460 ( Fig 4D , t test , t ( 12 ) = 5 . 9 , p < 0 . 001 ) . To confirm that IEM-1460 did not affect AMPA-mediated excitatory postsynaptic currents in SPNs , we recorded spontaneous up-state currents in putative SPNs in the presence of QX-314 ( 5 μM , intracellular ) and AP5 ( 100 μM , bath application ) to block active sodium currents and N-methyl-D-aspartate ( NMDA ) receptors , respectively . To minimize inhibitory postsynaptic currents , voltage-clamp recordings were performed at the estimated GABA reversal potential , Vh = −59 mV . As expected , local ejection of the selective AMPA receptor antagonist DNQX significantly reduced up-state currents in all putative SPNs ( Fig 4E , t test , t ( 12 ) = 4 . 6 , p < 0 . 001 ) . In contrast , local ejection of IEM-1460 did not significantly change the average peak amplitude of spontaneous compound postsynaptic currents in putative SPNs ( Fig 4F , t test , t ( 12 ) = 0 . 3 , p = 0 . 75 ) . Taken together , these results show that IEM-1460 selectively reduces spontaneous firing in striatal INs without altering AMPA-mediated inputs to SPNs , in line with a previous study [38] . Although the wire arrays used in vivo allowed us to study interactions between striatal neurons , they do not allow for a more detailed analysis of local clusters of neighboring striatal neurons in relation to cortical avalanche dynamics . We therefore recorded intracellular , spontaneous calcium transients in local populations of striatal neurons in these cultures during cortical avalanche activity ( 12–100 neurons , average: 45 . 7 ± 1 . 3 , n = 11 cultures ) . Neurons were loaded with the calcium indicator Oregon Green 488 BAPTA-1 ( OGB; Fig 5A ) , and background-corrected calcium transients of spontaneous activity were converted to changes in fluorescence over baseline fluorescence , ΔF/F ( see Materials and Methods ) . Simultaneous loose-patch recordings and calcium imaging ( Fig 5B ) demonstrated a linear relationship between the number of striatal spikes and corresponding peak ΔF/F amplitudes ( Fig 5C ) , as reported previously [56 , 57] . Under normal conditions , spontaneous striatal population activity was characterized by irregularly occurring , near-simultaneous episodes in which most neurons participated with largely varying peak amplitudes ( Fig 5D , baseline ) . Amplitude heterogeneity was seen both within episodes and within neurons . Within <30 s of local striatal PTX application ( 100 μM ) , peak amplitudes increased ( Fig 5F and 5G; n = 8 , rANOVA , F ( 2 , 14 ) = 36 . 74 , p < 0 . 001 ) and became highly similar across neurons for each episode ( Fig 5D , PTX ) . This effect was largely reversed after 5 min of drug washout ( Fig 5D–5G ) . Accordingly , the nonselective reduction of fast intrastriatal synaptic inhibition strongly increased the CC between striatal neurons ( Fig 5H , top; Fig 5I , rANOVA , F ( 2 , 14 ) = 57 . 23 , p < 0 . 001 ) in line with our in vivo finding . The unchanged rate of striatal activity episodes during PTX supports intrastriatal location of PTX action ( baseline: 0 . 15 ± 0 . 02 s−1 , PTX: 0 . 14 ± 0 . 02 s−1 , washout: 0 . 15 ± 0 . 02 s−1 , n = 8 , rANOVA , F ( 2 , 14 ) = 0 . 63 , p = 0 . 55; S8 Fig ) , given that cortical disinhibition would have induced prolonged activity periods at much lower rate in this system [58] . As further control , striatal changes to intrastriatal PTX application did not depend on midbrain inputs , further supporting exclusive intrastriatal PTX action ( S9 Fig ) . In contrast , when locally applying IEM-1460 to the striatum , average ΔF/F peak amplitudes in the local striatal population did not change ( Fig 5E and 5F bottom; Fig 5G , n = 11 , rANOVA , F ( 2 , 20 ) = 1 . 77 , p = 0 . 195 ) , and the average CC between neurons did not increase ( Fig 5H , bottom; Fig 5I , rANOVA , F ( 2 , 20 ) = 6 . 88 , p = 0 . 005; CCbaseline > CCIEM-1460 > CCwashout ) . These in vitro results demonstrate that , in the presence of cortical avalanches , striatal neurons show low CCs that depend on local GABAA-mediated inhibition and were not abolished after reduction of striatal IN-mediated inhibition . It confirms our initial results in vivo that nonselective intrastriatal disinhibition increases striatal synchrony , whereas a decorrelated striatal resting state is maintained after disruption of IN-mediated inhibition . The previous analysis provides a picture of average changes but , in general , does not capture individual alterations in ΔF/F amplitude of single neurons or pairwise correlations ( i . e . , CCs ) between neurons [59] . That is , different constellations of amplitudes or correlations could result in the same average . Indeed , the inability of IEM-1460 to change the average CC in the striatum was contrasted by its ability to significantly change individual CCs between neurons , that is , to reorganize the functional connectivity of the striatum while maintaining a low-correlation resting state . This is illustrated in more detail in Fig 6A , in which CC was quantified for consecutive segments of ΔF/F of each ~2-min duration . CC values from consecutive segments were plotted , and the coefficient of determination , RCC2 , was calculated using linear regression . A value of RCC2 close to one indicates little change of individual CCs between segments , whereas RCC2 towards zero indicates a strong change . The value of RCC2= 0 . 65 in Fig 6A provides a reference value for the expected change of CCs within a few minutes for a single culture . In this example , the comparison baseline versus IEM-1460 yielded a reduced value of RCC2= 0 . 19 ( Fig 6A , middle ) , demonstrating that individual CCs changed upon local application of IEM-1460 , as can be seen in the corresponding scatterplots . Fig 6B shows density plots of CCs for all consecutive segments and cultures ( PTX: n = 8; IEM-1460: n = 11 ) . The corresponding RCC2 values are summarized in Fig 6C , demonstrating that , similar to PTX , IEM-1460 led to a highly significant change in CCs ( rANOVA; PTX: F ( 4 , 28 ) = 16 . 21 , p < 0 . 001; IEM-1460: F ( 4 , 40 ) = 15 . 72 , p < 0 . 001 ) . The analysis of the change in individual ΔF/F peak amplitude averages revealed a similar picture . That is , although IEM-1460 did not lead to changes in the grand average ΔF/F ( Fig 5G ) , it changed the ΔF/F responses in individual striatal neurons significantly ( Fig 6D , rANOVA , PTX: F ( 4 , 28 ) = 21 . 79 , p < 0 . 001; IEM-1460: F ( 4 , 40 ) = 5 . 38 , p = 0 . 0015 ) . That changes in individual CCs under IEM-1460 as quantified by R2 were of similar magnitude compared to PTX ( Fig 6C and 6D ) further suggests that the lack of synchronization under IEM-1460 cannot be explained by insufficient blockade of IN inhibition . In summary , these results strongly suggest that , under normal conditions , the low-correlation state among striatal neurons requires local GABAA-mediated inhibition and that reduction of spontaneous IN firing changes the pairwise correlation state while maintaining a low average correlation ( Fig 6E ) .
In the current study , we used two pharmacological agents that affect striatal inhibition . The first , PTX , blocks GABAA receptors expressed in SPNs and INs . In the past , GABAA-antagonists have been extensively used to study the effect of striatal disinhibition on neuronal firing and motor behavior [41–45] . The second drug , IEM-1460 , influences striatal inhibition indirectly by blocking AMPA-mediated inputs to striatal inhibitory INs , thus leading to the disinhibition of SPNs by reducing IN-to-SPN activity . Although PTX also affected the latter connection ( i . e . , IN-to-SPN synaptic transmission ) , we observed in our experiments distinct activity and behavioral phenotypes . In vivo , both substances increased striatal synchrony and induced involuntary movements . However , local striatal PTX increased striatal synchrony even in the absence of a closed corticostriatal loop ( via globus pallidus/substantia nigra/thalamus ) , leading to highly synchronized striatal events in our in vivo and in vitro preparation . In contrast , local striatal IEM-1460 showed increased synchrony only in vivo , most likely due to increased synchronous input from cortex ( and thalamus ) . That is , local striatal IEM-1460 application deviated cortical activity away from avalanches into a highly synchronized state not observed under PTX . In addition , PTX and IEM-1460 showed neuronal bursts and involuntary movements at very different frequencies . That even low doses of IEM-1460 ( 0 . 5 mM versus 5 mM ) induced striatal bursts at high rate further suggests that , indeed , PTX and IEM-1460 influence cortico-basal ganglia loop activity in very different ways . Thus , although both substances induced involuntary movements , our findings suggest distinct mechanisms underlying the emergence of these movements . We also note that the relatively high frequency of involuntary movement components under IEM-1460 could suggest tremor-like spontaneous movements . However , due to their variability ( S2 Movie ) and intermittency ( S2 Fig ) , these movements do not resemble a continuous tremor . These mechanisms and behavioral phenotypes need to be further explored in future studies to improve the understanding of normal and pathological conditions in the basal ganglia . Our combined in vitro and in vivo findings identified a low-correlation resting state of the striatum that is maintained in the presence of cortical neuronal avalanches and depends on intrastriatal inhibition . Avalanche dynamics in cortex are characterized by long-range spatial and temporal correlations and are described by a power law in burst size distribution with exponent close to –1 . 5 [4] . The low-correlation striatal resting state dynamics qualitatively differed from cortical neuronal avalanche activity as measured by a more negative power-law exponent in vitro , indicating a spatially more confined activation of striatal neuronal populations compared to cortex . Our results further show a differential participation of two major striatal microcircuit components in maintaining and regulating ongoing striatal and cortical avalanche activity through cortico-basal ganglia-thalamic loops during resting . This finding relied on a precise quantification of the cortical resting state , that is , the measurement of cortical avalanches and the quantification of deviations from avalanche dynamics . Avalanche dynamics are robustly identified using the LFP at the mesoscopic level , although recent advances with single-cell resolution have been obtained for cortex [7] . We confirmed that cortical LFPs are related to local neuronal activity and that they organize as neuronal avalanches both in vivo and in vitro . The low rate of neuronal population bursts and corresponding involuntary movements induced by nonspecific reduction of intrastriatal inhibition is due to a refractoriness of cortex , with an absolute refractory period >300 ms [45] . Disfacilitation of inhibitory striatal INs using IEM-1460 , which left the feedback inhibition between SPNs intact , quickly abolished cortical neuronal avalanche dynamics and induced corticostriatal population bursts , often less than 300 ms apart [60] . This suggests that the striatum might require lateral inhibition between SPNs to efficiently entrain cortical activity at a subsecond time scale . This finding leads us to propose that it is not the change in average correlation or activity in striatal output but rather the specific functional connectivity of the striatum , supported by lateral SPN inhibition , that influences ongoing cortical avalanche dynamics , presumably via substantia nigra/globus pallidus and thalamus by promoting certain avalanche patterns in cortex . The striatum receives excitatory and inhibitory input from various sources that are part of intricate feedback loops , such as cortex [61 , 62] , thalamus [63] , globus pallidus [64] , and substantia nigra [65] . Using an open-loop in vitro system that exhibits the same resting state dynamics as in vivo , i . e . , cortical neuronal avalanches , allowed us to isolate those aspects of striatal dynamics and corresponding microcircuits that underlie the observed dynamical changes in vivo . We confirmed in vitro that nonselective reduction of intrastriatal inhibition using PTX synchronizes striatal action potential firing , in line with the striatal changes at the multi-unit and LFP levels in vivo . Importantly , we could demonstrate in vitro that avalanche-induced striatal firing remains decorrelated when reducing IN firing with IEM-1460 , in line with a low increase in relative striatal synchrony observed in vivo under those conditions ( Fig 2E ) . Taking advantage of monitoring local clusters of striatal neurons at high spatial resolution using intracellular calcium imaging , our in vitro approach allowed us to dissect the apparent discrepancy between the strong effect of IN manipulation in the absence of major changes in striatal synchrony . We could demonstrate in vitro that IEM-1460 strongly affected which neurons were ( co- ) active with little or no influence on the average CC between striatal neurons and average single neuron response amplitudes , respectively . We believe that this finding introduces the specific functional connectivity maintained dynamically by local striatal inhibition as a major factor in the regulation of activity in cortico-basal ganglia loops . We note that changes in single neuron activity under IEM-1460 , quantified by the coefficient of determination , were comparable to PTX ( Fig 6C and 6D ) . In addition , local IEM-1460 injections in vivo induced strong changes in striatal neuron activity at high as well as ten times lower concentrations , with corresponding strong changes in cortical avalanche dynamics . This suggests that even small reductions in IN inhibition induce strong dynamical changes in cortico-basal ganglia loops . In addition to the reduction of AMPA-mediated currents for receptors lacking the glutamate receptor 2 ( GluR2 ) subunit , IEM-1460 has been shown to reduce NMDA receptor currents at high concentrations , thereby possibly influencing SPN input . However , the effectiveness of blocking NMDA currents is two orders of magnitude smaller compared to the effect on AMPA currents [66] . Importantly , such NMDA receptor blockade would have been expected to decrease SPN neuron firing . However , our in vitro results showed no change in average response amplitude in SPNs , and a subset of SPNs even increased their responses to IEM-1460 application ( see also [38] ) . IEM-1460 has been shown to target AMPA receptors in cholinergic INs , and cholinergic neurons via inhibitory neuropeptide Y-positive neurogliaform neurons can influence SPN firing [67–69] . However , the absence of correlations between cholinergic INs and SPNs in nonhuman primate recordings [70] suggests that this pathway might not dominate striatal resting activity in vivo or in general during cortical neuronal avalanches . Accordingly , even after blockade of cholinergic transmission , selective reduction of IN firing using IEM-1460 can induce hyperkinesia [38] . Our pharmacological approach in vitro allowed for the manipulation of intrastriatal circuits in the absence of cortico-basal ganglia feedback loops and inhibitory inputs originating from globus pallidus or midbrain . However , our approach is not able to exclude other possible sources that might contribute to the observed decorrelation effect , such as inputs from diverse striatal IN classes or from a newly described corticostriatal inhibitory pathway [71] . While cell–specific manipulations can be achieved in striatal SPNs and INs using optogenetic techniques in transgenic mice [67 , 72] , changing SPN firing to precisely test whether inhibition between SPN maintains an intrastriatal low-correlation resting state currently faces two caveats . First , manipulation of SPN firing does not allow differentiating between intrastriatal ( i . e . , SPN-to-SPN ) and loop ( i . e . , striatopallidal/-nigral ) connectivity . Second , SPN firing was used as a readout of the network state to calculate response amplitudes and CCs . Dissecting the functional role of feedback inhibition between SPNs would require an opto- or pharmacogenetic approach that directly manipulates SPN-to-SPN synapses , for which techniques are currently being developed [73 , 74] . In our in vivo experiments , MUA did not allow us to differentiate striatal cell types involved , and even single-unit analysis in the striatum is limited in mapping waveforms to identifiable cell types [75 , 76] . Although our multi-unit and LFP analyses identified the differential effect of PTX and IEM-1460 on cortico-basal ganglia loops , we were unable to demonstrate the corresponding specific changes in striatal IN firing . Naïvely , one might assume that the net effect of IEM-1460 in vivo reduces IN firing; however , as shown by the dramatic changes in loop activity , loop reverberation does not permit interpretations of changes in IN activity based on direct drug action alone . Therefore , we extended our in vivo approach to in vitro , in which we recorded up to a hundred striatal neurons at single-cell resolution in an open-loop configuration to further quantify the network changes in the striatum . These in vitro results showed reduced IN firing during spontaneous avalanche dynamics under IEM-1460 as well as a decorrelated striatal state . The open-loop findings in vitro are in line with a reduced glutamatergic drive of INs and the limited role of INs in decorrelating striatal activity . The average low correlation in the striatum was maintained when manipulating INs , supporting the view that lateral ( i . e . , feedback ) inhibition between SPNs [28–30] might be responsible for the low-correlated striatal resting state , in line with prediction from theory and simulations [31 , 32] . That feedback inhibition can affect the population of striatal neurons was indeed shown in acute slices through antidromic electrical activation [77] ( with potential contributions from pallidal-striatal projections [64] ) . The increase in striatal synchrony upon nonselective reduction of intrastriatal inhibition using PTX is also in line with another study [78] , in which acute slices were activated by electrical cortical stimulation or NMDA receptor activation . Computational studies suggest that networks of inhibitory neurons with realistic connectivity regimes for lateral inhibition reduce the level of activity , increase the contrast of responses , i . e . , decorrelate striatal input [79 , 80] , and can cause transitioning between striatal cell assemblies [32 , 81] . Although lateral inhibition is not the only mechanism by which neuronal network activity can be decorrelated [82] , it can greatly enhance pattern decorrelation , as recently shown in a computational network model of neurons with threshold nonlinearities [33] . Thus , threshold nonlinearities [83] and corticostriatal connectivity [62] are likely to contribute to the observed decorrelation in striatal activities . The above models have in common that they require the collective inhibitory influence of cell groups . We propose that the large number of SPNs and wide distribution of measured synaptic strengths [35 , 36 , 84] provide the basis for lateral inhibition to affect striatal output and , consequently , future cortical activity [85] . Striatal inhibitory INs , on the other hand , might influence the functional connectivity of SPNs , thus promoting changes between different states of low correlation in the striatum that might encode specific motor programs . This idea is supported by a recent study [86] , which found that striatal fast-spiking INs increase their firing particularly during the choice execution period in a choice task . In the context of our study , we propose that a change in IN activity promotes switching between low-correlation states in the striatum , which entrain cortico-basal ganglia loops supported by lateral inhibition between striatal projection neurons . In summary , our results uncover different dynamical influences of two major intrinsic striatal microcircuits in regulating cortico-basal ganglia resting activity important for the suppression of involuntary movements in normal behavior .
Male Sprague-Dawley rats ( 5–8 wk old ) were used for behavioral assessment and/or chronic recording of LFPs and MUA in the cortex or striatum . To study the influence of the striatal inhibitory mechanisms , two different substances were microinjected into the dorsal striatum ( AP: 0 . 9–1 . 5 mm , ML: 2 . 2–2 . 6 mm , 4 . 2–5 . 5 mm from cortical surface ) through a chronic cannula ( 26 gauge , 1–2 mm projection; Plastics One , Roanoke , VA , United States ) : ( 1 ) PTX ( Sigma-Aldrich ) , a GABAA-receptor antagonist , and ( 2 ) IEM-1460 ( Tocris Bioscience ) , an antagonist of GluR2-lacking AMPA receptors selectively expressed in striatal INs [46 , 47 , 87] . Implantation of the cannula guide and the recording array was done under isoflurane anesthesia ( 1 . 5%–4% , 100% oxygen ) and presence of the analgesic ketoprofen ( 5 mg/kg , subcutaneous ) . All cannula guides , cannulas , and recording arrays were sterilized . During the implantation surgery , care was taken to avoid blood vessels . To prevent unnecessary brain injury , the dura was carefully ruptured and the cannula guide and/or recording array was slowly lowered at a rate of ~150–200 μm per min . Ketoprofen was given for up to 2 d post surgery , and animals were allowed to recover for 2–5 d before recordings . Spontaneous activity for LFP and MUA analyses ( see below ) was recorded up to 2 wk post surgery from superficial layers of the primary motor cortex and/or the somatosensory forelimb region ( AP: 0 . 5–2 . 2 mm , ML: 3 . 2–3 . 5 mm , and 0 . 2–1 . 1 mm from cortical surface ) using 8×4-MEAs ( 8 shanks with 4 electrodes each , plus additional reference electrode implanted along the anterior-posterior axis; 28–32 working electrodes; 200 μm inter-electrode spacing; 23 μm electrode diameter; Neuronexus , Ann Arbor , MI , US ) , or the dorsolateral striatum ( AP: 0 . 7–2 . 1 mm , ML: 3 . 2–3 . 5 mm , 3 . 2–3 . 5 mm from cortical surface ) using 16-channel MWAs ( 8×2 electrodes plus additional reference wire implanted along the anterior-posterior axis; 14–16 working electrodes; 150 μm inter-wire distance; 0 . 6–0 . 9 MΩ impedance; Microprobes , Gaithersburg , MD , US ) . The ground wire was connected to a scull screw located ~1 mm posterior to lambda . Data were recorded for at least 30–60 min at 30 kHz using a Cerebus data acquisition system ( Blackrock Microsystems ) . After baseline recordings , 0 . 8–1 . 5 μl sterile drug solution ( PTX , 1 mM; IEM-1460 , 5 mM ) was injected at a rate of 0 . 3 μl/min for 3–5 min . The internal cannula was left in place for 1–2 min post injection , after which recordings were performed . Animals were allowed to recover for 1 d before the next recording session . In n = 3 rats , we tested a ten times lower IEM-1460 concentration ( 0 . 5 mM ) and found that two out of three rats showed involuntary movements that were of similar nature as under higher IEM-1460 concentration , that is , intermittent movements at high rate in the contralateral front paw . Animal behavior was video-recorded with a Logitech c920 camera ( 10–30 frames per s , fps ) for behavior-only recordings , or simultaneously with LFP and MUA using a triggered CMOS camera ( 40 fps; Thorlabs ) . Involuntary movements were analyzed using custom scripts in Matlab ( Mathworks , MA , US ) . We defined a “movement” signal as 1 minus the frame-to-frame correlation for a region of interest ( i . e . , contralateral front paw or neck ) , and involuntary movements were extracted by applying a threshold of 2–3 SDs ( Fig 1C and 1D ) . Only periods during which animals were resting ( i . e . , no locomotion , cage exploration , or grooming ) were included in the video analysis . After recordings were finished , brains were dissected and the locations of cannula and electrode placements were confirmed in a subset of animals . In total , data from 17 rats were analyzed in this study . All but one rat were chronically implanted with a cannula guide for local drug infusion in the striatum . A subset of rats was implanted with an MWA in the striatum ( n = 8 rats ) or an MEA in the superficial layers of cortex ( n = 5 rats ) . A list of all rats and the recordings and observations is given in S1 Table . Coronal slices from rat cortex ( 350 μm thick , postnatal days 0–2; Sprague Dawley ) , striatum ( 500 μm thick ) , and midbrain ( substantia nigra pars compacta; 500 μm thick ) were cut on a vibratome ( VT1000 S , Leica , Wetzlar , Germany ) in ice-cold , sterile Gey’s balanced salt solution ( 0 . 4% D-glucose ) and cultured on poly-D-lysine coated and plasma-/thrombin-treated carriers to allow proper tissue adhesion [52] . After tissue adhesion to the carrier , standard culture medium was added ( 600 μl of 50% basal medium , 25% HBSS , 25% horse serum , 0 . 5% glucose , and 0 . 5% of 200 mM L-glutamine; Sigma-Aldrich ) and changed every 3–4 DIV . At 1 , 8 , and 20 DIV , 10 μl mitosis inhibitor ( 0 . 3 mM uridine , 0 . 3 mM ARA-C cytosine-β-D-arabinofuranoside , and 0 . 3 mM 5-fluoro-2′-deoxyuridine ) was added for 24 h to prevent excess glia cell formation . Cultures were incubated at 35 . 5 ± 0 . 5°C . Carriers were either coverslips for calcium imaging and patch recording experiments or 60-channel , planar MEAs for the recording of LFPs and MUA ( see below ) . Cultures on coverslips were incubated in a roller tube incubator at 0 . 6 rotations/min , and MEA cultures were incubated on a rocking storage tray at ±75° , 0 . 25 cycles/min ( ±25° , 0 . 6 cycles/min during the recording sessions except for developmental data , Fig 3C ) . Planar titanium nitride MEAs with 60 channels ( 59 recording electrodes plus one reference electrode; 200 μm inter-electrode distance , 30 μm electrode diameter ) were obtained from Multichannel Systems ( Reutlingen , Germany ) . For the developmental recordings , a standard 8×8 layout was used . For all other MEA recordings , a custom layout with two sub-arrays for cortex ( 8×4 , 31 electrodes ) and striatum ( 6×5 , 28 electrodes ) was used . Both sub-arrays were separated by 1 , 200 μm ( Fig 3A ) . Data were recorded at 25 kHz for MUA or 1 kHz for LFP using an MEA1060 amplifier and the MC Rack software ( Multichannel Systems ) . Spontaneous activity for the developmental data ( 20 min ) and the experiments with PTX bath application ( 4 μM , 60 min ) was recorded in culture medium under sterile conditions . Washout recordings were done 24–48 h after the culture medium was replaced with conditioned medium collected 3–4 d before the experiment . All recordings were performed at 35 ± 0 . 5°C after 2 wk in vitro if not stated otherwise . Calcium imaging was performed on coverslip cultures loaded with 50 μM OGB ( Life Technologies , NY , US ) dissolved in 10 μl pluronic F-127 ( 20% in DMSO; Life Technologies , NY , US ) and 790 μl freshly prepared artificial cerebrospinal fluid ( ACSF ) [88] . ACSF was bubbled with 95% O2 and 5% CO2 and contained ( in mM ) : 124 NaCl , 3 . 5 KCl , 10 D- ( + ) -glucose , 26 . 2 NaHCO3 , 0 . 3 NaH2PO4 , 1 . 2 CaCl2 , and 1 MgSO4 . Cultures were incubated for 60–90 min in a roller tube incubator and perfused with ACSF ( flow rate ~100 ml/h ) for 20–30 min before imaging . After baseline recordings ( 5 min ) , PTX ( 100 μM ) or IEM-1460 ( 500 μM ) was ejected locally in the striatum at a rate of 12 μl/min for 5 min using glass pipettes with a tip diameter of ~80–100 μm , while intracellular calcium was simultaneously imaged . Washout conditions were recorded 10–20 min after the drug application ended . Drug spillover to the cortex was prevented by using a two-compartment chamber in which a glass coverslip separated the bath between the cortical and striatal tissue . The glass coverslip was positioned ~300 μm above the tissue and sealed with agar pieces around the recording chamber . ACSF and drug flow was directed away from cortex . This approach was highly efficient in avoiding any drug spillover to cortex , as shown in S8 Fig . All recordings were performed between 13–28 DIV . Image sequences ( 12 bit , 2×2 binning , 320×240 pixels ) were acquired with a Peltier-cooled CCD camera ( Imago from TILL Photonics , Gräfelfing , Germany ) on an inverted microscope ( Olympus IX70 ) with a 20× water-immersion objective ( numerical aperture 0 . 7 ) . Excitation wavelength was set to 492 nm using a monochromator ( Polychrome II , TILL Photonics ) . Excitation , dichroic , and emission filters from Omega Optical ( Brattleboro , VT , US ) were XF1087 ( 445–495 nm band-pass ) , XF2077 ( reflection <500 nm ) , and XF3105 ( 508–583 nm band-pass ) , respectively . Image sequences of up to 320 s ( 7 , 000 frames ) were obtained at a rate of 21 . 7 frames/s ( cycle time 46 ms , exposure 28 ms ) using the TILLvisION 4 . 0 software ( TILL Photonics ) . Image sequences were converted into TIF file format after acquisition and analyzed in Matlab using custom scripts . Regions of interest ( ROIs ) were manually selected by identifying typical cell bodies ( Fig 5A ) , and background subtraction was performed by automatically subtracting the fluorescence signal from a dark background region within the area of two cell body diameters . All fluorescence values are expressed as relative change in fluorescence from baseline , denoted by ΔF/F , and measured as percentage . Formally , ΔF/F is defined as the percentage change in fluorescence over baseline , that is , ΔF/F = 100 ( FROI−F0 ) /F0 , where FROI and F0 denote the background-corrected fluorescence intensities in the ROI and the baseline , respectively . For the spike-triggered detection of fluorescence changes ( Fig 5B and 5C ) , the baseline was calculated as the average fluorescence 50 ms before the spike . For all other analyses , the baseline was calculated from a 30-s sliding window as the average of the 50% smallest values ( i . e . , excluding transients that correspond to neuronal activity ) . To allow for a more robust detection of calcium transients , successive increases in fluorescence ( ΔF/F > 0 ) were summated , and the threshold detection was performed on this summated signal . The percentage of spuriously detected ΔF/F-peaks was lower than 0 . 5% ( n = 8 neurons ) . For the estimation of the rate of up-state events in striatal neurons , we used the summed widefield ( bulk ) fluorescence signal within the field of imaging . Because up-states among striatal neurons are correlated [51 , 89] and driven by cortical input , this approach gave a good approximation of the input rate arriving from cortex . Patch pipettes were pulled from borosilicate glass using a P-97 micropipette puller ( Sutter Instrument , CA , US ) , and had a resistance of 5–10 MΩ . For all recordings , pipette resistance and capacitance were compensated for . Loose-patch and cell-attached recordings were performed in voltage-clamp mode using patch pipettes that were filled with regular ACSF . Whole-cell patch-clamp recordings were done in current-clamp mode with an intracellular solution containing ( in mM ) 132 K-gluconate , 6 KCl , 8 NaCl , 10 HEPES , 2 Mg-ATP , and 0 . 39 Na-GTP , or voltage-clamp mode with an intracellular solution containing ( in mM ) 132 CsMeSO3 , 1 CsCl , 10 HEPES , 2 Mg-ATP , 0 . 39 Na-GTP , and 5 QX-314 . The intracellular solution was kept on ice during the experiment . For the local application of PTX ( 100 μM ) or IEM-1460 ( 500 μM ) , a second patch pipette was placed in close vicinity ( <60 μm; Fig 4A ) of the patched soma and drugs were ejected at 50–55 mmHg . As expected , all recorded neurons ( 5/5 ) responded to ejection of DNQX ( 50 μM , Fig 4E ) . Significance was calculated by comparing 100 s baseline plus 100 s washout with 80 s of drug data using Student’s t test . A subset of cultures was used for post-hoc immunostaining of TH . Cultures were rinsed in phosphate buffered saline ( PBS ) , fixed in 4% paraformaldehyde for 40–60 min , and incubated for 2 h at room temperature in blocking solution ( 10% normal goat serum and 0 . 5% Triton X-100 in PBS ) . For all subsequent steps , a carrier solution consisting of 1% normal goat serum and 0 . 3% Triton X-100 in PBS was used . Cultures were incubated for ~12 h at 4°C in a TH-antibody solution ( 1:1000 , antimouse , Immunostar , WI , US ) , washed three times for 10 min each , incubated 1–2 h at room temperature in secondary antibody solution ( 1:1000 , Alexa 555 anti-mouse , Invitrogen , NY , US ) , and washed again three times for 10 min each at room temperature . Before the confocal imaging , cultures were rinsed in PBS and mounted on coverslips using a fluorescence-preserving mounting medium ( Vector Laboratories , CA , US ) . Confocal images were obtained with a Zeiss LSM 510 using a 63× oil immersion objective ( numerical aperture 1 . 4 , 0 . 6 μm optical thickness ) . For the cell counting of TH-positive neurons in the substantia nigra pars compacta , images were obtained with a high-speed scanning confocal microscope ( Leica TCS SP5 II , 10× objective ) with tile scan function . Cell counts were obtained from maximum z-stack projections ( 42 μm thick , 6 μm optical thickness ) . For TH-positive neurons that were organized in dense clusters , only well-distinguishable somata or somata with distinct ( dark ) nucleus were counted ( Fig 3B , right panel ) , thus likely underestimating the actual number of dopaminergic neurons . For in vitro recordings , MUA was detected by band-pass filtering at 300–4000 Hz and subsequent thresholding ( –5 SD of each trace ) . LFPs were band-pass filtered at 1–100 Hz for the developmental data , which contained dominant frequency components above 50 Hz , and 1–50 Hz for all other analyses . nLFP deflections were detected by finding the minimum value of the LFP signal that crossed a given threshold z ( measured in SDs ) . Previous studies showed that cortical nLFPs are associated with increased activity and synchrony in local firing [8 , 10 , 49] . That cortical nLFP are correlated with cortical multi-unit firing was confirmed in this study ( S5 Fig ) . We furthermore found this relationship in the striatum in vitro ( Fig 3D ) despite small amplitudes of striatal nLFPs . The SD was determined for each channel individually and estimated from 2–3 s of baseline activity ( z = –4 . 5 ) . The threshold value z was varied to confirm the robustness of the reported power-law exponents ( see also [10 , 50] ) . For the power spectral analysis of the developmental data , ±500 ms around nLFP threshold crossings were analyzed . The power spectrum was calculated by using the fast Fourier transform with a Hann window function . Averages for individual cultures were calculated across all channels and subsequently normalized ( integral over the entire frequency range normalized to unity ) before calculating the average over all cultures . All in vitro data were analyzed using the phase-neutral filter implementation filtfilt in Matlab and the Neuroshare library ( http://neuroshare . sourceforge . net ) for data import . For in vivo recordings , presumable multi-unit spikes were extracted from the high-pass filtered signal ( >250 Hz ) by applying a threshold at –6 times the root mean square of the signal using the Cerebus Central software ( Blackrock Microsystems ) . Because movements could cause artifacts in the high-pass filtered signal , thresholded waveforms were subsequently offline-sorted using the Offline Spike Sorter ( Plexon Inc . , Dallas , TX , US ) . Only electrodes were used for analysis for which MUA could be isolated from movement artifacts based on the typical biphasic waveform of multi-unit spikes ( Fig 1G , inset ) . Calculation of LFPs was performed as described for in vitro using the entire signal for each electrode for the estimation of SD ( z = –2 . 5 ) . For the avalanche analysis , z was varied to confirm the robustness of the estimated power-law exponents ( see above ) . In the striatum , MUA was associated with pLFP deflections ( S4 Fig; Fig 1G , left ) . We therefore extracted pLFP deflections ( z = 2 . 5–3 ) from in vivo striatal recordings . CCs were calculated from binned time series ( rasters ) of p/nLFPs , multi-unit spikes , or from continuous ΔF/F traces . Values for p/nLFP and MUA rasters were discrete and corresponded to the number of p/nLFP or spike events per bin , respectively . The raw CC between two time series , xt and yt , was defined as CC ( τ ) = E[ ( xt−μx ) ( yt+τ−μy ) ]σxσy where E[·] denotes the expected value operator , τ the time lag , and μ and σ denote mean and SD , respectively . CC for n/pLFP or MUA rasters were shuffle-corrected by subtracting CCshuffle ( average of ten repetitions ) from CC . The calculation of CC for calcium imaging data was performed on the ΔF/F traces . The average CC was reported as the average value across all electrode or neuronal pairs for time lag τ = 0 if not stated otherwise . In Fig 6 , individual CCs were analyzed . Rasters of nLFP events that crossed a predefined threshold , z , were created by binning the nLFP times with bin size Δt = 2–4 ms [4 , 11 , 50] . Previous studies showed that cortical nLFPs can be used as a readout of cortical synchronized population activity ( see also S5 Fig ) [8 , 10 , 49] to measure the propagation of spatiotemporal activity clusters . Due to the predominantly local propagation of activity [11] , compact 8×4 MEAs ( Fig 2A in vivo , Fig 3A in vitro ) were used as described above . From the recorded nLFP rasters , spatiotemporal clusters were extracted by finding cascades of nLFP events that were separated by at least one bin width ( Fig 2F ) . The size of a cluster was defined as the number of nLFPs within the cluster ( “discrete , ” Figs 2G and 3H , left ) . Alternatively , cluster sizes can be defined as the sum of absolute nLFP amplitudes ( “continuous , ” measured in μV; Fig 3H , right ) , resulting in a continuous distribution [4] . Neuronal avalanches are defined by a distribution of cluster sizes that follows a power law with exponent –1 . 5 [4] up to the number of electrodes in the recording array . Importantly , the power law is invariant to the number of electrodes used in the recording array up to the so-called “cut-off , ” which is given by the number of electrodes in the recording array . This property allows for a robust estimation of the power law exponent [11 , 50] , as described below . Power-law exponents were estimated using a maximum-likelihood approach [50 , 90]: α^=arg maxα l ( α|s ) where l ( α|s ) = ∑i=1nln pα ( si ) denotes the log-likelihood of observing the vector of given cluster sizes s = ( s1 , … , sn ) assuming a power law with exponent α , that is , pα ( s ) =sα∑x=1Nxα In cortical networks , the cut-off is typically at the system size , N , which is given by the number of electrodes in the cortical array ( see [4 , 11 , 50] ) . Thus , cortical event size distributions were fitted on the range from one to the number of electrodes in the cortical array . Correspondingly , exponents for striatal distributions are reported for a model that ranged from one to the number of electrodes in the striatal array . For the comparison of power law versus exponential distribution ( the expected distribution for independent neuronal activity ) , we used the LLR test [50 , 90]: LLR ( s ) =l ( α|s ) −l ( λ|s ) where l ( α|s ) denotes the log-likelihood for a power law with exponent α , and l ( λ|s ) the log-likelihood for an exponential distribution with parameter λ pλ ( s ) = e−λs∑x=1Ne−λx For the comparison of distributions to a power law with exponent –1 . 5 , or across different experimental conditions , we used the KS statistic [50] DKS=maxx|Pdata ( x ) −Pcompare ( x ) | where Pdata denotes the cumulative distribution of the data and Pcompare the cumulative distribution of the reference power-law model [i . e . , Pcompare ( x ) =∑s=1xpα ( s ) ] or data from a different experimental condition . For paired comparisons of two or more means , we used the paired Student’s t test and repeated-measures ANOVA with Bonferroni correction , respectively . Values are expressed as mean±standard error of the mean if not stated otherwise .
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Even in the absence of apparent motor output , the brain produces a rich repertoire of neuronal activity patterns known as “resting state” activity . In the outer layer of the cortex , resting state patterns emerge as neuronal avalanches , precisely scale-invariant spatiotemporal bursts that often engage large populations of neurons . Little is known about how the brain suppresses involuntary movements during such activity . Here , we show that the striatum , which is part of the cortex-basal ganglia loop , maintains a low-correlation state during resting activity . By using a combination of in vivo and in vitro approaches with pharmacological manipulations , we demonstrate that the precise configuration of this low-correlation state effectively contributes to involuntary movements . Nonselective blockade of intra-striatal inhibition abolished the low-correlation striatal resting state , barely affected cortical avalanches , and led to involuntary movements at low rate . In contrast , selectively reducing striatal interneuron inhibition strongly affected cortical avalanches and triggered involuntary movements at high rate while maintaining a relatively decorrelated striatal resting state . Our results demonstrate the importance of different inhibitory striatal circuits in the suppression of involuntary movements and suggest that the precise spatiotemporal configuration of striatal activity plays an active role in the regulation of cortical resting state activity and motor control .
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2016
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A Low-Correlation Resting State of the Striatum during Cortical Avalanches and Its Role in Movement Suppression
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Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits . While selection on quantitative traits is much more common , very few signals have been detected because of their polygenic nature . We searched for positive selection signals underlying coronary artery disease ( CAD ) in worldwide populations , using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk . We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk . These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness . We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome , with evidence that the relationship between CAD and lifetime reproductive success is antagonistic . This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans . Lastly , we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines , which further highlights the unique biological significance of candidate adaptive loci underlying CAD . Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD .
It is well established that modern human traits are a product of past evolutionary forces that have shaped heritable variation , but we are far from a good understanding of whether recent natural selection has acted on these and how this process has left its imprint across the genome . While many genome-wide multi-population scans have searched for signatures of positive selection [1–9] , these studies have detected relatively few adaptive candidates for common traits or diseases [10–12] . This suggests that classic ‘selective sweeps’ have been relatively rare in recent human history [13–16] and that current tools may not be appropriate for detecting and validating smaller shifts in adaptive variation , thus limiting our understanding of how natural selection acts on common diseases and traits [12] . Research in this area is also important as the combination of positive selection and significant GWAS signals at the same locus supports the existence of functional variation for disease . Here , we aimed to comprehensively identify selection signals for coronary artery disease ( CAD ) loci with methods designed to detect recent signals of positive selection . We compared selection signals in 12 worldwide populations ( HapMap3 ) with CAD genetic risk ( CARDIoGRAMplusC4D ) to help understand how selection acts on disease variation at the genetic level and prioritize genes most likely modified in relation to CAD . We examined the association between selection signals and gene expression to further test whether adaptive candidates are functionally important for CAD in terms of gene regulation . Lastly , we tested if CAD genes are associated with reproductive fitness to try to understand why this common disease persists in modern humans . Classic population genetics theory describes positive selection with the selective-sweep ( or hard-sweep ) model , in which a strongly advantageous mutation increases rapidly in frequency ( often to fixation ) resulting in reduced heterozygosity of nearby neutral polymorphisms due to genetic hitch-hiking [17 , 18] and a longer haplotype with higher frequency . Many methods have been developed to detect these signatures [19 , 20] , including traditional tests that detect differentiation in allele frequencies among populations ( i . e . Wright’s fixation index , Fst [21] ) and more recently developed within population tests for extended haplotype homozygosity ( i . e . integrated haplotype score , iHS [9] ) . Some of the most convincing examples of human adaptive evolution have been uncovered for traits influenced by single loci with large effects . For example , the lactase persistence ( LCT ) and Duffy-null ( DARC ) mutations affecting expression of key proteins in milk digestion [10] and malarial resistance [22] both display hallmarks of selective sweeps . Other loci that are not clearly monogenic but also show selective sweeps are associated with high-altitude tolerance ( EPAS1 [23] ) and skin pigmentation ( SLC24A5 and KITLG [24] ) . These studies show that rapid selective sweeps mainly occurred for new mutations with large effects on phenotypes . Motivated by these initial successes and the increasing availability of global population data genotyped on higher resolution arrays ( i . e . HapMap Project , 1000 Genomes Project ) , many recent genome-wide scans for candidate adaptive loci have recently been performed [11] . These suggest that selection may have operated on a variety of biological processes [10] in ways that differ among populations ( i . e . local adaptation ) [25] , been prevalent in genetic variation linked to metabolic processes [26] , and may often target intergenic regions and gene regulatory variants rather than protein-coding regions [12] . Often only the larger signals underlying monogenic ( or near-monogenic ) traits are typically considered for follow-up because of losses in the statistical power needed to quantify significance for smaller candidate adaptive signals after correcting for genome-wide multiple testing [20] . The adaptive status of many smaller candidate signals also remains uncertain due to inconsistencies in results between studies that utilized the same data [14] , and it is inherently more difficult to functionally validate candidate adaptive signals underlying complex polygenic traits compared to monogenic traits where only one or a few variants may have been under selection due to their influence on fitness [27 , 28] . In contrast to population genetics , research in quantitative genetics has shown that rapid adaptation can often occur on complex traits that are highly polygenic [29 , 30] . Under the ‘infinitesimal ( polygenic ) model’ , such traits are likely to respond quickly to changing selective pressures through smaller allele frequency shifts in many polymorphisms already present in the population [13 , 31] . Selection on such variation is generally less likely to push it towards fixation due to genetic correlations , thus producing smaller changes in surrounding heterozygosity over time that are harder to detect with most current population genetic methods [14 , 28 , 32] . Note that polygenic and classic sweep models are not mutually exclusive [13 , 33] , for alleles with small- and large-effects may both underlie a polygenic trait , which suggests that there will be some variation in the degree to which candidate alleles are modified after selective events . Because most common diseases are highly polygenic , we need to improve how we detect and classify the adaptive signatures underlying these traits . Recent studies investigating genomic selection on polygenic traits have taken two approaches . The first scans for significant selection signals for a subset of large effect SNPs that have previously been identified as genome-wide significant . For example , Ding and Kullo [34] found significant population differentiation ( Fst ) for 8 of 158 index SNPs underlying 36 cardiovascular disease phenotypes , and Raj et al . [35] observed elevated positive selection scores ( Fst , iHS ) for 37 of 416 index susceptibility SNPs underlying 10 inflammatory-diseases . The second approach tests if aggregated shifts in genome-wide significant allele frequencies are associated with phenotypic differences by population , latitudinal , or environmental gradients , which might indicate local adaptation . For example , Castro and Feldman [36] used 1300 index SNPs underlying many polygenic traits and found elevated adaptive signals ( Fst and iHS ) above background variation , and Turchin et al . [37] demonstrated moderately higher frequency of 139 height-increasing alleles in a Northern ( taller ) compared to Southern ( shorter ) European populations . These approaches all assume that genome-wide significant variants are the most probable selection targets , but many if not most such variants are tags for the causal variants , which may be at lower frequencies . This suggests an approach more sensitive for detecting subtle signals of polygenic selection is needed . We chose CAD as a model for examining polygenic selection signals for complex disease because it has ( and continues to ) impose considerable disease burden ( and possible selection pressure ) in humans [38] , its underlying genetic architecture has been extensively studied [39 , 40] and many of its risk factors ( cholesterol , blood pressure ) have been under recent natural selection [41] related to potential pleiotropic effects or tradeoffs with CAD . Antagonistic pleiotropy describes gene effects on multiple linked traits where selection on one may cause negative fitness effects ( i . e . reproduction , survival , and disease ) in the other due to their antagonistic genetic association [42] . Two common misconceptions are that CAD only occurs in older people and is a disease that has mainly afflicted modern humans . If either were true , selection might not have had either the opportunity or sufficient time to affect genetic variation associated with CAD . However , CAD begins to manifest during reproductive ages [43 , 44] and disease origins can be detected even in adolescence through degree of atherosclerosis [44 , 45] and myocardial infarction events [46] . CAD is also a product of many heritable risk factors ( cholesterol , weight , blood pressure ) whose variation is expressed during the reproductive period , when CAD could drive selection directly or indirectly . Furthermore , CAD has impacted human populations since at least the ancient Middle Kingdom period , with atherosclerosis detectable in Egyptian mummies [47] . This suggests that there has been enough time for evolutionary responses to CAD to have occurred , genomic signatures from which may be detectable in modern humans . By combining several 1000 Genomes-imputed datasets including HapMap3 and Finnish SNP data , a large genetic meta-analysis of CAD , HapMap3 gene expression data and lifetime fitness data from the Framingham Heart Study , we sought to address the reason ( s ) why CAD exists in humans by answering the following questions: 1 ) Has selection recently operated on CAD loci ? 2 ) How do selection signals underlying CAD loci vary among populations and are they enriched for gene regulatory effects ? 3 ) Do candidate adaptive signatures overlap directly with CAD genetic risk and is this useful for highlighting disease-linked selection signals ? 4 ) Do CAD-linked selection signals display functional effects and evidence of antagonistic pleiotropy , in that they are also linked to biological processes or traits influencing reproduction ?
We utilised the integrated Haplotype Score ( iHS ) to estimate positive selection for each SNP underlying CAD genes within each population separately . Because iHS is typically used to detect candidate adaptive SNPs where the selected alleles may not have reached fixation [9] , this estimate is well suited for detecting recent signals of selection as opposed to other measures [20] . iHS is also better suited for detecting selection acting on standing variation in polygenic traits [20 , 48] . Candidate selection signals were found for many of the 76 CAD genes within each of the 12 worldwide populations ( 11 HapMap3 populations and Finns; Fig 1A for top 40 based on their association with CAD log odds genetic risk , S1 Fig for all 76 ) . These were defined as ‘peaks’ of significantly elevated iHS scores across SNPs within each gene-population combination , with the apex approximating the likely positional target of positive selection . The results for the largest iHS score per gene and population ( Fig 1A ) show that most candidate selection signals were relatively small , but a few larger signals were detected . For example , out of the 912 gene-by-population combinations ( S1 Fig ) , 354 ( 38% ) contained weak-moderate candidate selection signals ( significant iHS between 2–3 ) , 84 ( 9% ) contained moderate-strong signals ( significant iHS between 3–4 ) , and 6 ( 0 . 6% ) had very strong signals ( significant iHS > 4 ) . The 6 largest candidate signals were found in the following gene-population combinations: BCAS3 in GIH ( iHS = 4 . 45 ) , MEX ( iHS = 4 . 23 ) and CEU ( iHS = 4 . 86 ) , PEMT in MKK ( iHS = 4 . 24 ) , ANKS1A in LWK ( iHS = 4 . 03 ) , and CXCL12 in JPT ( iHS = 4 . 10 ) , with all iHS p values <0 . 0001 . Six genes ( BCAS3 , SMG6 , PDGFD , KSR2 , SMAD3 , HDAC9 ) exhibited candidate selection signals consistently within all populations ( Fig 1A ) , and many genes also contained consistent selection signals for all populations within similar ancestral groups ( e . g . African , European etc , Fig 1A ) . Within CAD genes , multiple candidate selection signals were sometimes present ( particularly within larger genes , within separate linkage disequilibrium ( LD ) -blocks ) ; these varied between and sometimes within a population . For example , eleven ( of the twelve ) populations had candidate selection signals in PHACTR1 introns 4 , 7 or 11 ( Table 1; see also S2 Fig , comparing cross-population selection signals in PHACTR1 ) that were in separate LD-blocks ( see S2 Fig , LD plots ) . For eight populations , there was a broad and relatively weak set of candidate selection signals in intron 4 ( the largest PHACTR1 intron , ~300kb in length ) . Intron 4 is also the location of the published CAD index SNP ( rs12526453 ) for PHACTR1 . Other interesting candidate selection signals present in other CAD genes ( S1 Fig ) are not discussed here . Such patterns suggest that candidate selection signals are sometimes complex and often do not correspond to the SNPs with largest effect on disease . For each CAD gene within each population , we used a mixed effects linear model to regress SNP-based estimates of CAD log odds genetic risk ( ln ( OR ) , obtained from cardiogramplusc4d . org ) against iHS selection scores ( see Methods ) . We accounted for LD structure by including the first eigenvector from an LD matrix of correlations ( r2 ) between SNPs within each gene as a random effect . For a subset of CAD loci , we found significant quantitative associations between disease risk and selection signals and for each of these the direction of this association was often consistent between populations ( Fig 1B ) . Furthermore , when compared to a null distribution of genes selected randomly from the genome , the strength of the CAD log odds versus selection signal at most loci was statistically significant ( Fig 1C ) . Fig 1B shows 40 genes ranked based on those with the most consistent number of significant associations across the 12 populations , with those that showed fewer than four significant associations excluded . Positive and negative associations indicate elevated selection signals present in regions with higher or lower CAD log odds genetic risk , respectively . In the comparison across populations , directionality of significant selection-risk associations tended to be most consistent for populations within the same ancestral group ( Fig 1B ) . For example , in PHACTR1 , negative associations were present within all European populations ( CEU , TSI , FIN ) , and in NT5C2 strong positive associations were present in all East Asian populations ( CHB , CHD , JPT ) . Other negative associations that were consistent across all populations within an ancestry group included five genes in Europeans ( COG5 , ABO , ANKS1A , KSR2 , FLT1 ) and four genes ( LDLR , PEMT , KIAA1462 , PDGFD ) in East Asians . Additional consistent positive associations included four genes ( CNNM2 , TEX41 , NT5C2 , MIA3 ) in East Asians , three ( BCAS3 , RAI1 , KCNK5 ) in Europeans , and one ( PPAP2B ) in Africans . In comparison to other ancestral groups , African populations showed fewer significant selection-risk associations ( 27 . 9% of all 76-gene x 12-population combinations ) than Asians ( 31 . 5% ) or Europeans ( 32 . 8% ) . Some associations were consistent in all but one population ( e . g . CNNM2 , ABCG8 in Europeans; BCAS3 , KCNK5 in Asians; CNNM2 , TEX41 in Africans ) or unique to one population within an ancestral group ( e . g . TEX41 in FIN , COG5 in ASW ) . Below we focus on BCAS3 ( Fig 2 ) and PHACTR1 ( Fig 3 ) , two of the strongest selection-risk associations which , when adjusting for LD ( see Methods ) , displayed varying directionality between at least two populations . The genetic risks of CAD for variants in BCAS3 were positively correlated with an extremely large candidate adaptive signal in all European and two of three East Asian populations ( Fig 1B ) . For example in CEU , the largest iHS score was 4 . 85 and highly significant , and was elevated across most of BCAS3 ( Fig 2B CEU , spanning introns 1–18 and various LD-blocks , Fig 2C ) , which matched the approximate trends in CAD log odds giving rise to a highly significant positive correlation ( Fig 2A CEU ) . In contrast , in YRI there was no detectable selection signal close to the index SNP ( Fig 2B YRI ) , but weak-moderate signals were present towards the end of BCAS3 ( Fig 2B YRI , introns 18–19 , smaller LD-blocks Fig 2C ) , which also corresponded with lower CAD log odds ( Fig 2B , YRI ) thus giving rise to a significant negative correlation in Fig 2A . For all European populations , PHACTR1 ( see CEU example , Fig 3A ) selection peaks were typically located within regions of consistently lower CAD log odds ( Fig 3B ) . This contrasted with most other non-European populations where the highest candidate selection peaks were located within regions with elevated CAD log odds ( including the index CAD SNP rs12526453 , intron 4 ) . The largest selection peak in GIH ( Fig 3B ) overlapped the CAD log odds peak in PHACTR1 giving rise to the strong positive association seen in Fig 3A . The two distinctive selection peaks in both CEU and GIH were separated by different LD-blocks ( Fig 3C ) , suggesting that these may have developed independently within PHACTR1 . Interestingly , the negative association found for the MKK population was due to the location of the selection peaks more closely matching those of the European populations in intron 11 ( S2 Fig ) . To establish whether variants with evidence of selection in CAD genes also showed evidence of function , we performed an eQTL scan in 8 HapMap3 populations with matched LCL gene expression . We compared all SNPs in each CAD locus against expression for each focal gene within each population . We found that SNPs with significant integrated Haplotype Scores ( iHS ) were often also involved in gene regulation , compared to SNPs with non-significant selection scores ( Fig 4 , Kolmogorov-Smirnov test p value <0 . 001 ) . To assess which biological pathways were enriched for the highest-ranked genes according to Fig 1B , i . e . those where selection scores were most closely associated with CAD log odds genetic risk , we included the top 10 genes into the Enrichr analysis tool [49] and found that these genes are especially enriched in pathways related to metabolism , focal adhesion and transport of glucose and other sugars . More interestingly , we found connections to reproductive phenotypes in the associations of these genes with pathways , ontologies , cell types and transcription factors . For example , we found links to ovarian steroidogenesis and genes expressed in specific cell types and tissues including the ovary , endometrium and uterus ( see S1 Table for Enrichr outputs ) . To test whether CAD genes are directly associated with human lifetime reproductive success ( LRS or total number of children born across reproductive lifetimes ) , a prerequisite for responses to selection , we examined their association with LRS for women in the Framingham Heart Study ( FHS ) . Out of the 76 CAD genes ( representing 20 , 254 SNPs in total; a minimum , average and maximum of 18 , 266 and 2121 SNPs tested per gene , respectively ) , 51 genes contained SNPs that were significantly nominally associated with LRS ( p<0 . 05 ) , 30 genes contained SNPs associated at p<0 . 01 and 12 genes contained SNPs associated at p<0 . 001 , based on both nominal p values from FaST-LMM and permuted p values ( see S2 Table ) . For example , the most significant associations per gene included rs56152906 in PPAP2B ( p = 5 . 23E-06 , permuted p<0 . 0001 ) , rs7896502 in LIPA ( p = 0 . 0002 , permuted p = 0 . 0001 ) and rs2479409 in PCSK9 ( p = 0 . 0003 , permuted p = 0 . 0001 ) including a further 9 ( COL4A2 , FLT1 , HDAC9 , KSR2 , LPA , MIA3 , PDGFD , PLG , SMAD3 ) genes with significant LRS associations at permuted p<0 . 001 . The two previous studies that have investigated genome-wide SNP associations with LRS found associations with similar levels of evidence to our study . For example , the leading SNP in Kosova et al . [50] for completed family size was rs10966811 with p = 5 . 57E-06 . The top two leading SNPs in Aschebrook-Kilfoy et al . [51] for LRS were rs10009124 ( p = 7 . 65E-08 ) and rs1105228 ( p = 2 . 16E-06 ) . When we considered these associations using fastBAT that combines SNP associations within a gene ( accounting for LD-redundancy ) into single gene-level p value , similar results were obtained with 8 genes significantly associated with LRS ( e . g . PPAP2B , p = 0 . 0004 , permuted p = 0 . 001 , SMAD3 , p = 0 . 0061 , permuted p = 0 . 007 , MIA3 , p = 0 . 008 , see S2 Table ) . To test the null hypothesis that CAD variation is no more significantly associated with LRS than is variation in the rest of the genome , we used a permutation approach . We sampled 20 , 254 non-CAD related SNPs ( matched within MAF bins to the CAD SNPs ) randomly ( without replacement ) across the genome 100 times . The permuted p value was based on the number of times each random sample of 20 , 254 non-CAD SNPs shared significantly more associations with LRS than did the 20 , 254 CAD SNPs . The total sample of randomly selected SNPs ( n = 2 , 025 , 400 ) was also compared against the 20 , 254 CAD SNPs with a Kolmogorov-Smirnov ( K-S ) test . We found that CAD genetic variation was significantly ( p = 9 . 49E-08 and p = 1 . 90E-07 based on one- and two-sided K-S tests , respectively; permuted p<0 . 01 ) more enriched for LRS compared to the rest of the genome ( see S2 Table for other fitness-related traits ) , providing strong evidence in the FHS for shared fitness effects at CAD loci . This was also the case when we tested this at the gene-level using fastBAT results ( permuted p = 0 . 026 , S2 Table ) . To test whether effects between CAD loci and LRS were antagonistic , we cross-referenced the genome-wide significant index SNPs for CAD from Nikpay [40] with significant SNPs for LRS from the FaST-LMM analysis . Of the 56 CAD index SNPs in Nikpay [40] , 53 were genotyped or imputed in the FHS to a high confidence . In FHS , six of those SNPs ( 11 . 3% ) were significantly associated with LRS ( FaST-LMM p < 0 . 05 ) , with 5 out of those 6 antagonistic , i . e . the allele that increases LRS also increases risk for CAD ( see S3 Table ) . For example , in FLT1 , rs9319428-A significantly increases both LRS ( ß = 0 . 041 , p = 0 . 0143 ) and CAD risk ( ß = 0 . 039 , p = 7 . 13E-05 ) , and similarly , rs2048327-C in LPA significantly increases both LRS ( ß = 0 . 041 , p = 0 . 00894 ) and CAD risk ( ß = 0 . 057 , p = 2 . 46E-09 ) . This suggests that antagonistic effects occur in some loci , but the power to detect and define this for smaller effect variants on LRS is limited in the FHS ( e . g . see S3 Fig for power estimates ) . Compared to the CARDIoGRAMplusC4D study [40] where the 56 genome-wide significant CAD index SNPs were obtained using a meta-sample of ~184 , 000 individuals , SNP effects on LRS were based on 1 , 579 women from the FHS . Given that power to detect small effects ( i . e . |ß|<~0 . 3–0 . 4 or OR <~1 . 2–1 . 3 ) in these studies is poor when n is small ( i . e . ~1000 individuals [52] ) suggests that larger samples of women and men with completed reproduction are needed to test for antagonistic effects comprehensively to avoid false negatives . We further tested whether SNPs are associated with both LRS and CAD due to potential confounding effects rather than antagonistic pleiotropy , i . e . confounding effects would occur if CAD SNPs influence LRS , which in turn cause significant changes in CAD risk due to physiological , hormonal or social changes related to childbearing/rearing . We tested the association between CAD SNPs and CAD in FHS females , stratified by LRS ( see S3 Fig for full analysis ) . We found no significant effect of LRS modifying SNP effects on CAD ( see S3 Fig ) , which supports the antagonistic pleiotropy hypothesis , however we caution that larger , better powered studies may show some level of attenuation . Extending this investigation to understand why CAD genes are significantly enriched for LRS , i . e . what possible underlying reproductive processes are contributing , we performed an extensive systematic literature search on the 40 top-ranked genes in Fig 1 and a random set of 20 non-CAD genes . While gene set enrichment had been performed ( above ) suggesting some connections to reproductive phenotypes , such tools cannot capture the full range of possible effects on multiple fitness traits , some that are themselves rarely tested in other mammalian ( non-human ) species due to ethical limitations . We found evidence for direct links between CAD genes and fitness ( S4 and S5 Tables ) including genes associated with reproductive ( PPAP2B , [53] ) or twinning ( SMAD3 , [54] ) capacity and number of offspring produced ( e . g . KIAA1462 , [55] , SLC22A5 , [56] ) . PHACTR1 , LPL , SMAD3 , ABO and SLC22A5 may contribute to reproductive timing ( menarche , menopause ) in women [57–59] and animals [60] . Expression of PHACTR1 [61] , KCNK5 [62] , MRAS and ADAMST7 [63] appear to regulate lactation capacity . Some gene deficiencies also cause pregnancy loss ( e . g . LDLR , [64] , COL4A2 , [65] ) . Evidence for other pleiotropic links related to fitness included 25 genes that shared links with traits expressed during pregnancy ( S4 and S5 Tables ) , i . e . variation that can negatively influence the health and survival outcomes of both the fetus and mother [66] . For example , a variant of CDKN2B-AS1 significantly contributes to risk of fetal growth restriction [67] , both FLT1 [68] and LPL [69] are significantly differentially expressed in placental tissues from pregnancies with intrauterine growth restriction ( IUGR ) , and preeclampsia and LDLR-deficient mice had litters with significant IUGR [70] . A further 29 and 19 genes were linked to traits that can directly influence female and male fertility , respectively ( 13 influence both ) ( S4 and S5 Tables ) . For example , BCAS3 and PHACTR1 are highly expressed during human embryogenesis [71 , 72] , SWAP70 is intensely expressed at the site of implantation [73] , and PHACTR1 may play a role in receptivity to implantation [74] . For ABCG8 and KSR2 , animal models provide further support as gene expression deficiency can cause infertility in females ( ABCG8 , [75] ) and males ( KSR2 , [76] ) . Pleiotropic connections were also apparent in the classification of specific disorders or from studies investigating single-gene effects . For example , women with polycystic ovarian syndrome ( PCOS ) have higher rates of infertility due to ovulation failure and modified cardiovascular disease risk factors ( i . e . diabetes , obesity , hypertension [77] ) . While reduced fecundity associated with PCOS might suggest it would not fit the model of antagonistic pleiotropy , some hypothesize that it is an ancient disorder and may have provided a rearing advantage in ancestral food-limited environments [78] . A number of CAD genes in this study ( e . g . PHACTR1 , LPL , PDGFD , IL6R , CNNM2 ) are found differentially expressed in PCOS women [79–83] , suggesting possible links between perturbed embryogenesis and angiogenesis . In males , this can be demonstrated with a mutation in SLC22A5 that causes both cardiomyopathy and male infertility due to altered ability to break down lipids [84 , 85] . More generally , many recent studies link altered cholesterol homeostasis with fertility , which is most apparent in patients suffering from hyperlipidemia or metabolic syndrome [86 , 87] . For the random set of non-CAD genes that were approximately the same size as the top 20 genes in Fig 1 , we were only able to find three ( out of 20 ) with at least one potential link with fitness ( S6 Table ) using the same systematic literature search further demonstrating the relative abundance of CAD loci effects on fitness earlier in life .
One of our most interesting findings was the significant association between selection signals and CAD log odds genetic risk . This approach of integrating genome scans of positive selection with genome-wide genotype-phenotype data has been promoted previously as a tool to uncover biologically meaningful selection signals of recent human adaptation [12 , 88] but has rarely been applied . Among the exceptions , Jarvis et al . [91] found a cluster of selection and association signals coinciding on chromosome 3 that included genes DOCK3 and CISH , which are known to affect height in Europeans . For highly-ranked genes ( according to the number of significant associations present within the 12 populations ) in Fig 1B such as BCAS3 , CNNM2 , TEX41 , SMG6 and PHACTR1 , the consistent overlap between selection and genetic risk of CAD suggests that many of these may have been modified by CAD-linked selective pressures . If so , then two conditions must have been met . Firstly , CAD was present for long enough to be involved in these genetic alterations , an evolutionary process which generally takes thousands of years . Indeed , precursors of CAD ( i . e . atherosclerosis ) are detectable in very early civilizations [47] . Secondly , the effects of CAD were directly or indirectly expressed during the reproductive period and trait variation was under natural selection due to its effects on reproductive success . It is only possible for natural selection to directly act on CAD if those outcomes modify individual fitness relative to others in the same population . As outlined in the introduction , this is possible as CAD outcomes ( i . e . myocardial infarction ) do occur in young adults . However , early-life CAD outcomes are relatively rare , suggesting selection is more likely to operate indirectly on CAD via its risk factors ( or other pleiotropically linked traits , discussed below ) , which provides a more likely explanation for the close associations we found between positive selection and genetic risk . Supporting this , phenotypic selection has been found operating on CAD risk factors [41] , suggesting that these selection pressures are still present in modern humans . Some genes had large signals of selection but showed weak or no consistent overlap with CAD genetic risk . For example HDAC9 ( Histone Deacetylase 9 ) shows extensive evidence for having undergone recent selection within most populations , especially those of European or Mexican decent , but little or no overlap with CAD risk was evident in most populations . This suggests positive selection has operated on this gene due to its effects on a trait unrelated to CAD , which may not be surprising given HDAC9’s broad biological roles ( as a transcriptional regulator , cell-cycle progression ) and association with other very different phenotypes including ulcerative colitis [92] and psychiatric disorders [93] . This further demonstrates that this approach is useful for separating candidate selection signals important for the disease or phenotype of interest from those that aren’t . We found direct evidence in the Framingham Heart Study for shared fitness effects at CAD loci , which were specifically significantly enriched for their effects on female lifetime reproductive success relative to the rest of the genome . This novel finding shows a connection between direct fitness and later disease expressed through CAD loci . An extensive literature review supported this conclusion . All 40 CAD genes from Fig 1 shared at least one ( often more ) connection with fitness ( S4 and S5 Tables ) . Some appear to directly influence fitness ( offspring number , age at menarche , menopause , survival ) , while many were associated with early-life reproductive traits that are likely to correlate with fitness , including variation in ability to fertilize/conceive or fetal growth , development and survival . This suggests further pleiotropic links between CAD and early-life fitness-related traits . Directly testing for antagonistic effects between fitness and CAD , we found evidence at specific loci for the leading CAD index SNPs , where the allele that significantly increased LRS also significantly increased CAD . We further found no evidence that this link between CAD and LRS was due to confounding ( e . g . physiological , hormonal ) effects of LRS on CAD risk . While this is promising , the Framingham study is limited in its power to detect small fitness and CAD effects; better powered studies may yet be needed to definitively establish antagonistic effects at all loci . Fitness traits collected on genotyped populations are currently rare , but this is likely to change as more biobank-scale studies come online . To facilitate interpretation of selection occurring on early-life traits or CAD phenotypic risk factors that share pleiotropic connections and possible evolutionary tradeoffs with coronary artery disease , we present a conceptual figure ( Fig 5 ) . These pleiotropic effects are important because many of them affect traits expressed early in life , some extremely early in life . Any allele that increases reproductive performance enough early in life to more than compensate for a loss of associated fitness late in life will be selected [42] . Such a mechanism has been recently suggested to help explain the maintenance of polymorphic disease alleles in modern human populations [94] . While such tradeoffs have been previously tested for in humans using genotypes , LRS and lifespan ( e . g . [95] ) , there is not yet much evidence that such a mechanism influences human disease . A 2017 study by Rodríguez et al . [96] that used an indirect measure of fitness provides support for antagonistic pleiotropy acting on general early health and later life disease . Our study demonstrates that CAD genes are significantly and directly enriched for fitness with evidence that some of the leading CAD effect SNPs share an antagonistic relationship with fitness through significant positive effects on LRS . This provides support for such a mechanism influencing CAD and may help to explain our vulnerability to this disease . There are also some limitations to our approach . We utilized CAD genetic risk estimated from a meta-analysis based on predominantly European ( 77% ) with smaller contributions from south/east Asian ( 19% ) , Hispanic and African American ( ~4% ) ancestry [40] . Genetic risk variation for CAD might be different in the un-represented ( i . e . Mexican ) or less-represented ( i . e . African ) populations in this meta-analysis . If that were the case , it would reduce the usefulness of comparing selection and risk estimates in those populations . We also saw fewer significant selection-risk associations in the African populations ( Fig 1B ) , however this may be due to selection signals in the African populations being less obvious than those in East Asian and European populations , perhaps due to lesser linkage disequilibrium , as is consistent with results from previous studies [99] . Calculating disease risk and selection variation from populations within the same ancestral group might help resolve this , however it only represents a potential shortcoming for our cross-population analyses and not observations of antagonistic pleiotropy . In this study , we found evidence that natural selection has recently operated on CAD associated variation . By comparing positive selection variation with genetic risk variation at known loci underlying CAD , we were able to identify and prioritize genes that have been the most likely targets of selection related to this disease across diverse human populations . That selection signals and the direction of selection-risk relationships varied among some populations suggests that CAD-driven selection has operated differently in these populations and thus that these populations might respond differently to similar heart disease prevention strategies . The pleiotropic effects that genes associated with CAD have on traits associated with reproduction that are expressed early in life strongly suggests some of the evolutionary reasons for the existence of human vulnerability to CAD .
We started with the 56 lead index SNPs from Supplementary Table 5 in Nikpay et al . [40] corresponding to 56 CAD loci . When the index SNP was genic , all SNPs within that gene were extracted ( using NCBI’s dbSNP ) including directly adjacent intergenic SNPs ±5000bp from untranslated regions ( UTR ) in LD r2>0 . 7 ( with any respective genic SNP ) . When the index SNP was intergenic , that SNP and other directly adjacent SNPs ±5000bp and in LD>0 . 7 ( with the index SNP ) were extracted and combined with SNPs from the respective linked gene listed in Nikpay including SNPs ±5000bp from UTR regions in LD r2>0 . 7 with that gene . This resulted in SNP lists for 56 genes . To further explore other genes not directly connected with lead index SNPs , but that were within the CAD loci identified by the two most recent CARDIoGRAMplusC4D studies–including Deloukas et al . [39] ( i . e . 46 loci and 61 genes listed in their Tables 1–2 ) and Nikpay et al . [40] ( i . e . 10 loci and 15 genes listed in their Table 1 ) —we extracted SNPs within each of those genes ( plus SNPs ±5000bp from UTR regions in LD r2>0 . 7 with that gene ) . This resulted in SNP lists for a further 20 genes , bringing the total number of candidate genes for CAD to 76 . The per-SNP log odds ( ln ( OR ) ) values for the 76 genes were obtained for the additive model from Nikpay et al . [40] available at http://www . cardiogramplusc4d . org/downloads and used in the analysis described below . Genotype data ( 1 , 457 , 897 SNPs , 1 , 478 individuals ) were downloaded for 11 HapMap Phase 3 ( release 3 ) populations ( http://www . hapmap . org [100] ) including: Yoruba from Ibadan , Nigeria ( YRI ) , Maasai in Kinyawa , Kenya ( MKK ) , Luhya in Webuye , Kenya ( LWK ) , African ancestry in Southwest USA ( ASW ) , Utah residents with ancestry from northern and western Europe from the CEPH collection ( CEU ) , Tuscans in Italy ( TSI ) , Japanese from Tokyo ( JPT ) , Han Chinese from Beijing ( CHB ) , Chinese in Metropolitan Denver , Colorado ( CHD ) , Gujarati Indians in Houston , TX , USA ( GIH ) , and Mexican ancestry in Los Angeles , CA , USA ( MEX ) . We also included another HapMap3 population , the Finnish in Finland ( FIN ) sample ( ftp://ftp . fimm . fi/pub/FIN_HAPMAP3 [101] ) . These data had already been pre-filtered , i . e . SNPs were excluded that were monomorphic , call rate < 95% , MAF<0 . 01 , Hardy-Weinberg equilibrium p<1x10-6 . Before phasing and imputation , we performed a divergent ancestry check with flashpca [102] to check accuracy of population assignments , converted SNP data from build 36 to 37 with UCSC LiftOver ( https://genome . ucsc . edu/cgi-bin/hgLiftOver ) , checked strand alignment in Plink v1 . 9 [103] to ensure all genotypes were reported on the forward strand , and kept only autosomal SNPs . To speed up imputation , data were first pre-phased with Shapeit v2 [104] using the duoHMM option that combines pedigree information to improve phasing and default values for window size ( 2Mb ) , per-SNP conditioning sates ( 100 ) , effective population size ( n = 15000 ) and genetic maps from the 1000 Genomes Phase 3 b37 reference panel ( ftp . 1000genomes . ebi . ac . uk/vol1/ftp/release/20130502/ ) . Phased data were imputed in 5 Mb chunks across each chromosome with Impute v2 [105] . We then removed any multiallelic SNPs ( insertions , deletions etc ) from the imputed data and excluded SNPs with call rate < 95% , HWE p<1x10-6 and MAF<1% . The final dataset was then phased with Shapeit v2 , and alleles were converted to ancestral and derived states using python script . Ancestral allele states came from 1000 Genomes Project FASTA files and derived 6-primate ( human , gorilla , orangutan , chimp , macaque , marmoset ) Enredo-Pecan-Ortheus alignment [106] from the Ensembl Compara 59 database [107] . Integrated Haplotype Score ( iHS ) : Using the package rehh [108] in R version 3 . 1 . 3 , per SNP iHS scores were calculated within each population ( after excluding non-founders ) using methods described previously [9] . iHS could not be calculated for SNPs without an ancestral state , or whose population minor allele frequency is <5% , or for some SNPs that are close to chromosome ends or large regions without SNPs [9] . Rehh was also used to standardize ( mean 0 , variance 1 ) iHS values empirically to the distribution of available genome-wide SNPs with similar derived allele frequencies . For analyses in the main text , we considered a SNP to have a candidate selection signal if it had an absolute iHS score > 2 , a permuted p value <0 . 05 , and was within a ‘cluster’ of SNPs that also had elevated iHS scores . Although permuting p values is computationally more intensive , it provides more flexibility to detect smaller selection signals that may be incorrectly classified with the more stringent Bonferroni correction that is often applied to these estimates . For the analyses described below , even though we only used iHS estimates for the SNPs defined in the CAD genes ( and additional SNPs for permutation purposes ) , we calculated per-SNP iHS scores genome-wide ( rather than locally , i . e . within 1MB regions around focal SNPs ) , for this provides more accurate estimates because final adjustments are made relative to other genome-wide SNPs of similar sized derived allele frequency classes . P values for iHS scores were permuted based on comparison of nominal p values against 10000 randomly selected estimates from within the same derived allele frequency classes . We first tested the null hypothesis that there is no association between CAD genetic risk and signals of positive selection for CAD genes . For each gene within each population , we used a mixed effects linear model to regress SNP-based estimates of CAD log odds ( ln ( OR ) ) genetic risk against selection scores ( iHS ) resulting in 912 separate regressions . To account for LD structure ( and potential confounding of highly correlated SNPs ) within each gene , we also included the first eigenvector derived from an LD matrix of correlations ( r2 ) between SNPs within each gene as a random effect . We chose to model LD structure with mixed-effects models rather than LD-prune because for many genes , the SNP samples would have been too small for regression analyses . Also , it would be very difficult to properly capture both selection and the CAD log odds peaks needed to compare these variables . We did however investigate alternative models to validate our approach ( i . e . running the same models without the LD structure variable; using smaller multiple LD-pruned subsets of SNPs per gene ) with consistent results suggesting our approach was largely robust to LD effects and likelihood of false positive associations . We accounted for multiple testing by permuting p values for each regression based on comparing each nominal p value against 10000 permuted p values derived from shuffling iHS scores . Genes were then ranked based on the number of significant associations summed across the 12 populations . The 40 genes with at least four or more significant associations are shown in Fig 1B . To illustrate the positional architecture of these selection-risk associations , plots for selected highly-ranked genes are shown in Figs 1 and 2 . By demonstrating how CAD genetic risk peaks and valleys correspond to variation in the magnitude of selection scores ( iHS ) , this allowed visual assessment of potential modifications made to the phenotype-genotype map by selective pressures imposed directly or indirectly by CAD . It also helped us localize selection peaks within genes and compare them between populations . Similar peaks suggested similar selection and different peaks suggested local adaptation . This way of presenting the results also allowed us to detect the smaller adaptive shifts in allele frequencies typically expected to underlie selection on polygenic traits . We then tested a second null hypothesis: that the selection-risk associations using the CAD genes are not unique compared to non-CAD associated loci . For each of the 76 CAD genes , we randomly ( without replacement ) chose 100 genes of similar length across the genome and performed the same mixed effects regression procedure described above for each gene by population combination using both CAD log odds values from Nikpay et al . [40] , iHS scores estimated from the SNP data , and the first LD eigenvector from SNPs within a gene . Permuted p values were derived by comparing the nominal p value for each CAD gene against the 100 null distribution p values from the non-CAD associated genes . Results are shown in Fig 1C . To examine whether candidate adaptive signals within each gene corresponded to a gene’s regulatory variation , we regressed SNPs within focal genes and gender against that gene’s probe expression levels , which had previously been quantified in lymphoblastoid cell lines from circulating peripheral blood using Illumina’s Human-6 v2 Expression BeadChip for eight of the 12 populations [109] . Given gene expression in peripheral blood is known to be an important marker for cardiovascular disease , we therefore might expect this cell type a good candidate to search for association between selection signals and regulatory variants important for these genes . The raw gene microarray expression data had previously been normalized on a log2 scale using quantile normalization for replicates of a single individual then median normalization for each population [109] . P values for each SNP-probe association were permuted using 10000 permutations by randomly shuffling gene probes expression . P values were then extracted for the most significant iHS score for each gene-population combination and compared to the same number of p values randomly drawn from different LD blocks underlying SNPs with non-significant iHS scores across each gene-population combination . A Kolmogorov-Smirnov test was used to compare the distribution of p values from each . To examine what biological processes were associated with the top ranked genes from Fig 1 , we uploaded the top 10 genes into Enrichr ( http://amp . pharm . mssm . edu/Enrichr/ ) to define associated pathways ( i . e . KEGG 2016 , kegg . jp/kegg ) , ontologies ( MGI Mammalian phenotypes , informatics . jax . org ) , cell types ( Cancer cell line Encyclopedia , broadinstitute . org/ccle ) and transcription factors ( ChEA 2015 , amp . pharm . mssm . edu/lib/chea . jsp ) . We tested whether CAD SNPs were directly associated with human fitness . For a trait to evolve , this is one of the main prerequisites , but it also helps demonstrate whether alleles that influence disease also influence reproduction , which in the case of CAD suggests there may be antagonistic trade-offs between early versus late life . We used the Framingham Heart Study dataset because it has completed reproductive outcomes ( lifetime reproductive success ( LRS ) or number of children ever born ) , genotypes , pedigree data , cardiovascular outcomes and demographic and socioeconomic data . LRS was derived from clinical questionnaires and further validated with pedigree data . We did not include other datasets for validation here , as it is extremely hard to find others that include all these variables . There were 1 , 579 women from the Original and Offspring cohorts who had genotypes and all phenotypes available also after excluding non-founders . FHS 500k Affymetrix genotypes were 1000-Genomes imputed using the same pipeline described above bringing the total number of SNPs available ( at MAF>1% ) to 7 , 486 , 901 . LRS was adjusted to deal with secular demographic change where data was broken into six groups based on year women were born and divided by the mean reproductive success of women in that group ( same as described in [41] ) . We examined the association of all SNPs available in the FHS for the 76 CAD genes ( 20 , 254 SNPs ) with LRS using linear mixed models implemented in FaST-LMM [110] that account for potential confounding effects of genetic similarity by including a k-spectral decomposition variable derived from the realized relationship matrix ( RRM ) of an LD-pruned subset of SNPs . SNPs used for RRM were not in LD with CAD SNPs to avoid proximal contamination . Factors that may affect LRS—education , smoking status , whether the person was born in the US , and estrogen usage ( hormone therapy or contraceptive use ) —were included as covariates . Permutations with 10 , 000 iterations were also run for each SNP in order to validate nominal p values obtained directly from FaST-LMM , where permuted p values were based on the number of times nominal p values for 10 , 000 randomly chosen SNPs ( within a similar MAF bin ) were greater than the target SNP nominal p value . Bonferroni and FDR adjustment was also applied to p values based on 20 , 254 tests . To test the null hypothesis that CAD SNPs are collectively no more enriched for fitness compared to non-CAD SNPs , we randomly sampled without replacement 20 , 254 non-CAD SNPs ( matched within MAF bins to the CAD-SNP sample ) 100 times . The permuted p value was based on the number of times ( out of 100 ) that the number of significant p values in the random sample exceeded that for the CAD SNP sample . We also compared the distribution of p values between all randomly chosen SNPs ( 2 , 025 , 400 ) from this analysis to the 20 , 254 CAD SNPs with a Kolmogorov-Smirnov test . One- and two-sided tests were run . The one-sided test specifically tested whether the distribution of p values for CAD SNPs was stochastically larger compared to non-CAD SNPs . We then used fastBAT [111] to test whether CAD is enriched for fitness at the gene-level . fastBAT combines SNP-based summary-level data from GWAS and LD reference data to give locus-based estimates of association . We also ran 100 permutations for each of the 76 genes in order to estimate a permuted p value for each locus . Permuted p values were based on the number of times p values for the 100 randomly chosen similarly-sized genes were greater than that for each CAD gene . We also tested whether CAD genes were collectively more enriched for fitness at the gene-level , relative to non-CAD genes . We randomly chose 76 non-CAD genes of similar size with 300 permutations ( sampling without replacement ) and asked how many times the number of p values for the non-CAD genes exceeded that of the CAD genes . Other traits that may influence fitness were also tested ( using the same analysis/permutation tests as above ) for FHS women including age at first and last birth , interbirth interval , menarche and menopause . Menarche and menopause were derived from questionnaires , while birth timing/spacing were estimated from pedigrees . We did not consider reproductive outcomes for men as that data was only available from pedigrees , which is less reliable than clinical records . Age at first and last birth and interbirth interval were also adjusted for secular demographic changes ( same as above ) . Alternative simplified models for LRS , AFB and ALB were run in FaST-LMM where fitness measures were not adjusted for temporal effects and no covariates were included . This boosted sample sizes ( S2 Table ) due to avoiding missing values associated with covariates , however results were largely comparable ( S2 Table ) suggesting no power gain from unadjusted models . We only tested for antagonistic effects for LRS as that is the most direct measure of fitness and was the only fitness trait where CAD SNPs were significantly and consistently enriched across ( un ) adjusted models ( S2 Table ) . To assess whether antagonistic effects were present between LRS and CAD , genome-wide significant CAD index SNPs were taken from Nikpay et al . [40] and cross-referenced with significant LRS SNPs from the FaST-LMM regression results . In an extended analysis ( results not shown ) , we also included any SNP in high-LD ( r2> = 0 . 8 ) and proximal ( ±1MB ) to the index SNP to boost the number of SNPs available for comparison: results were virtually identical for the significance of LRS and CAD effects and the consistency of antagonistic effects . An antagonistic effect was defined as an allele that significantly increased LRS and significantly increased CAD risk . We also tested whether CAD SNPs were associated with both LRS and CAD due to other confounding ( rather than pleiotropic ) effects ( see S3 Fig for methods and findings ) .
|
How genetic variation contributes to disease is complex , especially for those such as coronary artery disease ( CAD ) that develop over the lifetime of individuals . One of the fundamental questions about CAD––whose progression begins in young adults with arterial plaque accumulation leading to life-threatening outcomes later in life––is why natural selection has not removed or reduced this costly disease . It is the leading cause of death worldwide and has been present in human populations for thousands of years , implying considerable pressures that natural selection should have operated on . Our study provides new evidence that genes underlying CAD have recently been modified by natural selection and that these same genes uniquely and extensively contribute to human reproduction , which suggests that natural selection may have maintained genetic variation contributing to CAD because of its beneficial effects on fitness . This study provides novel evidence that CAD has been maintained in modern humans as a by-product of the fitness advantages those genes provide early in human lifecycles .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
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] |
2017
|
Genetic loci associated with coronary artery disease harbor evidence of selection and antagonistic pleiotropy
|
Epileptic seizures are known to follow specific changes in brain dynamics . While some algorithms can nowadays robustly detect these changes , a clear understanding of the mechanism by which these alterations occur and generate seizures is still lacking . Here , we provide crossvalidated evidence that such changes are initiated by an alteration of physiological network state dynamics . Specifically , our analysis of long intracranial electroencephalography ( iEEG ) recordings from a group of 10 patients identifies a critical phase of a few hours in which time-dependent network states become less variable ( "degenerate" ) , and this phase is followed by a global functional connectivity reduction before seizure onset . This critical phase is characterized by an abnormal occurrence of highly correlated network instances and is shown to be particularly associated with the activity of the resected regions in patients with validated postsurgical outcome . Our approach characterizes preseizure network dynamics as a cascade of 2 sequential events providing new insights into seizure prediction and control .
Epilepsy is among the most common neurological disorders , with an estimated prevalence of about 1% of the world’s population and almost 2% in low-income families in developed countries [1] . Epilepsy is characterized by the seemingly random occurrence of seizures , which can greatly affect the quality of life of patients . Approximately one-third of all epileptic patients are resistant to pharmacotherapy [2] and could benefit from a variety of surgical options . Among them , closed-loop neuromodulation based on an accurate prediction of seizure occurrences is a promising tool . Over the last decades , several studies have shown that seizures are preceded by detectable changes in brain dynamics that can be measured via intracranial recordings . Although not fully understood , these changes have been associated with the existence of a transition of interictal ( period between seizures ) activity into the preictal state [3 , 4] . These findings have motivated intense research on the development of seizure prediction algorithms for therapeutic use in patients with pharmacoresistant epilepsy [5–8] . Although significant progress has been made to attain above-chance level performance results [9] , there is yet a long road to turn seizure prediction into therapeutic devices [8 , 10] . A major caveat of current seizure prediction is the lack of understanding about the neurophysiological processes associated with the emergence and maintenance of the preictal state . Indeed , most studies have resorted to fully data-driven methods to discriminate the preictal state with multiple signal features , which are typically patient specific and difficult to interpret [8] . Nowadays , epilepsy research is gradually adopting a network approach to study seizure dynamics at a global level and assess the contribution of the epileptogenic zone [11–14] . In this growing field , most studies have identified specific graph theoretical properties of functional networks during ictal and interictal periods [15–18] . In particular , a few groups have started to characterize the temporal variability of such functional networks during ictal [19–21] and interictal epochs [22–24] . Specifically , some authors have employed state spaces to classify recurrent functional networks during seizures to pinpoint those states that were responsible for the generation , maintenance , and termination of ictal activity [20 , 21] . More recently , a similar approach has been applied to a large sample of 10-min interictal epochs showing that interictal activity exhibits larger fluctuations than ictal periods over a common set of states [24] . In this context , however , the crucial question on whether there exist network dynamics changes pointing towards an upcoming seizure remains unaddressed . It is therefore due to ask: how are recurrent network states dynamically altered before epileptic seizures ? And more generally , can network dynamics provide a common principle of the preictal state ? In the current study , we addressed these questions for the first time by analyzing time-dependent alterations in the dynamic repertoire of the functional connectivity [25] during long continuous periods preceding seizures . Based on insights from other models [26 , 27] and recent findings showing network dynamics alterations between interictal and ictal epochs [24] , we hypothesized that the variability of physiological ( nondysfunctional ) network states was reduced as interictal activity approached epileptic seizures . Under this hypothesis , we developed a novel analysis to study specific variability changes prior to seizures preceded by long interictal periods in 10 epileptic patients monitored with intracranial electroencephalography ( iEEG ) during presurgical diagnosis . We made use of a graph theoretical property—the eigenvector centrality—to characterize network states [20] as instances of a time-varying multivariate continuous variable and resorted to the Gaussian entropy [28] to describe their variability . A controlled analysis using time-matched periods of interictal activity from additional days revealed a consistent and sustained decrease of the variability of network states before the seizure occurred . Remarkably , in all patients , this loss of variability was specifically associated with an abnormal occurrence of high-connectivity states ( HCSs ) during the preseizure period . We also investigated the contribution of the epileptogenic sites to the measured effect in 2 patients with long-lasting ( >4 y ) very good postsurgical outcome . In particular , the application of our analysis to the mapped epileptogenic sites of these seizure-free patients showed a significant alteration in the resected areas of the patients’ epileptic networks . Overall , our approach provides 2 main contributions in the analysis of epileptic network dynamics . First , it characterizes the preictal state as a 2-stage process in which epileptic networks undergo a functional reorganization before seizure onset . Second , it develops methodological aspects that may be considered to improve seizure prediction algorithms . More broadly , the results presented here open new lines to investigate dynamic alterations in pathological networks by studying the time-varying nature of brain activity .
We tracked network state dynamics for each patient separately over each recording session . To do so , we computed functional connectivity using Pearson correlation across all recording sites ( also referred to as sites; average value: 98 . 3 ± 25 . 1 sites; mean ± SD ) over consecutive and nonoverlapping time windows of 0 . 6 s ( Fig 1D ) . Networks in each window were characterized as a weighted undirected graph , such that electrode contacts represented the nodes and absolute-valued pairwise correlations represented their weighted edges ( Fig 1D ) . We then evaluated a centrality measure for each connectivity matrix to track network dynamics in a reduced and interpretable dimensionality space . Indeed , we computed the eigenvector centrality to reduce each N x N connectivity matrix to an N-dimensional vector , such that N was the total number of recording sites , thus obtaining a centrality sequence for each recording site ( Fig 1D ) . This measure can be equivalently interpreted as the first principal component of the absolute-valued correlation matrix of the set of intracranial recordings in each window . Our initial hypothesis was that the preictal state was associated with a reduction of physiological network states . We therefore tested this hypothesis by quantifying changes in the distribution of the eigenvector centrality sequences representing these network states . In particular , we assumed that the centrality time series could be approximated by a multivariate Gaussian distribution for a sufficiently large number of samples ( n > 100 ) [29] . In principle , the second-order variability of a multivariate variable may exhibit 2 components: the temporal component , i . e . , how the centrality of a recording site varies as a function of time , and the spatial component , i . e . , how the centrality consistently varies across recording sites at a given time instance . A measure that simultaneously quantifies both components is the multivariate Gaussian entropy , which monotonically depends on the product of the covariance matrix’s eigenvalues ( Fig 1C ) . This measure corresponds to the differential entropy of multivariate normally distributed variables [28] , but it can be proved useful to approximate the variability of more general variables whose distribution is asymptotically Gaussian . First , we centered our analysis on the preseizure period and the time-matched period from the previous day ( preseizure , control ) . Over both periods , we computed the multivariate Gaussian entropy in consecutive and nonoverlapping time windows of 200 centrality samples ( 120 s ) and normalized the measure to lie within the interval ( 0 , 1 ) per patient . We shall refer to this applied measure as centrality entropy in the remainder of the article . The straightforward application of the centrality entropy to both periods in the main patients showed that centrality sequences were generally less entropic during the preseizure period ( see S1A Fig ) , showing a gradual increase and successive decrease of this crossperiod difference as the seizure onset approached . In order to localize this effect in a specific and significant time segment , we grouped consecutive entropy values into intervals and made use of a nonparametric test to identify the cluster of consecutive centrality entropy intervals that was significantly yielding the largest entropy decay per patient ( Materials and methods ) . The results of this test are illustrated for the main patients in Fig 2A where average centrality entropy curves are plotted for the control ( in blue ) and preseizure period ( in red ) together with the identified significant time segment ( in cyan ) during the 9 . 5 h preceding the seizure . In each patient , this segment highlighted intervals in which the same centrality entropy reduction could not be achieved by shuffling the entropy values within each interval across the preseizure and control periods ( P < 0 . 01; S1B Fig ) . Intriguingly , the pinpointed segment was rather patient specific , exhibiting offset times that were not generally attached to the seizure onset . However , when grouping samples across the main patients , significant intervals turned out to be regularly distributed around the proximity of the seizure onset , with the interval ( −2 . 5 , −1 . 5 ) being the most frequent ( 87 . 5%; Fig 2B ) . In particular , this distribution was statistically different ( P < 0 . 01 , Kolmogorov-Smirnov test ) from a surrogate distribution obtained by randomly placing the same segments per patient in every possible location of the preseizure period ( Fig 2C ) . In addition , relevant features of the significant segment such as the onset and offset times and the test’s statistic value were not correlated with the seizure onset time ( S2B , S2C and S2D Fig ) . These findings corroborated that our analysis controlled for possible underlying circadian modulations of the iEEG data ( S2A Fig ) . Finally , the results obtained in both control patients were rather different from each other ( S3A Fig ) . In particular , the crossperiod difference measured in patient 9 was the least significant across all patients ( S3B Fig ) , suggesting that the previous received electrical stimulation might have had an effect on the preseizure dynamics . In contrast , the occurrence of a subclinical seizure in patient 10 did not yield a quantitatively different significance effect . We analyzed the stability of the results over the main patients using a synchronization measure over a wide range of frequency bands and an alternative centrality measure ( Materials and methods ) . The separate application of both measures unravelled similar trends with weaker statistical effects ( S4 and S5 Figs ) . In conclusion , our initial findings suggested that significant and sustained reductions of network state variability over a precedent-day baseline could be related to a preictal state . Furthermore , this reduction in variability was statistically mapped to a patient-specific time subperiod per patient . This subperiod will be referred to in the following as the critical phase . As observed earlier , the critical phase was not , in general , attached to the seizure onset of every patient . Therefore , how could the critical phase be related to earlier reported evidence on the preictal state ? To address this question , we divided both recording sessions into the critical phase and subperiods immediately before ( pre- ) and after ( post- ) the critical phase ( Figs 2C and S3C for control patients ) . For those patients with critical phases attached to the seizure onset ( patients 1 , 6 , and 8 ) , we considered the postcritical phase to comprise the last window time samples of the critical phase . In each subperiod , we evaluated the mean functional connectivity during both recording sessions . Fig 2C shows that the mean connectivity exhibited a nonsignificant increase during the critical phase of the preseizure period ( Fig 2C , P > 0 . 2 , paired Wilcoxon test , n = 7 patients ) . In contrast , when comparing the critical and the postcritical phases of the preseizure period , the mean connectivity decreased significantly over all patients ( Fig 2C , P < 0 . 02 , n = 8 patients ) in concordance with previous works [4 , 30 , 31] . This result was validated at a single-patient level in 7 out of 8 main patients ( S6 Fig ) . Importantly , the postcritical effect was not present during the control period ( P > 0 . 5 ) , suggesting that the global connectivity decrease was specific to the preseizure period and could be a consequence of the critical phase . As introduced earlier , the centrality entropy quantified the ( spatiotemporal ) variability of simultaneous centrality sequences in a single scalar value . Then how was the variability reduction individually expressed along recording sites and along time samples ? To answer this question , we repeated the previous nonparametric statistical analysis ( Fig 2A ) over both recording periods using the spatial and temporal versions of centrality entropy independently ( Materials and methods ) . S7B Fig shows that the statistical effect was present in both dimensions for every patient , but it was not equally distributed over space and time in all cases ( S7 and S8 Figs ) . In sum , the decrease of network state variability observed during the preseizure period was associated with the occurrence of more similar centrality values over time ( less temporal variability ) , which in general exhibited more homogeneous centrality values across recording sites ( less spatial variability ) . The previous results described that network states ( as modelled by the eigenvector centrality measure ) became more temporally redundant and more spatially homogeneous during the critical phase . In turn , this reduced variability was associated with a nonsignificant variation of the mean connectivity across patients ( Fig 2C ) . Yet what was the actual interplay between network dynamics and connectivity alterations during the preseizure period like ? An initial time-varying analysis of the mean functional connectivity ( averaged over all recording sites’ pairs ) did not reveal consistent and sustained crossperiod differences over patients ( S9 Fig ) . We then related the reduction in network variability to alterations in the occurrence of certain states . In particular , were there specific time-varying states producing the reported effect ? We here explored this question and inspected the eigenvector centrality sequences during the control and preseizure periods . A visual inspection of these vector sequences for every patient suggested the hypothesis that the amount of “homogeneous states” ( represented as yellow strips in the plot ) was larger during the preseizure period than in the control period . Interestingly , these homogeneous states were specifically associated with high-connectivity correlation matrices in most of the patients ( Fig 3A ) . Centrality vector sequences like the one presented in Fig 3A were observed to be recurrent over time . Then , we used a clustering algorithm to extract the 12 most representative vectors over both periods of interest and classified each centrality vector at any given time accordingly ( Materials and methods ) . Consequently , the sequence of centrality vectors turned into a sequence of discrete states whose frequency ( or probability ) over any time window could be computed and compared across control and preseizure periods . Then , we formally tested the hypothesis that the larger presence of homogeneous states during the preseizure period was associated with the observed reduction in network state variability in each patient . For each patient , we linearly regressed the crossperiod centrality entropy difference over 2 independent state regressors—state probability and state heterogeneity—the latter being measured as the SD across recording sites within a state ( Fig 3B ) . We then computed the variance explained by each regressor via its coefficient of determination ( R-squared ) . To investigate the group-level influence of every state’s connectivity into these associations , states were sorted for each patient in decreasing order of connectivity ( i . e . , mean connectivity of its associated absolute-valued correlation matrix ) , and coefficients of determination linked to state probability ( Fig 3C , top ) and state heterogeneity ( Fig 3C , bottom ) differences were distributed in boxplots for each state . Fig 3C ( left ) shows , for both regressors ( state probability and state heterogeneity ) , that the most influential states on the reduced variability effect were those with highest-connectivity correlation matrices . Specifically , the difference between the variance explained by the highest-connectivity states and the remaining ones was significant in both state probability ( P < 0 . 01 , Wilcoxon test ) and state heterogeneity ( P < 0 . 05 ) with large effect sizes ( D = 3 . 2 , D = 1 . 6 , Cohen’s d ) . Then , we computed the Spearman correlation between the highest-connectivity state regressors and the centrality entropy reduction across the main patients to unravel group-level correlation trends . Correlation values were of r = 0 . 7 ( P < [1 × 10−5] , n = 2328 time samples ) and r = −0 . 45 ( P < [1 × 10−5] , n = 2328 time samples ) for state probability and heterogeneity increases , respectively , indicating that the reduction of network variability was mostly explained by an increase in the frequency rate and homogeneity of the highest-connectivity states . To further investigate the interplay of HCSs with the preseizure period , we evaluated crossperiod state probability and heterogeneity differences at the patient level during the critical phase previously identified in Fig 2A ( Fig 3C right ) . First , we found that the probability of HCS was significantly different in all patients across both periods ( paired t test , P < 0 . 01 , multiple test–corrected , D > 0 . 5 ) . In 6 out of 8 patients , HCSs occurred significantly more often during the critical phase , while they were less frequent in the 2 remaining patients ( patients 2 and 5 ) . Second , the homogeneity of HCSs were significantly increased in most of the patients ( paired t test , P < 0 . 01 , multiple test–corrected , D > 0 . 5 ) , except in patient 5 , for whom it significantly decreased , and in patient 2 , for whom it remained statistically equal ( P > 0 . 05 ) . Although the influence of HCSs into the preseizure period was consistent across all patients , the differentiated trends found in some specific patients ( patients 2 and 5 ) suggest that this influence might be modulated by context-dependent variables . In sum , HCSs strongly contributed to make state dynamics less variable over time by altering the overall states’ variability and imposing homogeneous centrality values across recording sites . The key influence of HCSs into preseizure dynamics prompted us to evaluate the underlying traces of iEEG data during their corresponding time instances in periods of high- and low-centrality entropy . Our inspection of iEEG data from distinct epileptogenic sites over sequences of HCS and non–high-connectivity state ( nHCS ) instances ( see S11 Fig for an example ) identified these states as time segments in which the recorded electrical activity became transiently ( low-centrality–entropy epoch ) or more persistently ( high-centrality–entropy epoch ) synchronized . This synchronization was manifested through diverse patterns of oscillatory activity , which often included a slow wave . In parallel , a clinical evaluation by the epileptologists discarded any stereotyped epileptiform activity . We identified network dynamics changes in the preseizure period that were consistently expressed with a similar trend ( sustained variability reduction ) across a heterogeneous cohort of patients ( Fig 1 ) . Critically , these time-dependent changes could be associated with a common factor in all patients , namely , an alteration of recurrent high-connectivity time instances ( 0 . 6 s ) across recording sites . However , was this characterization specific to the preseizure period ? Or could it be alternatively ascribed to a postimplantation effect ? To shed light onto these questions , we analyzed an additional 121 h of interictal activity in 6 patients from time-matched periods that were placed 2 d before the seizure ( “precontrol” period ) and a varying number ( across patients , mean = 3 . 83 ) of days after the seizure ( “postcontrol” period ) . These new interictal data were introduced in the analysis as schematized in Fig 4A As control experiments , we defined 2 additional time-matched comparisons: a comparison between the precontrol and control periods ( “C1” ) and a comparison between the seizure and postseizure period ( “C2” ) . These new comparisons were then confronted with the original comparison particularized to the 6 patients ( “C0” ) . The overall analysis was made under the condition that period lengths were time matched and balanced across comparisons for each patient . First , for every comparison , we repeated the nonparametric statistical analysis of Fig 2A to determine the existence of putative critical phases in other periods . While comparison C2 only yielded 1 patient with a significant effect , C1 revealed that entropy reductions could also occur in non-preseizure periods in 5 out of 6 patients ( Fig 4B ) . Nonetheless , when grouping the 6 patients in Fig 4C , the entropy reductions of C1 were not followed by a functional connectivity decrease , in contrast to C0 , where the decrease showed a significant trend ( P < 0 . 1 , Wilcoxon test ) . Finally , we repeated the regression analysis of Fig 3B in patients with significant entropy reductions of C1 ( 5 patients ) and C0 ( original comparison in 6 patients ) and represented the results analogously for each comparison . Crucially , for C1 periods , the variability decrease was more weakly explained by crossperiod HCS differences than in C0 periods . Indeed , the significant trend of C0 in the superior variance explained by HCSs ( as compared to nHCSs ) in both state probability ( P < 0 . 1 , D = 1 . 5 ) and state homogeneity ( P < 0 . 1 , D = 1 . 6 ) could not be reproduced by C1 ( P > 0 . 1 ) . In conclusion , although decreases in network state variability may occur across consecutive days ( C1 ) preceding a seizure , we showed that those occurring during the preseizure period were specifically tied to HCS alterations and a subsequent functional connectivity decrease . Importantly , network dynamic changes observed during the preseizure period could be associated with an altered occurrence of HCSs in all patients . Yet how could this seemingly physiologic alteration evolve into generating seizures ? In particular , how was this effect manifested in those regions that were involved in seizure generation ? To relate our findings to the regional generation of seizures , we particularized our analysis to the clinically mapped epileptogenic sites of 2 patients with very good postsurgical outcome ( Engel I ) and a follow-up period of more than 4 y ( patients 1 and 3 , Fig 1 , Materials and methods ) . Both patients are seizure free ( Engel I ) , with patient 3 exhibiting some residual ictal symptomatology ( seizure auras ) . In these patients , we specifically investigated the influence of epileptogenic sites in the preseizure network dynamic changes . To provide a complete comparison of sites , we independently analyzed seizure-onset zone ( SOZ ) sites ( brain zone involved in the initial stages of the seizure spread ) , resected zone ( RZ ) sites ( brain zone that rendered seizure-freeness after its resection ) , and the remaining sites ( nonepileptogenic zone [nEZ] sites ) . In both patients , we note that the SOZ was not fully included in the RZ , and therefore the SOZ and RZ were partially overlapping regions . To carry out this region-specific analysis , we first evaluated the temporal mean and SD of the recording sites’ centrality in the SOZ , RZ , and nEZ sites over the control and preseizure periods . Fig 5A plots the time-average centrality of RZ and nEZ as a function of the remaining time to seizure onset . This figure illustrates in both patients that the time-average centrality of the RZ was higher than the nEZ over each period of interest , and—during the critical phase ( in cyan ) —the centrality of RZ sites was reduced at the expense of an increase in the centrality of nEZ sites . This preliminary observation suggested that both regions could participate in the preictal dynamics . However , was this participation equal across the 3 considered regions ? Fig 5B characterizes the network dynamics of the 3 regions by comparing the temporal SD of their recording site’s centrality in SOZ ( inner left ) , RZ ( inner central ) , and nEZ ( inner right ) regions for control ( blue ) and preseizure ( red ) periods , inside ( outer left ) and outside ( outer right ) the critical phase . To assess crossperiod differences across regions of variable size , we highlighted significant differences ( P < 0 . 05 , paired t test , multiple test–corrected ) exceeding an effect size threshold of 0 . 5 ( large effect , Cohen’s d ) . Using this quantification , Fig 5B shows that the largest decrease in the centrality variability ( D > 0 . 5 ) of patient 1 was only localized in the RZ during the critical phase . For patient 3 , large effect sizes were found in RZ but also in nEZ during the critical phase . Outside the critical phase , crossperiod differences attained lower effect sizes ( D < 0 . 3 ) . We next investigated the influence of HCSs on epileptogenic and nonepileptogenic sites to further describe the functional alterations occurring during the critical phase . More specifically , we compared the average connectivity per site ( node strength ) in the RZ , SOZ , and nEZ during the presence of the HCS and the remaining states ( nHCS ) in each patient for control and preseizure periods in the critical phase ( Fig 5C ) . This analysis revealed several findings . First , in both patients , crossperiod differences in strength occurred more prominently during HCSs ( average D > 1 . 8 ) than in nHCSs ( average D < 0 . 7 ) . Second , during HCSs , strengths increased from control to preseizure periods consistently in the 3 studied regions , while the differences were of varying signs across regions during nHCSs . Third , the region that exhibited the highest increase in strength was the RZ for both patients ( D = 2 . 9 , 2 . 8 ) , followed by the nonepileptogenic sites ( D = 2 . 2 , 1 . 4 ) and the SOZ ( D = 1 . 3 , 0 . 7 ) . Therefore , the abnormal occurrence of HCSs altered the connectivity gradient between epileptogenic and nonepileptogenic regions by strongly boosting the connectivity of the RZ sites . In particular , during the critical phase of the preseizure period , this increased connectivity was more persistent than in the control period , resulting in a reduced variability of RZ centrality values ( Fig 5B ) . Finally , we evaluated how the postcritical functional connectivity decrease ( Fig 2C ) was spread over the 3 regions in both patients . S12 Fig shows that this effect was reproduced in each region ( D ≥ 1 . 2 ) , with , again , the RZ showing a more prominent decay ( average D = 2 . 1 ) . To relate some of our regional findings with the patients’ postoperative outcome , we extended the analysis of the sites’ temporal variability ( Fig 5B ) to the main patients’ entire cohort ( S13 Fig ) . This included 3 patients who underwent RFTC with variable outcomes ( patients 2 , 6 , Engel I and patient 8 , Engel III ) , 2 patients with bad postsurgical outcome after a follow-up period of more than 1 y ( patients 4 and 5 , Engel III ) , and 1 patient who was seizure free after SEEG monitoring ( patient 7 ) . The results are depicted for each patient in S13 Fig . Despite the variety of treatments and outcomes , S13 Fig consistently shows for all patients the larger contribution of epileptogenic sites than nonepileptogenic to the network variability change during the critical phase . Therefore , we elaborated on this observation in S4 Fig to show the temporal variability change of the nonresected and nonablated sites of all main patients during the critical phase as a function of their postoperative outcome . In general , the high values of the nontreated regions in Engel III patients ( relative to Engel I patients ) during the critical phase provide preliminary evidence that bad postoperative outcomes are associated with regions of large preseizure alterations not being treated .
This study examined the existence of a common alteration principle in brain network dynamics during long-lasting periods of activity preceding the first clinical seizure in 10 patients with focal pharmacoresistant epilepsy . Using a comparative analysis between genuine preseizure periods and time-matched periods of interictal activity per patient , we were able to consistently show a sustained decrease in the variability of network states that was followed in most of the patients by a functional connectivity drop of approximately 30 min before the seizure onset ( Fig 6 ) . Further analysis revealed factors altering this variability in the temporal ( time samples ) and spatial ( recording sites ) domains . First , this decrease in network variability was associated with an abnormal occurrence of HCSs during preseizure periods as compared to previous days . Second , the reduction in temporal variability and the functional connectivity decrease was mainly localized in the RZ of the 2 patients with best postsurgical outcome . Over the last decade , functional MRI ( fMRI ) studies have showed growing evidence that dynamic connectivity patterns ( “brain dynamic repertoire” ) may be an intrinsic property of brain function and disease [25] . Particular examples of disrupted dynamics have been found in Alzheimer disease [32] and neuropsychiatric disorders [33] for which translation to new clinical biomarkers is still a matter of discussion ( [34] and references therein ) . In modern epilepsy research , the dynamic principle of brain function has been postulated to be commonplace to understand how seizures are generated [35] , but most network studies have studied alterations in static functional network parameters , with a few recent exceptions [20 , 24 , 36–39] . In this context , our approach differs from previous works in several key elements . To name a few , we formulate a hypothesis about the variability of functional network states at short time scales ( rather than using a grand-average measure ) , the analysis of long-lasting ( approximately 10-h ) continuous interictal periods ( rather than a selection of short epochs ) , and—more importantly—the use of time-matched reference epochs outside the preseizure period to assess specificity . Next , we further elaborate on the latter point . When studying the variability of brain dynamics along long recording periods , one is confronted with the confounding effect of circadian rhythms [23 , 36 , 40] , which span across sleep and wake phases . These rhythms may become critical when one characterizes specific brain configurations associated with the preictal state , which has been shown to last approximately 4 h [41] . Previous studies on the preictal state have analyzed preictal changes with reference to previous interictal periods , not necessarily time-matched . Inspired by a previous work [42] , the strategy used here tackled this issue by defining time-matched reference periods from precedent and subsequent days , thus allowing for a more specific identification of preictal changes in brain network dynamics . Although this approach may not be sufficient to control for all daily physiological state transitions , our preliminary data on the relationship between patients’ putative critical phases and seizure onset times discard the influence of daily rhythms into our main results . However , a larger cohort of patients with variable seizure times and a good readout of their sleep phases will be necessary to address this question in the future . Another key aspect of the study was the use of the first monitored clinical seizure occurring during the first implantation days . This choice was pivotal to analyze comparable long-term network dynamic changes across patients with limited influence of confounding factors such as the reduction of antiepileptic drugs , the effect of previous ictal processes , and the response to clinical stimulation . In most of the studied patients , this first seizure was the first event of a succession of seizures separated by short interictal periods of a few hours or minutes , which are clinically known as seizure clusters [43] . Therefore , understanding the preictal process of this initial seizure can also have important consequences for the control of later ictal activity . In any event , the analysis introduced here should be extended to subsequent seizures in future studies to determine whether the presented characterization is specific to seizures preceded by long interictal periods . A central question in seizure prediction research has been the role of synchronization [44] during the preictal period . Some studies have reported drops in synchronization a few hours before seizure onset [30] , while others have pinpointed the coexistence of distinct synchronization states depending on the recorded structures [12 , 31] . Even though a clear mechanism of such alterations is still missing , the most successful algorithms applied to large data sets make use of correlation matrices as key data features [9] . The findings presented in this study support the view that preictal correlation patterns are state dependent [22 , 24 , 31] over time windows of 600 ms , and therefore their alterations should be also analyzed and interpreted at this time scale . More precisely , our results suggest that a time-dependent variation in the occurrence of highly correlated time instances may be at the origin of the preictal state . This variation was manifested in most of the patients as an excess of HCSs , while in 2 patients it was manifested as a deficit . Although preictal connectivity trends are known to be patient specific [44] , they should be further investigated against the influence of patient-dependent variables ( e . g . , implantation schemes , monitored behavioral states ) , a question that was outside of the scope of this study . In recent years , there has been accumulated evidence that seizure generation and spread involves complex interactions between seizure-generating and surrounding areas [14 , 19 , 21] . Evaluating network dynamics in patients with good postsurgical outcome ( >4 y ) , we were able to relate our findings to clinically mapped epileptogenic sites , namely the SOZ and the RZ , as well as the remaining sites . In these patients , the network centrality was higher in the epileptogenic than in nonepileptogenic sites , in line with previous studies [45 , 46 , 47] . Not surprisingly , changes in overall centrality within periods simultaneously occurred during the critical phase where centrality values from both regions approached ( Fig 5A ) . Crucially , this occurred during a significant decrease in the ( temporal ) centrality variability of the RZ ( Fig 5B ) , which was specific in patient 1 and also present in the nonepileptogenic sites of patient 3 , who presented a slightly worse postsurgical outcome . The analysis of the influence of HCSs on validated epileptogenic sites supports the idea that these states might destabilize physiological state dynamics by increasing the connectivity of key sites within the epileptic network during the critical phase ( Fig 5C ) . The follow-up of this phase is shown to be a global functional connectivity decrease , which is again more prominently manifested across resected nodes ( S12 Fig ) . We speculate that this decrease in connectivity could be the result of central nodes of the epileptic network adopting a more autonomous activity that would result in the generation of a seizure . The inclusion in the analysis of additional patients with different postoperative outcome suggests that preseizure alterations in centrality variability may be a promising biomarker for targeting epileptogenic regions during surgery and ablation ( S14 Fig ) . Yet a larger study including more seizure-free patients will be necessary to fully elucidate the mutual influence of physiological network dynamics and the epileptic network during the transition from interictal activity to focal seizures . The results shown in this study prompt us to introduce new ingredients in seizure-prediction algorithms such as the control for daily rhythms [48] and the continuous tracking of time-dependent linear connectivity alterations at short time scales ( <1 s ) . Some considerations are yet to be mentioned . First , the use of intracranial recordings is a limiting factor in the spatial analysis of brain states , thus making them a priori subject-dependent . Nonetheless , it is recognized that the SEEG methodology offers an optimal temporal and spatial resolution of neurophysiological recordings for neural signal analysis in comparison with other techniques in patients with epilepsy . Second , this study was aimed at defining network states in a linear and instantaneous form using zero-lagged functional connectivity rather than effective connectivity [49] . Although our results were validated against a nonlinear coupling measure at different narrow bands , the extension of our analysis to nonlinear [50] and linear [51] directional methods in follow-up studies may provide additional information on specific connectivity changes underlying preseizure alterations . In conclusion , this work provides electrophysiological evidence for characterizing the preseizure period as a long-lasting process in which epileptic networks undergo a sequential functional reorganization . Further investigations under this conception will help unravel seizure generation mechanisms from a network perspective , provide practical insights into how to predict and control ictal activity , and may constitute a general approach to analyze dynamic alterations of other neuropathologies .
All diagnostic and surgical procedures were approved by The Clinical Ethical Committee of Hospital del Mar , and all clinical investigation was conducted according to the principles expressed in the Declaration of Helsinki . Following the Declaration of Helsinki , patients were informed about the procedure , and they gave their written consent beforehand . A total number of 344 h of iEEG recordings from 10 patients with pharmacoresistant focal-onset seizures were analyzed . A summary of the patients’ characteristics is given in Table 1 . We included patients who presented the first spontaneous clinical seizure in a timeframe that allowed us to perform a controlled analysis of EEG recordings during the preseizure period . Specifically , each patient in the study was selected if her first video SEEG–recorded clinical seizure had occurred after at least 30 h ( average value: 71 . 4 ± 19 . 1 h; mean ± SD ) with no presence of spontaneous clinical seizures . Among the selected patients , we included 2 patients presenting potential perturbation factors affecting the preseizure period ( patients 9 and 10 ) . Patient 9 had been electrically stimulated 16 . 5 h before the first recorded seizure , and patient 10 presented a subclinical seizure 6 . 1 h before the first clinical seizure onset . For each patient , the selection of recording sessions was as follows . We considered up to 12 h before the first monitored clinical seizure occurred . As a baseline reference , we selected the same time period from the previous day ( control period ) . For independent validation of our results , we selected additional time-matched periods of variable length in 6 patients ( patients 2–6 and 8; average period length: 10 h ) from 2 d before the seizure onset ( precontrol period ) and a few days after the seizure onset ( postcontrol period; average value = 3 . 83 d ) . No more patients could be added to the validation analysis for time limitations ( patients 7 and 10 ) , a substantial modification of the implantation montage during the first monitoring days ( patient 1 ) , or the presence of direct electrical stimulation in the iEEG recordings ( patient 9 ) . After detecting recording cuts in a few patients , we restricted the analysis to 11 h per session in patients 1 through 9 and to 2 . 4 h per recording session in patient 10 to ensure a time-matched crossperiod comparison . Among the selected patients , 2 patients achieved seizure freedom after surgical resection and radiofrequency thermocoagulation ( RFTC , [52] ) with a follow-up of 4 y and 3 y , respectively ( patients 1 and 2 , Engel IA ) . An additional patient only exhibited seizure auras after surgical resection and a follow-up of 4 y ( patient 3 , Engel IB ) . We considered patients 1 and 3 to have a validated very good postsurgical outcome . Therefore , for the purpose of analyzing epileptogenic sites , we separately considered the diagnosed SOZ and the RZ of these 2 patients in Fig 5 . The SOZ was independently marked by 2 epileptologists ( AP and RR ) and consisted of n = 5 ( anterior hippocampus ) and n = 9 ( anterior hippocampus , amygdala ) recording sites for patient 1 and 3 , respectively . The RZ covered 24 contacts in patient 1 ( parts of anterior hippocampus , temporal pole , and entorhinal cortex ) and 12 contacts in patient 3 ( parts of anterior , posterior hippocampus , and amygdala ) . The remaining patients presented one of these cases: they had not undergone surgery ( patients 2 , 6 , 8 , 9 ) , had a non–sufficiently long follow-up period ( <18 mo , patients 4 and 5 ) , had not yet been operated on ( patient 7 ) , or exhibited a bad postoperative outcome ( patient 10 ) . All recordings were performed using a standard clinical EEG system ( XLTEK , subsidiary of Natus Medical , Pleasanton , CA ) with a 500 Hz sampling rate . A uni- or bilateral implantation was performed accordingly , using 5 to 15 intracerebral electrodes ( Dixi Médical , Besançon , France; diameter: 0 . 8 mm; 5 to 15 contacts , 2 mm long , 1 . 5 mm apart ) that were stereotactically inserted using robotic guidance ( ROSA , Medtech Surgical , New York , NY ) . Intracranial EEG signals were processed in the referential recording configuration ( i . e . , each signal was referred to a common reference ) . Examples of iEEG signals are displayed in S11 Fig . All recordings were filtered to remove the effect of the alternate current ( Notch at 50 Hz and harmonics using a FIR filter ) . Then , signals were further band-pass filtered between 1 Hz and 150 Hz to remove slow drifts and aliasing effects , respectively . Artifacts were removed in each period by detecting time window samples ( 600 ms ) such that mean ( over pairs of sites ) absolute-valued correlation values and mean ( over sites ) absolute-valued voltage amplitudes were 3 SDs larger than the median values across each period . To perform functional connectivity analysis , each iEEG signal was divided into consecutive and nonoverlapping 0 . 6 s–long windows ( 300 samples with 500 Hz sampling rate ) to balance the requirements of approximate stationarity of the time series ( requiring short epochs ) and of sufficient data to allow accurate correlation estimates ( requiring long epochs ) . There are different methods to assess functional connectivity from time series data based on coupling measures [53 , 54] . Previous research on the comparison of linear and nonlinear coupling measures has resulted in having distinct “ideal” measures for distinct studied situations [55] . Here , we chose to employ Pearson correlation—a zero-lagged linear correlation measure—for its good tradeoff between simplicity and robustness [54] and , more importantly , because it allowed for a convenient definition of network state as it will be explained later . Let x and y be 2 N-length time series representing 2 recorded signals and let x- and y- be their respective sample means . Their sample Pearson correlation is estimated as r ( x , y ) =∑i=1N ( x ( i ) −x- ) ( y ( i ) −y- ) ∑i=1N ( x ( i ) −x- ) 2∑i=1N ( y ( i ) −y- ) 2 ( 1 ) For each patient and each consecutive 0 . 6 s–long window , we computed the absolute value of the coupling measure across all pairs of electrode contacts . For most of the patients , the overall pairwise computations resulted in approximately 123 , 000 sequential connectivity matrices combining both recording sessions ( control and preseizure periods ) . In the current study , we did not test the statistical significance of each pairwise coupling because our purpose was to track the overall network dynamics regardless of pairwise thresholding methods . For each patient , we characterized each correlation matrix as a functional network . This network was modelled as a weighted undirected graph , such that electrode contacts represented the nodes and absolute-valued pairwise correlation values across represented their weighted edges [56] . Then , we computed the network measure of eigenvector centrality for each connectivity matrix [57] . For a given graph G= ( V , E ) , let A= ( av , t ) be its weighted adjacency matrix . The relative centrality score xv of vertex v can be defined as xv=1λ∑t∈Vav , txt , ( 2 ) which can be rearranged in a matrix form as λx=Ax . Given the requirement that all entries in x must be non-negative , the Perron–Frobenius theorem implies that only the greatest eigenvalue results in a proper centrality measure [57] . Therefore , the centrality measure is given by the eigenvector associated with the largest eigenvalue of the connectivity matrix . Then , the ith contact is assigned the ith component of this eigenvector such that i goes from 1 to number of recording sites in a patient . The eigenvector centrality is by definition a self-referential measure of centrality , i . e . , nodes have high eigenvector centrality if they connect to other nodes that have high eigenvector centrality [58] , which ultimately provides a measure of relative importance of each node in the network . The eigenvector centrality measure has been applied to resting-state fMRI studies [59] and more recently to ECoG recordings of epileptic patients [20] . By computing the centrality in each 0 . 6 s–long connectivity matrix , we obtained—for each patient—independent eigenvector centrality sequences along each recording session . If we consider each connectivity matrix to represent a brain state [60] , these vectors can be regarded as representative elements of these states in a vector space of a dimension equal to the number of recording sites . Furthermore , these vectors point to the direction that best summarizes the original brain state . In particular , every time that a significant change arises in the connectivity matrix , the eigenvector centrality rotates to update the relative importance ( “centrality” ) of each contact within the new network configuration . Computing the eigenvector centrality over zero-lagged connectivity matrices was key for regarding our network state measure as an informative summary of how the set of simultaneous iEEG recordings were instantaneously coupled within a short time window . Indeed , under these conditions , the eigenvector centrality corresponds , by definition , to the first principal component of the absolute-valued correlation matrix , i . e . , the vector in the space of recording sites that accounts for the largest variance of the whole set of ( normalized ) iEEG recordings in a given time window . Combinations of other coupling measures and network features could lead to alternative definitions of network states . For the sake of comparison , we also provide in S4 Fig the results obtained by combining zero-lagged correlation with a different network feature—the node strength—which can be defined as the average pairwise connectivity of this node with the remaining ones [58] . Indeed , S4 Fig shows that the node strength yielded , in general , statistically weaker results than the eigenvector centrality . Furthermore , we investigated the possibility of combining a synchronization measure such as the phase-locking value [61] with the eigenvector centrality . This measure may capture contributions of non–zero-lagged couplings as well as nonlinear effects . To illustrate the difference between both measures in the frequency domain , we repeated the cluster-based statistical analysis of Fig 2A for consecutive frequency narrow bands over the range 1 to 120 Hz . S5 Fig shows that the results were qualitatively similar across all bands for most of the patients . Yet in those patients for whom discrepancies were found , the phase-locking value measure yielded weaker peaks than the ( absolute-valued ) zero-lagged correlation . Our goal was to evaluate the variability of these representative states in each period . The long sequence of centrality vectors for each period can be equivalently regarded as a stream of simultaneous centrality time series , one for each recorded contact . Then , one can evaluate the spatiotemporal variability of the centrality time series through the application of the multivariate Gaussian entropy [28] in a given estimation time window , which we choose for this study to be 120 s . The multivariate Gaussian entropy is defined as Hc=K2 ( 1+ln ( 2π ) ) +12ln ( detΣ ) , ( 3 ) such that K is the number of recording sites and Σ is the covariance matrix of the centrality time series estimated in the estimation windows . By considering centrality vectors to be independent , Σ in ( 4 ) becomes a diagonal matrix , and the Gaussian entropy captures the aggregated variability of the centrality vectors across the temporal dimension: Hc ( 1 ) =K2 ( 1+ln ( 2π ) ) +12∑i=1:KlnΣi , i . ( 4 ) By subtracting ( 4 ) from ( 3 ) , one can evaluate the variability of the centrality vectors across the spatial dimension: Hc ( 2 ) =12 ( ln ( detΣ ) −∑i=1:KlnΣi , i ) . ( 5 ) Therefore , the 2 contributions sum up to give the Gaussian entropy ( 4 ) : Hc=Hc ( 1 ) +Hc ( 2 ) . ( 6 ) The choice of 0 . 6 s ( 300 samples ) for the correlation window was critical to gain statistical power . Choices of 1 , 5 , or 10 s were shown to weaken the detection of network dynamics changes because they were intermingling high- and low-connectivity effects in the same window . On the other hand , values of entropy windows ranging from 100 to 200 s yielded quite stable results . We selected a window size of 120 s ( 200 samples ) because it offered a good tradeoff between estimation accuracy ( 200 samples are good enough to estimate covariance matrices of at most 120 variables ) and stationarity . To associate the network variability decrease observed in the main patients with the occurrence of specific recurrent connectivity states , we jointly clustered the eigenvector centrality sequences in the analyzed time-matched comparisons using the k-means algorithm [62] . In the main results , we fixed the number of clusters to 12 to cover a sufficiently wide range of visually inspected connectivity states per patient . This cluster size was selected after exploring the stability of the results illustrated in Fig 3C for the range of values n = 8–12 . In particular , S10 Fig shows that these results were qualitatively very similar for the choices n = 8 , 10 , 12 . The preseizure decrease in centrality entropy was statistically tested as follows . We started by windowing consecutive entropy samples ( n = 15 , 30 min ) in nonoverlapping and paired time segments across each period , and then we computed the effect size for each segment pair using Cohen’s d [63] . We then clustered adjacent segments with a criterion that effect size be larger than 0 . 15 ( moderate effect ) over a minimum of 4 adjacent segments ( 2 h ) and considered the aggregated sum of these segments’ effect sizes as the main statistic . We further checked the statistical significance of this value through nonparametric statistical testing based on Monte Carlo sampling [64] . More concretely , for each patient with time segments satisfying the above criterion , we computed 1 , 000 random permutations of the centrality entropy samples across both conditions ( within preseizure or control period ) at each time segment and repeated the same segment clusterization procedure to obtain 1 , 000 surrogate statistic values . These values were used to approximate a null distribution against which we compared the original aggregated effect size value via a right-tail–sided significance test . If the test’s significance value was below 0 . 05 , we considered the preseizure interval formed by the adjacent segments to exhibit significantly lower centrality entropy than the one obtained in the control period and we identified it as a critical phase . In addition , we made use of the Kolmogorov Smirnov test to assess that the critical phase distribution across patients was significantly different from a distribution of randomly placed significant clusters of the same duration . In general , to test paired or unpaired samples across time ( e . g . , preseizure versus control period ) or recording sites ( e . g . , seizure-onset sites across different periods ) per patient , we made use of the Wilcoxon test for small sample sizes and the t test for sufficiently large numbers of samples ( >30 ) . However , in most comparisons , noncomparable or very large numbers of samples could overestimate statistical effects . Therefore , in those cases , we computed and reported the effect size using Cohen’s d ( based on the difference between medians and/or means for Wilcoxon test and/or t test ) . To deal with the multiple-comparison problem , we applied the Holm–Bonferroni correction [65] over patients in Fig 3 and over combinations of regional comparisons in Fig 5 . We resorted to linear regression and the coefficient of determination ( R-squared ) to evaluate the association between crossperiod differences in state probability and/or heterogeneity and the decrease in centrality entropy in Fig 3 and Fig 4 . Finally , mean connectivity values across electrode pairs were computed using the Fisher transform [66] . The main results combined within-subject and group-level statistical tests depending on the question at hand . Within-subject tests can be found in Fig 2A , Fig 3C ( right ) , and Fig 5 . Group-level tests can be found in Figs 2B , 2C , 3C ( left ) , 4B , 4C , and 4D .
|
Understanding and predicting the generation of seizures in epileptic patients is fundamental to improving the quality of life of the more than 1% of the world population who suffer from this illness . Although seizure prediction has made important advances over the last decade , there is a lack of understanding of the common principles explaining the transitions that brain activity undergoes before a seizure . In this study , we characterized this transition from a novel perspective grounded on the mathematical analysis of continuous recordings inside the brains of epileptic patients over several days using depth electrodes . We show that the critical period preceding a seizure unfolds in a two-stage process . It begins with a phase of several hours when the highly correlated activity in the preceding days is altered , and it proceeds with a second , shorter phase of decrease in global connectivity before the seizure onset . Furthermore , our analysis reveals that these global alterations are more locally manifested in areas that are selected for surgical treatment . Our study suggests that preseizure activity might follow global stereotyped dynamics that could be targeted and modulated to prevent epileptic seizures .
|
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"Abstract",
"Introduction",
"Results",
"Discussion",
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"and",
"methods"
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2018
|
Degenerate time-dependent network dynamics anticipate seizures in human epileptic brain
|
Clostridium difficile spores must germinate in vivo to become actively growing bacteria in order to produce the toxins that are necessary for disease . C . difficile spores germinate in vitro in response to certain bile acids and glycine . In other sporulating bacteria , proteins embedded within the inner membrane of the spore sense the presence of germinants and trigger the release of Ca++-dipicolinic acid ( Ca++-DPA ) from the spore core and subsequent hydrolysis of the spore cortex , a specialized peptidoglycan . Based upon homology searches of known germinant receptors from other spore-forming bacteria , C . difficile likely uses unique mechanisms to recognize germinants . Here , we identify the germination-specific protease , CspC , as the C . difficile bile acid germinant receptor and show that bile acid-mediated germination is important for establishing C . difficile disease in the hamster model of infection . These results highlight the importance of bile acids in triggering in vivo germination and provide the first description of a C . difficile spore germinant receptor . Blocking the interaction of bile acids with the C . difficile spore may represent an attractive target for novel therapeutics .
Clostridium difficile infections ( CDI ) are steadily increasing in the United States and other countries [1] , [2] . The use of broad-spectrum antibiotics , often unrelated to CDI , leads to alteration of the colonic microbiota that normally provides resistance to C . difficile colonization [3] . In a host , C . difficile spores must germinate to form the actively growing , anaerobic bacteria that produce the two toxins that are necessary for disease ( TcdA and TcdB ) [4] , [5] , [6] . These two toxins are secreted by the bacterium where they then enter host epithelial cells by receptor-mediated endocytosis and , upon escape into the cytosol , glucosylate members of the Rho-family of GTPases [7] . The action of these toxins lead to symptoms normally associated with CDI ( e . g . diarrhea ) and release of C . difficile spores into the environment [8] . Metabolically dormant spores are formed by selected bacterial species in response to changes in environmental conditions , including nutrient availability [9] . During spore formation , the proteins required for germination are pre-packaged into the spore , priming the spore to germinate when conditions are appropriate [10] . In many spore-forming species , the interaction of the metabolically dormant spore with specific germination-inducing molecules ( germinants ) leads to the release of large amounts of Ca++-dipicolinic acid ( DPA ) from the dehydrated spore core in exchange for water . Subsequently , hydrolases embedded within the spore cortex , a specialized peptidoglycan , become activated and begin cortex hydrolysis . Once the core is rehydrated and the cortex is degraded , a vegetative cell begins to grow out from the germinated spore . This process is largely conserved among spore-forming bacteria , though the signals that initiate germination can vary . In Bacillus subtilis , L-alanine or a mixture of L-asparagine , glucose , fructose and potassium ions triggers germination , while spores of certain strains of Clostridium perfringens initiate germination in response to inorganic phosphate and sodium ions [11] . The proteins that respond to these signals , ger receptors , share homology among many spore-forming bacteria . However , based on homology searches , C . difficile is not among the spore-forming bacteria that have such canonical germinant receptors , suggesting that C . difficile responds to unique germinants or uses a novel mechanism for spore germination or both [12] . Approximately 30 years ago , Wilson and others showed that certain bile acids increased the frequency of C . difficile colony formation from environmental samples [13] , [14] , [15] . Bile acids are small amphipathic , cholesterol-based molecules that aid in the absorption of fats and cholesterol during digestion . Typically , the liver synthesizes two main bile acids , cholic acid ( 3α , 7α , 12α-trihydroxy-5β-cholanic acid ) and chenodeoxycholic acid ( 3α , 7α-dihydroxy-5β-cholanic acid ) , which are further modified with the addition of either a taurine or glycine amino acid [16] . Building on the work of Wilson and others , we demonstrated that all cholic acid derivatives can stimulate C . difficile colony formation from spores with approximately equal efficiency [17] . Further , we showed that exposure to the combination of taurocholic acid and glycine were required to initiate C . difficile spore germination [17] . Interestingly , chenodeoxycholic acid was unable to stimulate colony formation or the initiation of spore germination [17] . Subsequent studies identified chenodeoxycholic acid as a competitive inhibitor of cholic acid-mediated germination [18] , [19] . While the chemical signals that promote the initiation of C . difficile spore germination are known , the proteins that respond to these germinants had not been identified . Here , we applied a screen , previously used to identify loci involved in B . subtilis spore germination [20] , to the identification of C . difficile germination-null phenotypes . Using a combination of traditional chemical mutagenesis and contemporary massively parallel DNA sequencing , we identified single nucleotide polymorphisms ( SNPs ) that give rise to ger phenotypes and characterized the resulting strains . We found that mutations in the C . difficile cspC gene can abrogate the initiation of C . difficile spore germination . Further , we identified a mutation in cspC that allows chenodeoxycholic acid to act as a spore germinant , instead of an inhibitor of germination . These results suggest that C . difficile CspC is the bile acid-sensing germinant receptor . The identification of the molecular target of bile acids on the C . difficile spore has allowed us to test , for the first time , the in vivo role of bile acid-mediated germination during C . difficile infection .
Previously , we demonstrated that the cholic acid family of bile acids causes spores to initiate germination in rich medium [17] . To identify the C . difficile bile acid germinant receptor , we employed a strategy schematized in Figure 1A . We mutagenized C . difficile strain UK1 [19] using the DNA alkylating agent ethyl methanesulfonate ( EMS ) . The EMS-mutagenized bacteria were allowed to recover during overnight incubation in fresh medium and spread on solid medium to allow efficient spore formation . Spores were purified and incubated overnight at 37°C in rich medium+10% w/v taurocholic acid [ ( TA ) ; 185 mM] to germinate those spores that were still able to respond to TA as a germinant . The spore suspension ( containing both germinated and non-germinated spores ) was incubated at 65°C for 30 minutes to heat-kill the germinated spores; dormant , non-germinated spores are resistant to 65°C . The surviving spores were artificially germinated using thioglycollate and lysozyme [21] and then plated on rich medium to recover , as colonies , the artificially germinated spores . Mutants that failed to germinate under these conditions were enriched and 10 colonies , among thousands , were isolated and tested for the ability of their spores to germinate in response to TA . Spores from all 10 isolates ( ger1–ger10 ) were unable to form colonies on rich medium+TA , but did form colonies after artificial germination [21] ( Figure 1B; only wild-type C . difficile UK1 and ger 1 are shown ) . This suggests that the ger mutants are either blocked at the outgrowth stage of germination ( inability to grow as a vegetative cell from the germinated spore ) or blocked in the initiation of germination ( inability to respond to TA as a germinant ) To determine at what stage the mutants are blocked , we analyzed the initiation of germination as measured by a decrease in A600 over time . Wild-type C . difficile UK1 initiated germination in the presence of 5 mM TA and 50 mM TA but not in the absence of TA ( Figure 2A ) . However , spores derived from C . difficile ger1 ( Figure 2B ) did not initiate germination even at the highest TA concentration used ( 50 mM ) . Also , while wild-type C . difficile released DPA in response to TA and glycine , C . difficile ger1–ger10 spores were unable to release the majority of the stored DPA ( Figure 2C ) ; Ca++-DPA release from the spore core is one of the first measurable events in bacterial spore germination [10] . Together , these results suggest that the C . difficile ger isolates are defective in the earliest stages of spore germination and may be defective in recognizing TA as a germinant . The locations of the SNP ( s ) that gave rise to the germination-null phenotypes were determined using Illumina sequencing technology ( Table S1 ) . The DNA sequence of the 10 ger isolates were compared to determine if all had mutations in the same locus or loci . All isolates had in common mutations in 7 loci , with 6 loci having conserved mutations among all isolates ( Table 1 ) . Interestingly , C . difficile ger1–ger10 had several different mutations in the cspBAC locus ( Table 2 ) . In Clostridium perfringens , CspA , CspB and CspC are germination-specific proteases that cleave the spore cortex lytic enzyme , SleC , to the active form [22] , [23] , [24] . This allows precise control of the timing of cortex hydrolysis during germination . C . perfringens CspA , CspB and CspC , all members of the subtilisin-family of proteases , have identifiable catalytic triads , while , in C . difficile , only CspB has obvious catalytic residues . In wild-type C . difficile , cspB and cspA coding sequences have been fused . Further , the CspA and CspC catalytic triads appear to have been lost ( Figure S1 ) . Eight of the 10 mutant strains had mutations in cspC ( Table 2 ) , suggesting that , despite the apparent absence of catalytic activity , wild-type CspC may still have a role in C . difficile spore germination . To investigate the role of CspC in C . difficile spore germination , we generated a site-directed mutation using TargeTron technology [4] , [25] , [26] , [27] , [28] . The resulting strain , C . difficile JSC10 ( cspC::ermB ) , is unable to initiate germination in response to TA ( Figure 3B ) unless provided with the cspBAC locus expressed in trans from a plasmid ( Figure 3C ) ; wild-type C . difficile UK1 initiates germination in response to TA ( Figure 3A ) . Interestingly , when C . difficile JSC10 was complemented with the cspBAC locus , spores generated from this strain appear to germinate more rapidly than do C . difficile UK1 spores . Further work will be needed to characterize the germination rates of these spores . When analyzed for DPA release , wild-type C . difficile UK1 and C . difficile JSC10 ( pJS123 ) released DPA while C . difficile JSC10 was unable to release DPA ( Figure 3D ) . It was previously reported that a mutation in sleC prevents C . difficile spore germination [27] . Thus , mutations that affect germination do not necessarily indicate that the gene in which the mutation lies normally codes for a germinant receptor . To test the hypothesis that C . difficile CspC is a bona fide germinant receptor , we again mutagenized C . difficile UK1 and allowed the mutagenized bacteria to form spores . The purified spores were plated on BHIS medium supplemented with 0 . 5 mM chenodeoxycholic acid . We looked for colony formation after 48 hours of incubation at 37°C . Chenodeoxycholic acid is a competitive inhibitor of cholic acid-mediated germination for C . difficile UK1 [18] , [19] and other C . difficile strains [29] . Thus , in order to form colonies , these spores must have acquired an altered germinant specificity . Colonies were isolated and the phenotype confirmed as described above . We sequenced cspC from these newly generated strains and identified a single mutation , G457R . When the cspCG457R allele was used to complement C . difficile JSC10 , we observed that this strain germinated in response to either TA or chenodeoxycholic acid ( Figure 4 ) . These results suggest that C . difficile CspC is a receptor for bile acid germinants . The in vivo signals that trigger C . difficile spore germination are unknown , though bile acids are obvious candidates [30] . To test whether bile acid-mediated germination is required for C . difficile infection , Syrian hamsters were treated with clindamycin to induce sensitivity to C . difficile colonization and infection; the Syrian hamster has been used for approximately 30 years to assess C . difficile virulence and recapitulates the most severe form of human C . difficile infection , pseudomembranous colitis [31] . Hamsters were gavaged with 1 , 000 C . difficile UK1 spores or C . difficile JSC10 spores or C . difficile JSC10 ( pJS123 ) spores and monitored for signs of CDI . Animals infected with either C . difficile UK1 or C . difficile JSC10 ( pJS123 ) rapidly succumbed to disease . However , C . difficile JSC10 was unable to cause fulminant CDI and exhibited reduced virulence ( Chi-squared: p-value<0 . 02 ) ( Figure 5 ) . These results show that bile acid-mediated germination is important for C . difficile disease and suggest that inhibiting C . difficile spore germination may have therapeutic potential .
Classically , germinant receptors are embedded within the inner membrane of bacterial spores [10] , [32] . Germinants must pass through layers of coat proteins , an outer membrane , the cortex and germ cell wall before interacting with their respective receptors . Upon interaction , Ca++-DPA is released from the spore core in exchange for water . This exchange is essential to rehydrate the core and allow metabolism to begin . In some bacteria , the release of Ca++-DPA triggers the activation of cortex hydrolases allowing a vegetative bacterium to grow from the germinating spore [33] . In C . perfringens the germination-specific proteases cleave the cortex hydrolase , SleC , to an active form [23] , [24] . The signals that stimulate this proteolysis in C . perfringens are not known . In C . perfringens , CspA , CspB and CspC are all members of the subtilisin family of serine proteases and have complete catalytic triads , suggesting that any one of these proteins can activate SleC-mediated cortex hydrolysis . In C . difficile , the cspB and cspA coding sequences have been fused [34] . Only CspB contains a complete catalytic triad while CspA and CspC have lost their catalytic residues . Based on sequence analysis , one would predict that only CspB would have an active role in stimulating C . difficile cortex hydrolysis . Indeed , a recent study by Adams and colleagues has shown that CspBA undergoes autoprocessing to generate CspB , which can cleave the cortex hydrolase pro-SleC to an active form [34] . We have provided evidence that C . difficile CspC plays an active and essential role during germination by functioning as the bile acid germinant receptor . In C . difficile CspC , two of the three catalytic residues have been lost , T170 ( conserved H198 in C . perfringens CspC ) and G485 ( conserved S517 in C . perfringens CspC ) ( Figure S1 – red ) . Interestingly , several the SNPs identified in the germination-null screen lie near T170 or G485 ( Figure S1 – green ) . When we screened for C . difficile mutants that germinated in response to an inhibitor of germination ( chenodeoxycholic acid ) , we identified G457R ( Figure S1 – yellow ) . This residue is approximately 30 amino acids removed from G485 . G457R , being a fairly drastic substitution , may modify the bile acid binding pocket to allow for a less-stringent recognition of germination-inducing bile acids . The 12α-hydroxyl group that differentiates between cholic acid and chenodeoxycholic acid protrudes from the molecule . This hydroxyl , in wild-type CspC , may penetrate the hypothetical binding pocket , resulting in a conformational change that is transmitted to C . difficile CspB [34] . CspB would then cleave SleC , initiating cortex hydrolysis [34] . Two of the identified SNPs in the germination-null screen were nonsense mutations in cspBA ( Q632stop and W359stop ) . In the CspBA hybrid protein , Q632 is located in CspA while W359 is in CspB . The generation of a premature stop codon in cspB would result in a truncated protein with an incomplete catalytic triad [34] . The precise role of CspA in C . difficile spore germination is unknown , though our data suggest that CspA may be important . Our data indicate that host-derived bile acids mediate C . difficile spore germination and that recognition of bile acids is required for infection in the hamster model to be maximally effective . Still , 50% of the animals succumbed to disease when infected with the cspC mutant , suggesting ( i ) that enough spores spontaneously germinated in the GI tract of the animal to cause disease , or ( ii ) that other , as yet unidentified , host signals can stimulate spore germination . Lysozyme is able to induce germination of C . difficile spores in vitro [21] . However , recent evidence has suggested that lysozyme at physiological levels may not be able to stimulate C . difficile spore germination [35] and we observe most efficient lysozyme-mediated spore germination after spore coat removal . Further study will be needed to determine if other signals provided by the host can stimulate C . difficile spore germination . Previously , we identified inhibitors of C . difficile spore germination that had increased potency when compared to chenodeoxycholic acid [19] . It is not yet known whether these germination inhibitors have therapeutic importance but a recent study by Howerton and coworkers has shown dosing antibiotic-treated mice with an inhibitor of germination can reduce disease severity [36] . The identification of the molecular target of bile acids in the C . difficile spore may allow even more potent inhibitors to be rationally designed . Further , these inhibitors may aid in the identification in the bile acid-binding pocket in CspC by providing high-affinity interaction , instead of the relatively low affinity ( in the mM range ) for taurocholic acid [19] , [37] . The relative affinities of bile acids for the C . difficile spore were determined using kinetics of germination [18] , [19] , [37] , [38] , [39] . While these studies were important milestones in determining which bile acids affect C . difficile germination and what features are important for triggering or inhibiting germination , the precise interaction of the bile acid with the germinant receptor has not been analyzed . Also , it has been proposed that the bile acid germinant receptor binds taurocholic acid cooperatively [37] . The identification of the bile acid germinant receptor now permits testing these interactions . Stimulation of cortex hydrolysis may not be sufficient to fully activate C . difficile spore germination . C . difficile spores suspended in buffered taurocholic acid alone do not initiate spore germination unless a co-germinant , glycine , is added [17] . This suggests that a second , glycine-sensing receptor is required to trigger germination and the return to vegetative growth . We hypothesize that this other receptor may be localized to the inner membrane to aid in the release of Ca++-DPA from the spore core during germination .
All animal procedures were performed with prior approval from the Texas A&M Institutional Animal Care and Use Committee . Animals showing signs of disease were euthanized by CO2 asphyxia followed by thoracotomy as a secondary means of death , in accordance with Panel on Euthanasia of the American Veterinary Medical Association . Texas A&M University's approval of Animal Use Protocols is based upon the United States Government's Principles for the Utilization and Care of Vertebrate Animals Used in Testing , Research and Training and complies with all applicable portions of the Animal Welfare Act , the Public Health Service Policy for the Humane Care and Use of Laboratory Animals , and all other federal , state , and local laws which impact the care and use of animals . C . difficile UK1 [19] ( Table 3 ) was grown in a Model B , Coy Laboratory Chamber at 37°C under anaerobic conditions ( 85% nitrogen , 10% hydrogen , 5% carbon dioxide ) in BHIS medium ( Brain Heart Infusion supplemented with 5 g/L yeast extract and 0 . 1% L-cysteine ) . Antibiotics were added as needed ( 20 µg/ml thiamphenicol , 10 µg/ml lincomycin , 5 µg/ml rifampin ) . E . coli DH5α [40] was routinely grown at 37°C in LB medium . Antibiotics were added as needed ( 50 µg/ml kanamycin or 20 µg/ml chloramphenicol ) . Bacillus subtilis was grown at 37°C in LB medium and antibiotics were added as needed ( 2 . 5 µg/ml chloramphenicol , 5 µg/ml tetracycline ) . One overnight culture of C . difficile UK1 was diluted 1∶100 in 5 ml fresh medium and grown to OD600 = 0 . 5 before adding ethyl methanesulfonate ( EMS ) to 1% final concentration . The culture was incubated for 3 hours , washed in BHIS medium and recovered overnight in 40-ml BHIS . A sample was taken to score mutation frequency on rifampin-containing BHIS agar medium ( Table S2 ) and 50-µL samples were spread on 20 BHIS plates to allow spore formation of the mutagenized bacteria . Plates were incubated for 4 days before spores were harvested and purified as described previously [19] . Purified spores were suspended in 40 ml BHIS+10% w/v taurocholic acid ( TA ) and incubated overnight at 37°C to germinate those spores that recognized TA as a germinant . Spores were collected and heated to 65°C for 1 hour to inactivate germinated spores ( dormant spores are resistant to 65°C ) . To germinate the remaining dormant spores , spores were again collected and treated with 250 mM thioglycollate for 30 min at 50°C followed by incubation with 4 mg/ml lysozyme for 15 min at 37°C [21] and 25-µL aliquots were spread on BHIS agar plates to allow spore formation . To enrich for germination null phenotypes , spores were again collected and germinated as described above . To select for mutations that change the affinity of the germinant receptor from TA to chenodeoxycholic acid , C . difficile UK1 was mutated as described above with the following modification . Purified spores generated from mutated bacteria were spread on BHIS medium supplemented with 0 . 5 mM chenodeoxycholic acid . Colonies from spores that germinated on this medium were purified and the germination phenotype of their spores was confirmed using standard germination techniques ( below ) . High-quality , high-molecular weight genomic DNA was extracted , as described previously [41] , [42] , and submitted to Tufts University School of Medicine Genomics Core facility for Paired-End 50 Illumina re-sequencing . The samples were sonicated in a 4°C water bath with a Branson sonicator . Illumina libraries were then prepared using the Illumina TruSeq genomic DNA kit and tagged with individual Illumina barcodes . Final libraries were checked on said advanced analytical device , and then diluted to 10 nM prior to being loaded on a lane of an Illumina HiSeq2000 . Illumina single-end sequencing was carried out for 50 cycles . The resulting sequence data in fastq format was aligned against the C . difficile R20291 genome using CLC Genomics Workbench , and SNPs were called at any position where more than 66% of the reads had an alternate base from the reference The Tn916 oriT from Bacillus subtilis Bs49 was amplified using oligonucleotides 5′Tn916SLIC and 3′Tn916SLIC ( Table 4 ) and introduced into the BstAPI restriction site of pBL100 [43] using Sequence and Ligation Independent Cloning ( SLIC ) , generating pJS107 . The pJS107 plasmid was used as a TargeTron vector to introduce mutations in to C . difficile . The group II intron insertion sites for C . difficile cspC were identified using an algorithm that can be found at http://dna . med . monash . edu . au/~torsten/intron_site_finder/ . The intron fragment was generated as described previously using oligonucleotides cspC ( 115 ) EBS2 , cspC ( 115 ) IBS , cspC ( 115 ) EBS1 and EBSU , cloned into pCR2 . 1-TOPO and then sub-cloned at the HindIII and BsrGI sites of pJS107 , yielding pJS130 . The B . subtilis – C . difficile shuttle vector , pJS116 , was generated through the introduction of the Tn916 oriT into the ApaI restriction site of the E . coli – C . difficile shuttle vector , pMTL84151 [44] , using oligonucleotides 5′Tn916ApaI and 3′Tn916ApaI which amplify the Tn916 oriT . The C . difficile cspBAC loci were amplified with Phusion polymerase using 5′cspBA_CXbaI and 3′cspBA_CXhoI oligonucleotides and cloned into the B . subtilis – C . difficile shuttle vector , pJS116 . The nucleotide sequences for all constructs were confirmed before use . B . subtilis BS49 was used as a donor for conjugation with C . difficile . Plasmids were introduced into B . subtilis BS49 using standard techniques . Conjugation experiments were carried out as described previously [28] . C . difficile transconjugants were screened for the presence of Tn916 using tetracycline resistance . Thiamphenicol-resistant , tetracycline-sensitive ( plasmid-containing , transposon negative ) transconjugants were selected for further use . Potential TargeTron mutants were generated by screening lincomycin-resistant C . difficile for the insertion of the intron into C . difficile cspC using primers specific for full-length C . difficile cspC , the 5′ intron insertion site and the 3′ intron insertion site and a positive clone was identified , C . difficile JSC10 . Spores were purified from BHIS agar medium as described previously [19] with the following modification . Spores from antibiotic-resistant strains ( i . e . plasmid-containing or mutant strains ) were generated on SMC medium [45] supplemented with appropriate antibiotics and purified as described previously . The initiation of spore germination was analyzed in a Lambda 25 Perkin Elmer spectrophotometer at A600 every 18 seconds , as described previously [17] , [18] , [19] . DPA release was measured by incubating purified spores at 37°C in germination salts ( 0 . 3 mM ( NH4 ) 2SO4 , 6 . 6 mM KH2PO4 , 15 mM NaCl , 59 . 5 mM NaHCO3 and 35 . 2 mM Na2HPO4 ) supplemented with 10% TA and 1 mM glycine for 1 hour . Equal aliquots were incubated at 100°C as a measure of 100% DPA release ( positive control ) or incubated at 37°C in germination salts without TA addition ( negative control ) . Spores were sedimented and the supernatant was analyzed at A270 to measure the released DPA [46] . Female Syrian golden hamsters , 80 g–120 g , were housed individually in cages and had ad libitum access to food and water for the duration of the experiment . To induce susceptibility to C . difficile infection , hamsters were gavaged with 30 mg/kg clindamycin [31] , [47] . After 5 days , hamsters were gavaged with 1 , 000 spores of C . difficile UK1 or C . difficile JSC10 or C . difficile JSC10 pJS123 , 10 animals per strain , and monitored for signs of disease ( lethargy , poor fur coat and wet tail ) . Hamsters showing signs of disease were euthanized by CO2 asphyxia followed by thoracotomy as a secondary means of death in accordance with Panel on Euthanasia of the American Veterinary Medical Association . Fecal samples were collected daily and cecum samples were collected on those hamsters requiring euthanasia . All animal studies were performed with prior approval from the Texas A&M University Institutional Animal Care and Use Committee . Experiments were performed in triplicate and , where indicated , error bars represent 1 standard deviation from the mean . A representative sample for the initiation of germination experiments at A600 is shown , error bars obscure the data . The data varied by <5% . Statistical significance of DPA release was performed using the Student's T-test . Differences in hamster survival between those infected with C . difficile JSC10 and either C . difficile UK1 or C . difficile JSC10 pJS123 were analyzed using the Log-rank test ( GraphPad Prism ) .
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Clostridium difficile infections ( CDI ) are steadily increasing in the United States and other countries . C . difficile spores are the infectious agent and often contaminate environmental surfaces . However , to initiate infection , C . difficile spores must germinate in vivo to actively growing bacteria . Certain bile acids and glycine are the most effective compounds that stimulate C . difficile spore germination . While the signals that stimulate germination by C . difficile spores are known , with what these compounds interact remained unknown . Here , we identified the germination-specific protease , CspC , as the bile acid germinant receptor . In C . difficile , CspC is not predicted to have catalytic activity . However , we find that mutations in cspC alter the specificity of germinant recognition or abrogate the ability of C . difficile spore to germinate in response to bile acids . Further , we show that bile acid recognition by C . difficile spores is important for establishing infection in an animal model of C . difficile disease . Our results suggest a unique mechanism for C . difficile spore germination through direct stimulation of cortex hydrolysis by a spore germinant . A detailed understanding of germinant recognition by C . difficile CspC may aid in the identification of germination-blocking compounds , which may have importance in hindering C . difficile colonization .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"bacteriology",
"bacterial",
"physiology",
"microbial",
"pathogens",
"biology",
"microbiology"
] |
2013
|
Bile Acid Recognition by the Clostridium difficile Germinant Receptor, CspC, Is Important for Establishing Infection
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Receptor Ser/Thr protein kinases are candidates for sensors that govern developmental changes and disease processes of Mycobacterium tuberculosis ( Mtb ) , but the functions of these kinases are not established . Here , we show that Mtb protein kinase ( Pkn ) D overexpression alters transcription of numerous bacterial genes , including Rv0516c , a putative anti-anti–sigma factor , and genes regulated by sigma factor F . The PknD kinase domain directly phosphorylated Rv0516c , but no other sigma factor regulator , in vitro . In contrast , the purified PknB and PknE kinase domains phosphorylated distinct sigma regulators . Rather than modifying a consensus site , PknD phosphorylated Rv0516c in vitro and in vivo on Thr2 in a unique N-terminal extension . This phosphorylation inhibited Rv0516c binding in vitro to a homologous anti-anti–sigma factor , Rv2638 . These results support a model in which signals transmitted through PknD alter the transcriptional program of Mtb by stimulating phosphorylation of a sigma factor regulator at an unprecedented control site .
Mycobacterium tuberculosis ( Mtb ) is among the world's most harmful pathogens , causing approximately two million deaths annually [1] . In addition to the emergence of multi-drug–resistant strains , Mtb evades current therapeutics by shifting from active infection to a persistent , metabolically dormant state [2] . This transition exemplifies the distinctive Mtb life cycle , which encompasses unique developmental adaptations to distinct environments [3] . Little is known about the signaling mechanisms that mediate the biochemical changes that initiate and maintain the stages of Mtb development . Candidate regulators of Mtb development include receptor Ser/Thr protein kinases ( STPKs ) that modulate intracellular events in response to external stimuli . In eukaryotes , homologous STPKs sense environmental cues and transduce signals that regulate virtually all aspects of cell physiology . The Mtb genome encodes 11 such Hanks-type ( also called “eukaryotic-like” ) STPKs , including nine putative transmembrane receptor kinases [4] . Although the activating stimuli for these kinases have not been identified , the extracellular C-terminal sensor domains include a β-propeller interaction motif , a PASTA repeat thought to bind cell wall structures , and a redox-sensitive DsbG homolog [5–8] . The intracellular , N-terminal kinase domains structurally resemble eukaryotic homologs , and similar receptor STPKs are widely distributed in bacterial genera . The first reported bacterial STPK substrates include pThr-binding forkhead-associated ( FHA ) domains [9] , metabolic enzymes [10] , and apparent regulators of cell division [11 , 12] , but the mechanisms of signaling in vivo are not established . Genetic studies suggest that two of the 11 Mtb STPKs are essential for growth [13] and that the STPKs regulate characteristics such as cell shape [11] , virulence [14] , and nitrogen balance [15] . Identifying the intracellular targets of Mtb STPKs is essential to understanding their mechanistic roles in Mtb biology . A second class of bacterial Ser/Thr kinases , the anti–sigma factors , regulates gene expression by controlling alternative sigma factors [16] . Alternative sigma factors , such as sigma B ( SigB ) and sigma F ( SigF ) in Bacillus subtilis , mediate transcriptional responses to environmental cues by binding RNA polymerase and mediating promoter recognition . Work on B . subtilis has established the paradigm by which complex regulatory cascades influence alternative sigma factor activity ( reviewed by Hughes and Mathee [16] ) . Anti–sigma factor proteins ( e . g . , RsbW ) directly sequester cognate alternative sigma factors and prevent RNA polymerase binding . Anti-anti–sigma factors ( e . g . , RsbV ) relieve this transcriptional repression by binding the anti–sigma factor . The anti–sigma factors phosphorylate anti-anti–sigma factors on a conserved Ser or Thr , and this modification promotes dissociation of the complex . This basic regulatory organization is recapitulated for multiple layers in which paralogs of anti–sigma factors and anti-anti–sigma factors switch partners and ultimately determine the concentration of the active sigma factor [17] . In this “partner switching” mechanism , anti–sigma factor paralogs play two distinct roles . Some anti–sigma factors ( e . g . , RsbW ) antagonize transcription by directly sequestering alternative sigma factors . In contrast , other anti–sigma factors ( e . g . , RsbT ) act upstream to stimulate transcription by binding and activating the master “environmental sensing” phosphatase ( RsbU in B . subtilis [18] ) . This phosphatase reactivates anti-anti–sigma factors , which bind the cognate anti–sigma factor , thus increasing the concentration of free sigma factor . Environmental cues affect the phosphorylation state of upstream anti-anti–sigma factor paralogs ( such as RsbS and the RsbRA-D proteins ) , and these proteins form a complex ( termed the “stressosome” ) that binds the positive regulator of the phosphatase [19] . The central role of Ser/Thr phosphorylation in anti-anti–sigma factor regulation and the established role of eukaryotic kinases in gene regulation led us to test the hypothesis that the eukaryotic-like STPKs may impinge on transcription regulated by alternative sigma factors . Here , we demonstrate that increasing the activity of the PknD STPK in Mtb resulted in specific phosphorylation of a single anti-anti–sigma factor homolog , Rv0516c . Simultaneously , the Rv0516c gene was activated and transcription of genes regulated by the SigF alternative sigma factor was coordinately altered . PknD phosphorylated Rv0516c at a novel site , Thr2 , distinct from conserved Ser/Thr phosphorylation sites in the anti-anti–sigma factor family . Thr2 phosphorylation abolished binding to another anti-anti–sigma factor . These results demonstrate that PknD phosphorylates a putative sigma factor regulator in Mtb , alters binding of a cognate regulator , and , by a mechanism that has not been determined , changes the expression of SigF-dependent genes .
To investigate the pathways regulated by receptor STPK signaling , we constructed Mtb strains expressing either wild-type ( WT ) or kinase-dead ( Asp138Asn ) PknD under the control of an acetamide-inducible promoter [20] . The Asp138Asn mutation in the catalytic site reduced the in vitro activity of kinase domain ∼2 , 600-fold ( Figure S1 ) . In this approach , excess kinase substituted for an activating signal to stimulate downstream pathways . Western blotting with anti-PknD and anti-pThr antibodies showed that the WT or mutant kinases accumulated after induction and produced a concomitant increase in Thr phosphorylation ( Figure 1A ) . Expression of the attenuated Asp138Asn mutant produced a much smaller increase in phosphorylation of cellular targets . Consistent with the idea that the expressed PknD ( directly or indirectly ) mediated the observed phosphorylation in vivo , cellular–protein phosphorylation was blocked when the PknD variants were induced in the presence of SP600125 ( Figure S1B ) , a c-Jun N-terminal kinase ( JNK ) inhibitor that shows specificity for PknD over other Mtb STPKs ( C . Mieczkowski and T . Alber , unpublished data ) . Transcriptional profiling using microarrays confirmed the induction of PknD transcripts and revealed a set of genes regulated by PknD overexpression in a kinase-dependent manner ( Figure 1B; Table S1 ) . Remarkably , the transcripts most differentially expressed in the strain expressing WT PknD ( Figure 1B ) included the genes with the largest reductions in transcription during log phase growth of an Mtb mutant harboring a deletion of sigF [21] . Moreover , the Rv0516c gene , which is homologous to anti-anti–sigma factors , was dramatically induced by PknD overexpression . The established role of phosphorylation in anti-anti–sigma factor regulation supported the hypothesis that PknD specifically phosphorylates Rv0516c . To test this idea , we measured the phosphorylation by the purified PknD kinase domain of all predicted Mtb homologs of the B . subtilis alternative sigma factor regulators . Potential regulators were identified using iterative PSI-BLAST searches for homologs of Rv0516c , SpoIIAA , and SpoIIAB , and putative homologs were confirmed using 3D-PSSM [22] to verify that the predicted fold resembled anti– or anti-anti–sigma factors ( Figure 2 ) . All of the identified sigma factor regulators were cloned , expressed in Escherichia coli , and purified . Using a [γ-32P]ATP transfer assay , we found that the PknD kinase domain ( PknD1–378 ) efficiently phosphorylated Rv0516c , but not any of the other sigma factor regulator homologs ( Figure 3A ) . The SP600125 inhibitor blocked this Rv0516c phosphorylation ( Figure 3B ) in a dose-dependent manner , indicating that PknD catalyzed the observed phosphorylation . Rv0516c phosphorylation was reversed by PstP ( Figure 3C ) , the Mtb protein Ser/Thr phosphatase that dephosphorylates all Mtb STPK substrates tested to date [23] . These results showed that PknD and PstP act on the putative anti-anti–sigma factor Rv0516c in vitro . To determine if Mtb UsfX ( Rv3287c ) , the anti–sigma factor Ser kinase that controls SigF [24] , also phosphorylates Rv0516c , we incubated these proteins under conditions in which UsfX phosphorylated the model substrate , myelin basic protein ( MyBP ) . In contrast to PknD , UsfX failed to phosphorylate Rv0516c ( Figure S2 ) . The anti–sigma factor paralogs RshA [25] and Rv0941c also failed to phosphorylate Rv0516c ( unpublished data ) . Thus , unlike anti-anti–sigma factors that are phosphorylated by anti–sigma factors , Rv0516c is phosphorylated by a eukaryotic-like STPK , PknD . To determine if sigma factor regulator phosphorylation is a general function of Mtb STPKs , we assayed the ability of four other Mtb kinase domains ( PknA , PknB , PknE , and PknK ) to phosphorylate Rv0516c and the eight other purified Mtb sigma factor regulators . At concentrations of each kinase domain equally active in phosphorylating the nonspecific substrate , MyBP , Rv0516c was phosphorylated most efficiently by PknD , and to a lesser extent by PknB and PknE ( Figures 3D and S3 ) . Neither PknA nor PknK phosphorylated any of the sigma factor regulators in vitro . PknB and PknE also phosphorylated the anti–sigma factor RshA ( Rv3221A ) . The role of this phosphorylation remains to be determined , as the phosphorylation of an anti–sigma factor has not been described previously . PknE weakly phosphorylated Rv1904 and RsfA ( Rv1365c ) . The five kinase domains tested failed to phosphorylate any of the other sigma factor regulators . The specific in vitro phosphorylation of Rv0516c by the PknD kinase domain correlated with the transcriptional stimulation of Rv0516c by PknD in vivo . To explore the mechanism of PknD regulation of Rv0516c , we determined the site of Rv0516c phosphorylation by mass spectrometry and protein sequencing ( Figure 4 ) . Electrospray ion-trap mass spectrometry revealed a molecular mass of 17 , 392 . 4 ± 1 for purified , recombinant Rv0516c phosphorylated to completion in vitro using the PknD kinase domain . This mass corresponded to mono-phosphorylated Rv0516c ( the expected MR of the unphosphorylated protein is 17 , 312 . 7 ) . Matrix-assisted laser desorption ionization ( MALDI ) tandem time-of-flight ( TOF ) analysis of trypsin-digested phospho-Rv0516c indicated that the peptide consisting of the N-terminal nine residues was the only phosphopeptide ( Figure 4A ) . Tandem MS and N-terminal sequencing showed that Thr2 accounted for all of the Rv0516c phosphorylation ( Figure 4B ) . Eight Rv0516c N-terminal mutants—individual Ala substitutions of the five Ser or Thr residues in the N-terminal segment as well as deletions of up to eight residues—were created to confirm phosphorylation at Thr2 ( Figure 4C ) . As expected , PknD failed to phosphorylate the Thr2Ala Rv0516c and the two deletion mutants lacking Thr2 . The Thr7Ala variant showed a reduction in phosphorylation , suggesting that Thr7 plays a role in kinase binding and recognition . These data demonstrated that PknD phosphorylates Rv0516c on a unique N-terminal site , Thr2 . To determine if PknD phosphorylates Rv0516c at Thr2 in vivo , we constructed Mtb strains that co-expressed Rv0516c ( WT or Thr2Ala fused to a C-terminal 3XFLAG tag and expressed using a GroEL promoter ) and full-length PknD ( WT or kinase-dead with no tag expressed using an acetamide-inducible promoter ) . Western blots confirmed equivalent Rv0516c and PknD overexpression in each strain ( Figure 5A ) . Using anti–phospho-Thr antibodies , we found that Rv0516c was efficiently phosphorylated only in the strain overexpressing WT PknD and WT Rv0516c . Mutations that inhibited PknD ( Asp138Asn ) or eliminated the Rv0516c in vitro phosphorylation site ( Thr2Ala ) abolished this phosphorylation of recombinant Rv0516c in Mtb . These data indicated that PknD phosphorylated Rv0516c on Thr2 in vivo when both proteins were overexpressed . Although some anti-anti–sigma factor homologs of Rv0516c are known to be regulated by phosphorylation , Thr2 differs from the consensus phosphorylation sites in the anti-anti–sigma factor family . In Rv0516c , Gly80 occupies the position of the consensus Ser or Thr phosphorylation site , which occurs , for example , at Ser58 of SpoIIAA ( Figure S4A ) . This consensus Ser/Thr phosphorylation site is conserved in only two of the six Mtb anti-anti–sigma factor domains ( Figure S4B ) , but oxidation of cysteine at this position plays a key regulatory role for at least Rv1365c [24] . The Rv0516c peptide containing the corresponding segment was identified exclusively in an unphosphorylated form ( unpublished data ) in our MS analysis of PknD-phosphorylated Rv0516c . The absence of a Ser or Thr at the consensus phosphorylation site and our failure to observe Rv0516c phosphorylation by any anti–sigma factor in vitro are consistent with PknD phosphorylation at the distinct site , Thr2 . A yeast two-hybrid analysis of interactions among Mtb sigma factor regulators has suggested that Rv0516c can bind the homologous predicted anti-anti–sigma factor , Rv2638 [18] . To test this association and investigate the role of Thr2 phosphorylation in regulating the interaction , we used affinity chromatography to compare binding of purified Rv2638 to Rv0516c before and after PknD phosphorylation . Rv2638 bound Rv0516c , and Rv0516c phosphorylation by PknD abolished this association ( Figure 5B ) . These results showed that Thr2 phosphorylation regulates the interaction in vitro between Rv0516c and the anti-anti–sigma factor paralog , Rv2638 .
Because the identity of activating environmental signals remains unknown , we stimulated PknD receptor kinase activity in Mtb by overexpressing the protein ( Figure 1A ) . Overexpression was expected to stimulate phosphorylation of PknD substrates directly by increasing the concentration of the kinase and indirectly by favoring dimerization ( by mass action ) , which leads to allosteric activation [26] . PknD activity produced a transcriptional response that altered genes activated by SigF during log phase growth ( Figure 1B ) , including the anti-anti–sigma factor homolog Rv0516c [21] . Strikingly , the PknD kinase domain also directly phosphorylated the Rv0516c protein ( but none of the other Mtb sigma factor regulators ) in vitro and upon overexpression in vivo . In contrast to the conserved internal phosphorylation sites found in many anti-anti–sigma factors [16] , PknD phosphorylated Rv0516c on Thr2 in an N-terminal extension similar to that found in two additional mycobacterial anti-anti–sigma factors , Rv1904 and Rv2638 . Phosphorylation directly blocked Rv0516c binding to Rv2638 , indicating that Thr2 phosphorylation has a direct functional consequence . Although the roles of the Rv0516c:Rv2638 complex are unknown , alternative phosphorylation sites and functional interactions between upstream anti-anti–sigma factor homologs have been demonstrated in B . subtilis for the RsbS and RsbRA–RsbRD regulators [17 , 27–29] . These B . subtilis regulators form a large complex that controls the environmental sensing phosphatase RsbU , which dephosphorylates anti-anti–sigma factors [17 , 27–29] . The correlation between SigF-responsive genes [21] and genes that are transcriptionally sensitive to PknD activity ( Figure 1 ) is specific to PknD; overexpression of Mtb PknB produces a distinct transcriptional response ( T . Lombana , J . MacGurn , J . Cox , and T . Alber , unpublished data ) . Nonetheless , these data do not demonstrate a direct mechanistic link between Rv0516c and SigF . To the contrary , the lack of Rv0516c phosphorylation by the Mtb anti-SigF ( UsfX , Rv3287c ) or any other anti–sigma factor hints that PknD indirectly influences SigF-mediated transcription by phosphorylating Rv0516c or other substrates . The present data do not distinguish models in which repression of the SigF response is caused by Rv0516c phosphorylation or by a distinct signal generated by phosphorylation of one or more other proteins in vivo . The substrates of the Mtb STPKs are not restricted to transcriptional regulators . Rough estimates suggest that the number of Ser/Thr phosphoproteins in Mtb may exceed 100 [30] , and proposed Mtb substrates include metabolic enzymes [31] , regulatory proteins [12 , 32] , and membrane channels [33] . Using proteomic methods to analyze lysates phosphorylated in vitro by the PknD kinase domain , Perez and coworkers recently reported that PknD phosphorylates MmpL7 , the transporter for phthiocerol dimycocerosate ( PDIM ) , a lipid essential for virulence [34] . These studies , however , did not test whether MmpL7 is phosphorylated in vivo , whether phosphorylation altered the function of MmpL7 , or whether MmpL7 is a better substrate of other STPKs . Perez and coworkers did not detect PknD phosphorylation of Rv0516c , perhaps because this regulatory protein may not be sufficiently abundant in the Mtb lysates or because proteins <20 kDa ( such as Rv0516c ) were run off the two-dimensional gels used to identify potential substrates [34] . Similar reasons may explain the failure of Perez and coworkers to detect phosphorylation of small proteins containing FHA domains previously found to be in vitro substrates of PknD [9] . In contrast , the complementary approach used here , based on assaying the biochemical and transcriptional effects of kinase activation in vivo , is sensitive to changes in the activity of regulatory factors , even proteins present in small amounts . By assaying in vitro PknD phosphorylation of all the Mtb homologs of the B . subtilis SpoIIAA and SpoIIAB sigma factor regulators , we found that only Rv0516c was efficiently phosphorylated ( Figure 3 ) . Nonetheless , overexpressing PknD may cause abnormal phosphorylation or physiological changes that result in indirect transcriptional changes unrelated to normal kinase functions . The striking correlation between PknD phosphorylation of Rv0516c and activation of the Rv0516c gene , however , suggests a potential autoregulatory loop and sets the stage to explore the biological roles of this sigma factor regulator and the consequences of Rv0516c phosphorylation in vivo . Although bacterial STPKs phosphorylate many types of proteins [30] , alternative sigma factor regulators may be substrates of STPKs in diverse genera . In addition to the activity of PknD , the PknB and PknE kinase domains phosphorylated sigma factor regulators in vitro ( Figures 3D and S3 ) . In contrast , some kinase domains ( e . g . , PknA and PknK; Figure 3D ) apparently do not phosphorylate these sigma factor regulators . With up to 12 candidate alternative sigma factors in the Mtb genome , it is unlikely that each kinase controls a completely autonomous pathway . Instead , our data suggest that phosphorylation pathways may converge on overlapping sets of regulators ( Figure 3D ) . The specific phosphorylation of Rv0516c on a novel functional site by PknD suggests that STPK phosphorylation of sigma factor regulators goes beyond the paradigm established to date in B . subtilis .
The strains and plasmids used in this study are listed in Table 1 . M . tuberculosis ( Erdman ) cultures were grown in 7H9 medium and transformed as previously described [35] . Plasmids were maintained episomally by growth in medium containing antibiotics . Strains were grown to mid-log phase in 7H9 media before induction of PknD by addition of acetamide ( 0 . 2% ) . RNA was isolated from cultures at indicated time points as previously described [36] and quantified by measuring OD260 . RNA was random-primed and reverse transcribed in the presence of amino-allyl dUTP . Residual RNA was hydrolyzed by addition of 0 . 2 N NaOH , 0 . 1 M EDTA , and incubation at 65 °C for 15 min , followed by addition of 0 . 2 N HCl to neutralize . The cDNA was purified with Zymo binding columns ( Zymo Research , http://www . zymoresearch . com ) and conjugated to either Cy3 ( individual cDNA samples ) or Cy5 ( common reference pool cDNA ) . An equal quantity of each RNA sample within an experiment ( representing both Mtb strains at all time points ) was used to make a common cDNA reference pool . Dye-conjugated cDNA from each individual sample was mixed and co-hybridized with dye-conjugated cDNA from the common reference pool on microarray slides containing oligonucleotide spots representing every gene in M . tuberculosis ( Qiagen , http://www . qiagen . com ) . After 2 d of hybridization at 63 °C , arrays were washed and scanned using a GenePix 3000B scanner ( Axon Instruments , http://www . moleculardevices . com ) . Array gridding was performed in GenePix Pro 4 . 1 , and Nomad 2 . 0 was used to select high quality spots . For each spot , the ratio of medians ( Rm ) was averaged from repeat hybridizations and normalized to t = 0 ( uninduced ) . Cluster analysis was performed using Cluster 3 . 0 . Two biological replicates were performed , and each biological replicate was averaged over two hybridizations . Using Mtb H37Rv genomic DNA as a template for PCR amplification , gene segments encoding PknB1–308 , PknE1–286 , and PknK1–289 were cloned into pET-28b vectors ( Novagen , http://www . emdbiosciences . com ) . PknD1–378 was cloned into pET-24b ( Novagen ) . PknA1–337 and full-length clones of each anti–sigma factor or anti-anti–sigma factor were inserted into the Gateway vector pHMGWA [37] , which included NH2-terminal 6X-His and maltose binding protein ( MBP ) tags , followed by a tobacco etch virus ( TEV ) protease site . All constructs were confirmed by DNA sequencing . Proteins were expressed in E . coli BL21 CodonPlus ( Stratagene , http://www . stratagene . com ) at 18 °C . The kinase-domain constructs and Rv0516c were purified to homogeneity ( as assayed by SDS-PAGE ) by immobilized metal affinity chromatography ( IMAC ) using nickel-equilibrated HiTrap chelating Sepharose ( Amersham , http://www . amershambiosciences . com ) , size-exclusion chromatography using HiLoad 26/60 Superdex 75 ( Amersham ) , and anion-exchange chromatography using HiTrap Q Sepharose ( Amersham ) . The sigma factor regulators prepared for kinase-activity screens were purified by nickel-IMAC ( Rv0516c was purified by IMAC only for these assays as well ) . The molecular weight of each sigma factor regulator , as assayed by SDS-PAGE , corresponded to the mass predicted by the gene sequence . Because the kinase-domain constructs autophosphorylated during expression , migration on SDS-PAGE was slightly retarded . The sigma factor regulators were dialyzed into the reaction buffer ( 80 mM NaCl , 20 mM Tris [pH 7 . 5] , 0 . 5 mM Tris ( 2-carboxyethyl ) phosphine hydrochloride [TCEP] , 250 μM MnCl2 ) . In a total reaction volume of 19 μl , the final concentration of each IMAC-purified 6X-His-MBP–tagged sigma factor regulator was 20 μM , and the final concentration of kinase was 1 . 2 μM . The reaction was initiated with the simultaneous addition of 1 μL of [γ-32P]ATP ( 800 Ci/mmol and 10 mCi/ml; ICN , http://www . mpbio . com ) and ATP ( Sigma , http://www . sigmaaldrich . com ) to final concentrations of 250 nCi/μl and 50 μM , respectively . The reaction was allowed to proceed for 2 h at room temperature and quenched by the simultaneous addition of EDTA to 20 mM and 7 . 2 μg of TEV protease . The TEV cleavage was allowed to proceed 2 h or overnight at room temperature , resulting in efficient separation of each sigma factor regulator from the tag . The sequence GlyHisMet was left at the NH2-terminus after TEV cleavage of the tag . The cleavage reactions were separated by SDS-PAGE on 4%–12% NuPage Novex BisTris gels ( Invitrogen , http://www . invitrogen . com ) , and the gels were dried . Radioactivity was quantified with a Molecular Dynamics Typhoon 8600 phosphoimager . To assess the activity of the Asp138Asn mutant of PknD , we incubated 0 . 036 nM WT kinase or 3 . 6 nM Asp138Asn kinase with 0 . 5 mg/ml MyBP or 0 . 5 mg/ml Rv0516c . The reaction was carried out for 30 min under buffer , metal , and ATP concentrations similar to those described above , and then quenched with either 5X SDS-PAGE loading dye ( for MyBP ) or the TEV/EDTA mixture described above . Phosphorylation was quantified with ImageQuant ( GE Healthcare , http://www . gehealthcare . com ) after electrophoresis , drying , and phosphoimager data collection . Untagged PknD1–378 was purified by IMAC , cleaved with TEV , purified on HiLoad 26/60 Superdex 75 ( Amersham ) , and concentrated from the flow-through fraction of a second IMAC column . Each reaction was set up with or without 38 nM kinase , 20 μM Rv0516c , 250 nCi/μl [γ-32P]ATP , and 25 μM unlabeled ATP in 50 mM NaCl , 50 mM HEPES ( pH 7 . 5 ) , 0 . 5 mM TCEP , 10 mM MnCl2 , and 10 mM MgCl2 . SP600125 was diluted into water and added to a concentration of 20 nM to 20 μM . Reactions were carried out and analyzed as described above . PknD , Rv0516c , and PstP were purified to homogeneity [30] . Heat-inactivated PknD was prepared by incubation at 95 °C for 1 h . Phospho-Rv0516c prepared in a 2-h incubation with PknD and [γ-32P]ATP was treated with 2 . 3 μg of PstP . The reaction was quenched with EDTA and TEV after zero or 30 min . Separation and quantification were carried out as described above . Purified Rv0516c was phosphorylated using 6X-His-PknD1–378 and 2 mM ATP . The reaction proceeded overnight , and the kinase was removed by IMAC . The flow-through fraction was diluted with water and rocked at room temperature for 2 d to induce precipitation . Supernatant was removed , and the resulting pellet was dissolved in 6 M guanidinium hydrochloride . The mass of the intact protein was determined by electrospray ionization–ion-trap mass spectrometry . Rv0516c was digested with trypsin; the resulting digest mixture was separated on a reversed-phase C-18 column ( 0 . 15 × 150 mm ) , and fractions were collected . The MALDI TOF spectrum of each fraction was obtained , and the phosphorylated peptide was identified using MALDI-tandem TOF ( MS/MS ) . The MS/MS spectrum was used , along with Edman sequencing , to identify the phosphorylation site . Mutations to the N-terminus of Rv0516c were created with QuikChange ( Stratagene ) . Proteins were purified and phosphorylated as described , except that the Rv0516c variants were treated with TEV protease and quenched with the protease inhibitor , aminoethyl-benzene sulfonyl fluoride ( AEBSF ) ( MP Biomedicals , http://www . mpbio . com ) , prior to phosphorylation . Full-length PknD was cloned into an acetamide-inducible M . tuberculosis expression vector ( pGWdest3 . kan ) [38] . Full-length Rv0516c ( WT or mutant ) was cloned into a tuberculosis expression vector under the control of the constitutive GroEL promoter ( pGWdest1 . hyg ) . The vector also encoded a C-terminal antigenic FLAG ( DDDDK ) tag . Mutants were made using Quikchange ( Stratagene ) on the Rv0516c gene in the entry vector . Mtb Erdman was transformed by electroporation [35] , grown for 3–6 wk on solid rich medium , and single colonies were picked and grown to mid-log phase . Large ( 50 mL ) cultures were inoculated and adjusted to an optical density ( OD ) at 600 nm of 0 . 3 after 5 d . To induce PknD expression , acetamide was added to a final concentration of 0 . 2% at 24 , 8 , 4 , or 2 h before harvesting . Induced and uninduced cultures were grown to a final OD600 of ∼0 . 6 . Then , 10 mL of each culture were harvested by centrifugation , and resuspended in 200 μL of extraction buffer ( 1% SDS , 20 mM EDTA , 50 mM HEPES ( pH 7 . 5 ) , 1 mM AEBSF ) . Samples were immediately boiled for 25 min . Next , 200 μL of 100-μm glass beads were added , and samples were bead-beaten twice for 5 min . Samples were boiled a second time for 10 min and centrifuged . The soluble fraction was removed and diluted with SDS-PAGE loading dye . After electrophoresis in 10%–20% Tris-glycine gels , proteins were transferred to PVDF membrane , and detected with anti-phosphoThreonine ( Invitrogen ) , anti-DDDDK ( AbCam ) , anti-KatG , or anti-PknD antibodies ( Pacific Immunology , http://www . pacificimmunology . com ) . HRP-conjugated secondary antibody was used with Kodak BioMax MR film to develop the Western blots . In cases of multiple antibody detection , blots were stripped in 2% SDS/100 mM DTT , 62 mM Tris ( pH 7 ) , for 30 min at 50 °C . Rv2638 was expressed in E . coli in the pHxGWA ( N-terminal His6-thioredoxin ) vector [37] . Phosphorylated Rv0516c was prepared by incubation of purified His6-MBP–tagged protein with 5 mM MnCl2 , 2 mM ATP , and 10:1 ( w:w ) PknD1–378 . Phospho-Rv0516c was purified by IMAC , and both phosphorylated and unphosphorylated Rv0516c were dialyzed into the pull-down buffer ( 70 mM NaCl , 20 mM HEPES 7 . 5 , 0 . 5 mM TCEP ) . Pull-downs were performed by lysing ( by sonication ) E . coli that expressed Rv2638 in the presence of 200 μg MBP-tagged Rv0516c ( phosphorylated or unphosphorylated ) or His6-MBP control in 70 mM NaCl , 20 mM HEPES 7 . 5 , 0 . 5 mM TCEP , 1 mM AEBSF , and 10 mM MnCl2 . After rocking the lysate for 30 min at 4 °C , samples were centrifuged for 10 min at 14 , 000 rpm in a microcentrifuge at 4 °C . A small amount of the supernatant was retained for analysis , and the majority was applied to 50 μL of amylose-Sepharose ( New England Biolabs , http://www . neb . com ) pre-equilibrated in the buffer . After rocking for 10 min at 4 °C , resin was washed three times in buffer , resuspended in 40 μL of 2X SDS-PAGE loading dye , and boiled for 10 min . Samples were separated on 12% Tris-glycine gels ( Invitrogen ) , transferred to PVDF , blocked in 4% non-fat dry milk , and incubated overnight at room temperature with 1:2000 monoclonal anti-His6 clone HIS-1 ( Sigma ) . Blots were washed and imaged as described above . For loading controls , the same reactions were separated on 12% Tris-glycine gels and stained with Coomassie blue .
Please see Table 2 for a list of genes described in this study .
|
Many bacteria , including Mycobacterium tuberculosis ( Mtb ) , sense the environment using a family of signaling proteins called Ser/Thr protein kinases ( STPKs ) , but the functions of these sensors are not well understood . This study shows that the Mtb protein kinase ( Pkn ) D STPK attaches a phosphate group to one and only one member of a family of regulators of “alternative” sigma factors , which activate sets of genes in numerous bacteria . Phosphorylation of the regulator at an unprecedented position abolished binding in vitro to a putative partner . Remarkably , increasing PknD activity in Mtb not only strongly activated the gene encoding the specific regulatory protein phosphorylated by PknD , but also altered the expression of genes controlled by an alternative sigma factor . By providing evidence for a mechanistic link between PknD and gene regulation , this work supports a new model in which STPKs in numerous microorganisms transduce environmental signals by controlling expression of specific groups of genes . Thus , certain bacterial STPKs may orchestrate aspects of the coordinate control of gene expression essential for adaptation in the environment and in host infections .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods",
"Supporting",
"Information"
] |
[
"biochemistry",
"infectious",
"diseases",
"in",
"vitro",
"microbiology",
"molecular",
"biology",
"genetics",
"and",
"genomics",
"eubacteria"
] |
2007
|
M. tuberculosis Ser/Thr Protein Kinase D Phosphorylates an Anti-Anti–Sigma Factor Homolog
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Stress granules ( SGs ) contain stalled messenger ribonucleoprotein complexes and are related to the regulation of mRNA translation . Picornavirus infection can interfere with the formation of SGs . However , the detailed molecular mechanisms and functions of picornavirus-mediated regulation of SG formation are not clear . Here , we found that the 2A protease of a picornavirus , EV71 , induced atypical stress granule ( aSG ) , but not typical stress granule ( tSG ) , formation via cleavage of eIF4GI . Furthermore , 2A was required and sufficient to inhibit tSGs induced by EV71 infection , sodium arsenite , or heat shock . Infection of 2A protease activity-inactivated recombinant EV71 ( EV71-2AC110S ) failed to induce aSG formation and only induced tSG formation , which is PKR and eIF2α phosphorylation-dependent . By using a Renilla luciferase mRNA reporter system and RNA fluorescence in situ hybridization assay , we found that EV71-induced aSGs were beneficial to viral translation through sequestering only cellular mRNAs , but not viral mRNAs . In addition , we found that the 2A protease of other picornaviruses such as poliovirus and coxsackievirus also induced aSG formation and blocked tSG formation . Taken together , our results demonstrate that , on one hand , EV71 infection induces tSG formation via the PKR-eIF2α pathway , and on the other hand , 2A , but not 3C , blocks tSG formation . Instead , 2A induces aSG formation by cleaving eIF4GI to sequester cellular mRNA but release viral mRNA , thereby facilitating viral translation .
Stress granules ( SGs ) form in response to a variety of stresses such as oxidative stress , heat shock ( HS ) , hypoxia , nutrient deprivation , and viral infection [1] . During SG formation , messenger RNA ( mRNA ) translation initiation is inhibited , and polysomes are disassembled . Thus , SGs contain stalled pre-initiation complexes ( PICs ) consisting of translationally silent mRNAs , 40S ribosomal subunits , canonical eukaryotic initiation factors ( eIFs ) such as eIF4E , eIF4G , eIF4A , eIF4B , and eIF3 , and RNA-binding proteins ( RBPs ) . Two aggregation-prone RBPs , T-cell-restricted intracellular antigen 1 ( TIA-1 ) and the RasGAP SH3-domain binding protein 1 ( G3BP ) , appear to be critical for SG formation and are recruited to SGs [2 , 3] . SGs in general are considered to be transient and dynamic . Compounds such as cycloheximide ( CHX ) stabilize mRNAs on polysomes and inhibit SG formation and foster their disassembly [4 , 5] . The SG formation induced by the phosphorylation of eIF2α is well characterized . The protein kinase R ( PKR ) , PKR-like ER kinase ( PERK ) , general control nonderepressible 2 ( GCN2 ) , or heme regulated inhibitor ( HRI ) can phosphorylate eIF2α under different stress conditions . For example , PKR can be activated by viral dsRNA , and HRI can be activated by arsenite ( AS ) or HS . The phosphorylation of eIF2α interferes with the formation of the eIF2-GTP-tRNAiMet ternary complex and thereby stalls translation initiation [1 , 6–8] . However , eIF2α-independent SG formation also exists and includes eIF4A inhibition by either pateamine A or hippuristanol and inhibition of eIF4G-eIF4E interactions during hydrogen peroxide-induced oxidative stress [9–12] . Thus , SG formation can be caused by a variety of mechanisms that impair translation initiation . Although SGs formed in response to diverse stresses share many of the same components , certain factors appear to be recruited in a stress-specific fashion . For example , HS protein 27 ( HSP27 ) is found in SGs in HS cells but not in cells undergoing oxidative stress [13]; the p68 src-associated protein in mitosis ( Sam68 ) is recruited to SGs in picornavirus-infected cells but not to those formed in response to oxidative stress or HS . Thus , SGs may be compositionally different depending on the type of stress [14] , and distinct SGs may be regulated differentially and have multiple roles . However , the mechanisms by which SGs form have not been identified completely . Enterovirus 71 ( EV71 ) , a member of the Picornaviridae family , is widely spread and causes severe hand-foot-mouth disease in infants [15] . Thus , understanding the host factors that influence viral pathogenesis is critical to designing improved antiviral strategies . The EV71 genome ( ∼7 . 5 kb ) can be immediately translated into a single polyprotein via an internal ribosome entry sequence ( IRES ) -mediated , cap-independent mechanism of translation initiation , and this polyprotein is subsequently processed by proteases 2A and 3C into the structural and nonstructural proteins [16] . Furthermore , the IRES can drive the viral genome translation in the absence of functional eIF4F complex , which is disrupted due to cleavage of eIF4G in picornavirus-infected cells [17 , 18] . SGs are thought to be antiviral , and many viruses have hence evolved various strategies to disrupt SG formation to maintain efficient translation of their proteins and to prevent their genomes and transcripts from being stalled in SGs [19 , 20] . Poliovirus ( PV ) infection was initially indicated by the recruitment of HuR and G3BP to SGs in early phases [10] . Subsequently , White et al . found that eIF4G and polyA-binding protein ( PABP ) were also recruited to SGs early in PV infection [21] . However , further examination revealed that eIF4G , G3BP , and PABP were no longer found in SGs at later times , indicating that PV may actively disrupt SG formation at later times [21] . Furthermore , the discovery that G3BP was cleaved by 3C , which coincided with SG disassembly in infected cells , provided a possible explanation for these findings [21] . White et al . suggested a model whereby PV initially induces SG formation but induces SG disassembly at later stages via cleavage of G3BP , thus preventing SG formation even in the presence of external stress [21] . However , because most of the SG markers used in the study by White et al . can be cleaved by 2A or 3C , whether other SG components are also released from SGs is unclear . Therefore , Piotrowska et al . further examined SG formation in PV-infected cells and found that infection induced stable , compositionally unique SGs containing TIA-1 but lacking G3BP and eIF4G and that these SGs did not disassemble at late times in infected cells , which raised the possibility that PV might not induce the complete disassembly of SGs . As G3BP , eIF4G , and PABP are all cleaved by viral proteases , proteolysis may trigger their release from SGs . Alternatively , the release may be triggered by a mechanism not yet identified [14] . Furthermore , recent studies showed that 2A of picornaviruses induced SG formation and that no other viral proteins induced SG formation [22] . However , the molecular mechanism of these 2A-induced SGs and the cellular components that 2A targets to trigger SG formation remain unknown . Therefore , several questions raised in the aforementioned studies have not been resolved . ( 1 ) How do picornaviruses induce SG formation at early times and block SG assembly at later times ? ( 2 ) Is cleavage of G3BP by 3C critical for the inhibition of SG formation at later times during infection ? ( 3 ) What is the molecular mechanism of 2A-induced SG formation ? Are they typical stress granules ( tSGs ) ? ( 4 ) What are the organization and role of 2A-induced SGs in picornavirus-infected cells ? In this study , we demonstrate that the 2A protease of EV71 blocks tSG formation but induces atypical stress granule ( aSG ) formation to facilitate viral translation . These aSGs are induced by cleavage of eIF4GI and are different from tSGs in that they are devoid of G3BP and a series of eIFs , they are independent of eIF2α and PKR phosphorylation , they cannot be dissolved by CHX , and they can specifically sequester cellular mRNAs but not viral mRNAs . On the other hand , infection with a 2A protease activity-inactivated recombinant virus , EV71-2AC110S , induces tSG formation via the PKR-eIF2α pathway , and these tSGs are antiviral structures . These findings provide a new conceptual mechanism for SG regulation during picornavirus infection .
To explore the formation of SGs during picornavirus infection , we infected HeLa cells with EV71 for 6 hours ( h ) and visualized SGs via immunofluorescence ( IF ) with antibodies against Sam68 , TIA-1 , and G3BP . EV71 infection led to the formation of SGs containing Sam68 and TIA-1 , but devoid of G3BP , and as a control , AS induced the formation of tSGs containing TIA-1 and G3BP , but not Sam68 ( Fig 1A ) . To explore EV71-induced SG formation in more detail , we tried to clarify the dynamics of SG assembly during EV71 infection and visualized SGs at different time points post-infection ( pi ) . An antibody against EV71 was used to visualize EV71-infected cells , and TIA-1 and Sam68 were also visualized . When cells were mock- or EV71-infected for 2 hours , EV71 infection was undetectable via IF , and localization of TIA-1 and Sam68 did not change . As infection proceeded , IF revealed EV71 in 90% of the cells at 4 hpi and 95% of the cells at 6 hpi , TIA-1 and Sam68 assembled into foci and colocalized with each other in infected cells ( S1A and S1H Fig ) . Therefore , the appearance of TIA-1 and Sam68 foci can be used as indicators of EV71 infection . However , although TIA-1-related protein ( TIAR ) aggregated and persisted in infected cells with TIA-1 and Sam68 , the other tSG markers such as G3BP , PABP , 40S ribosomal protein S3 ( RPS3 ) , eIF1a , eIF3a , eIF4G , eIF4A , and eIF4E aggregated in less than 30% of cells at 4 hpi and were evenly distributed at 6 hpi ( S1B–S1H Fig ) . Similar results were observed in EV71-infected rhabdomyosarcoma ( RD ) cells ( S1H Fig ) , suggesting that the persistent SGs containing TIA-1 , TIAR , and Sam68 might not be tSGs . To confirm which protein of EV71 induced the formation of persistent SGs , we expressed all the viral proteins in HeLa and RD cells and found that only 2A protease induced the formation of TIA-1 foci ( S2A Fig ) , which also contained Sam68 and TIAR but did not contain PABP , G3BP , RPS3 , eIF1a , eIF3a , eIF4G , eIF4A , or eIF4E ( Fig 1B and S2B Fig ) , suggesting that 2A expression alone is sufficient to trigger the formation of persistent SGs during EV71 infection and the formation of Sam68 or TIA-1 foci can also be used as an indicator of 2A expression . Next , we sought to determine whether 2A-induced persistent SGs share features with tSGs . First , a previous study showed that tSGs are dynamic structures of which TIA-1 rapidly shuttles in and out [23] . Thus , we analyzed the dynamics of TIA-1 in tSGs and persistent SGs via fluorescence recovery after photobleaching ( FRAP ) assay . To rule out the impact of size , typical and persistent SGs with similar size ( 1 . 5–2 μm in dimeter ) were analyzed . We found that GFP-TIA-1 in typical and persistent SGs were rapidly recovered ( Fig 1C ) , suggesting that persistent SGs are also dynamic structures . Second , previous studies also showed that stresses not only induce tSG formation but also induce adjacent processing body ( p-body ) formation [24–26] . Thus we also analyzed the location of the p-bodies in EV71-infected cells by using a widely used marker of p-bodies—mRNA-decapping enzyme 1A ( DCP1A ) , and found that p-bodies were adjacent to EV71-induced persistent SGs at 4h post-infection , but disappeared at 6h post-infection , suggesting that EV71-induced persistent SGs were distinct from p-bodies but similar to tSGs ( S2C and S2D Fig ) . Third , we evaluated the effect of eIF2α phosphorylation on the formation of TIA-1 foci and found that expression of eIF2αS51A ( an eIF2α non-phosphorylated mutant ) [27–29] blocked AS-induced tSG formation but had no effect on EV71- and 2A-induced formation of persistent SGs ( Fig 1D and 1E ) , indicating that 2A induced the formation of persistent SGs in a phospho-eIF2α-independent manner . Fourth , we found that CHX dispersed AS-induced tSGs but had no effect on EV71- and 2A-induced persistent SGs ( Fig 1F and 1G ) . Therefore , we defined EV71- and 2A-induced persistent SGs as atypical stress granules ( aSGs ) . Next , we sought to determine the role 2A plays in aSG formation . Since 2A is an important viral protease , we determined whether 2A protease activity is required for the formation of aSGs . Previous studies showed that a 2A mutant , 2AC110S , was catalytically inactive [30 , 31] . We also found that 2AC110S indeed lost the ability to cleave eIF4G ( Fig 2A ) ; subsequently , 2AC110S also lost the ability to induce aSG formation ( Fig 2B and 2C ) , demonstrating that 2A protease activity is essential for aSG formation . Furthermore , based on three facts , ( 1 ) both eIF4G and PABP were cleavage substrates of 2A and excluded from 2A-induced aSGs; ( 2 ) both eIF4GI and eIF4GII play similar functions in translation initiation , but cleavage of eIF4GI by 2A of picornaviruses is more sensitive than cleavage of eIF4GII [32 , 33]; ( 3 ) the mRNA level of eIF4GI was previously shown to be much higher than that of eIF4GII in mammalian cells [34] , therefore , we hypothesized that cleavage of eIF4GI/PABP by 2A might be critical for 2A-induced aSG formation . To this end , HeLa cells transiently expressing eIF4GIG689E ( a 2A cleavage-resistant eIF4GI mutant ) [35] or PABPM490P/Q540N ( a 2A and 3C double-resistant mutant ) [36 , 37] were infected with EV71 or treated with 2A . We found that eIF4GIG689E and PABPM490P/Q540N were indeed resistant to 2A cleavage ( Fig 2D and S3A Fig ) , and eIF4GIG689E expression dramatically blocked EV71- or 2A-induced aSG formation ( Fig 2E and 2F , cells marked by “yellow arrow” and “+” indicate eIF4GIG689E expression with EV71 infection or 2A expression ) , whereas PABPM490P/Q540N expression had no effect on the formation of aSGs ( S3B and S3C Fig ) , suggesting that cleavage of eIF4GI is critical for the formation of 2A-induced aSGs . Because EV71 induced the formation of aSGs that were distinct from tSGs , we sought to determine whether tSG formation could be blocked during EV71 infection . We infected HeLa cells with EV71 , treated them with AS or HS for 1 h prior to fixation at the indicated times , and stained them with antibodies against Sam68 ( a marker of EV71-infected cells ) , TIA-1 ( a marker of both tSGs and aSGs ) , G3BP ( a marker of tSGs ) , or HSP27 ( a marker of HS-induced tSGs ) . When cells were mock- or EV71-infected for 2 h , tSGs marked by G3BP and HSP27 were observed in all the cells upon treatment with AS or HS . As infection proceeded , tSGs were observed in only 20% of the cells at 4 hpi and 10% of the cells at 6 hpi , despite treatment with AS or HS ( Fig 3A and 3B ) ; similar results were also observed in EV71-infected RD cells ( S4A and S4B Fig ) , suggesting that EV71 infection blocks the formation of AS- or HS-induced tSGs . However , EV71 infection had no effect on the AS- or HS-activated phosphorylation of eIF2α ( S4C Fig ) , indicating that blockage of tSG formation by EV71 infection is not due to inhibition of eIF2α phosphorylation . Next , we sought to determine how EV71 blocks tSG formation . Previous studies reported that 3C protease of picornaviruses inhibited tSG formation by cleavage of G3BP , and G3BPQ326E ( a 3C cleavage-resistant mutant of G3BP ) restored SG formation competency in picornavirus-infected cells [21 , 38] . We confirmed that GFP-G3BPQ326E was indeed cleavage-resistant upon EV71 infection ( Fig 3C ) or 3C expression ( S4D Fig , left panel ) , and GFP-G3BPQ326E rescued tSG formation in 3C-expressing cells ( S4D Fig , right panel ) . To determine whether EV71 inhibits tSG formation in a manner similar to that of previous reported picornaviruses , we assessed tSG formation in the presence of EV71 infection , GFP-G3BP or GFP-G3BPQ326E expression plus AS . At 2 hpi with EV71 , GFP-G3BP and GFP-G3BPQ326E localized to AS-induced tSGs . As infection proceeded , AS-induced tSG formation was blocked in EV71-infected cells despite expression of GFP-G3BPQ326E ( Fig 3D and 3E ) . Similar results were observed in EV71-infected RD cells expressing GFP-G3BP or GFP-G3BPQ326E ( S4E Fig ) , suggesting that 3C cleavage of G3BP is dispensable for the inhibition of tSG formation during EV71 infection . To confirm whether 3C protease is required for the inhibition of tSG formation during EV71 infection , we used guanidine hydrochloride ( GuHCl , an ATPase inhibitor ) to suppress viral replication to an extremely low level in HeLa and RD cells [39 , 40] . Under these conditions , viral proteins were undetectable , and the level of full-length G3BP in EV71-infected cells was comparable with that in uninfected cells , but eIF4G was remarkably cleaved ( Fig 3F and S4F Fig ) , as reported previously [21 , 41] , indicating that 3C cannot work and the cleavage of eIF4G can be used to distinguish the infected cells . However , the AS-induced tSG formation was still inhibited in EV71-infected cells ( Fig 3G and 3H and S4F Fig ) . Taken together , our results demonstrate that the blockage of tSG formation during EV71 infection is not due to 3C protease . Since 3C was dispensable for the blockage of tSG formation , and 2A-induced aSGs did not contain tSG components such as G3BP and eIF4G , we hypothesized that 2A plays a critical role in inhibiting tSG formation . To validate this possibility , we examined tSG formation induced by AS or HS in the presence of 2A ( Sam68 foci indicate 2A-expressing cells ) and found that AS- or HS-induced tSGs ( marked by G3BP or HSP27 ) appeared in 96% of empty vector-transfected cells but appeared in only 35% of 2A-transfected cells at 12 h and in less than 20% of 2A-transfected cells at 24 h ( Fig 4A–4C ) . 2A-expressing cells all failed to form tSGs ( Fig 4A and 4B , “+” indicates expression of 2A ) . Similar results were observed in 2A-transfected RD cells ( S5A and S5B Fig ) . Furthermore , 2A expression had no effect on AS- or HS-activated eIF2α phosphorylation ( S5C Fig ) , suggesting that 2A blocks tSG formation without inhibiting eIF2α phosphorylation , which is consistent with those in EV71 infection conditions ( S4C Fig ) . To confirm that 2A indeed plays a critical role in the inhibition of tSG formation during EV71 infection , we expressed Myc-tagged 2A in HeLa cells stably expressing GFP-G3BPQ326E and then treated cells with AS and found that 2A , but not 3C , blocked the formation of tSGs ( S5D and S5E Fig ) , suggesting that 2A , but not 3C , plays a critical role in the inhibition of tSG formation during EV71 infection . In addition , we found that 2AC110S also lost the ability to block the formation of AS-induced tSGs ( Fig 4D and 4E ) , suggesting that 2A protease activity is essential for its blockage of tSG formation . Having found that eIF4GIG689E blocked aSG formation , we further analyzed whether eIF4GIG689E could restore tSG formation in the presence of AS . To our surprise , we found that 2A still blocked tSG formation in spite of expression of eIF4GIG689E ( S5F and S5G Fig ) , suggesting that the blockage of tSG formation is not due to cleavage of eIF4GI by 2A . To further elucidate the critical role of 2A protease activity in blocking tSG formation and inducing aSG formation during EV71 infection , we generated recombinant EV71 with the 2AC110S mutation ( EV71-2AC110S ) . Since 2A is important for the viral life cycle , the replication activity of EV71-2AC110S is much lower ( 50-fold less in viral titer ) than that of EV71 and VP1 expression of EV71-2AC110S was also much lower than that of EV71 ( S6A Fig ) . Correspondingly , EV71-2AC110S could not shut off cellular translation as quickly as EV71 ( S6B Fig ) . Therefore , we infected cells with a higher MOI of EV71-2AC110S and a lower MOI of EV71 and found that when the 3C protein levels and G3BP cleavage levels were comparable , eIF4G was no longer cleaved in EV71-2AC110S-infected cells ( Fig 5A ) . Correspondingly , EV71-2AC110S infection failed to induce aSG formation; instead , EV71-2AC110S induced the formation of tSGs containing G3BP and TIA-1 in about 65% of infected cells , which could be completely dispersed by CHX ( Fig 5B and 5C ) . With additional AS or HS treatment , all the EV71-2AC110S-infected cells formed tSGs ( Fig 5B and 5D and S6C and S6D Fig ) . Taken together , these data demonstrate that EV71 infection induces tSG formation independent of 2A protease activity , but 2A inhibits EV71-induced tSG formation and induces aSG formation . We next sought to determine how EV71 infection induces tSG formation . Since EV71 is a positive-sense single-stranded RNA virus , it generates significant amounts of viral replication intermediate dsRNAs during replication . And the dsRNAs commonly activate PKR to phosphorylate eIF2α , which results in tSG assembly [42] . To determine whether EV71-2AC110S induces tSG formation via the PKR-eIF2α pathway , we generated HeLa cells with stable knockdown ( KD ) of PKR ( shPKR-HeLa cells ) and infected them with EV71 or EV71-2AC110S . We found that KD of PKR decreased the phosphorylation levels of PKR and eIF2α in EV71- or EV71-2AC110S-infected cells ( Fig 6A ) . In shPKR-HeLa cells , the formation of EV71-induced aSGs was not affected , but the formation of EV71-2AC110S-induced tSGs was blocked ( Fig 6B and 6C ) . Furthermore , expression of eIF2αS51A blocked the formation of EV71-2AC110S-induced tSGs but not EV71-induced aSGs ( Fig 6D and 6E ) . Taken together , these results suggest that , unlike aSGs , tSGs are induced via the PKR-eIF2α pathway by viral dsRNAs during EV71 infection . Next , we sought to determine why 2A blocks tSG formation but induces aSG formation . We hypothesized that it is a strategy by which the virus facilitates its own translation . Thus , we generated a Renilla luciferase mRNA reporter , the translation of which is driven by EV71-UTR to mimic EV71 translation ( UTREV71-Rluc ) ( Fig 7A ) . We found that eIF4GIG689E did not influence translation of UTREV71-Rluc in EV71-2AC110S-infected cells , but once aSG formation was inhibited by eIF4GIG689E in EV71-infected cells , the translation efficacy of UTREV71-Rluc was dramatically decreased ( Fig 7B ) , suggesting that aSG formation benefits EV71 translation . Conversely , the translation efficacy of UTREV71-Rluc was not influenced by KD of PKR in EV71-infected cells , but increased at least three-fold when tSG formation was inhibited by KD of PKR in EV71-2AC110S-infected cells ( Fig 7C ) , suggesting that tSGs inhibit EV71 translation . Next , we sought to determine how aSGs benefit viral translation . We hypothesized that different mRNAs are sequestered in aSGs and tSGs to regulate viral translation . First , using poly ( A ) fluorescence in situ hybridization ( FISH ) assays , we confirmed that numerous mRNAs were present in the EV71- or 2A-induced aSGs and in the AS-induced tSGs ( Fig 7D ) . Second , using RNA FISH assays , we evaluated the localization of viral mRNAs ( positive-strand RNA , +vRNA ) and cellular PABPC1 mRNAs ( with high TIA-1 affinity ) [43] in HeLa cells stably expressing GFP-TIA-1 . In EV71-infected cells , PABPC1 mRNAs , but not +vRNA , efficiently localized in the aSGs ( Fig 7E , top panel ) . In EV71-2AC110S-infected cells , both PABPC1 mRNAs and +vRNA efficiently localized in the tSGs ( Fig 7E , bottom panel ) . Furthermore , we generated a Renilla luciferase mRNA reporter , the translation of which is driven by PABPC1-UTR to mimic PABPC1 translation ( UTRPABPC1-Rluc ) ( S7A Fig ) . We found whether the aSGs was blocked by eIF4GIG689E in EV71-infected cells or the tSGs was blocked by KD of PKR in EV71-2AC110S-infected cells , the translation efficacy of UTRPABPC1-Rluc mRNA increased ( S7B and S7C Fig ) , suggesting that both aSGs and tSGs inhibit PABPC1 mRNA translation . Taken together , our results suggest that tSGs stall both cellular and viral mRNAs to shut down overall translation , resulting in the inhibition of viral translation; however , 2A of EV71 blocked tSG formation but induced aSG formation to facilitate viral translation by stalling only cellular mRNAs . The function of the 2A protease is highly conserved among Picornaviridae . Thus , we sought to determine whether its role in SG formation regulation is conserved among picornaviruses . We used Sam68 cytoplasmic re-localization as a marker of 2A expression in IF assays . Indeed , expression of 2A of EV71-BrCr , PV , and coxsackievirus A ( CVA ) also triggered Sam68 and TIA-1 to form aSGs that were devoid of G3BP and resistant to CHX ( Fig 8A , upper panel , and Fig 8B ) . Furthermore , 2A of these picornaviruses also blocked AS- and HS-induced tSG formation ( Fig 8A , lower panel , and Fig 8C and 8D ) . Similarly , 2A of these picornaviruses cleaved eIF4GI but not eIF4GIG689E ( S8A Fig ) , and 2A of these picornaviruses also failed to induce the formation of aSGs in eIF4GIG689E-expressing cells ( S8B and S8C Fig ) . Taken together , these findings suggest that although different picornaviruses may use different mechanisms to alter host cell function , the effect of 2A on the regulation of SGs is common .
In previous studies , TIA-1 foci have been observed during picornavirus infection; however , the essence of these aggregates was ambiguous and controversial . The 2A-induced TIA-1 foci were thought to be tSGs [22] . We also found that 2A-induced TIA-1 foci share some features with tSGs , such as they are dynamic and adjacent to p-bodies ( Fig 1C and S2C Fig ) , but they are different from tSGs and thus named them aSGs . The conclusion of aSGs different from tSGs is supported by multiple lines of evidence . First , the aSGs contained TIA-1 , TIAR , and Sam68 but were devoid of G3BP , a series of eIFs and viral mRNA ( S1A–S1G and S2B Figs and Fig 7E ) . Second , the formation of aSGs was independent of PKR activation ( Fig 6B and 6C ) and the phosphorylation of eIF2α ( Fig 1D and 1E ) . Third , the aSGs could not be disassembled by CHX ( Fig 1F and 1G ) . Fourth , EV71-2AC110S-induced TIA-1 foci were tSGs , which contained TIA-1 , G3BP , eIF4G , and viral mRNA , and could be completely dispersed by CHX , and the formation of which was dependent on PKR activation and the phosphorylation of eIF2α ( Figs 5B , 6B and 7E ) . Although both eIF4G and PABP were cleavage substrates of 2A , the cleavage efficiency of PABP is much lower than that of eIF4G [44] . We found that the only eIF4GIG689E blocked the aSGs formation , indicating that 2A induces aSG formation by cleaving eIF4GI ( Fig 2E and 2F and S3A–S3C Fig ) . PABP is also a cleavage substrate of 3C , but expression of 3C is unable to induce aSG formation ( S2A Fig ) . Therefore , we thought that even if the cleavage of PABP is more robust , cleavage of PABP should not result in aSG formation . We also found that 2A-induced aSGs are a common phenomenon in picornaviruses ( Fig 8 ) , and the dynamics of TIA-1 in aSGs were similar to those of TIA-1 in tSGs ( Fig 1C ) . Thus , it is possible that aSGs are also non-membrane-bound cellular compartments and formed via liquid-liquid phase separation ( LLPS ) , as is the case for tSGs . Although the details of LLPS are not clear , previous studies have shown that the high concentration of RBPs , which contain intrinsically disordered regions ( IDRs ) , triggers LLPS [45–47] . When the concentration of IDR-containing RBPs reaches a certain level , the LLPS of these RBPs can be spontaneously initiated by IDR-mediated interaction , thus promoting tSG formation . Furthermore , during molecular crowding , IDR-containing RBPs can initiate LLPS at lower protein levels [46] . The expression of 2A could shuttle many nuclear IDR-containing RBPs , including hnRNPs , TDP-43 , HuR , and Sam68 , to the cytoplasm [14 , 48–51] , thus resulting in increased concentrations of IDR-containing RBPs in the cytoplasm . Furthermore , the cleavage of eIF4GI by 2A leads to the accumulation of stalled PICs , thus resulting in molecular crowding . In cells expressing eIF4GIG689E and 2A , translation is initiated , molecular crowding is inhibited [35 , 52] , and tSG formation is blocked ( S5F and S5G Fig ) , and aSGs are therefore unable to form ( Fig 2E and 2F and S8 Fig ) . In principle , the PICs rapidly exchange between tSGs and polyribosomes , the addition of CHX during AS and HS treatment inhibits the dissociation of polyribosomes and results in the disassembly of tSGs [4 , 5] . However , we found that aSGs could not be dissolved by CHX ( Fig 1F and 1G ) . Furthermore , we also found that the aSGs did not contain eIF1a , eIF3a , eIF4A , eIF4E , eIF4G , and RPS3 ( S1A–S1H and S2B Figs ) , indicating that the mRNAs in aSGs are not equipped with eIFs and 40S ribosomal subunits , and cannot participate in translation . Therefore , the mRNAs within aSGs cannot flow to polyribosomes and aSGs cannot be dissolved by CHX . Piotrowska et al . found that poliovirus did not block HS-induced tSG formation at 4 hpi [14] , but we found that both AS- and HS-induced tSG formation were inhibited at 4 hpi and 6 hpi during EV71 infection ( Fig 3A and 3B and S4A and S4B Fig ) . We speculate that poliovirus could not block HS-induced tSGs completely at 4hpi , but as infection proceeded , poliovirus blocked HS-induced tSGs eventually . To our knowledge , we are the first to find that tSGs are totally abrogated specifically by 2A , but not by 3C . Our conclusion is supported by three lines of evidence . First , EV71 and 2A still blocked tSG formation in cells expressing 3C cleavage-resistant G3BP ( G3BPQ326E ) ( Fig 3D and 3E , S4D , S4E , S5D and S5E Figs ) , which contradicts previous findings [21 , 38 , 49] . We speculate that most of the viruses failed to replicate in cells expressing G3BPQ326E , because G3BP exhibits antiviral activity against several picornaviruses [53] , thus resulting in an eight-fold reduction in viral titer and tSG formation rescue [21] . Although tSG formation was inhibited in 3C-expressing cells ( S4D Fig ) , we think this is just a phenomenon accompanying the cleavage of G3BP by 3C to inhibit the antiviral activity of G3BP in the late phase of EV71 infection , because tSG inhibition occurred much earlier than G3BP cleavage ( Fig 3C and 3D ) . Second , the addition of GuHCl in EV71-infected cells suppressed viral replication to an extremely low level , and the protease activity of 3C could not be detected ( Fig 3F and S4F Fig ) , but tSG formation was still blocked in infected cells ( Fig 3G and 3H and S4F Fig ) , suggesting that 3C is not required for blocking tSG formation . Third , by using the EV71-2AC110S mutant virus , in which 2A protease activity was abolished but 3C protease activity was intact ( Fig 5A ) , we found that EV71-2AC110S induced tSG formation instead of inhibiting it ( Fig 5B–5D ) , demonstrating that 2A is indispensable for the EV71-mediated inhibition of tSG formation . We also tried to rescue recombinant EV71 with a catalytically inactive 3C mutation but failed , which may be attributed to the presence of many 3C cleavage sites in the viral polyproteins . 2A of EV71 was previously suggested to induce tSG formation , but the exact mechanism is unknown [21 , 22] . To our knowledge , we are the first to demonstrate that EV71 induces tSG formation through the PKR-eIF2α pathway via dsRNA , but not 2A ( Fig 6 ) ; on the contrary , 2A is indispensable for the blockage of tSG formation ( Figs 4 and 5 and S5 Fig ) . Although both induction of aSG formation and blockage of tSG formation require 2A protease activity , the molecular mechanism of 2A contribution to induction of aSG formation and blockage of tSG formation is different . The aSG formation is accompanied by the tSG blockage in 2A-expessing or EV71-infected cells ( Figs 3A , 4A and 4B , S4A and S5A Figs ) , but inhibition of 2A-induced aSGs by expression of eIF4GIG689E is unable to recover tSGs in the presence of AS ( Fig 2E and 2F and S5F and S5G Fig ) ; Furthermore , KD of PKR or expression of eIF2αS51A inhibits EV71-2AC110S-induced tSG formation ( Fig 6 ) , but has no effect on EV71-induced aSG formation ( Figs 1D , 1E , 6B and 6C ) , suggesting that blockage of tSG formation and induction of aSGs by virus are independent to each other , not due to turning tSGs into aSGs . The molecular mechanism of how 2A prevents tSG formation should be more complicated . EV71-2AC110S-induced tSGs contained eIFs and both viral and cellular mRNAs ( Figs 6B , 7D and 7E ) to inhibit viral translation ( Fig 7C ) . But EV71-induced aSGs did not contain a series of eIFs or viral mRNA ( S1A–S1H Fig , Figs 6B , 7D and 7E ) and instead contained selectively confined host mRNAs ( Fig 7E ) to facilitate viral translation ( Fig 7B ) . The mechanism of how viral RNA avoids being recruited to the aSGs is unclear , but we thought differences of RNA-binding proteins within aSGs and tSGs result in elimination of viral RNA from aSGs . It has been reported that many cellular mRNAs also contained IRES [54] , and if the binding proteins of IRES-containing cellular mRNAs are eliminated from aSGs , the aSGs should not stall these IRES-containing cellular mRNAs either . In conclusion , our findings reveal the common molecular mechanisms and functions of picornavirus-mediated regulation of SG formation ( Fig 9 ) . On one hand , host cells recognize viral dsRNA via PKR during EV71 infection , which activates the PKR-eIF2α signaling cascade and results in tSG formation . Both cellular and viral mRNAs are sequestered in tSGs , which leads to an overall shutdown of translation to inhibit viral translation . On the other hand , 2A protease of EV71 blocks tSG formation drastically to remove the antiviral effects of tSG formation from host cells . Furthermore , 2A induces aSG formation by cleaving eIF4GI to sequester cellular mRNA but releases eIFs and viral mRNA , which benefit viral translation . Thus , the blockage of tSG formation and induction of aSG formation are strategies used by EV71 to survive in host cells . Further studies are needed to reveal the complete RNA and protein composition of aSGs and the mechanisms of EV71-induced blockage of tSG formation . Likewise , the full effect of the regulation of SG formation on aspects of cell physiology other than translation control of host mRNAs should be further explored . Previous studies have suggested that persistent SG formation is linked to some neurodegenerative diseases [55–57] . Research in these areas may offer fascinating new insights into cellular function and may also yield novel therapeutic strategies in picornavirus-induced disease .
Human RD ( Rhabdomyosarcoma cells and were obtained from China Center for Type Culture Collection ) , HEK293T ( Human embryonic kidney 293 cells and were obtained from China Center for Type Culture Collection ) , HeLa cells ( Human cervical cancer epithelial cells and were obtained from China Center for Type Culture Collection ) , and stably expressing cells ( GFP-G3BP-HeLa/RD , GFP-G3BPQ326E-HeLa/RD , GFP-TIA-1-HeLa ) derived from HeLa or RD cells were cultured in Dulbecco’s modified Eagle’s medium ( DMEM ) ( Gibco ) supplemented with 10% fetal bovine serum ( FBS ) ( Gibco ) and 100 U/ml penicillin/streptomycin ( Gibco ) at 37°C and 5% CO2 . Other stably expressing cells ( eIF4GI-HA-HeLa , eIF4GIG689E-HA-HeLa ) , cells with KD of PKR ( shPKR-HeLa ) or negative control ( shNC-HeLa ) cells derived from HeLa cells were maintained in DMEM with 10% FBS , 100 U/ml penicillin/streptomycin , and 1 μg/ml puromycin ( Sigma-Aldrich ) at 37°C and 5% CO2 . For infection , HeLa or RD cells were infected with DMEM containing viruses with a multiplicity of infection ( MOI ) of 10 plaque-forming units ( PFUs ) or as indicated in the figure legends . After 1 h incubation , the medium was replaced with fresh DMEM with 4% FBS , and this time point was considered 0 hpi; cells were harvested for further analysis at 6 hpi or as indicated . For transfection , plasmids and RNAs were transfected by using Lipofectamine 2000 ( Invitrogen ) according to the manufacturer’s instructions , and cells were harvested or subjected to further treatment at 24 h post-transfection ( hpt ) or as indicated . For tSG induction , cells were treated with 200 μM AS ( Sigma-Aldrich ) or incubated at 43°C ( HS ) for 1 h ( or otherwise as indicated ) before being harvested for further analysis . For quantification of the foci of different protein markers in EV71-infected or 2A-expressing cells , EV71- or Myc-tagged cells with Sam68 and TIA-1 foci were counted from cells containing EV71 or Myc tag , and others were counted from cells forming TIA-1 foci . For quantification of tSG formation in EV71-infected or 2A-expressing cells , G3BP was used as an AS- or HS-induced SG marker , and HSP27 was used as an HS-induced SG marker . Cells were considered tSG positive only if they had SGs containing the indicated marker , and the diameter of the biggest SGs in EV71-infected or 2A-expressing cells was at least 1 . 5 μm ( the diameter of the biggest SGs in mock-treated cells was about 3–5 μm ) . To distinguish tSGs and aSGs , we treated SG-formed cells with 50 μg/ml CHX ( Sigma-Aldrich ) for 1 h before fixation . The tSGs would disassemble , and aSGs would remain; as a positive control , cells were treated with AS ( 200 μM for 0 . 5 h ) to induce tSG formation and then treated with both CHX and AS for another 1 h . In the GuHCl treatments , HeLa or RD cells were infected with 2 mM GuHCl ( Sigma-Aldrich ) after viral incubation for 1 h; for Western blotting assays , cells were harvested at 6 hpi , and for IF assays , cells were treated with 200 μM AS in the presence of GuHCl for the final 1 h and fixed at 6 hpi . The coding regions of G3BP ( NCBI accession no . NM_005754 . 2 ) , TIA-1 ( NCBI accession no . NM_022037 . 2 , isoform 1 ) , eIF2α ( NCBI accession no . NM_004094 . 4 ) and PABP ( NCBI accession no . NM_002568 . 3 ) were obtained from HeLa cells via RNA extraction and subsequent reverse transcription polymerase chain reaction ( RT-PCR ) and cloned into the PmeI–Bsp119I sites in pWPI vector with a N-terminal GFP or HA tag ( the original region of EMCV and GFP in pWPI was removed ) . To clone full-length eIF4GI ( NCBI accession no . NM_001194947 . 1 , isoform 6 ) , the N-terminal coding region ( 1–203 aa ) was generated by chemosynthesis , and the C-terminal coding region ( 204–1606 aa ) was obtained from HeLa cells via RT-PCR; the full-length clone was generated via overlapping PCR and cloned into pHAGE ( puro ) vector ( substituting fluorescent tag in pHAGE-CMV-MCS-IRES-ZsGreen [EvNO00061605] with puromycin ) with an HA tag at the C-terminal . The GFP-PABPM490P/Q540N mutant was generated by using overlapping PCR; PABPM490P was cloned first , and then a Q540N mutation was added . A plasmid , pCDNA3 . 0-EV71-CDS , containing completed CDS of EV71 ( Hubei-Xiangyang-09 , genotype C4 ) was obtained from Dr . K . L . Wu ( State Key Laboratory of Virology , Wuhan University , China ) . The 5’-UTR was obtained from the total RNAs of EV71-infected HeLa cells by using a 5´ RACE System ( Invitrogen ) for rapid amplification of cDNA ends according to the manufacturer’s instructions ( GSP1 , AGGGCAGTGCGTTTATGTATGG; GSP2 , GGGTGACTGTCTTCCGTTCCT ) . The 3’-UTR was obtained from the EV71-infected HeLa cells by using RT-PCR ( GGAGAGATCCAGTGGGTTAAG and oligo[dT]18 ) . A completed genome of the EV71 clone ( pCDNA3 . 0-EV71 ) was generated via overlapping PCR and cloned into the pCDNA3 . 0 vector , and it was taken as a template for creating all other clones that contained the region of the EV71 genome . EV71 proteins were obtained via PCR and cloned into the pCAGGS vector . To generate a vector containing an IRES located in multiple clone sites upstream ( pCDNA3 . 0-IRES ) , the 5’-UTR of EV71 was cloned into the EcoRI–ClaI sites in the pCDNA3 . 0 vector . The 2A protease and 2AC110S were obtained via PCR and cloned into the pCDNA3 . 0-IRES vector . To clone the 2A protease of EV71-BrCr ( NCBI accession no . U22521 ) , PV ( NCBI accession no . NC_002058 . 3 ) , and CVA ( NCBI accession no . KC117318 . 1 ) , the coding regions of the three respective viral proteases were generated by chemosynthesis and cloned into the pCDNA3 . 0-IRES vector . All the structures were confirmed by DNA sequencing . The shRNA constructs were designed by using the pLKO . 1 vector [58] according to protocols recommended by the manufacturer . For stable KD of target protein expression , HEK293T cells were cotransfected with plasmid psPAX2 , pMD2 . G , and shRNA constructs for 48 h to generate lentiviral particles . The medium was harvested and filtered by a 0 . 45 μm filter and then divided and stored at -80°C . When the lentivirus was used for infection , HeLa cells were seeded in 6-well plates ( 1–2 x 105 cells per well ) , and medium containing the lentivirus was added . After 24 h incubation , the infection medium was replaced with fresh complete growth media . Then , 24 h later , the infected cells were replated and selected in complete growth media with the addition of 2 μg/ml puromycin . After 48 h , the selected cells were replated and selected again in complete growth media with the addition of 2 μg/ml puromycin for another 48 h . Then , the selected cells were maintained in complete growth media plus 1 μg/ml puromycin or subjected to Western blotting to confirm deletion of target proteins . The stable KD cell lines were used for subsequent experiments . The target sequences for the shRNA constructs were: shPKR , GAGGCGAGAAACTAGACAAAG; shNC , GCGCGATAGCGCTAATAATTT . Cells were infected with lentiviruses that were generated by cotransfection of plasmid psPAX2 , pMD2 . G , and target protein expression constructs . The eIF4GI-HA-HeLa and eIF4GIG689E-HA-HeLa cell lines were obtained as previously described for stable KD cell lines . For the other cell lines with overexpression of GFP-tagged targets , GFP-positive cells were sorted from the infected cells via flow cytometry and cultured in complete growth media . The cell lines with stable overexpression were used for subsequent experiments . The full-length recombinant EV71 infectious clone was constructed into a pBS vector bearing a T7 promoter upstream of the virus genome ( pBS-T7-EV71 ) . The 2A protease activity-deficient EV71 infectious clone was constructed using site-directed mutagenesis via overlapping PCR ( pBS-T7-EV71-2AC110S ) . An IRES structure was inserted between the sequence of VP1 and 2A to counteract the 2Apro defect . Constructs were then linearized by restriction enzyme and purified by phenol:chloroform and ethanol precipitation . To package EV71 viruses , viral RNA was transcribed using the TranscriptAid T7 High-Yield Transcription Kit ( ThermoFisher Scientific ) and purified using the RNeasy Mini Kit ( Qiagen ) . The viral RNA ( 2 μg ) transcripts were transfected into HeLa cells grown in a monolayer on 6-well plates by using Lipofectamine 2000 for 3 days . The supernatants were passaged on fresh RD cells for further amplification . After 3 days , the supernatants were collected and stored at -80°C , and the cells were collected and divided into two groups , one for Western blotting to confirm the viral infection and the other for RT-PCR and DNA sequencing to confirm the mutation . A single recovered recombinant EV71-2AC110S was isolated by removing the agar plug during a plaque assay . The agar plug was dissolved in 500 μl of opti-MEM overnight at 4°C , and half was used for EV71-2AC110S amplification by infecting RD cell monolayers . Finally , the whole genome sequence of EV71-2AC110S was confirmed by RT-PCR and DNA-sequencing , and the titer of EV71-2AC110S was measured via plaque assay . For IF , cells were fixed with 4% ( wt/vol ) paraformaldehyde/phosphate-buffered saline ( PBS ) and permeated with 0 . 2% ( wt/vol ) Triton X-100/PBS solution at room temperature ( RT ) for 20 min , respectively , and then blocked with 3% ( wt/vol ) bovine serum albumin ( BSA ) in PBS at RT for 30 min . Primary antibodies were diluted in 1% ( wt/vol ) BSA/PBS and incubated overnight at 4°C , followed by incubation of secondary antibodies at RT for 2 h . The following dye-conjugated secondary antibodies were used for this analysis: Alexa Fluor 647 donkey anti-goat immunoglobulin ( IgG ) H+L , Alexa Fluor 488 donkey anti-rabbit IgG H+L , and Alexa Fluor 594 donkey anti-mouse IgG H+L ( Life Technologies ) . After being stained with 1 μg/ml DAPI ( Roche ) in PBS for 5 min , cells were mounted with Prolong Diamond Antifade Mountant ( Life Technology ) and examined on a Leica confocal microscope . For Western blotting , cells were harvested and lysed in lysis buffer ( 150 nM NaCl , 50 nM Tris-HCl [pH 7 . 4] , 1% Triton X-100 , 1 mM EDTA [pH 8 . 0] , and 0 . 1% sodium dodecyl sulfate [SDS] ) with a protease inhibitor cocktail , incubated on ice for 30 min , and centrifuged at 4°C for 30 min at 12 , 000 g . The supernatants were boiled in SDS-polyacrylamide gel electrophoresis ( PAGE ) loading buffer at 100°C for 10 min and then resolved on SDS-PAGE and detected on a Fujifilm LAS-4000 imaging system . The indicated primary and horseradish peroxidase-conjugated secondary antibodies ( ThermoFisher Scientific ) were used . The following primary antibodies were used: mouse monoclonal anti-c-Myc ( Cat #sc-40 ) , rabbit polyclonal anti-c-Myc ( Cat #sc-789 ) , rabbit monoclonal anti-Sam68 ( Cat #sc-333 ) , goat polyclonal anti-TIA-1 ( Cat #sc-1751 ) , mouse monoclonal anti-GAPDH ( Cat #sc-32233 ) and rabbit monoclonal anti-GFP ( Cat #sc-8334 ) were purchased from Santa Cruz Biotechnology . Mouse monoclonal anti-G3BP ( Cat #611127 ) and mouse monoclonal anti-TIAR ( Cat #610352 ) were purchased from BD Transduction Laboratories . Mouse monoclonal anti-β-actin ( Cat #AC004 ) , rabbit polyclonal anti-eIF4A ( Cat #A5294 ) , rabbit polyclonal anti-eIF4E ( Cat #A2162 ) , rabbit polyclonal anti-eIF1a ( Cat #A5917 ) , rabbit polyclonal anti-eIF3a ( Cat #A0573 ) , rabbit polyclonal anti-RPS3 ( Cat #A11131 ) , and rabbit polyclonal anti-3C ( Cat #A10003 ) were purchased from ABclonal . Rabbit monoclonal anti-eIF4G ( Cat #2469S ) , rabbit monoclonal anti-p-eIF2α ( Cat #9721 ) , and rabbit monoclonal anti-eIF2α ( Cat #9722 ) were purchased from Cell Signaling Technology . Mouse monoclonal anti-Flag ( Cat #F1804 ) , mouse monoclonal anti-HA ( Cat #H9658 ) , and rabbit monoclonal anti-HA ( Cat #H6908 ) were purchased from Sigma-Aldrich . Mouse monoclonal anti-PABP ( Cat #ab6125 ) was purchased from Abcam . Mouse monoclonal anti-HSP27 ( Cat #ADI-SPA-800D ) was purchased from StressGen . Mouse monoclonal anti-EV71 ( Cat #MAB979 ) and Mouse monoclonal anti-puromycin , clone 12D10 ( Cat #MABE343 ) were purchased from Millipore . Mouse monoclonal anti-VP1 was purchased from Abmax ( Clone 22A14 ) [59] . For detection of total polyadenylated mRNA ( polyA+ mRNA ) , cells were plated on coverslips and incubated overnight before treatment with AS , EV71 , or 2A . Cells were fixed with 2% formaldehyde for 10 min and processed as previously described [60] by using a 3’-biotinylated oligo ( dT ) 40 probe . Cells were then processed as those described for the aforementioned IF assays . The oligo ( dT ) 40 probe was visualized by streptavidin conjugated to cyanin 3 ( Cy3 ) . The ViewRNA ISH Cell Assay Kit and probes for EV71 positive-strand RNA ( +vRNA ) and PABPC1 mRNA were purchased from Affymetrix and used to detect target mRNAs according to protocols recommended by the manufacturer . A Renilla luciferase gene sequence was constructed into the aforementioned EV71 infectious clone backbone ( pBS-T7-EV71 ) by replacing the whole viral protein-coding sequence ( UTREV71-Rluc ) . The UTRPABPC1-Rluc reporter was generated by replacing the EV71 UTR region by PABPC1 UTR region . The RNAs were transcribed using the TranscriptAid T7 High-Yield Transcription Kit ( ThermoFisher Scientific ) and purified using the RNeasy Mini Kit ( Qiagen ) . To evaluate the influence of aSGs on EV71 or PABPC1 translation , eIF4GI-HA- and eIF4GIG689E-HA-HeLa cells were seeded in 24-well plates , and the RNA ( 0 . 4 μg/well ) transcripts were transfected into the cells after EV71 ( MOI = 10 ) infection for 3 hours or EV71-2AC110S ( MOI = 10 ) infection for 6 hours , then analyzed the reporter expression at 1 . 5 hpt and 3 hpt . Cells infected with EV71-2AC110S served as negative control and analyzed the reporter expression at 3 hpt . To evaluate the influence of tSGs on EV71 or PABPC1 translation , shNC- and shPKR-HeLa cells were seeded in 24-well plates and the RNA ( 0 . 4 μg/well ) transcripts were transfected into the cells after EV71-2AC110S ( MOI = 10 ) infection for 6 h or EV71 ( MOI = 10 ) infection for 3 h . The reporter expression in EV71-2AC110S-infected cells were analyzed at 3 hpt and 6 hpt and the reporter expression in EV71-infected cells were analyzed at 3 hpt as control . Renilla luciferase activity was assessed by using a Renilla Luciferase Assay Kit ( Promega ) according to the manufacturer’s instructions . All experiments were performed in triplicate , and assays were repeated at least three times . Statistical analysis was performed using GraphPad Prism v6 . 01 . All results are expressed as means ± SD of at least three independent experiments ( n≥3 ) . The p value was calculated using an unpaired Student's t-test . In all tests , p>0 . 05 was considered non-statistically significant ( n . s . ) , and p<0 . 05 was considered statistically significant , marked as follows: * , p<0 . 05; ** , p<0 . 01; *** , p<0 . 001 .
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When cellular translation initiation is stalled , translation initiation complexes aggregate in cytoplasm . We call these aggregations stress granules ( SGs ) , and they can be marked by components such as TIA-1 . SGs are always considered to be antiviral structures during viral infection , but viruses also regulate SG formation to facilitate their survival . Here , we show that the 2A protease of EV71 induced TIA-1 foci formation , and we analyzed these TIA-1 foci and found that they were different from typical stress granules ( tSGs ) ; thus , we named them atypical stress granules ( aSGs ) . 2A alone could block tSG formation , and we found that protease activity of 2A was required for aSG induction and tSG blockage , but functioned in different ways . When the protease activity of 2A in EV71 was blocked ( EV71-2AC110S ) , the tSGs but not aSGs appeared in infected cells . These tSGs contained cellular and viral mRNAs and translation initiation factors to inhibit viral translation , but aSGs contained only cellular mRNAs to promote viral translation . We propose a model revealing that EV71 escapes cellular antiviral response by manipulating SG formation: 2A transforms the overall translation shutdown system to a selective virally beneficial system by switching from tSGs to aSGs .
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2018
|
Picornavirus 2A protease regulates stress granule formation to facilitate viral translation
|
Cutaneous and mucosal leishmaniasis is widely distributed in Central and South America . Leishmania of the Viannia subgenus are the most frequent species infecting humans . L . ( V . ) braziliensis , L . ( V . ) panamensis are also responsible for metastatic mucosal leishmaniasis . Conventional or real time PCR is a more sensitive diagnostic test than microscopy , but the cost and requirement for infrastructure and trained personnel makes it impractical in most endemic regions . Primary health systems need a sensitive and specific point of care ( POC ) diagnostic tool . We developed a novel POC molecular diagnostic test for cutaneous leishmaniasis caused by Leishmania ( Viannia ) spp . Parasite DNA was amplified using isothermal Recombinase Polymerase Amplification ( RPA ) with primers and probes that targeted the kinetoplast DNA . The amplification product was detected by naked eye with a lateral flow ( LF ) immunochromatographic strip . The RPA-LF had an analytical sensitivity equivalent to 0 . 1 parasites per reaction . The test amplified the principal L . Viannia species from multiple countries: L . ( V . ) braziliensis ( n = 33 ) , L . ( V . ) guyanensis ( n = 17 ) , L . ( V . ) panamensis ( n = 9 ) . The less common L . ( V . ) lainsoni , L . ( V . ) shawi , and L . ( V . ) naiffi were also amplified . No amplification was observed in parasites of the L . ( Leishmania ) subgenus . In a small number of clinical samples ( n = 13 ) we found 100% agreement between PCR and RPA-LF . The high analytical sensitivity and clinical validation indicate the test could improve the efficiency of diagnosis , especially in chronic lesions with submicroscopic parasite burdens . Field implementation of the RPA-LF test could contribute to management and control of cutaneous and mucosal leishmaniasis .
Dermal and mucosal leishmaniasis are widely distributed in Central and South America , affecting an estimated 190 , 000–300 , 000 people annually [1] . Many different Leishmania species grouped under the subgenera Leishmania or Viannia can produce dermal leishmaniasis . Epidemiologically , Viannia is the most relevant subgenus in this region since it is highly prevalent and also responsible for metastatic mucosal leishmaniasis ( L . ( V . ) braziliensis , L . ( V . ) panamensis , L . ( V . ) guyanensis ) , the severe form of tegumentary disease [2 , 3] . Microscopy is still the most common diagnostic method used in endemic regions but its sensitivity is not ideal and markedly affected by the experience of the microscopist [4] . Furthermore , the sensitivity of this method tends to decrease with disease chronicity , which is characterized by a low number of amastigotes in the lesions [4] . Serological tests were used in the past and the identification of new antigens and formats for serodiagnosis of American cutaneous leishmaniasis is still considered [5 , 6] . However , in general , they have proven to be of limited value due to the variable immune responses of patients and no clear distinction between current disease and past infections or exposure . Conventional or quantitative PCR from dermal or mucosal samples have high diagnostic sensitivity ( ≈87–98% ) and specificity ( ≥84% ) [7] . This molecular method is currently the gold standard in leishmaniasis reference centers or tertiary care facilities . However , the need for expensive equipment , trained personnel , and relatively complex laboratory facilities are beyond the capability of the typical health infrastructure in endemic areas . Therefore , there is a clear need to provide primary health systems with diagnostic tools that are simple , easy to use and have good sensitivity and specificity . To address this critical gap , we developed a novel-point-of-care molecular test to diagnose dermal and mucosal leishmaniasis produced by Leishmania Viannia spp . We designed primers and probes that targeted the kinetoplast DNA minicircles , similar to the strategy we used previously to detect L . infantum chagasi [8] . Leishmania DNA was amplified using isothermal Recombinase Polymerase Amplification ( RPA ) , a method originally described by Piepenburg et al . [9] . The amplification product was detected in a lateral flow immunochromatographic strip ( LF ) which is read with the naked eye . Its analytical sensitivity and specificity indicated that it could be used as a point-of-care diagnostic test for dermal and mucosal leishmaniasis in endemic areas of Latin America .
The current study was approved by the Office of Sponsored Programs of the University of Texas Medical Branch . The activities of NAMRU-6 were conducted in compliance with all applicable federal and international regulations governing the protection of human subjects . This study was approved by the Institutional Review Board of the U . S . Naval Medical Research Unit 6 ( NMRCD . 2007 . 0018 ) , and administratively approved by the Madre de Dios Regional Health Directorate in Peru . CIDEIM provided DNA samples stored in its cryobank and consent forms from patients for multiple uses were obtained . The IRB of UTMB waived ethical approval for this study based on the utilization of DNA from de-identified patients . The primer sets for Leishmania Viannia are 30–35 nucleotides long and target conserved sequences identified by computational alignment of L . Viannia kDNA minicircle sequences reported in GenBank . Primers were designed with 40–60% GC content , few direct/inverted repeats , and absence of long homopolymer tracts . We focused principally on conserved regions and to a lesser extent on regions with moderate variability , obtaining a 120 bp RPA amplicon in agarose gels . To enable detection by lateral flow , the reverse primer was biotinylated at the 5’ end . We designed a 45bp conserved internal probe ( Biosearch technologies -Petaluma , CA ) that included FAM ( 5’-carboxy fluorescein amidite ) at the 5’ end , an internal dSpacer and a SpacerC3 in the 3’ end , as suggested by the manufacturer ( TwistDx ) . Forward Primer: Fw- GATGAAAATGTACTCCCCGACATGCCTCTG . Reverse Primer: Rev-bio-CTAATTGTGCACGGGGAGGCCAAAAATAGCGA . Internal Probe: The probe contains a 5’-fluorescein group ( FAM ) , an internal ( THF ) -tetrahydrofuran residue , and a C3 spacer block at the 3’ end . Probe-FAM-GTAGGGGNGTTCTGCGAAAACCGAAAAATG[THF]CATACAGAAACCCCG[C3-spacer] . Promastigote suspensions of reference strains or clinical strains thawed from cryopreserved stocks or absorbed in Whatman FTA filter paper ( Sigma-Aldrich ) were subjected to 95°C for 2 minutes in a dry bath to lyse the parasites . DNA purification for the majority of the samples was carried out using the DNeasy Blood & Tissue Kit ( Qiagen ) following the recommendations of the vendor and adjusted to10 ng/μL . In addition , a small number of clinical samples ( n = 8 ) obtained from ulcers of Peruvian patients suspected of having cutaneous leishmaniasis were absorbed in Whatman FTA filter paper . The filter papers ( n = 2 of 6 mm diameter ) were placed in direct contact with the ulcer allowing lymph and cells to be absorbed by the papers . Once dried , each patient sample was packed individually using sealed plastic bags which were labeled and transported to the central lab at room temperature . Two 3mm diameter filter papers were punched from the original samples , washed 3 times with 200 μL of FTA buffer ( Whatman , GE Healthcare Life Sciences ) followed by 3 washes with TE buffer pH 8 ( Sigma ) . The papers were then suspended in water and heated at 95°C for 30 minutes; 2 . 5 μL of the solution were used to run the RPA-LF test . The amplification mixture was comprised of: 1 ) forward primer , 2 ) biotinylated reverse primer , 3 ) FAM-labeled probe ( stocks-5μM ) , 4 ) magnesium acetate , and 5 ) the rehydrated cocktail ( Twist amp nfo RPA kit -TwistDx , UK ) . Parasite DNA ( 5–25ng/μL ) was immediately added to the mixture and subjected to amplification at 45°C for 30 minutes using a dry bath . The RPA product was diluted 1:25 in the dipstick assay buffer and 30 μL were placed in a 1 . 5 Eppendorf tube or 96-well microplate . The bottom tip of the lateral flow strip was then immersed in the sample ( GenLine HybriDetect , Milenia Biotec , Germany ) making the amplification product run upwards by capillarity . Parasite amplification was confirmed with the naked eye after 5 minutes by the appearance of the test band in the lower part of the strip . This band is produced when anti-biotin antibodies immobilize the amplified DNA which contains the biotinylated primers . The gold particles , which are covered with mouse anti-FAM antibodies , bind to the probe labeled with FAM making the test band visible . The reaction was validated by the appearance of the control band in the upper part of the strip . This band appears upon the immobilization of excess free-gold particles ( which are covered with mouse antibodies ) by means of anti-mouse antibodies . The RPA-LF sensitivity was compared with SYBRgreen real-time PCR using the primers described by Pita-Pereira et al . [10] . The analytical evaluations of RPA-LF were carried out using known concentrations of DNA ( 10ng/μL ) . We evaluated banked strains of L . braziliensis from Brazil ( n = 15 ) , Colombia ( n = 5 ) , and Peru ( n = 13 ) ; L . guyanensis from Brazil ( n = 11 ) and Colombia ( n = 6 ) ; L . panamensis from Colombia ( n = 7 ) , Nicaragua ( n = 1 ) , and Panama ( n = 1 ) ; L . lainsoni from Brazil ( n = 3 ) and Peru ( n = 7 ) ; and L . shawi ( n = 2 ) and L . naiffi ( n = 6 ) from Brazil . Also , we evaluated DNA purified from lesion biopsies of patients from Peru who were infected with L . braziliensis ( n = 9 ) and L . guyanensis ( n = 4 ) , as well as non-leishmanial ( PCR-negative ) skin lesions ( n = 5 ) .
The RPA-LF amplified Leishmania DNA with an analytical sensitivity equivalent to 0 . 1 parasite per reaction , which corresponded to aCt value of 28 in the real-time PCR used as the gold standard ( Fig 1 ) . The capacity of RPA-LF to detect the most relevant species of the subgenus Viannia was initially determined by the amplification of a small number of banked strains of Leishmania Viannia spp: L . braziliensis , L . panamensis , L . guyanensis , L . lainsoni , L . shawi and L . naiffi . The specificity was confirmed by the lack of amplification of L . donovani , L . chagasi , L . mexicana , L . amazonensis , L . major , Trypanosoma cruzi and human DNA ( Fig 2 ) . We further evaluated panels of strains from different species within the Viannia subgenus isolated in endemic areas of Brazil , Colombia , and Peru . Fifteen out of 15 L . braziliensis strains from Brazil , 6/6 strains from Colombia , and 12/12 from Peru , isolated from humans or dogs from different geographical areas , were amplified by RPA-LF ( Table 1 ) . The test also demonstrated good sensitivity to detect several L . guyanensis strains obtained from endemic regions of Brazil ( 11/11 ) and Colombia ( 6/6 ) ( Table 1 ) . Similarly , L . panamensis strains originally isolated from patients of Colombia ( 7/7 ) , Nicaragua ( 1/1 ) , and Panama ( 1/1 ) were readily amplified by RPA-LF . A small group of L . Viannia species known to occasionally infect humans were also evaluated by RPA-LF . Two Brazilian strains of L . shawi , a species closely related to L . guyanensis , produced strong bands indicating that the primers efficiently amplified this parasite species . However , 5/6 strains of Leishmania naiffi , usually found in mammals of the Amazon region and less frequently in other parts of South America , were amplified less efficiently than other Viannia species and generated weaker bands ( Table 1 ) . In the case of L . lainsoni , a parasite found in wild mammals and sporadically infecting humans , RPA-LF produced a weak yet clearly detectable band in 3/3 strains from Brazil and 6/7 from Peru . One L . naiffi-L . lainsoni hybrid from Brazil was also detected by RPA/LF . Collectively , these results indicated that the test is capable of detecting all the epidemiologically relevant species of the Viannia subgenus . We developed an interactive map that depicts the geographical distribution of Leishmania species evaluated by RPA-LF ( http://www . scribblemaps . com/maps/view/Leish_Viannia/9-18-15 ) . In a small number of clinical samples we found that RPA-LF has excellent agreement with PCR as determined in DNA samples from patients of Peru infected with L . braziliensis or L . guyanensis ( Table 2 ) . All 9 of the samples from clinical lesions due to L . ( V . ) braziliensis , and all 4 of the samples from clinical lesions due to L . ( V . ) guyanensis were positive by RPA-LF . The samples from negative controls were uniformly negative by RPA-LF . The high sensitivity and specificity identified with these limited number of samples warrants large-scale field testing to determine the diagnostic sensitivity of the RPA-LF . A potential limitation for field application of molecular diagnostic methods is the need for equipment such as vortex and high speed centrifuge to purify DNA from the clinical sample . We evaluated a DNA extraction method based on brief washing , elution and 95°C heating of the sample absorbed in filter paper ( details in Materials & Methods ) . Using this approach we successfully amplified by RPA-LF all the samples of patients infected with Leishmania Viannia spp . as confirmed by real time PCR ( Fig 3 ) . This result indicated that RPA-LF could be implemented in basic diagnostic settings .
We developed a field-applicable molecular diagnostic test that distinguishes between the subgenera Viannia and Leishmania by selectively detecting strains of the Viannia subgenus . Our primers and probes were designed to target the kinetoplast DNA minicircles due to the high copy number ( ≈ 10 , 000 ) of this circular network of genomic mitochondrial DNA [11] . This remarkable number of copies provides a comparative advantage over other parasite targets with regard to test sensitivity . We targeted the Viannia subgenus because it encompasses the most relevant species causing cutaneous leishmaniasis in Latin America . The evaluation of the RPA-LF test included strains from Brazil , Colombia , and Peru , in which the recently reported incidence was 26 , 008 , 17 , 420 , and 6 , 405 cases/year , respectively [1] . The number of patients requiring diagnosis in these countries could be even greater since it was estimated that under-reporting varied between 2 . 8 and 4 . 6 fold [1] . The discrimination between Viannia and Leishmania subgenera is clinically relevant because in Latin America these infections may be treated differently [12] . Also , infection with L . braziliensis , L . panamensis , and less frequently L . guyanensis require prolonged patient follow up due to the risk of mucosal metastasis after apparent successful treatment [13 , 14] . Leishmania ( V . ) shawi was readily detected by the RPA-LF test . Early studies suggested that L . shawi was not frequently reported in humans and seemed to be of low prevalence in nature [15 , 16] . However , more recent studies in Northeastern Brazil found that 6 . 5% ( 5/77 ) of isolates were identified as L . shawi and that some of them could be considered hybrids with L . braziliensis [17] . The RPA-LF was less efficient at amplifying L . naiffi , a species found in armadillos and occasionally infecting humans in different countries of South America [18 , 19] . Therefore , further test optimization would be necessary for epidemiological studies aimed at this particular species . During the development phase , we detected variability in distinct batches of the lateral flow strips ( Milenia Biotec , Germany ) regarding increased background that led to the appearance of faint test bands in the negative controls . The problem was resolved by using higher dilutions of the amplification product ( 1:100–1:200 ) . Each laboratory should standardize and select the lateral flow strips that best suits its needs . There are different commercial options of immunochromatographic strips for lateral flow reading . They are offered in containers with multiple strips ( Milenia , Biotec ) , individual cards ( Abingdon Health , UK ) , or cassettes ( UStar , China ) that are putatively less prone to contamination . Scrapings or brushings of cutaneous lesions absorbed in filter paper were shown to be amenable to molecular diagnosis using PCR [20] . We have already shown that RPA-LF could use this preservation-transportation method to amplify Leishmania DNA from the blood of dogs infected with L . chagasi [8] . The test was capable of amplifying DNA equivalent to 0 . 1 parasites in the reaction mix , which was comparable to the detection limit of our qPCR . Preliminary results using a small number of samples from lesions suggested that RPA-LF can efficiently detect parasite DNA in the presence of host DNA with high sensitivity and specificity . Nevertheless , the diagnostic sensitivity will have to be evaluated under field conditions in a larger number of patients . It is well established that parasite burdens tend to be highly variable and that parasites are more difficult to detect in chronic lesions [4] . Therefore , it will be particularly important to evaluate the diagnostic sensitivity of the RPA-LF in chronic lesions with >3 months of evolution . A significant advantage of the RPA-LF is that samples can be rapidly processed , without the need of sophisticated equipment , outside of a traditional laboratory ( e . g . at a house , school , or community center ) . Furthermore , initial evaluations strongly suggested that DNA extraction could be accomplished efficiently using a method that does not require equipment other than a boiling bath , giving additional support to the feasibility of adapting RPA-LF to the POC . RPA-LF is a less complex test than other isothermal amplification methods . RPA-LF results would be available in approximately one hour and the patients could initiate treatment if tested positive . Compared to a PCR reference test , this approach should enable earlier initiation of treatment , significantly increasing compliance and treatment efficacy . The need for delivering samples to a central reference lab , that leads to delayed therapeutic decisions and increased risk of patient loss , would be avoided . Importantly , the implementation of the field-applicable RPA-LF could replace or repurpose the need for experienced microscopists ( and microscopes ) . It will improve the efficiency to diagnose leishmaniasis of short evolution time and , more importantly , in chronic lesions with parasite burdens below the microscopy threshold . The RPA-LF test may well fill the need for a field-applicable test , which is critical to cutaneous and mucosal leishmaniasis management .
|
Cutaneous leishmaniasis is a parasitic disease transmitted by the bite of sandflies that produces skin ulcers . The severe , disfiguring form of the disease is characterized by parasite dissemination to the mucosa of the nose and palate . Current diagnosis is based on microscopy which has low sensitivity in chronic cases . Molecular methods ( PCR ) that detect parasite DNA are highly sensitive but costs and personnel training make it impossible to implement it in resource-limited areas . We developed a novel molecular method ( RPA-LF ) that could be applied in the field because it does not require sophisticated equipment . It is also very sensitive and specific to detect the principal Leishmania species that produce cutaneous leishmaniasis in Latin America . Future field implementation of RPA-LF could have a positive impact on disease management and control .
|
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2016
|
An Innovative Field-Applicable Molecular Test to Diagnose Cutaneous Leishmania Viannia spp. Infections
|
The Aspergillus fumigatus sterol regulatory element binding protein ( SREBP ) SrbA belongs to the basic Helix-Loop-Helix ( bHLH ) family of transcription factors and is crucial for antifungal drug resistance and virulence . The latter phenotype is especially striking , as loss of SrbA results in complete loss of virulence in murine models of invasive pulmonary aspergillosis ( IPA ) . How fungal SREBPs mediate fungal virulence is unknown , though it has been suggested that lack of growth in hypoxic conditions accounts for the attenuated virulence . To further understand the role of SrbA in fungal infection site pathobiology , chromatin immunoprecipitation followed by massively parallel DNA sequencing ( ChIP-seq ) was used to identify genes under direct SrbA transcriptional regulation in hypoxia . These results confirmed the direct regulation of ergosterol biosynthesis and iron uptake by SrbA in hypoxia and revealed new roles for SrbA in nitrate assimilation and heme biosynthesis . Moreover , functional characterization of an SrbA target gene with sequence similarity to SrbA identified a new transcriptional regulator of the fungal hypoxia response and virulence , SrbB . SrbB co-regulates genes involved in heme biosynthesis and demethylation of C4-sterols with SrbA in hypoxic conditions . However , SrbB also has regulatory functions independent of SrbA including regulation of carbohydrate metabolism . Loss of SrbB markedly attenuates A . fumigatus virulence , and loss of both SREBPs further reduces in vivo fungal growth . These data suggest that both A . fumigatus SREBPs are critical for hypoxia adaptation and virulence and reveal new insights into SREBPs' complex role in infection site adaptation and fungal virulence .
Invasive fungal infections have increased in frequency due to a substantial rise in the number of immune compromised patients [1]–[3] . In particular , the filamentous fungal pathogen Aspergillus fumigatus is a major cause of morbidity and mortality in patients undergoing immunosuppressive therapy for organ transplants and/or cancer treatment [2] , [4] , [5] . Treatment options for invasive aspergillosis ( IA ) remain limited and associated mortality rates are high [6] . Epidemiological studies suggest that over 200 , 000 cases of aspergillosis occur worldwide on an annual basis , and there is general consensus that disease caused by A . fumigatus is under diagnosed [2] . It is clear that new insights into the pathophysiology of this too often lethal disease are needed to develop new diagnostic and treatment strategies to improve patient outcomes . Along these lines , investigating fungal growth in vivo at infection site microenvironments is an important area of research with significant therapeutic potential . Observations from human IA cases and recent discoveries in murine models of invasive pulmonary aspergillosis ( IPA ) indicate that the infection microenvironment is characterized in part by low oxygen availability ( hypoxia ) [7]–[10] . Hypoxia is associated with poor clinical outcomes for many human diseases , but its impact on invasive fungal infections remains understudied [11]–[16] . One hypothesis is that hypoxia promotes fungal virulence through induction of a fungal metabolic , or bioenergetics , program that contributes to host damage . In support of this hypothesis , fungal genes required for hypoxic growth are generally critical for fungal virulence in murine models , and airway ischemia was recently shown to promote A . fumigatus invasion in an orthotropic tracheal transplant model of Aspergillus infection [15]–[20] . One fungal gene family required for hypoxia adaptation and growth is the sterol regulatory element binding protein family ( SREBP ) [21] . First identified in mammals , two distinct mammalian SREBP genes exist , SREBP-1 and SREBP-2 . SREBP-1 produces two isoforms , SREBP-1a and SREBP 1-c , derived from alternative splicing of the first exon [22] . These SREBP-1 isoforms share the same DNA-binding domain , the sterol regulatory element ( SRE ) , and have been shown to mainly regulate lipid metabolism , whereas SREBP-2 predominantly regulates cholesterol metabolism [23] . Recent genomic approaches have yielded new insights into mammalian SREBP functions through identification of novel target genes . In mice , ChIP-seq analyses revealed that SREBP-1c binds upstream of genes associated with lipid biosynthesis , insulin dependent pathways , carbohydrate metabolism , and additional novel gene ontology ( GO ) categories including intracellular protein trafficking , cell proliferation and differentiation , and apoptosis [24] . ChIP-seq analysis of SREBP-2 target genes in murine hepatic chromatin revealed new roles for this protein in apoptosis and autophagy [25] . Thus , it has been suggested that SREBPs are necessary for coordination of the cellular nutritional state and transcriptional activation by interacting with different cofactors in response to dynamic nutritional microenvironments [26] . With regard to SREBP function in fungi , a seminal study in the fission yeast Schizosaccharomyces pombe identified a molecular link between SREBP function and fungal hypoxia adaptation and growth [27] . In this organism , the SREBP bHLH domain containing protein , Sre1 , has been identified as a primary regulator of anaerobic gene expression [28] . Accordingly , an sre1 deletion mutant is unable to grow in anaerobic conditions confirming an indirect molecular mechanism of oxygen sensing through Sre1 mediated monitoring of ergosterol levels [27] , [29] . Sre1 proteolytic cleavage requires an E3 ligase , which is distinct from the mammalian SREBP cleavage mechanism utilizing site-1 and site-2 proteases [27]–[35] . Subsequent studies in the human pathogenic yeast Cryptococcus neoformans and filamentous fungus A . fumigatus identified a critical role for fungal SREBPs and associated regulatory factors in hypoxia adaptation , iron homeostasis , azole drug responses , and importantly fungal virulence [18] , [19] , [36]–[39] . The molecular basis for fungal SREBPs' role in virulence remains to be fully elucidated . Identification of putative SREBP target genes through genome-wide gene expression analyses indicates that fungal SREBPs are important regulators of ergosterol metabolism and iron uptake [18] , [21] , [38] , [39] . In A . fumigatus , microarray analyses of gene expression in the presence and absence of SrbA in hypoxic environments revealed significant changes in transcript levels of approximately 12% of the genes in the genome [36]–[38] . Many of the gene transcript levels that are affected by SrbA are associated with biological processes induced by hypoxia in wild type A . fumigatus including: ergosterol biosynthesis , iron homeostasis , cell wall biosynthesis , amino acid biosynthesis , general carbon metabolism , and the GABA shunt [40] . However it remains unclear which hypoxia induced genes are directly SrbA dependent . Understanding fungal SREBP function is further complicated by the presence of at least two SREBPs in many of the fungal genomes queried to date [21] , [27] , [36] , [41] , [42] . Data also suggest that additional SREBP interacting partners are required for proper modulation of sterol levels in several organisms [21] , [26] , [43] . Given the little we know of direct fungal SREBP target genes , and the differing transcriptional networks that organisms utilize to respond to similar microenvironments , we sought to precisely define the SrbA-mediated transcriptome ( regulon ) of A . fumigatus in response to hypoxia . In order to definitively delineate the SrbA hypoxia regulon , we utilized a multi-faceted approach to validate not only direct transcriptional targets of SrbA , but also the putative significance of these targets during an invasive pulmonary infection . In addition to identifying a role for A . fumigatus SrbA in direct transcriptional regulation of novel genes involved in the fungal hypoxia response , we identified and functionally characterized a second SREBP family member , designated SrbB , which is a direct transcriptional target of SrbA in hypoxia . Together , SrbA and SrbB regulate and co-regulate genes critical for fungal metabolism , virulence , and responses to antifungal drugs . These results place SrbA and SrbB as central transcriptional regulators of fungal metabolic responses required for in vivo fungal growth and host damage . Consequently , further characterization of the pathways and networks regulated by SrbA-SrbB is expected to promote a novel research direction aimed at inhibiting the function of this in vivo associated fungal genetic network to improve IPA prognosis .
The workflow for this study was informed by previous research that assessed the significance of SrbA in hypoxia growth and fungal pathogenesis [36] and subsequent studies looking at transcriptional changes associated with the A . fumigatus response to hypoxia [38] , [40] , [44] . To gain new mechanistic insights into how SrbA mediates these important phenotypes , ChIP-seq analysis using an SrbA specific antibody after 4 hours ( two biological samples ) and 12 hours ( one biological sample ) exposure to hypoxia was conducted [37] , [38] . The overall number of Illumina 76 base-pair paired end reads used for peak calling among the three sets of ChIP-seq samples were 2992021 and 3345809 for ChIP and input control respectively ( Table S1 ) . Reads were aligned to the A . fumigatus A1163 genome ( Figure 1A ) and used for peak calling with the Macs2 program either in aggregate , or one sample at a time [45] . By including input controls ( samples with no SrbA antibody ) in the analysis with an FDR of 0 . 05 , a core set of 111 peaks corresponding to 97 genes were identified ( Table S2 ) . A subset of 30 genes of biological interest associated with SrbA binding events are listed in Table 1 . 25 of 30 ( 83% ) of these peaks were located within 1 kb upstream of translational start sites ( Table 1 ) . Figure 1B shows examples of peak regions from eight target genes . Using additional independent biological replicates , ChIP-qPCR confirmed SrbA binding to the promoter regions of the selected genes in response to hypoxia ( Figure 1C ) . An SrbA-bound DNA motif ( Figure 1D ) was discovered using multiple EM for motif elicitation ( MEME ) of the identified peaks [46] . The SrbA DNA binding motif was identified as an 11-bp binding region predominated by ATCA in positions 1–4 , a cytosine in position 7 , and an adenine in position 9 . Other positions were more variable , with a predominance of cytosine residues . This DNA motif ( 5′ ( A/G ) TCA ( T/C/G ) ( C/G ) CCAC ( T/C ) -3′ ) is similar to a previously identified SrbA DNA binding motif that was discovered using bioinformatic tools , 5′-ATC ( G/A ) ( T/G ) ( A/G ) ( C/T ) ( G/C ) AT-3′ [47] . The sequence TCACNCCAC has been identified in humans as the SRE binding motif [48] , [49] . Additionally in S . pombe , a motif was defined using MEME to be ( A/G ) ( C/T ) C ( A/G/T ) NN ( C/T ) ( C/T/G ) A ( C/T ) , which contains similar conserved residues as our sequence [28] . Recently , the bHLH transcription factor Hms1 in C . albicans was found to bind the consensus sequence ATCACCCCAC , which is strikingly similar to the identified motif for SrbA [50] . Using this motif , we analyzed a previously published ΔsrbA microarray dataset , which revealed that this SrbA DNA binding motif is overrepresented among the differentially expressed genes when comparing wild type to ΔsrbA further validating the SRE motif [38] . Five of the identified peaks had two-to-three occurrences of the motif , including SrbA itself . The binding of SrbA to its own promoter reveals an autoregulatory positive feedback loop for modulation of srbA mRNA levels . To further determine the biological processes and molecular function of SrbA direct target genes , SrbA target genes were analyzed for gene ontology ( GO ) and FunCat enrichment with FungiFun2 ( Figure 1E , Table S3 ) [51] . Of the 97 unique SrbA target genes , only 19 were significantly enriched in FunCat categories ( P≤0 . 05 ) and 33 in GO categories ( P≤0 . 05 ) . Overall , approximately 35% of the SrbA target genes are not currently annotated . Consistent with our previous microarray-based transcriptome analysis , and known functions of yeast and mammalian SREBPs , SrbA is a direct regulator of genes involved in lipid , fatty acid and isoprenoid biosynthesis , which includes ergosterol biosynthesis ( Table S3 ) . In addition , A . fumigatus SrbA target genes were associated with heme and oxygen binding and nitrate metabolic processes . Taken together , annotated SrbA direct target genes are associated with biological processes impacted by both oxygen and iron limitation that are critical for fungal virulence . These results thus indicate that SrbA is a major transcriptional regulator of fungal metabolism ( bioenergetics ) in response to hypoxia . To further define SrbA target genes and confirm SrbA regulation of genes with associated SrbA DNA binding events in their promoter regions , RNA-seq analysis of the hypoxia transcriptome of ΔsrbA was conducted pooling total RNA samples from independent biological cultures in triplicate . A 30 and 120 minute response to hypoxia was examined by comparing ΔsrbA samples to the same time point as the wild type . Consistent with the previously published microarray and RNA-seq analyses of the A . fumigatus hypoxia response , RNA-seq analyses here revealed substantial changes to the transcriptome of wild type and ΔsrbA in response to hypoxia [38] , [40] , [44] . Somewhat surprisingly , loss of SrbA had minimal effect on the transcriptome of A . fumigatus after 30 minutes exposure to hypoxia , as only 48 genes had transcript levels decrease 4-fold or greater in ΔsrbA compared to wild type ( Table S4 ) during this time period . Perhaps of interest , these 48 genes were enriched for functions involving post-translational modification of amino acids . Notably , genes involved in ergosterol biosynthesis are generally unaffected at this time point in the absence of SrbA . However , at 30 minutes post-hypoxia exposure , loss of SrbA resulted in transcript level increases for 383 genes compared to wild type . Interestingly , these genes were enriched for degradation of the amino acids tyrosine and phenylalanine . Previously , an analysis of the free amino acid pool in ΔsrbA in response to iron replete and limiting conditions revealed substantial changes in the amino acid pools of ΔsrbA [38] . SrbA's role in hypoxic adaptation becomes evident at 120 minutes post-exposure to hypoxia with 520 genes having a 4-fold or greater decrease in transcript levels in the absence of SrbA compared to wild type . These genes are enriched for fatty acid and lipid biosynthesis , iron ion binding , carbohydrate metabolism , virulence , isoprenoid metabolism , and cellular oxidoreductase activity ( Figure 2A ) . Importantly , the majority of SrbA direct target genes identified in our ChIP-seq analysis fall into this group of genes with reduced mRNA levels strongly suggesting that SrbA directly positively regulates their mRNA abundance in response to hypoxia . Conversely , 467 genes had a 4-fold or greater increase in transcript levels in the absence of SrbA compared to wild type . These genes were enriched in part for transcription factor activity , and as no enrichment of the SRE motif could be found in this dataset ( P-value - 0 . 96 Fisher Exact test ) , we interpret the increase in transcript levels of these genes as indirect responses to the loss of SrbA activity in the cell , rather than SrbA acting as a transcriptional repressor of these genes . Alternatively , SrbA may positively regulate an unidentified transcriptional repressor ( s ) . Taken together , these results strongly suggest that SrbA is a direct positive transcriptional regulator of genes required for adaptation to hypoxia . Moreover , these results strongly suggest that loss of SrbA fundamentally alters fungal cellular bioenergetics in response to hypoxia . To gain insights into SrbA target genes critical for pathogenesis , we interrogated the mRNA abundance of a sub-set of SrbA target genes in an in vivo murine model of IPA , and in vitro in response to normoxia and hypoxia utilizing Nanostring nCounter technology [52] , [53] . Consistent with the RNA-seq data , nCounter analyses confirmed that transcript abundance of sterol biosynthesis genes in hypoxia decreased in vitro with loss of srbA ( Figure 2B ) . Moreover , erg3B , erg11A , erg25A , erg25B , all displayed high transcript levels in vivo in lung parenchyma tissue consistent with their SrbA-dependent hypoxia induction in vitro and the occurrence of hypoxia in vivo ( Figure 2B , Table S5 ) . Additional genes that showed strong SrbA dependency in vitro and high transcript levels in vivo included AFUB_091650 ( sit1 ) , a putative siderophore-iron transporter , that is critical for response to low iron and previously shown to be directly transcriptionally regulated by SrbA using ChIP-qPCR [38] , [54] . Sit1 may be critical for virulence as mRNA abundance is higher in vivo than in either of the tested in vitro conditions . The high transcript levels of sit1 early in infection confirm the iron-limited environment of the murine lung . These data support direct regulation of iron uptake in vivo by SrbA , and further support the link between SrbA , hypoxia adaptation , and iron homeostasis in A . fumigatus . In addition to sit1 , two other metabolic genes , hem13 and alcC , show less SrbA dependency in vitro than the ergosterol biosynthesis genes , but significant transcript induction in vivo . Hem13 is a coproporphyrinogen III oxidase that involved in heme biosynthesis , and heme has been characterized as a major oxygen-sensing molecule in S . cerevisiae [55] . It has been reported that expression of genes encoding the main heme biosynthesis enzymes are induced in response to hypoxia in S . pombe , C . neoformans , and A . fumigatus [19] , [27] , [38] . In yeast , heme and oxygen negatively regulate HEM13 expression , and the repression of HEM13 involves a negative transcriptional regulator of hypoxic genes , ROX1 [56] , [57] . AlcC is the alcohol dehydrogenase critical for ethanol fermentation in A . fumigatus and important for in vivo fungal growth as previously observed by Grahl et al . 2011 . While SrbA is involved in regulation of these two metabolic genes , their dependency on SrbA is not as significant as genes involved in ergosterol biosynthesis . SrbA itself intriguingly displays higher transcript levels in vivo than in vitro and 2 additional putative transcriptional regulators , AFUB_090280 ( Table S5 ) and AFUB_099590 ( Figure 2B ) , display strong in vitro hypoxia induction that is partially SrbA dependent with strong expression in vivo . Previous informatics based analyses of AFUB_099590 [21] , [58] , suggested an important role for this DNA binding protein in both metabolism and virulence . Transcript levels for AFUB_099590 , which we designate srbB , are highly induced in response to hypoxia in vitro in a partially SrbA dependent manner as our microarray based analysis of ΔsrbA also previously suggested . Intriguingly , srbB transcript is one of the highest in vivo abundant genes relative to in vitro normoxic conditions . Moreover , a temporal analysis of srbA and srbB transcript levels in response to hypoxia revealed that srbB mRNA levels increase before srbA transcript levels and rise five minutes after exposure to hypoxia ( Figure 3 ) . Consequently , functional characterization of SrbB was undertaken with genetic and phenotypic analyses . Amino acid sequence alignment of SrbB ( HLH domain , Figure S1 ) revealed that this protein is an SREBP homolog , as previously suggested [21] . Characteristic of SREBP family members , SrbB contains a tyrosine substitution in the basic portion of the bHLH domain . Intriguingly , SrbB does not contain any predicted transmembrane domains , suggesting this SREBP family member may not be regulated via proteolytic cleavage like SrbA . Functional analysis of srbB was initiated through generation of a genetic null mutant and reconstituted strain ( Figure S2 ) . Loss of SrbB results in ∼50% reduction in colony radial growth on solid glucose minimal media ( GMM ) in hypoxia ( Figure 4A ) . In addition to the decrease in growth rate on solid medium , ΔsrbB colonies were noticeably less dense and often contained fluffy mycelia in hypoxic conditions . Though not statistically significant , there was a trend toward increased growth and mycelial density in normoxic conditions with ΔsrbB . The impact of SrbB loss in response to hypoxia was pronounced in liquid GMM culture conditions where a significant reduction of biomass was observed compared to normoxia cultures ( Figure 4B ) . These results strongly suggest that SrbB is a major transcriptional regulator of the fungal response to hypoxia . Unlike our previous reports with ΔsrbA , a minimal increase in tolerance to the triazole voriconazole was observed in ΔsrbB in normoxia and hypoxia suggesting a limited role for SrbB in regulating responses to triazoles ( Figure 4C ) . Of significant note , upon culture in liquid GMM , ΔsrbB exhibited a strong red pigmentation of the mycelia ( Figure 4D ) . This coloration was limited to the mycelia , and only occurred in hypoxic conditions . To better understand SrbB's function in hypoxia , the origin of the red pigment produced in ΔsrbB hypoxic mycelia , and SrbB's genetic relationship to SrbA , RNA-seq analysis was conducted with ΔsrbB and wild type under the same conditions and time points as ΔsrbA ( Figure 2 , Figure 5 ) . In contrast to ΔsrbA , but consistent with SrbB's early induction in response to hypoxia ( Figure 3 ) , the transcriptome of ΔsrbB was significantly changed at 30 minutes post-exposure to hypoxia . 490 genes had 4 fold or greater reductions in transcript levels in ΔsrbB compared to wild type under hypoxic conditions ( Table S4 and S6 ) . These genes were enriched ( P≤0 . 05 ) in FunCat categories of carbohydrate metabolism , virulence , secondary metabolism , and detoxification ( Figure 5 ) . In contrast , 135 genes had transcript levels increase 4-fold or greater in ΔsrbB compared to wild type at this early hypoxia time point . Genes with increased transcript levels in ΔsrbB were enriched in transport of toxic products , which could suggest a global dysregulation of metabolism in ΔsrbB . At 120 minutes post-exposure to hypoxia , the impact of SrbB loss on transcript levels was particularly strong , with 1026 transcripts decreasing 4-fold or greater . Over half of these genes are not currently annotated ( 522 ) , but those annotated are enriched in carbohydrate and nitrogen metabolism , virulence , secondary metabolism , and transport of various molecules . Moreover , at 120 minutes 491 genes had transcript levels increased 4-fold or greater in ΔsrbB compared to wild type . Perhaps associated with the enrichment of toxic product detoxification in the genes with reduced transcript levels , genes with increased transcript levels in ΔsrbB were associated strongly with amino acid metabolism and degradation . Overall , these data suggest a significant metabolic or bioenergetics dysregulation in A . fumigatus cultured under hypoxic conditions when SrbB function is absent . Consequently , loss of SrbB results in major alterations of the A . fumigatus hypoxia transcriptome that impact hypoxia growth . Interestingly , hem13 transcript levels were markedly reduced in ΔsrbB mycelia exposed to hypoxia , providing a potential cause of the red pigment previously observed in this strain . To test the hypothesis that the red pigmentation of ΔsrbB is associated with a defect in heme metabolism , we quantified the accumulation of heme biosynthesis intermediates in ΔsrbB in normoxia and hypoxia ( Figure 6A–B ) . Consistent with the red pigmentation and RNA-seq analysis of ΔsrbB , a striking accumulation of heme biosynthesis intermediates including protoporphyrin IX were observed in ΔsrbB ( Figure 6A–B ) . Intriguingly , when 5 µM hemin was exogenously added into the culture media , ΔsrbB growth was significantly improved in hypoxia compared to GMM alone ( Figure 6C ) . In contrast , addition of hemin to ΔsrbA did not restore this strain's growth under the conditions examined . Taken together , these data suggest that SrbB is a critical regulator of heme biosynthesis in A . fumigatus and that accumulation of toxic heme intermediates may contribute to the hypoxia growth defect observed in ΔsrbB . Inspection of genes regulated by SrbA and SrbB identified using ChIP-seq and RNA-seq analyses suggested a close functional relationship between these two SREBP family members . To compare expression patterns of strains lacking each respective transcription factor , a hierarchical clustered heat map was generated for SrbA direct annotated target genes ( Figure 7 ) . Examination of the heat map reveals that a sub-set of SrbA target genes also depends on SrbB for wild-type transcript levels in hypoxia . Examples of these target genes include hem13 , niiA , and erg25A . In contrast , a sub-set of SrbA target genes had increased or wild type transcript levels in the absence of SrbB . These include srbA itself and its target genes erg11A/cyp51A , erg11B/cyp51B , and erg3B . These latter genes appear to be dependent on SrbA and not SrbB under the examined conditions . Next , to further define the genetic relationship between SrbA and SrbB , we generated 3 additional strains: ( 1 ) ΔsrbAΔsrbB ( 2 ) srbB over-expression in ΔsrbA ( srbB-ove;ΔsrbA ) and ( 3 ) srbA over-expression in ΔsrbAΔsrbB ( srbA-ove;ΔsrbB ) . In order to over-express srbB in ΔsrbA , the A . fumigatus flavohemoprotein ( flavA ( p ) , AFUB_099650 ) or A . nidulans glyceraldehyde 3-phosphate dehydrogenase ( gpdA ( p ) , AN8041 ) promoters were utilized . These promoters were chosen because their respective genes are highly expressed in hypoxia in glucose minimal media with nitrate as a sole nitrogen source . The flavA ( p ) was chosen from the RNA-seq conditions where AFUB_099650 was one of the highest expressed genes in response to hypoxia [59] . Previously , in A . oryzae , it was reported that the FlavA homolog responds strongly to nitric oxide stress , which could occur in our media conditions with NO3 as a nitrogen source [60] . The resulting strains were designated TDC43 . 18 ( flavA ( p ) :srbB;ΔsrbA ) and TDC44 . 2 ( gpdA ( p ) :srbB;ΔsrbB ) , respectively , and TDC43 . 18 was selected to study gene expression in the srbB-ove;ΔsrbA strain . qRT-PCR analysis of select SREBP targets was conducted on cultures exposed to hypoxia for four hours , similar to ChIP-seq conditions . Consistent with the RNA-seq data , loss of SrbB resulted in a modest increase in srbA transcript levels ( Figure 8 ) . Conversely , loss of SrbA results in a strong decrease in srbB transcript levels suggesting that SrbA positively regulates srbB mRNA levels in hypoxia . Transcript levels of nine genes , plus srbA and srbB , representing ergosterol biosynthesis , heme biosynthesis , carbohydrate metabolism , and nitrate assimilation from ChIP-seq data were investigated in ΔsrbA , ΔsrbB , ΔsrbAΔsrbB , srbB-ove;ΔsrbA , and srbA-ove;ΔsrbB compared to wild type in hypoxia for four hours . Genes that require both SrbA and SrbB for full abundance include erg1 , erg25A , niiA , and hem13 as suggested by the RNA-seq analysis . In contrast , expression of erg3B , erg5 , erg11A , and niaD requires SrbA but not SrbB ( Figure 8 ) . However , interpretation of this data is complicated by the fact that SrbA positively regulates srbB transcript levels . This is exemplified with mRNA levels of the ethanol fermentation and virulence factor alcC . Loss of SrbA significantly reduces alcC transcript levels , but not to the extent as loss of SrbB ( Figure 8 ) . SrbA is modestly enriched on the alcC promoter ( Table 1 , Table S2 , Figure 1 ) . However , over-expression of SrbB in ΔsrbA essentially fully restores alcC transcript levels . Taken together , these results strongly suggests that alcC transcript levels are primarily regulated by SrbB , although SrbA can bind the SRE site found in the alcC promoter and contribute to its regulation . To seek further insights into regulation of a sub-set of these target genes by SrbA and SrbB , we performed ChIP-qPCR with a SrbB:GFP strain using a GFP antibody . SrbB tagged with GFP was ectopically expressed in the A . fumigatus wild type background . Transcript levels of srbB in the SrbB:GFP strain under the same conditions used for ChIP-qPCR was similar to wild type , and SrbB:GFP is localized to the nucleus in this strain ( Figure S3 ) . Cultures for ChIP were prepared in hypoxia for 4 hours and enrichment of SrbB on the SrbA binding sites of srbA , srbB , erg11A , erg25A , hem13 and alcC was examined compared to wild type ( Figure 9A ) . The negligible SrbB enrichment on the actin promoter supports binding specificity of the GFP antibody used for ChIP . ChIP-qPCR results show that SrbB binds to the SrbA binding sites of srbA , erg25A , and hem13 whose transcript levels require both SrbA and SrbB as described above . In contrast , SrbB enrichment on the SrbA binding site of erg11A , whose transcript level solely relies on SrbA , was not significant compared to wild type . Interestingly , similar to SrbA , SrbB binds to its own promoter ( Figure 9A ) . We next tested whether loss of SrbB would affect binding of SrbA to its direct target genes ( Figure 9B ) . Compared to wild type , SrbA binding on the promoters of srbA , srbB , and erg11A did not change in ΔsrbB . Considering that both SrbA and SrbB are able to bind promoters of hypoxic genes including srbA , srbB , and erg11A ( Figure 9A ) , these two transcription factors may form either homodimers or heterodimers to regulate gene expression . Thus , similar SrbA enrichment between wild type and ΔsrbB observed in Figure 9B is likely because the SrbA homodimer ( or monomer ) is the major form bound to the promoters of these genes . Overall , our data suggest that SrbA and SrbB are critical for hypoxia adaptation in A . fumigatus with both dependent and independent functions in regulation of genes critical for hypoxia adaptation and growth . These data suggest that SrbB co-regulates a sub-set of SrbA target genes and that loss of SrbA also markedly reduces SrbB levels . Consequently , we hypothesized that restoration of full SrbB levels in ΔsrbA may ameliorate the severe hypoxic growth defect of ΔsrbA . As described above , we generated two strains that have restored srbB expression in ΔsrbA using two promoters , flavA ( p ) and gpdA ( p ) ( TDC43 . 18 and TDC44 . 2 , respectively ) . Quantitative real-time PCR was conducted to verify if these promoters induced transcript level increases of srbB . Compared to ΔsrbA , srbB transcript levels increased by 5 . 1- and 3 . 7-fold in normoxia and 2 . 7- and 1 . 4-fold in hypoxia in TDC43 . 18 ( Figure 10A ) . Restoration of srbB transcript levels strongly promotes growth of ΔsrbA in hypoxia , however growth is not fully restored to wild type levels and was dependent on srbB transcript levels ( Figure 10B ) . In addition , as predicted , restoration of srbB transcript levels in ΔsrbA did not rescue the triazole drug susceptibility of ΔsrbA ( Figure 10C ) . This result is consistent with cyp51A/erg11A mRNA levels primarily regulated directly by SrbA . The ΔsrbAΔsrbB strain generated to study gene transcript levels of SrbA target genes was further characterized to study the genetic relationship between SrbA and SrbB . ΔsrbAΔsrbB showed similar phenotypes to ΔsrbA , with a complete lack of growth in hypoxia and marked increased in azole drug susceptibility compared to wild type ( Figure S4A–B ) . Moreover , when srbA was over-expressed in ΔsrbAΔsrbB , the resulting strain grew similar to wild type in hypoxia ( Figure S4C ) . Taken together , these data are consistent with a model where SrbA positively regulates srbB gene expression in response to hypoxia . It also further supports that both SrbA and SrbB are involved in hypoxic gene regulation but SrbA plays a dominant role over SrbB with regard to genes essential for hypoxia growth in the tested conditions . Of particular importance for understanding A . fumigatus pathogenesis , loss of SrbB results in a significant virulence attenuation in a steroid murine model of IPA ( Figure 11A ) . Kaplan-Meier curves with ΔsrbB show a significant increase in survival for animals inoculated with ΔsrbB compared to wild type and reconstituted strains ( Log rank test , p = 0 . 0027 ) . To gain insights into the relative contributions of SrbA and SrbB to virulence , we examined total fungal growth in vivo utilizing qRT-PCR based quantitation of fungal burden as we have previously described ( Figure 11B ) [7] , [61] . As expected , ΔsrbA displayed a significant decrease in fungal burden compared to wild type consistent with its attenuated virulence in murine models of IPA ( P = 0 . 008 ) [36] , [37] . Surprisingly , ΔsrbB fungal burden was as low as ΔsrbA despite it having a higher level of virulence than ΔsrbA as measured by murine survival . Consequently , ΔsrbAΔsrbB exhibited an even a greater reduction in virulence than either single mutant alone ( P = 0 . 016 between ΔsrbB and ΔsrbAΔsrbB ) , though the difference with ΔsrbA did not achieve statistical significance ( P = 0 . 31 ) , Figure 11B ) . Taken together , these data suggest that SrbB is an important SrbA-dependent regulator of the fungal response to hypoxia and required for full fungal virulence , and that both SrbA and SrbB make novel contributions to A . fumigatus virulence .
Previously , a link between the transcription factor SrbA , and the ability of A . fumigatus to cause disease in murine models of IPA has been observed [36]–[38] . However , the mechanism ( s ) by which SrbA mediates in vivo fungal growth and virulence are not fully defined . Given the conservation of SrbA with mammalian SREBPs , uncovering the fungal specific functions of SrbA is important in order to yield potential mechanisms that can be targeted for therapeutic development . Support for this rationale comes from several elegant studies showing that targets of conserved transcription factors are often not shared between distantly related organisms and even closely related species [62]–[65] . Thus , in order to fully maximize the attenuated virulence of fungal pathogens lacking SREBP homologs for therapeutic benefit , in-depth investigation into their regulons and mechanisms of regulation and activity are needed . Here , the A . fumigatus SrbA transcriptional regulon in response to hypoxia was interrogated utilizing ChIP-seq , RNA-seq and Nanostring nCounter technologies . Ninety-seven genes whose promoters were strongly bound by SrbA were identified in the ChIP-seq analysis . This number appears low considering the large number of genes differentially expressed in the absence of SrbA as detected here via RNA-seq and previously with microarray analysis [38] . However , a low overlap between transcript levels of genes affected by transcription factor loss and target genes identified in ChIP experiments appears to be the norm rather than the exception [66] . Consequently , our results suggest that we may have herein underestimated our direct SrbA targets or , more likely , there is an extensive network of genes involved with SrbA that are indirectly regulated though other transcription factors , small molecules , and proteins . The identification of ergosterol biosynthesis genes as SrbA direct targets and the sequence conservation of the ChIP identified SRE DNA binding motif strongly support the robustness of our analyses . A major novel finding from our study of SrbA target genes was the identification of SrbB and its genetic relationship with SrbA . Based on sequence similarity , Bien and Espenshade hypothesized that SrbB was an SREBP-like transcription factor [21] . While our amino acid sequence analysis of SrbB did not reveal the presence of transmembrane domains that are found in the prototypical SREBPs , SrbB contains the hallmark tyrosine residue in the bHLH domain characteristic of SREBP family members . Moreover , a srbB::GFP fusion protein was observed to localize solely to the nucleus on preliminary analyses ( Figure S3 ) further suggesting that SrbB is not membrane bound like SrbA and other SREBP family members ( though constitutive cleavage cannot currently be ruled out ) . Transcript levels of srbB were strongly induced in response to hypoxia , earlier and to a greater magnitude than srbA . Thus , transcriptional regulation of srbB mRNA levels appears to play a major role in regulation of its function . In hypoxia , SrbA was found to bind to the promoter region of srbB at three locations . Loss of SrbA , however , did not completely eliminate srbB transcript levels in hypoxia suggesting the presence of additional srbB transcriptional regulators that remain to be defined . Consistent with increased transcript in vitro in response to hypoxia and strong induction of transcript levels in vivo in a murine model of IPA , loss of SrbB markedly attenuated hypoxia growth and virulence of A . fumigatus . Unlike loss of SrbA , loss of SrbB had a minor effect on susceptibility to triazole antifungal drugs . The lack of an azole drug phenotype is consistent with the observation that SrbB does not appear to regulate cyp51A/erg11A mRNA levels , at least under the conditions tested here . However , full expression of the ergosterol biosynthesis genes erg1 and erg25A does require the presence of SrbB . In a similar manner , a major finding with regard to SrbB function is its clear importance for regulation of heme biosynthesis in normoxia and hypoxia . Heme plays a critical role in oxygen sensing and gene expression regulation in many organisms , and here our results link SrbB mediated regulation of heme biosynthesis with A . fumigatus hypoxia growth and virulence [67]–[70] . While SrbA binds to the promoter of hem13 , and hem13 mRNA levels are reduced in ΔsrbA , SrbB appears to be the major transcriptional regulator required for hem13 in hypoxia and consequently heme biosynthesis ( Figure 8 ) . Further investigations are needed into the role of heme in oxygen sensing and virulence in A . fumigatus . SrbB displays significant sequence similarity with the recently characterized Aspergillus oryzae transcription factor sclR that is critical for hyphal morphology and sclerotial formation [71] . Intriguingly , the authors noted that loss of sclR negatively affected pellet formation in liquid culture . ΔsclR pellets exhibited hollow interiors and fluffy exteriors that is consistent with SclR having a role in hypoxic adaptation . In addition to sclR , SrbB has sequence similarity with the Candida albicans bHLH transcription factor Cph2 , though reciprocal BLAST analyses do not confirm orthology . Like srbB , CPH2 is expressed in vivo in models of candidiasis and is required for colonization of the murine gastrointestinal tract [72]–[75] . Its role in hypoxia adaptation in C . albicans is unclear; though also similar to SrbB it is induced early in the Candida hypoxic response [76] . While further analyses are needed to define the genetic and potentially physical relationships between SrbA and SrbB in A . fumigatus , our data hint at likely mechanisms that are modeled in Figure 12 . First , data suggest that SrbA and SrbB have both mutually exclusive and co-regulated target genes in their regulons , and that they are involved in reciprocally regulating transcript levels . The increase in srbA transcript levels in the absence of srbB suggests that at some level SrbB could act as a transcriptional repressor . It is unclear if the effect on srbA transcript levels is direct and experiments to uncover direct SrbB target genes are ongoing in our laboratory . Analysis of SrbB DNA binding utilizing a SrbB:GFP fusion protein strongly suggests that SrbB can bind the SRE motif found in the srbA promoter region . It is likely , however , that the increase in transcript levels of several SrbA target genes in ΔsrbB is driven by increases in SrbA levels and activity . In this model , besides its role as a transcriptional activator of genes important for the hypoxia response , SrbB also functions in a negative feedback loop to modulate SrbA activity . Accordingly , persistence of high SrbA levels would at some point become detrimental to cellular homeostasis perhaps through increases in an SrbA dependent molecule ( s ) that become toxic to the cell . We note that genes associated with export of toxic molecules were enriched in the upregulated gene set in ΔsrbB . Of course there are several possible mechanisms through which SrbA and SrbB could co-regulate gene transcription , however in mammals it is known that SREBPs can physically interact to regulate gene expression through formation of homo and heterodimers [77] , [78] . It may be possible that genes co-regulated by SrbA and SrbB in response to hypoxia are regulated through heterodimer formation , while genes exclusive to the respective transcription factor are regulated in part by homo-dimer formation . Moreover , in mammals , SREBP homo-and heterodimers have different levels of transcriptional activity [77] . Thus , it is plausible that in ΔsrbB , SrbA homodimers are more potent activators of SrbA target genes such as srbA itself than an SrbA-SrbB heterodimer that is present in the wild type . It is well established that the ability of bHLH proteins to form multiple dimer combination based on availability of binding partners and environmental conditions is a critical and elegant form of gene regulation [79] . Along these lines , genetic null mutants of fungal SREBPs alter the stoichiometric ratios of potential binding partners , which is further complicated by the fact that SrbA and SrbB are involved in regulating the other's expression . We also note that a third SREBP family member , SrbC , exists in A . fumigatus and awaits further investigation . Whether a preferred dimer form exists for regulation of specific SREBP regulated genes has not been extensively studied . Together , our data suggest that transcriptional activity of SrbA homodimer is efficient to activate erg3B , erg5 , erg11A , and niaD , and an SrbA homodimer might be a preferred or dominant dimerization form for regulation of these genes over SrbA-SrbB heterodimers . In contrast , erg1 , erg25A , niiA , alcC , and hem13 might be favorably regulated by SrbA-SrbB heterodimers rather than SrbA- or SrbB- homodimers . Another possibility is that the promoter of erg1 , erg25A , niiA , alcC , and hem13 might contain an SrbB-specific binding site ( s ) in addition to the identified SrbA SRE motif . Consequently , both SrbA and SrbB could simultaneously regulate these genes by binding at the separate promoter sites . However , the utilization of genetic null mutants and over-expression strains in null mutant backgrounds has allowed us to pinpoint the contribution of SrbA and SrbB to expression of specific target genes ( Figure 8 ) . These target genes yield new additional insights into how A . fumigatus adapts and grows in the mammalian lung environment . Of particular interest is the strong reduction in ΔsrbB growth in the murine model that was similar to the reduction in growth observed in mice inoculated with ΔsrbA . The difference in murine survival between mice inoculated with the two strains could be due to increases in host damage caused by ΔsrbB . For example , as SrbB is the major regulator of the ethanol fermentation alcohol dehydrogenase AlcC , one would predict an increase in inflammation in ΔsrbB inoculated mice due to the immune suppressive effects of ethanol previously reported in our murine model [7] . Alternatively or in conjunction with increased immunopathogenesis , it may be plausible that host heme is utilized by ΔsrbB to promote growth and host death later in infection when host damage is more severe and free heme may be available as addition of hemin to ΔsrbB partially restored in vitro hypoxia growth . In addition , the further decrease in fungal burden observed in ΔsrbAΔsrbB strain inoculated strongly suggests that the combination of decreased iron uptake and ergosterol biosynthesis , regulated by SrbA , and defects in carbon metabolism and heme biosynthesis , regulated by primarily by SrbB , consequently severely inhibit in vivo fungal growth . As all of these biological processes related to fungal metabolism/bioenergetics are impacted by oxygen availability , manipulation of in vivo oxygen levels may be a viable therapeutic strategy to reduce A . fumigatus growth in vivo . In conclusion , while it is well established that fungal SREBPs are critical regulators of ergosterol biosynthesis and iron homeostasis , our analyses of SrbA and SrbB expand the known functions of these fungal virulence and antifungal drug-associated transcription factors ( Figure 12 ) . The major enrichment of genes involved in oxidoreductase activity , carbohydrate and nitrogen metabolism , and heme biosynthesis in the regulons of SrbA and SrbB presents an exciting and important area for further investigation into how these processes affect hypoxia adaptation , fungal virulence , and responses to antifungal drugs . From the big picture of the SrbA-SrbB regulons , we propose that the SrbA-SrbB genetic network allows A . fumigatus to “reprogram” its bioenergetics to allow invasive growth to cause disease in the mammalian lung in the face of oxygen and iron limitation . Consequently , these fungal SREBPs are much more than regulators of sterol biosynthesis , rather they are global regulators of fungal bioenergetics potential/metabolism; also an emerging theme with mammalian SREBPs [80] . Finding a mean ( s ) to unplug this fungal genetic network is an ongoing research goal that is expected to yield a significant therapeutic breakthrough for IPA .
Aspergillus fumigatus strain CEA17 was used to construct the ΔsrbA mutant [36] . The wild type strain referred to in this article is strain CBS 144 . 89 , also called CEA10 . All strains are routinely grown on glucose minimal media ( GMM ) that contains 1% glucose , salt solution and trace minerals , at 37°C [81] . The recipe for liquid glucose minimal media is identical to that for GMM , except without agar . Liquid cultures for RNA analysis were grown under agitation ( 200 RPM ) in baffle flasks . To generate an srbB null mutant , a 1 . 2 kb up- and downstream sequences were PCR-amplified from A . fumigatus genomic DNA ( gDNA ) . As a selectable marker , a 3 . 2 kb pyrG from A . parasiticus was PCR-amplified from the plasmid pJW24 . The three DNA fragments were used as a template to generate a final construct via double-joint PCR , and the PCR product was transformed to A . fumigatus wild type CEA17 [30] . Southern blot analysis was conducted to confirm homologous gene replacement ( Figure S2 ) . To regain srbB expression in the srbB deletion strain , a 4 . 1 kb DNA fragment including a srbB promoter and a coding sequence was PCR-amplified . As a selectable marker , a 3 . 0 kb hygB fragment was PCR-amplified from pBC-hyg plasmid DNA . These two PCR products were used as a template to generate a final reconstituted construct via a double-joint PCR [82] . The final PCR product was transformed to ΔsrbB and transformants were screened using PCR . A double null mutant of srbA and srbB was generated by deletion of srbB in the ΔsrbA ( pyrG- ) strain . The srbB deletion construct designed to generate ΔsrbB above was transformed to ΔsrbA . Gene replacement in the resulting transformants were screened by PCR and verified by Southern bot analysis . To over-express srbB in ΔsrbA background , either A . fumigatus flavohemoprotein ( flavA ( p ) , AFUB_099650 ) or A . nidulans glyceraldehyde-3-phosphate dehydrogenase ( gpdA ( p ) , AN8041 ) promoter was utilized . A 1 kb flavA ( p ) and a 2 kb gpdA ( p ) DNA fragment was PCR-amplified from A . fumigatus and A . nidulans gDNA . A 2 . 5 kb DNA fragment including the srbB coding region and downstream sequence was PCR-amplified from A . fumigatus gDNA . As a selectable marker , a 3 . 2 kb pyrG from A . parasiticus was PCR-amplified from the plasmid pJW24 . These three PCR products were used to generate a 6 . 5 ( flavA ( p ) ) and 7 . 5 kb ( gpdA ( p ) ) final construct via double-joint PCR [82] . The final constructs were transformed into ΔsrbA resulting in TDC43 . 18 ( flavA ( p ) ) or TDC44 . 2 ( gpdA ( p ) ) strains . Single copy integration of the srbB-overexpression construct in ΔsrbA was confirmed by Southern blot analysis . To over-express srbA in ΔsrbAΔsrbB , srbA was amplified along with 1 . 2 kb 5′ upstream sequence from A . fumigatus wild type gDNA . Purified PCR product was transformed in the ΔsrbAΔsrbB strain . Transformants were selected in hypoxia using the inability of hypoxia growth of ΔsrbA . Over-expression of srbA in the resulting transformants was confirmed by qRT-PCR ( Figure 8 ) . For ChIP experiments , 1×106 spores/mL of Aspergillus fumigatus strain CBS144 . 89 and ΔsrbA were grown in 200 mL of liquid glucose minimal media ( LGMM ) in 500 mL shaking flask cultures for 24 hours . Samples were centrifuged , and 200 mg of mycelia were transferred to 100 mL pre-conditioned fresh LGMM in 250 mL Erlenmeyer flasks , and then placed in hypoxia chamber on platform shaker at 200 rpm for 4 and 12 hours hypoxia exposure . Samples were collected by vacuum filtration and transferred to cross-linking solution for ChIP experiments , or flash frozen and lyophilized for RNA extraction . A sample of mycelia for later RNA isolation was frozen on liquid nitrogen immediately before crosslinking , and stored at −80°C . Remaining filtered samples were added to 20 mL of buffer for crosslinking ( 0 . 4 M Sucrose , 10 mM Tris-HCl , pH 8 . 0 , 1 mM EDTA , adding 1 mM PMSF and 1% formaldehyde just before use ) in a 125 mL flask for 20 min under shaking ( 100 rpm ) at 30°C . Crosslinking was stopped by adding 1 mL of 2 M glycine , and continued shaking incubation for 10 minutes . Mycelia were collected and dried using vacuum filtration and rinsed with sterile ddH2O and transferred sample to 2 mL screw cap tube , and frozen immediately with liquid nitrogen and stored at −80°C . Approximately 200 mg of frozen mycelia were ground to a fine powder in a chilled mortar and pestle with liquid nitrogen added . Powder was transferred to 10 mL of ChIP lysis buffer ( CLB: 50 mM HEPES pH 7 . 5 , 150 mM NaCl , 1 mM EDTA , 1% Triton X-100 , 0 . 1% Deoxycholate ( Sigma D6750 ) , 0 . 1% SDS , 1 mM PMSF , 1× fungal proteinase inhibitor cocktail ( Sigma , USA ) ) . Each sample was vortexed and then split into multiple 300 µl volume ( maximum volume for sonication ) 1 . 5 mL microfuge tubes appropriate for sonication . Samples were sonicated with Biorupter UCD-200 ( Diagenode , USA ) with the following condition: 30 sec ON and 30 sec OFF at power level High for a total of 30 minutes in a cold room . Ice was added every 10 minutes to ensure samples remain at 4°C . Tubes were centrifuged at 10 , 000 g for 5 minutes at 4°C . Supernatant was transferred into new tube . 30 µL was reserved as input control ( IC ) fraction for reverse crosslinking to verify sonication and control for ChIP and qPCR . 30 µL of Protein A Dynabeads ( Dynal , Invitrogen ) were used for each sample . Beads were washed twice on magnetic stand with 500 µL of CLB , with 5 minutes of slow rotation at 4°C for each . 100 µL of blocking buffer ( 0 . 1 mg BSA , 200 µg Yeast tRNA , in 1 mL of CLB ) with 1 µg of antibody/100 µL ( IgG ( Invitrogen , Rabbit ) or SrbA ( Willger et al . 2008 , anti-rabbit antibody ) was added to the washed Dynabeads on a magnetic stand . The beads and blocking buffer were incubated 16 hours at 4°C with slow rotation to coat Dynabeads . After incubation , Dynabeads were washed twice by 500 µL of CLB as above . Immediately after removing last wash , 100 µL of sonicated sample was added to beads . Samples were incubated 16 h at 4°C with rotation . In cold room , samples were washed twice by 500 µL of CLB as above , then washed as above with 0 . 5 ml of LNDET ( 0 . 25 M LiCl; 1% NP40 ( Nonidet P40 Substitute , USB ) ; 1% Deoxycholate; 1 mM EDTA ) , and finally washed twice with 0 . 5 ml of Tris-EDTA ( TE: 10 mM Tris-HCl , pH 8 . 0; 1 mM EDTA , pH 8 . 0 ) . After removal of last TE wash , DNA was eluted from antibody with 50 µl of fresh elution buffer ( EB: 1% SDS; 0 . 1 M NaHCO3; 0 . 2 mg/ml proteinase K; 1 mM DTT ) and incubated at 65°C for 10 minutes . On a magnetic stand , supernatant was transferred to a new tube . A second elution with 50 µl of EB was performed so that the final elution volume was 100 µl . All samples were incubated for 16 hours at 65°C for reverse crosslinking . After reverse crosslinking , samples were treated with 2 . 5 µg of RNase A and incubated for 30 minutes at room temperature . DNA was extracted either by using PCR purification kit ( Qiagen ) following the high pH protocol , or EtOH precipitation , with 50 µL as final volume . 5 µL of sample was assayed on Qubit using high sensitivity dsDNA kit ( Invitrogen ) . To check sonication , 10 µL of IC was run on E-gel EX 2% agarose gel ( Invitrogen ) and fragment size ranged from 1 kb to 100 bp . ChIP-seq libraries were created following a published Illumina ChIP-seq library preparation protocol [83] . Briefly , fragmented ends were repaired , an adenine molecule was added to the repaired end , PAGE-purified adapters were added to the overhang , and the mixture amplified with primer 1 . 0 and primer 2 . 0 with an individual index tag to allow for multiplex of samples in a single lane . Samples were gel purified to obtain a size range between 200–400 bp . Libraries were validated by real time PCR , concentration was determined with Qubit ( Invitrogen ) and integrity was checked with an Agilent Bioanalyzer . Samples were sent to the Ohio State University sequencing facility for 76 bp paired end sequencing and four ChIP samples were indexed per lane on the Illumina HiSeq 2000 . Full read data are deposited at the NCBI GEO repository under accession GSE61974 . Paired end reads from three independent ChIP-seq experiments ( multiplexed in 1 lane each ) were quality checked with fastqc ( http://www . bioinformatics . babraham . ac . uk/projects/fastqc/ ) . Reads were trimmed and cleaned of contaminating Illumina adaptors using trimmomatic [84] and aligned to the A . fumigatus A1163 CADRE genome from ensembl fungi , version 18 using bowtie2-2 . 1 . 0 [85] . Reads that aligned concordantly as paired ends were retained and used for peak calling . The resulting bam files were used as input for peak calling and for plotting . Peaks were called using Model-based Analysis for ChIP-Sequencing ( MACS2 ) version 2 . 0 . 10 . 20131216 [45] , with the subpeak calling option enabled . Peak calling was done with the wild type ChIP-seq samples and wild type input control samples using an fdr cutoff of 0 . 05 . Results reported herein are for the combined reads from all 3 samples . Similar sets of peaks and genes were identified when each independent biological replicate was assessed separately . To find sequence motifs within ChIP-seq peaks , 100 bp centered on each of the peaks ( Table S2 ) were selected . Multiple Em for motif elicitation ( Meme ) version 4 . 9 . 1 [86] was run with the minimum and maximum motif widths of 4 and 12 , the zoops model and the x_branch option . The resulting 11 bp motif was reported for 54 sites . Similar motifs were found using the meme oops and anr models or using other motif discovery tools [87] , [88] . Prior to sequencing , all ChIP samples were diluted 10-fold for PCR . 1 µl of template was used in a 10 µl total volume reaction using Promega 2× GoTaq qPCR master mix and 0 . 4 µM of each primer . Realtime PCR was performed with 40 cycles of 95°C for 15 s and 60°C for 30 s on Mastercycler ep realplex PCR machine . PCR was performed in triplicate for each separate ChIP experiment using primers designed for regions identified as enriched in preliminary analysis . Three genes were chosen from this analysis as positive for enrichment in all ChIP conditions ( srbA , erg11A and erg25A ) based on previous microarray experiments [40] . Percent input method was used to calculate the signal of enrichment of the promoter region for each gene ( http://cshprotocols . cshlp . org/cgi/content/full/2009/9/pdb . prot5279 and Invitrogen website ) . Briefly , 100* ( 2 ( InputCt-ChIPCt ) ) was calculated for each reaction and the average and standard deviation calculated from these values . No correction for adjusted input was necessary as both templates were diluted equally prior to PCR . Lack of enrichment for at least two of the three genes , or non-amplifying PCR , was evidence for poor ChIP , and these samples were not sequenced . ChIP-qPCRs with SrbB:GFP were performed for the genes that showed significant SrbA enrichment on the promoters . ChIP samples were prepared from cultures grown under the same conditions used for ChIP-seq . All ChIP samples were diluted 10-fold for PCR . 2 µl of template was used in a 20 µl total volume reaction using SYBR green master mix ( BioRad ) and 0 . 4 µM of each primer . Fold enrichment method was used to calculate the signal of the promoter region for each gene ( http://www . lifetechnologies . com/us/en/home/life-science/epigenetics-noncoding-rna-research/chromatin-remodeling/chromatin-immunoprecipitation-chip/chip-analysis . html ) . For RNA experiments , 1×106 conidia of Aspergillus fumigatus strain CBS144 . 89 , ΔsrbA and ΔsrbB strains were grown in 50 mL of LGMM in 250 mL shaking baffle flasks for 16 hours at 300 RPM . Samples were transferred to a hypoxia chamber on platform shaker at 200 RPM for variable hypoxia exposure . Samples were collected by vacuum filtration , flash frozen in liquid nitrogen and lyophilized for RNA extraction . Lyophilized tissue was mixed with 0 . 2 mL of 0 . 5 mm glass beads ( BioSpec , USA ) and mixed for 30 seconds on Mini-beadbeater-16 ( BioSpec , USA ) . Ground mycelia were suspended in 1 mL of TriSure ( BioLine , USA ) , and incubated for 5 minutes . 200 µl of chloroform was added and mixed well , incubated two minutes . Samples were centrifuged at maximum speed for 15 minutes at 4°C . Upper layer was collected and mixed with an equal volume of 80% EtOH , and pipetted immediately to RNeasy spin column ( Qiagen , USA ) . Columns were centrifuged one minute , flow through discarded and washed twice with kit supplied RPE buffer , and column completely dried after last wash . Filter column was transferred to RNase free 1 . 5 mL tube , and 200 uL of RNase free water was added an incubated for 1 minute , and then centrifuged to obtain nucleic acid . Samples were analyzed with NanoDrop ND-1000 ( Thermo-Fisher ) . To identify transcriptionally active genes , cDNAs obtained from the fungal mycelia incubated at stated conditions were sequenced with the Illumina platform to determine transcript abundance . Samples were DNased using the RNeasy kit ( Qiagen ) , following the protocol for DNase Digestion before RNA Cleanup . Sequencing libraries were generated using the ScriptSeq kit v2 ( Epicenter ) following manufacturer's directions . After each preparation step sample quality and quantity was assessed using Bioanalyzer and the Agilent RNA 6000 Nano Kit ( Agilent ) . All cDNA libraries were sequenced ( 4 samples per lane ) using the Illumina HiSeq2000 instrument ( www . illumina . com ) at the Oregon Health Sciences University Massively Parallel Sequencing Shared Resource ( http://www . ohsu . edu/xd/research/research-cores/mpssr/ ) . RNA-seq analysis was performed using the bowtie-tophat-cufflinks pipeline [85] , [89] , [90] . RNA-seq data is deposited at NCBI SRA under BioProject ID PRJNA240563: accession numbers SAMN02677488 , SAMN02677489 , SAMN02677490 . The FungiFun2 2 . 27 beta web-based server https://elbe . hki-jena . de/fungifun/fungifun . php was utilized to interrogate the functional enrichment of FunCat and gene ontologies in the respective datasets . For RNA-seq analysis , genes whose mRNA levels changed 4 fold or greater were included in the analysis . The A1163 genome selection was utilized for all analyses . Settings used for statistical significance include: significance level 0 . 05 , significance test Hypergeometric distribution , and the Benjamini-Hochberg adjustment method . Aspergillus fumigatus strains were cultured in liquid media ( glucose-minimal-media or induction/repression minimal media ) for sixteen hours , then shifted to hypoxia for the indicated times . Mycelia were harvested via vacuum filtration and lyophilized overnight prior to homogenization with 0 . 1 mm glass beads . Total RNA was extracted using TRisure ( Bioline ) according to the manufacturer's instruction and purified via RNeasy column protocol ( Qiagen ) . Genomic DNA purification was completed with Turbo DNAse I ( Ambion ) . A secondary genomic DNA purification was done with the Qiagen QuantiTect Reverse Transcription Kit ( Qiagen ) , as well as oligo-DT-primed cDNA synthesis . qRT-PCR was conducted in technical duplicates except where noted . The normalized fold expression graphed in each figure represents the mean and percent error of two-to-three biological replicates as normalized to the housekeeping gene tefA . A no-template mRNA control was used to ensure no gDNA contamination in each analysis . Virulence study for ΔsrbB , wild type and reconstitution strains ( 20 animals per strain , 2 experiments ) was conducted in CD1 mice ( Charles Rivers , USA ) using the triamcinolone infection model for A . fumigatus as previously described [7] . For in vivo RNA analysis , mouse lungs were harvested on day 2 , 3 and 4 post-infection . Lungs were flash frozen in liquid nitrogen and lyophilized for 24–48 hours until lung tissue was completely dry . Tissue was processed in same manner as above for fungal RNA . Final RNA samples were combined as whole lung , after verifying fungal RNA was present in each sample by qRT-PCR . For the determination of fungal burden , triamcinolone mouse model of IPA was utilized as described previously [7] . Briefly , mice were immunosuppressed with a single sub-cutaneous injection of steroid triamcinolone ( Kenalog −10 ) ( 40 mg/kg ) on day −1 . Mice were inoculated with 106 conidia of the respective strains in 40 µl PBS intranasally on day zero . Control mice were infected with PBS only . Lungs were collected on day +3 and were immediately frozen in liquid nitrogen . DNA was isolated from lyophilized lungs , and treated with RNAse overnight . qRT-PCR was done to determine the amount of fungal DNA in each sample by comparing with a standard curve of known concentrations as described previously [7] , [61] . Data represented are the mean and standard error of 3–5 mice per group and analyzed by t-tests between 2 experimental groups . We carried out our animal studies in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Research Council ( Council , 1996 ) . The animal experimental protocol was approved by the Institutional Animal Care and Use Program ( IACUC ) at Montana State University Federal-Wide Assurance Number: A3637-01 ) and by the Institutional Animal Care and Use Committee ( IACUC ) at Dartmouth College ( Federal-Wide Assurance Number: A3259-01 ) . Digital counts for 60 genes ( ChIP targets , housekeeping genes and other genes of interest ) were adjusted for binding efficiency with background subtraction using the included positive and negative controls from the manufacturer ( Nanostring Technologies , Seattle , WA , USA ) , as per Nanostring nCounter data analysis guidelines . Data sets were normalized to facilitate across sample comparisons using the geometric mean of 20 stably expressed genes . A subset of 12 of these genes were examined and presented herein with complete data in Table S5 . Boxplots were generated in R [91] . Sequentially diluted spore suspensions in 5 µl sterile water ( 102–105 conidia ) were dropped on GMM plates and cultured at 37°C for 3 days in normoxia or hypoxia ( 1% O2 , 5% CO2 ) . In order to study biomass production , 108 conidia were incubated in 200 mL liquid GMM at 37°C , 200 rpm for 2 days . Mycelia were harvested , lyophilized , and weighed . Biomass test was performed in triplicate . Susceptibility of fungal strains to VCZ was tested using either commercially available E-test strips ( Biomerieux , Inc . Durham , NC ) or a semi-quantitative method directly using VCZ ( Sigma ) solutions with appropriate concentrations . Five mL of RPMI media or GMM containing 105 conidia were overlaid onto a 25 mL RPMI/GMM plate . Then , E-test strips were placed on the plate , or VCZ ( Sigma ) solutions were added in the center of the plate . After 2 days incubation at 37°C , clearance of fungal growth was observed and susceptibility to VCZ was decided . Porphyrins were extracted from powdered dried mycelia by homogenization in phosphate buffered saline and the protein content determined in an aliquot by the Bradford method . The extract was then mixed with an equal volume of acetone/concentrated HCl ( 97 . 5/2 . 5 v/v ) , centrifuged and the supernatant analyzed for porphyrins by reversed phase HPLC with fluorescence and UV detection [92] using porphyrin standards from Frontier Scientific ( Logan , UT , USA )
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Despite improvements in diagnostics and antifungal drug treatments , mortality rates from invasive mold infections remain high . Defining the fungal adaptation and growth mechanisms at the infection site microenvironment is one research focus that is expected to improve treatment of established invasive fungal infections . The Aspergillus fumigatus transcription factor SrbA is a major regulator of the fungal response to hypoxia found at sites of invasive fungal growth in vivo . In this study , new insights into how SrbA mediates hypoxia adaptation and virulence were revealed through identification of direct transcriptional targets of SrbA under hypoxic conditions . A major novel finding from these studies is the identification of a critical role in fungal hypoxia adaptation and virulence of an SrbA target gene , srbB , which is also in the SREBP family . SrbB plays a major role in regulation of heme biosynthesis and carbohydrate metabolism early in the response to hypoxia . The discovery of SrbA-dependent regulation of srbB gene expression , and the target genes they regulate opens new avenues to understand how SREBPs and their target genes mediate adaptation to the in vivo infection site microenvironment and responses to current antifungal therapies .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"animal",
"models",
"of",
"infection",
"mycology",
"aspergillus",
"fumigatus",
"medical",
"microbiology",
"microbial",
"pathogens",
"biology",
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"microbiology",
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] |
2014
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ChIP-seq and In Vivo Transcriptome Analyses of the Aspergillus fumigatus SREBP SrbA Reveals a New Regulator of the Fungal Hypoxia Response and Virulence
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Coordinated surveillance , vaccination and public information efforts have brought the Chinese rabies epizootic under control , but significant numbers of fatalities are still reported annually with some cases occurring in previously rabies free regions . Tibet has remained virtually rabies free for 16 years , but since 2015 one human rabies case has been reported each year . To better understand the origins of these cases , we sequenced three human samples and an additional sample isolated from a dog in 2012 . Three genomes were sequenced from brain samples: human case 1 ( reported in 2015 ) , human case 3 ( 2017 ) , and the 2012 dog case . For human case 2 ( 2016 ) , the rabies N gene was sequenced from a limited saliva sample . Phylogenetic analysis shows that Case 1 ( CXZ1501H ) and the dog case ( CXZ1201D ) belong to China IV lineage ( equivalent to Arctic-like-2 in global rabies ) , suggesting an association with a wildlife spillover event . However , Case 2 ( CXZ1601H ) is placed within the dominant lineage China I , and was most similar with recent strains from neighboring Yunnan province , indicating the current epizootic has finally reached Tibet . Most surprisingly however , was the finding that Case 3 ( CXZ1704H ) is distinct from other Chinese isolates . This isolate is placed in the Indian Subcontinent clade , similar to recent Nepal strains , indicating that cross-border transmission is a new source for rabies infections . Thus , the complex mixture of the rabies epizootic in Tibet represents a major new challenge for Tibet and national rabies control .
China has been facing an ongoing rabies epizootic since the middle of the 1990s [1–3] that , consistent with many other countries experiencing major extended rabies outbreaks [4] is primarily spread by domestic dogs transmitting the rabies virus ( RABV ) [1 , 3] , a species of the Genus Lyssavirus [4–6] . China is a large country with a diverse geography , climate and demographics and , consequently , the burden of rabies varies by region . The southern and eastern parts of the country report the majority of human cases [3 , 7] , but almost all provinces have experienced some degree of impact from the disease . Therefore , to reduce rabies fatalities and bring the epizootic under control , the government established a comprehensive surveillance program and investigated the efficacy of different control methods such as post exposure treatment , vaccination and education[7] . As a result , the number of cases has steadily decreased in the last ten years [3 , 7 , 8] . However , the number of provinces reporting cases has slowly expanded to encompass most of the country , with sporadic events even reported in regions in western China , which had previously been rabies free for more than 20 years [9] . Investigation of the diversity and evolution of viruses over the course of an epidemic can help in the development of strategies to combat and control viral diseases [1 , 10 , 11] . Based on our continued nationwide surveillance and other Chinese reported rabies studies , the Chinese street strains of RABV can be divided into six major lineages [1 , 12] . In the context of global RABV clades , China I , China II , China V and China VI are sub-clades of the Asian clade; China III corresponds to Cosmopolitan clade; and China IV corresponds to Arctic-like-2 in the Arctic-related clade [1 , 9 , 13 , 14] . Among these lineages , China I has emerged to become the dominant lineage in the current rabies epizootic [1] , and has expanded into most provinces in mainland China , including western provinces such as Ningxia , and Gansu [9 , 15] . At the same time , sporadic human and dog cases have been reported in Qinghai and Tibet , but our earlier analysis of these samples indicates they belong to the China IV sub-clade , suggesting they are associated with spillover from wildlife , rather than the main epizootic [9] . A human case was reported in Tibet in 2015[16] , after a 16 year hiatus and since then , additional cases have been reported[8] , with the most recent case reported in 2017 . As the national reference laboratory for China rabies surveillance , our lab received brain samples from both cases and these were confirmed by direct immunofluorescence assay ( DFA ) . These two human samples , and a dog specimen also reported in Tibet in 2012 with no associated human cases [9] , were subjected to whole genome sequencing and phylogenetic analysis . In addition , a further suspected Tibetan human case reported in 2016 was subsequently confirmed by the Sichuan provincial CDC and the N gene of the isolate was sequenced and analyzed .
The program for collection of human brain specimens was approved by the Ethical Committee of the National Institute of Viral Disease Control and Prevention , China CDC , which is the national referral center for rabies diagnosis . Due to their medical condition , subjects were unable to provide consent once a rabies infection was suspected and so written informed consent was obtained in both cases from their relatives after death . Data on Tibet human rabies cases were collected from the Chinese Notifiable Disease Reporting System ( NDRS ) of the China CDC [3] . The reporting methods and how cases were determined to be associated with rabies were the same as described previously [3 , 17] . More detailed epidemiological information of the cases was collected by the local CDCs using a standard report format . From 2015 to 2017 , a total of three human cases were reported in Tibet , one each year . Specimens of each case were collected before or after death ( Table 1 ) . The first reported human case , named Case 1 , was collected as a brain sample after death and sent to the China CDC rabies laboratory for diagnosis . The second case , named Case 2 , was transferred to a hospital in Sichuan from Tibet on July 15 , 2016 , 5 days after the onset of the disease . The saliva and cerebrospinal fluid ( CSF ) samples were collected and detected by Sichuan CDC . Samples for the third case , named Case 3 , were collected from saliva , urine and serum before death , and the brain and skin at the nape of the neck samples were collected after death . All of the samples were sent to the China CDC rabies laboratory by the Tibet CDC . The brain tissue and the neck skin specimens were tested for rabies using DFA as described previously [18] , and showed positive results , confirming the presence of rabies in Case 1 and Case 3 . For the liquid specimens from Case 3 , nested-PCR was used for detection as described previously [19] , and all of them returned negative results . The saliva and CSF samples of Case 2 were tested using real-time PCR by the lab of Sichuan CDC [20] with a rabies virus nucleotide detection kit ( DAAN GENE , Guangzhou , China ) , and the saliva and CSF samples tested positive and negative , respectively . The brain tissues of Case 1 ( named CXZ1501H ) and Case 3 ( named CXZ1704H ) were then used to amplify the rabies genome . Total RNA extraction , cDNA synthesis and sequencing were performed using the same protocols as described previously [19 , 21] . In addition , genome sequencing was also performed on a dog brain specimen collected in Tibet in 2012 ( CXZ1201D ) as reported previously for the nucleoprotein ( N ) gene [9] . The full length of CXZ1501H and CXZ1201D are 11927bp , CXZ1704H is 11925bp . The saliva of Case 2 ( named CXZ1601H ) was used to amplify the N gene of RABV as described previously [9] , since insufficient volume was available to amplify the rabies genome . To investigate the lineages of the isolates on a national and global scale , a reference dataset was created comprising: the three new Tibetan human strains ( Case 1 , Case 2 and Case 3 ) , the 2012 Tibetan dog strain and 41 representative reference N sequences of both Chinese street strains and worldwide strains ( S1A Table ) . A genome reference dataset ( S1B Table ) , comprising two human Tibetan strains ( Case 1 and Case 3 ) and the 2012 dog sample plus domestic and global strains [22] , was also created for comparative purposes . Multiple alignments for both datasets were produced using the Clustal X v2 . 1 program [23] . Phylogenetic reconstruction was performed on each dataset using the MEGA7 software package with the Neighbour-Joining ( NJ ) method and 1000 bootstrap replicates [24] . The NJ method was used here as the goal was simply to determine the major lineage ( as opposed to making any predictions related to most recent common ancestor , or mutation rate ) of the new Tibetan strains relative to ( i ) the six major rabies lineages , China I to China VI , that have been observed in China and ( ii ) the four major global rabies lineages . Genome sequences were submitted to GenBank , with accession numbers KY175229 ( case 1 ) , KY175230 ( case 3 ) and MH671332 ( dog specimen ) . The accession number of the N gene from Case 2 is MH746442 .
Tibet is located in the Qinghai-Tibet Plateau , a sparsely populated and geographically remote region with climatic extremes , and relatively isolated from the outside world . Since the 1990’s , Tibet has reported few human rabies cases ( one case in 1992 and two cases in 1998 ) , and has remained human rabies free for the last 16 years ( 1999–2014 ) [9] . However , since 2015 one human rabies case has been reported each year . Case 1: On September 16 , 2015 , a young male herdsman , from Yongqu village in Nierong County , Naqu Prefecture , Tibet ( Fig 1 ) died in the local hospital . He had exhibited clinical symptoms consistent with rabies 6 days previously . He was bitten on his left wrist by a stray dog approximately two months earlier , and he washed the wound but did not seek vaccination after the event . Consequently , this patient was reported as a suspected rabies case to the NDRS of China CDC . As this represented the possibility of the first human rabies case in Tibet in 20 years , the following day the family agreed to collection of his brain tissue , which was sent to the China CDC rabies laboratory ( our lab ) for laboratory diagnosis and subsequently confirmed as rabies positive . Case 2: A young man , living in Karuo District , Changdu City in Tibet ( Fig 1 ) began to show clinical symptoms on July 10 , 2016 and went to a local hospital . On July 15 , the patient was transferred to West China Hospital , in Sichuan province , and his saliva and CSF samples were collected and submitted to Sichuan CDC on July 18 . The samples were investigated by Real-time PCR and the saliva sample was confirmed positive on the next day . The patient had been in contact with dogs , but had no biting injury in recent years , and died on July 26 . Case 3: On January 21 , 2017 , Zhongba County CDC , in Shigatse city , Tibet , received a call reporting a suspected rabies case from Payang town health center ( Fig 1 ) . The CDC staff went to Payang to obtain more details and collected the saliva , urine , and serum specimens of the patient . The patient was a herdswoman , 39 years old , and she began to exhibit some clinical symptoms on January 19 , 2017 , about 9 months after she was bitten on the right arm by a stray dog in a pasture , and failed to seek post-exposure prophylaxis ( PEP ) . On January 23 , the patient died , and her brain and neck skin specimens were collected , and all the specimens , including the liquid specimens collected 2 days previously , were handed to Tibet CDC and then transported to our lab at China CDC in Beijing . According to the epidemiology survey performed by the local staff with the case’s relatives , a stray dog has bitten the woman and had also bitten another person , who had died before this reported case and was given a sky burial . The sky burial master was found by the local CDC , and was given PEP . Canine Sample: In addition to these cases , in 2012 , 6 villagers in Jiali County in Naqu Prefecture ( the same location as Case 1 ) were bitten by a stray dog . The dog was killed , vaccination was arranged for the affected villagers , and brain specimens were collected from the dog by Tibet CDC and sent to our lab for testing and confirmed to be positive [9] . This remains the only recent reported animal case in Tibet until now . The estimated phylogenetic tree is shown in Fig 2 . Isolates CXZ1201D and CXZ1501H , appear to be very similar and are placed within the China IV lineage , together with another recent isolate collected from Qinghai in 2012 [9] , consistent with our original hypothesis that they were a consequence of wildlife spillover , rather than associated with the current epizootic[9] . However , surprisingly , the most recently collected isolate CXZ1704H ( Case 3 ) is evolutionarily distinct from the 6 currently known Chinese lineages [1] . The structure of the tree is consistent with the corresponding genome tree ( S1 Fig ) . Both figures place CXZ1704H in the Indian subcontinent clade ( commonly associated with Indian and Sri Lankan isolates ) , rather than being placed in the Asian or Arctic-like clades with other Chinese strains[13] . The closest strain in the reference set was the isolate from Nepal [25] . Shigatse city in Tibet , which is where the patient lived , neighbors with Nepal ( Fig 1 ) . This is the first report of an Indian subcontinent strain in Tibet and in China as a whole . We therefore placed it in a new Chinese rabies lineage , China VII . Additionally , the staff of Sichuan CDC was able to complete N gene sequencing for Case 2 , using the remainder of the saliva sample . The sample is placed in the China I lineage ( Fig 2 ) , and closest to strains from Yunnan , located in southeast China ( Fig 1 ) whose northwestern borders are adjacent to southeast Tibet . China I is the dominant lineage in the current rabies epizootic , expanding from South to North China , and has encroached into most western provinces in recent years [1 , 9] . Thus , China I has finally spread to Tibet , which is the last province in mainland China to report human cases .
Effective strategies have been developed for rabies eradication in the western hemisphere including large scale dog vaccination , controlling populations of roaming dogs and bait drops [26 , 27] . However , for large countries such as China , with broad geographical diversity , these strategies can aid control of an epizootic , but the magnitude of the task raises new challenges; for example , the size of the country makes widespread bait dropping unfeasible . Thus , eradicating an epizootic requires a longer term strategy . Monitoring programs play a key role in evaluating the efficacy of control strategies and identifying potential new cases in low incidence regions to halt further dissemination of the virus [3 , 7] . Tibet has remained virtually rabies free for almost 20 years , but recent sporadic cases have raised concerns that the current epizootic may gain a foothold in this region . The first rabies cases in 16 years was reported for a dog with rabies in Naqu Prefecture in 2012 [9] and in 2015 the first human case was reported , also in Naqu Prefecture ( Fig 1 ) . Our previous investigations of sequences from isolates collected from the national surveillance program have established a detailed view of the dissemination of the current epizootic [1 , 12 , 17] . The current epizootic was initially associated with the China I and China II lineages , however the latter was associated with the previous epizootic and was subsequently displaced by China I as the dominant lineage [1] . Nevertheless , China II remains associated with a number of cases in high incident regions [1] . China III to VI are present at lower levels and our analyses indicate that they are associated with spillover from wildlife [9] . For example , our analysis of recent isolates from West China indicated that they were a consequence of both the current epizootic ( Gansu and Ningxia ) and spillover from wildlife ( Tibet and Qinghai ) [1 , 9] . Interpreted in this context , our current results indicate that CXZ1201D and CXZ1501H , placed within the China IV lineage , are associated with wildlife spillover . This is consistent both with the placing of the other recent isolates from the neighboring provinces of Ningxia and Gansu and with the current rabies situation in these provinces and Qinghai and Tibet; human cases in Gansu rose to 11 cases in 2015 , Ningxia increased to 14 cases in 2014 , whereas Qinghai and Tibet have only reported one or no cases each year in recent years [8] . It was therefore surprising to find that isolate from the 2017 Tibet case ( CXZ1704H ) is placed in a clade that is distinct from other Chinese isolates and which corresponds to the Indian subcontinent clade [13] ( Fig 2 ) . This is particularly striking as our 2013 analysis of rabies strains in China and neighbouring countries bordering South and Southwest China ( i . e . , Thailand , Viet Nam , Cambodia , Laos , Nepal , India , Myanmar and Bhutan ) indicated that national borders appeared to be effectively halting the spread of rabies [1 , 12] . However , in recent years there have been many new economic trade agreements [28] to promote trade with neighboring countries . For example , Zhangmu ( 樟木 ) was the major customs port between Nepal and China , but at the end of 2014 a second customs port , Jilong ( 吉隆 ) , was opened ( Fig 1 ) . However , after the earthquake in Nepal 2015 , Jilong became the major customs port placing greater burden on border controls [16] . Thus , it seems this new incursion is likely a consequence of the increased trade between Nepal and China; this not only increases the likelihood of inbound rabies cases but other diseases as well . Thus , the surveillance and research of infectious diseases needs to be strengthened , including host animal control and management . The other conclusion from this study is that effective communication between national and local CDCs is crucial for rapid response to rabies events . Case 2 was transferred to a hospital in Sichuan where they were diagnosed with rabies , the diagnosis was confirmed by laboratory testing by the Sichuan CDC , and this was reported as a confirmed rabies case to the NDRS via the Internet . Our staff in the national laboratory of China CDC can access data in NDRS , but unfortunately there was sufficient delay so that when we contacted Sichuan CDC , the patient had already died and there was insufficient sample volume for genome amplification . If there had been a protocol in place to ensure rapid communication between local and national CDCs upon identification of a positive case , more work could have been done , i . e . collecting more saliva or serum samples before death , or obtaining a brain sample after death . This is a focus of a current review of the infrastructure between national and local CDCs . Fortunately , the N gene of Case 2 was obtained from the limited saliva sample . Surprisingly , it belongs to China I lineage ( Fig 2 ) , which indicates the dominate lineage in the current rabies epizootic has expanded into Tibet , from neighboring Yunnan , which in recent years has experienced a reemergence of dog rabies [29] . However , given that Tibet is a vast but sparsely populated territory , it is unlikely this first case will be followed by a rapid increase in cases , giving us the opportunity to ensure further controls methods are in place to halt further spread of cases . Our ongoing surveillance of the China rabies epizootic highlights the benefits of combining surveillance and phylogenetic data , as it presents a more complete picture and helps to better interpret the epidemic situation [1 , 9 , 17 , 18 , 30] . Nevertheless , our findings to date indicate the geographical distribution of rabies , as well as the virus lineages in China are changing . We believe more comprehensive , timely and specific surveillance will be needed to adapt to these changes to continue to reduce the number of rabies cases in the country .
|
Until recently , Tibet , “the third pole” of the earth , has been relatively isolated from the outside world , and has stayed rabies free for almost two decades . However , from 2015 to 2017 , one human case has been reported each year . Investigation of the origins of these cases revealed each of the three human cases has distinct origins . Case 1 ( 2015 ) seems to be a result of a wildlife spillover event , and is consistent with rabies virus strains found in Russia , and Qinghai , Inner Mongolia and Heilongjiang in China . Case 2 ( 2016 ) is associated with the current Chinese epizootic and appears to have originated from the neighboring province of Yunnan . Lastly , Case 3 ( 2017 ) is most closely related to a few recent Nepalese strains and originates from the Indian subcontinent clade , also found in India and Sri Lanka . Thus , Tibet is facing a major rabies threat on three fronts .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
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"epizootics",
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] |
2019
|
The reemergence of human rabies and emergence of an Indian subcontinent lineage in Tibet, China
|
Global Program to Eliminate Lymphatic Filariasis ( GPELF ) launched by WHO aims to eliminate the disease by 2020 . To achieve the goal annual mass drug administration ( MDA ) with diethylcarbamazine ( DEC ) plus albendazole ( ABZ ) has been introduced in all endemic countries . The current policy however excludes pregnant mothers and children below two years of age from MDA . Since pregnancy and early childhood are critical periods in determining the disease outcome in older age , the present study was undertaken to find out the influence of maternal filarial infection at the time of pregnancy on the susceptibility outcome of children born in a community after implementation of MDA for the first time . The participants in this cohort consists of pregnant mothers and their subsequently born children living in eight adjacent villages endemic for filarial infections , in Khurda District , Odisha , India , where MDA has reduced microfilariae ( Mf ) rate from 12% to 0 . 34% . Infection status of mother and their children were assessed by detection of Mf as well as circulating filarial antigen ( CFA ) assay . The present study reveals a high rate of acquiring filarial infection by the children born to infected mother than uninfected mothers even though Mf rate has come down to < 1% after implementation of ten rounds of MDA . To attain the target of eliminating lymphatic filariasis the current MDA programme should give emphasis on covering the women of child bearing age . Our study recommends incorporating supervised MDA to Adolescent Reproductive and Sexual Health Programme ( ARSH ) to make the adolescent girls free from infection by the time of pregnancy so as to achieve the goal .
Lymphatic filariasis ( LF ) is the second leading cause of chronic disability worldwide . According to recent estimate around 120 million people have been infected with LF in 73 countries and more than 1 . 1 billion ( 20% of the world’s population ) are at risk of acquiring infection [1] . Two-thirds of the endemic population resides in South-East Asia and one-third lives in India [2] . Out of 30 states in India , seven states namely Andhra Pradesh , Bihar , Kerala , Odisha , Uttar Pradesh , Tamil Nadu , and West Bengal contribute over 86% of Mf and 97% of disease cases in the country [3] . In 1997 , WHO and its member states made a commitment to eliminate LF as public health problem by 2020 through World Health Assembly Resolution WHA 50 . 29 . The National Health Policy ( 2002 ) has set the goal of elimination of LF in India by 2015 by annual mass drug administration ( MDA ) . Odisha , an eastern Indian state , has experienced 10 rounds of MDA since 2004 . But according to NVBDCP ( National Vector Borne Disease Control Programme , India ) though the Mf rate has come down from 2 . 6% to 0 . 34% during this time yet complete elimination of filariasis has not been achieved [4] . The concept of MDA includes administration of single dose of DEC ( 6mg/kg body weight ) plus albendazole ( 400mg ) to everybody in the community . Since DEC can cause anaphylactic reactions pregnant women , children below two years of age and persons who are very sick from other illness are not covered under MDA . When a proportion of the population fails to comply with MDA , a potential reservoir for the parasite is left untreated , opening the door to recrudescence or to potential risk factors for increasing the susceptibility status of new born and thus reducing the probability of the program’s success . Our previous studies have shown that transplacental transfer of circulating filarial antigen ( CFA ) can lead to in-utero sensitization and immune-modulation in neonates born to filarial infected mother [5–7] . Hence question arises whether the sensitization of the foetus and immune-modulation at the time of delivery can ultimately influence the disease outcome in children during their natural exposure to filariasis in MDA ongoing area , where the Mf rate has come down to below threshold level ( <1% ) . Therefore the present investigation was undertaken to find out the influence of maternal infection on the susceptibility outcome of children born after implementation of MDA for the first time and its implication on the success of the current elimination programme .
The human ethical committee of Regional Medical Research Centre , Bhubaneswar has approved the study and recommended to obtain oral consent from the study participants . All enrolled mothers have been explained about the purpose of study in local language in presence of an impartial witness of the community like Auxiliary Nurse Midwife ( ANM ) / Accredited Social Health Activist ( ASHA ) / Anganwadi Workers ( AWW ) . All the enrolled mothers have given face to face consent to participate in the study for themselves and their children as well without a sign consent form . The name and detailed address of the participants who have given consent was recorded in our data sheet at the time of enrolment for tracking during follow-up . The oral consent was preferred because of linguistic or literacy demands of the written format . The district Khurda situated on the coast of the Bay of Bengal is one of the highly endemic districts for LF [8] and has experienced 10 rounds of MDA with > 85% coverage . The district has reported Mf rate of 0 . 34% in 2013 compared to 12% in 2004 . Currently , around 1 . 8 million people are at risk of filarial infection in the district . Amongst them 51 . 91% lives in rural areas ( total 1358 villages ) and 48 . 09% in urban areas ( total 3 municipalities and 2 notified area councils ) . This is a hospital based cohort study conducted in eight adjacent villages of Bajapur Panchayat of Khurda block-a highly endemic area for filariasis ( Wuchereria bancrofti ) . Women admitted in O&G Department of Khurda District Headquarter Hospital for delivery from July 2009–July 2011 and are permanent residents of these villages have been enrolled for the study conveniently . Mother-infant pairs were excluded from the study in case of i ) complicated infant delivery resulting in significant infant morbidity at birth , ii ) premature delivery , iii ) mother who had known chronic illness or iv ) the family who had plans to relocate after delivery . Upon enrolment , mothers underwent a detailed questionnaire that queried their age , parity , education level , clinical history of filariasis and history of drug consumption in MDA . None of the mothers had signs/symptoms of clinical filariasis at the time of admission . Based on their statement all the enrolled mothers have consumed the antifilarials distributed during MDA before pregnancy . Paired cord and maternal blood samples were collected at the time of uncomplicated delivery . Venous blood samples were collected from mothers before delivery . Venous umbilical cord blood samples from neonates were collected immediately after birth . The collection of cord blood involved direct aspiration via puncture of the ethanol-sterilized umbilical vein at a site distal to the placenta , to reduce minimum cross-contamination . Maternal and cord blood samples were collected in different sized tubes to avoid the chance of mislabelling . Sera were stored at -70°C till further use . The children born full-term , healthy and whose mothers agreed to continue participation have been enrolled during follow up . Out of 158 mother-newborn pairs enrolled during 2009–2011 , 63 . 9% ( 101/158 ) could be followed up along with their children during house to house visit in 2014 . At the time of follow-up the mothers averaged 29 . 2 years of age , and most of them had a primary school education . Majority of the enrolled mothers ( 81% ) identified ‘‘Homemaker/Housekeeper” as their primary occupation . The physical assessment of mothers and children were conducted by a physician and examined for presence of Mf . Venous blood samples ( 1ml ) were collected from enrolled mothers and their children along with detailed clinical history . W . bancrofti infection was detected in mother and their children either by detection of Mf in thick blood smear of peripheral blood collected at night between 20:30 and 22:30 by microscopy or by detection of CFA in serum samples using commercially available Og4C3 antigen detection assay kit ( Trop BioMed , Townsville , Australia ) . The statistical analysis was done using GraphPad Prism software . Differences in proportions between the two groups were assessed using the Fisher exact test and the power of the study was measured using post hoc power analysis . The level of significance was set at 0 . 05
An overview of the enrolment and follow up of participants is presented in Fig 1 . A total number of 179 pregnant women admitted to O& G clinic for delivery from July 2009 to July 2011were selected for the study . Of them 21 ( 11 . 7% ) mothers were excluded because of complication during delivery or infant death or unwillingness . None of the mothers have been enrolled more than once . Finally 158 mother-new born pairs were enrolled for the study . Amongst them 24% of the mothers have multiparity status . As would appear from the baseline characteristics about 45% of the mothers were positive for CFA ( GM: 1925 , range: 630–16596 ) and 11 . 8% for Mf ( 3–210 per 60μl blood ) . The transplacental transfer of CFA from mother to cord was detected in 15 . 8% of the infected mother , while none of the cord blood was found to be positive for Mf . Out of 158 mother-new born pairs a total of 101 pairs have been examined during the follow-up . Amongst them 33 children were found to born from mothers who had filarial infection ( MF+ve /CFA+ve: 4 and Mf -ve / CFA +ve: 29 ) at the time of delivery and 68 from filarial uninfected mother ( CFA-ve and Mf-ve ) . Out of 33 infected mothers , 18 mothers are still harbouring filarial infection ( CFA +ve but Mf -ve ) , 5 mothers have cleared CFA but developed acute symptoms of filariasis and 10 have cleared CFA without developing any clinical signs/symptoms of filariasis . The geometric mean ( GM ) of CFA levels of the mothers at the time of follow-up was 232units ( range: 128–7762 ) compared to 2125 ( range: 930–16596 ) at the baseline of the study . All mothers were free from Mf at the time of follow-up compared to 12 . 1% ( 4/33 ) at the time of enrolment . Interestingly all 68 uninfected mothers maintained infection free status at the time of follow-up . Out of 33 children born to infected mothers 9 ( 27 . 2% ) have acquired filarial infection and became CFA positive ( GM: 147 , range: 128–230 ) , while 6 out of these 9 children belongs to mothers ( n = 15 ) who are CFA negative during follow up . Moreover amongst these 6 children 3 belongs to mothers who have developed clinical filariasis during follow up and rest 3 belongs to mothers who are free from CFA and clinical signs/symptoms . In contrast 2 . 9% ( 2/68 ) of the children born to uninfected mothers have become CFA positive ( GM: 133 ) during this period . None of the children had developed either any clinical signs/symptoms of filariasis or Mf in their peripheral blood ( Table 1 ) . Comparison of data shown that there is an extremely significant association ( P = 0 . 0006 , 95% confidence interval = 0 . 01628 to 0 . 4011 , power of the study: 92 . 2% ) between infection status of mother and acquiring of infection by the children born to them .
We can conclude that there is a strong association between maternal filarial infection and the infection outcome in children born to them . This might be one of the reasons for persistence of filarial infection among the children < 5 years even though Mf rate has come down to below threshold level in this endemic area after implementation of 10 rounds of MDA . Hence the present finding reinforces the importance of implementation of more efficient prevention strategies of lymphatic filariasis in pregnant women and their children . In order to achieve the target of eliminating lymphatic filariasis by 2020 globally and by 2015 in India the current MDA programme can include supervised MDA therapy in to the current Adolescent Reproductive and Sexual Health Programme ( ARSH ) so as to make the women of child bearing age free from infections before pregnancy , because it has been observed that continuous reduction of CFA level after repeated treatments can eliminate W bancrofti infection .
|
Lymphatic filariasis , commonly known as elephantiasis , is a painful and profoundly disfiguring disease . A massive global effort has been undertaken to eliminate this disease by 2020 using annual mass drug administration ( MDA ) . However the MDA excludes pregnant women and children below two years of age , which are the two critical periods thought to be playing a major role in determining the disease susceptibility in older age . We have been working on the impact of filarial infection at the time of pregnancy on neonates since 2009 in India . We have assessed the impact of maternal infection among a group of children from the time of their birth till they attain early childhood . We have observed that children born to mothers having filarial infection at the time of pregnancy were more prone to infection at early childhood than born to infection free mother in an area having very low infection rate after MDA . Our finding reveals that infection in mother at the time of pregnancy plays a crucial role in acquiring infection in children . Hence to achieve the goal of elimination of filariasis the women of child bearing age should be treated with antifilarials through MDA under supervision .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
Maternal Infection Is a Risk Factor for Early Childhood Infection in Filariasis
|
The nematode Caenorhabditis briggsae is an emerging model organism that allows evolutionary comparisons with C . elegans and exploration of its own unique biological attributes . To produce a high-resolution C . briggsae recombination map , recombinant inbred lines were generated from reciprocal crosses between two strains and genotyped at over 1 , 000 loci . A second set of recombinant inbred lines involving a third strain was also genotyped at lower resolution . The resulting recombination maps exhibit discrete domains of high and low recombination , as in C . elegans , indicating these are a general feature of Caenorhabditis species . The proportion of a chromosome's physical size occupied by the central , low-recombination domain is highly correlated between species . However , the C . briggsae intra-species comparison reveals striking variation in the distribution of recombination between domains . Hybrid lines made with the more divergent pair of strains also exhibit pervasive marker transmission ratio distortion , evidence of selection acting on hybrid genotypes . The strongest effect , on chromosome III , is explained by a developmental delay phenotype exhibited by some hybrid F2 animals . In addition , on chromosomes IV and V , cross direction-specific biases towards one parental genotype suggest the existence of cytonuclear epistatic interactions . These interactions are discussed in relation to surprising mitochondrial genome polymorphism in C . briggsae , evidence that the two strains diverged in allopatry , the potential for local adaptation , and the evolution of Dobzhansky-Muller incompatibilities . The genetic and genomic resources resulting from this work will support future efforts to understand inter-strain divergence as well as facilitate studies of gene function , natural variation , and the evolution of recombination in Caenorhabditis nematodes .
Caenorhabditis nematodes , first described over one hundred years ago [1] , are easily cultured and have been employed since the 1960s as model organisms in a number of fields . C . briggsae exhibits many features desirable of a genetic model organism: a self-fertilizing hermaphrodite , presence of rare males for genetic crosses , and broods of hundreds that reach sexual maturity in a few days [2] . Sydney Brenner initially touted C . briggsae as the model system of choice for studying the genetic basis of cellular development , although he eventually championed the now-famous C . elegans [3] , [4] . The many similarities between C . briggsae and C . elegans [5] led to confusion as to which strains belonged to which species until 1977 [6] , and it seems C . briggsae could easily have been the more widely-studied species today . More recent reports have revealed key ways in which C . briggsae differs from C . elegans . For example , genetic and phylogenetic studies have demonstrated that C . elegans and C . briggsae independently evolved self-fertile hermaphroditism by means of distinct genetic mechanisms [7]–[11] . Surprising differences also exist in their early embryonic patterning [12] and anatomy of the excretory system [13] , [14] . C . elegans and C . briggsae also differ in their phylogeography . Global sampling of natural isolates suggests near-panmixia among C . elegans populations [15]–[24] , while strong latitudinal population structure exists in C . briggsae [17] , [25]–[28] . Thus , while sharing reproductive mode and cosmopolitan distribution , C . elegans and C . briggsae appear to migrate and interbreed at different rates , and as a result have differing levels of species-wide genetic variation [18] , [26] . Despite its minimal population structure , however , C . elegans harbors a polymorphic ( and potentially selfish ) incompatibility locus that causes hybrid lethality [29] . Evidence of outbreeding depression in C . briggsae has also been noted [17] , though its genetic structure is unknown . The greater genetic and phenotypic variation in C . briggsae makes it useful for mapping loci affecting various traits , such as male tail development , vulva cell fate , and fecundity [17] , [27] , [30]–[33] , and refutes an early criticism of Caenorhabditis “that the animal has few morphological and behavioral traits” [4] . Some of these studies sought to identify ecological correlates of phylogeography , such as temperature , that might explain the diversity exhibited among C . briggsae strains . However , no such correlations between geography , genotype , and phenotype have been made for C . elegans , and they might not exist [34] , [35] . Thus , C . briggsae can be both a critical companion species for comparative analysis with C . elegans and also a potentially better choice for studies investigating the genetic architecture of ecological adaptation in nature . Both of these roles demonstrate the value of continued development of C . briggsae as a model system . Research on C . briggsae has enjoyed a recent surge in popularity [e . g . 8] , [17] , [26] , [31] , [36] since its genome was sequenced [37] . The last decade has seen improvement of the genetic and genomic research tools available [37]–[40] , but they still lag behind those for C . elegans . Initially motivated by a desire to improve C . briggsae as a genetic system , we produced and genotyped advanced-intercross recombinant inbred lines . Such cross designs have been employed in other species [15] , [41]–[43] and are particularly useful for expanding genetic maps [44] . Such an improved map allows precise comparisons of recombination landscapes for homologous chromosomes . C . briggsae is similar to C . elegans in a number of genetic and population genetic characteristics ( e . g . low effective population size [24] , [28] , frequent self-fertilization , equivalent genome size [37] , and strong crossover interference [38] ) . This raises the possibility that variation in recombination rate might contribute to their different levels of DNA polymorphism [18] , [26] . Previous studies suggest that a general chromosome-wide pattern of recombination rate domains is conserved between the two species [15] , [38] . However , the low resolution and sparse density of genetic markers in the previous C . briggsae genetic map diminish the accuracy of such a comparison . Intra-species variation of recombination rates among wild-type strains has been examined in C . elegans [15] , [45]; a comparison of intra-species ( C . briggsae ) and inter-species ( C . elegans – C . briggsae ) recombination profiles might reveal how recombination rates evolve over timescales as small as hundreds of thousands of years . The stereotyped and discrete domains of recombination common to Caenorhabditis [15] , [38] also aid identification of correlates of change in recombination rate . For example , inversions alter recombination when heterozygous , often suppressing ( but not always absolutely ) recombination within them [46]–[50] and increasing it around them [51] . Such rearrangements are also thought to contribute to adaptation and speciation [52]–[56] . A comparison of intraspecific genetic maps could clarify the relationship between inversions , adaptation and speciation in different populations . In this study , we produced and genotyped two sets of C . briggsae recombinant inbred lines ( RIL ) . One set was generated from the strains AF16 and HK104 using an advanced-intercross design ( AI-RIL; Figure 1 ) . Roughly half of these AI-RIL were established in one cross direction ( AF16×HK104 , where the first strain listed provides the male , by convention ) and half in the other ( HK104×AF16 ) . [Note: when discussing both subsets of AI-RIL without respect to cross polarity , the notation “AF16/HK104” will be used] . The second set of RIL was generated from the strains AF16 and VT847 using an F2 cross scheme . The linkage maps derived from these two sets of RIL are suited for revealing differences in relative recombination rates . We also used the sets of RIL to detect selection occurring on hybrid genotypes and to identify inter-strain genetic incompatibilities , revealing the potential utility of C . briggsae for studying the process of incipient speciation in a highly selfing species .
The first-generation C . briggsae genetic map was produced by RIL generated by the selfing of F2 founders [38] . C . elegans chromosomes generally experience one recombination event per meiosis [57] . Assuming that C . briggsae is similar , F2 RIL contain few recombination breakpoints per chromosome , limiting their utility for making genetic maps [38] . We therefore created a set of advanced-intercross recombinant inbred lines ( AI-RIL ) for C . briggsae in order to improve the genetic map . We used six generations of mating prior to ten generations of selfing to decrease the size of haplotype blocks in the AI-RIL ( Figure 1 ) . The parental strains were C . briggsae AF16 , the standard laboratory strain from India whose genome has been sequenced [37] , and HK104 , a divergent Japanese strain already used for SNP discovery and mapping [7] , [16] , [39] , [58] . AF16 and HK104 are members of distinct tropical and temperate clades of C . briggsae [28] , respectively , that diverged roughly 90 , 000 years ago [26] . 180 AI-RIL and the parental strains were genotyped at 1 , 536 single nucleotide polymorphism ( SNP ) markers . 167 AI-RIL and 1 , 032 SNP markers passed quality control thresholds and inspections ( Materials and Methods ) , resulting in 172 , 344 genotype calls for the AI-RIL ( Table S1 ) . After exclusion of lines apparently heterozygous at many markers ( Materials and Methods ) , only three heterozygous genotype calls remain in the final genotype data set . The remaining genotypes were homozygous for one of the parental strains ( 67 , 286 AF16/AF16; 105 , 055 HK104/HK104 ) . Homozygosity of the parental strains at each marker was confirmed directly ( Table S1 ) . 89 F2 RIL were produced by repeatedly selfing the offspring of VT847×AF16 F1 hybrids . VT847 is a C . briggsae isolate from Hawaii [30] , part of the same clade of tropical isolates as AF16 [17] . These RIL were genotyped at the same 1 , 536 SNPs . Mostly because many of these SNPs are monomorphic between the parental strains , only 209 markers passed quality control . Again , the vast majority of genotype calls were homozygous for one of the parental strains ( 9 , 344 AF16/AF16; 9 , 184 VT847/VT847 ) ; 50 calls were heterozygous ( Table S1 , but see Materials and Methods ) . 132 markers were successfully genotyped in both sets of RIL . Genetic maps of the five autosomes and X chromosome comprising the nuclear genome were estimated de novo from the final AF16/HK104 AI-RIL SNP genotype data set . Marker compositions and lengths of the maps are given in Table 1 . The expanded AI-RIL genetic maps for autosomes range from 148 . 6 to 173 . 2 centimorgans ( cM ) in cumulative length; the X chromosome map length is 100 . 0 cM . The new C . briggsae genome assembly ( see below ) inferred from the genetic map allowed us to plot the recombination rate as a function of physical position ( Marey maps; [59] , Figure 2 ) . This reveals the presence on each chromosome of small tip domains and larger central domains that host less recombination compared to the chromosome “arm” domains ( Caenorhabditis chromosomes are holocentric [60] ) . As previously found in C . elegans and C . briggsae , the X chromosome domain boundaries are qualitatively less evident than those of the autosomes [15] , [38] . Of the 1 , 031 C . briggsae SNPs used to produce chromosome assemblies ( one marker was genetically mapped but not used in the chromosome assemblies ) , only 443 genetic intervals are defined , owing to the complete linkage of a number of SNPs . The average size of an interval is 101 . 3 kbp , with median size 43 . 8 kbp and maximum of 1 . 45 Mbp . The average marker spacing is 2 . 1 cM , with median spacing 1 . 2 cM and a maximum of 18 . 7 cM . We note that these values represent cumulative genetic distance defined for the AI-RIL , not per-meiosis distances . Normalizing each linkage group to the expected per-meiosis map length of 50 cM , the average marker spacing becomes 0 . 6 cM . The genotypes of the VT847×AF16 RIL were also used to estimate de novo genetic maps; the genetic positions of markers and the genotypes of the RIL are given in Table S1 . The estimated genetic maps for autosomes range in length from 82 . 1–110 . 6 cM; the X map is 43 . 0 cM . The number of autosomal recombination breakpoints captured by the C . briggsae AF16/HK104 AI-RIL constructed for this study ranged from zero to six with an average of 1 . 59 ( Table 2 ) , less than might be expected given the cross design . Nevertheless , in the AI-RIL , autosomes exhibit almost twice as many evident recombination events compared to our F2 RIL and to the F2 RIL used to create the previous C . briggsae genetic map version [38] ( Table 2 ) . The AI-RIL and F2 RIL reported here also almost double the observed number of recombination events on the X chromosome . The 1 , 032 genetically mapped markers represent a four-fold increase in the number of markers used to produce C . briggsae genome assembly version cb3 [38] ( Table 1 ) . Combined with the increased number of recombination breakpoints afforded by the AI-RIL , the new genetic map facilitated the incorporation of unplaced sequence supercontigs , orientation of previously unoriented supercontigs , and identification and resolution of some existing assembly errors . Table 1 provides statistics on the new assembly , version cb4 . Most notably , we have confidently ordered an additional 14 Mbp of sequence ( 13% of the genome ) , representing a 2 . 5-fold reduction in the amount of sequence unassigned to chromosomes and a 34-fold reduction in the amount of sequence unable to be ordered within chromosome assemblies . Importantly , 1 . 8 Mbp of sequence contained on 15 supercontigs has changed chromosomal assignment from cb3 to cb4 . We also orient sequence contigs comprising 21 Mbp ( 20% of the genome ) . Additional details of the assembly are available in Text S1 . With an improved genome assembly , we re-evaluated the extent of chromosomal synteny between C . elegans and C . briggsae using a genome-wide plot of nucleotide conservation . By identifying only maximal unique matches ( MUMs ) in each comparison sequence , orthologous coding regions are predominantly identified ( Figure 3 , by comparison with plots of MUMs using translated nucleotide sequence , not shown ) . Extensive matches exist in the self-diagonal ( comparisons between homologous chromosomes of C . elegans and C . briggsae ) , but relatively few off-diagonal ( interchromosomal ) MUMs are apparent . The center domains of the autosomes have extensive colinearity in MUMs , while synteny in the arms is much less apparent . Although syntenic blocks on the X are larger and comprise a larger proportion of the chromosome than on autosomes , the order of blocks on the X nevertheless differs between the species . While interspecies inversions and translocations are evident in these chromosomal plots , the presence and extent of polymorphic inversions among C . briggsae strains is unknown . By comparing our AF16/HK104 AI-RIL linkage maps with the VT847×AF16 F2 RIL linkage maps , we sought evidence for such inversions . Because heterozygous inversions present in hybrids should suppress recombination [46] , inversions are expected to manifest genetically as blocks of markers that are recombinant with each other in one linkage map and nonrecombinant in the other . For all 132 SNPs common to both genetic maps , we ordered the SNPs based on physical assembly position and then identified blocks of markers that exhibit this genetic signature of inversion ( Table S2 ) . Twenty-one blocks of markers are nonrecombinant in the F2 RIL but resolved in the AI-RIL; in the AI-RIL , four nonrecombinant blocks are resolved in the F2 RIL . Most of the former are expected due to the overall shorter F2 RIL map , whereas the latter might be enriched for true recombination suppressors . For example , ChrIV markers cbv19538 and cb58228 acted as a point in the AI-RIL genetic map , but were 1 cM apart in the F2 RIL map of ChrIV normalized to 50 cM . These markers reside in high recombination arm B of ChrIV , where the normalized breakpoint density in the AI-RIL map is 5 . 66 breakpoints/cM . We thus expect to see 5 . 03 breakpoints between them , averaged over the 89 F2 RIL . Assuming that the breakpoints are Poisson-distributed with an expected value of 5 . 03 , the observed value of zero is significantly different ( p = 0 . 006 ) . When Bonferroni-corrected for multiple tests , the genetic distance between these markers in the F2 RIL remains significant ( p<0 . 05 ) . We estimated the physical and genetic size and recombination rate of each domain ( Table 3 ) . To allow comparisons between maps of different overall lengths , the recombination rates in the AI-RIL were normalized by adjusting the map length of each chromosome to the expected per-meiosis length of 50 cM ( see Materials and Methods ) . Low synteny in the chromosome arms ( Figure 3 ) precludes meaningful direct comparisons of arms between species . We therefore refer to the arms of C . briggsae chromosomes as “A” and “B” rather than “L” ( left ) and “R” ( right ) to prevent inappropriate inference of homology , and we compare arm attributes between C . briggsae and C . elegans using ratios of lengths and rates from one arm to the other . The homology of center domains is not ambiguous , so their values can be compared directly . The center domains occupy more than a third of the physical length of each autosome ( Table 3 ) . However , they are relatively smaller in C . briggsae ( comprising 40–46% of the total chromosome length in C . briggsae vs . 47–52% in C . elegans [15] ) . On the X chromosome in both species , the center domain occupies closer to a third of the chromosome length . Compared to their physical lengths , the genetic lengths of central domains are short compared to the arms in both species ( but they still exhibit variation , e . g . ChrI , ChrV ) . Tip domains tend to occupy larger proportions of the chromosome length in C . elegans than C . briggsae . The absence of tip domains on the B arms of C . briggsae ChrII and ChrV could represent real diversity or be due to poor marker coverage in those regions . The ratios of arm physical sizes are similar , ranging from 1 . 11–1 . 59 in C . briggsae and 1 . 12–1 . 77 in C . elegans ( Table 3 ) . However , arm genetic lengths vary more between species . For example , the ratio of genetic lengths of the two ChrII arms is 1 . 45 in C . briggsae , but 1 . 06 in C . elegans . Strikingly , genetic and physical length ratios do not always correlate . C . briggsae ChrIV arms have the largest asymmetry in physical length ( 1 . 59-fold ) but the smallest in genetic length ( 1 . 17-fold ) . The opposite pattern is seen in C . elegans , whose ChrIV arms have a physical length ratio of 1 . 18 but a genetic length ratio of 1 . 82 . Arm ratios for the X are similar between the two species . Chromosomal attributes that dictate the sizes or boundaries of recombination domains are expected to co-vary in the two species . To identify candidate attributes , we compared three characteristics of homologous C . elegans and C . briggsae center domains: their genetic length , physical length and proportion of the chromosome physical length . We also examined the degree of asymmetry in arm pairs as measured by the ratios of their genetic and physical lengths . Of these , the fraction of the total physical chromosome length occupied by a given central domain in one species was the most predictive of the state for the homolog in the other ( R2 = 0 . 8253 ) . To identify variation in the recombination domains on a shorter time scale , we compared their characteristics in the AF16/HK104 AI-RIL and VT847×AF16 F2 recombination maps ( Figure 4 ) . As the low marker density of the F2 VT847-based map precludes precise de novo determination of recombination domain boundaries , we used the boundaries determined for the AI-RIL for both maps ( visual inspection of the F2 RIL Marey maps , Figure 4 , indicates this is reasonable ) . The comparison reveals two ways in which apparent recombination rates vary across a given chromosome ( Figure 4 ) . First , while the genetic lengths of the two arm domains of a given autosome are generally symmetrical in the AF16/HK104 map ( fold-change range 1 . 17–1 . 72 ) , observed recombination is often heavily biased to one arm in the VT847×AF16 maps ( fold-change range 1 . 41–7 . 09 ) . Second , the genetic lengths of the center domains can differ between AF16/HK104 and VT847×AF16 ( for ChrIII and ChrIV , over two-fold ) . Thus , the Marey map curves visibly differ in the two maps for ChrI , ChrIII , ChrIV , and ChrV . In the crossing scheme used to produce the AI-RIL , each parental strain is expected to contribute half of the alleles at any autosomal locus; for ChrX , two-thirds of lines are expected to fix the allele of the hermaphrodite parent in the original cross ( Figure 1 ) . Deviation from the neutral-expected allele fraction value is called marker transmission ratio distortion ( MTRD ) and can indicate the action of selection on specific hybrid genotypes . We plotted the relationship between the proportion of lines fixed for the HK104 allele and the physical position of each marker in order to identify departures from the neutral expectations ( Figure 2 ) . For ChrI , ChrII and ChrX , in neither cross direction does allele fraction significantly deviate from expected . However , for markers on the remaining autosomes , significant MTRD towards the HK104 parental allele was common . On ChrIV and ChrV , significant departure from the expected allele fraction value occurred only in one cross direction . On ChrIV , the AF16×HK104 AI-RIL were biased ( maximum allele fraction = 0 . 81; 7 . 3 Mbp significantly biased ) ; on ChrV , the HK104×AF16 AI-RIL were biased ( maximum allele fraction = 0 . 81; 7 . 4 Mbp significantly biased ) . We hypothesized that epistatic genetic interactions between one or more loci in the central recombination domains of ChrIV or ChrV and a factor dictated by cross direction produces the observed MTRD . To directly test for cross direction effects , we compared allele fractions between the crosses in these regions . For ChrV , the allele fraction values of three adjacent markers ( Figure 2 , asterisk ) were significantly different ( p<0 . 05 after Bonferroni correction ) , while no ChrIV markers met this standard . The most extreme MTRD was on ChrIII . The majority of ChrIII markers were biased toward the HK104 allele in both cross directions ( maximum allele fraction = 0 . 87; AF16×HK104: 8 . 2 Mbp and HK104×AF16: 7 . 6 Mbp significantly biased ) . Despite the MTRD , at no marker was the AF16 allele completely absent from the AI-RIL set . Line PB1149 , which had the fewest number of AF16/AF16 calls ( 137 of 1 , 032 ) , exhibits only six recombination breakpoints and is fixed for HK104 across all of ChrI , ChrII and ChrIII . During production of the AI-RIL , we noticed that approximately 20% of F2 hybrids from crosses between AF16 and HK104 exhibit a pronounced developmental delay ( Figure 5A and 5B; [17] ) . These delayed F2 take approximately four days to reach sexual maturity at 20°C , whereas P0s , F1s and most F2s reach sexual maturity in approximately three days . The delayed development of these F2s was associated with homozygosity for AF16 alleles in the central domain of ChrIII ( Figure 5C–5F ) , consistent with the under-representation of AF16 alleles on ChrIII in the AI-RIL . The delay phenotype is reproducible in crosses between AF16 and HK104 , but was not observed in VT847×AF16 F2 individuals during production of the F2 RIL ( not shown ) . Furthermore , while a bias against AF16 alleles can be seen in the ChrIII genotypes of AF16×HK104 F2 RIL [38] ( Figure 5G ) , no such bias is evident in the VT847×AF16 F2 RIL ( Figure 5H ) . Characterization of interchromosomal linkage disequilibrium ( LD ) in the lines could identify co-adapted loci that might affect hybrid fitness , enhance the utility of the AI-RIL , and determine whether X-autosome epistatic interactions explain the cross direction-specific MTRD for ChrIV and ChrV described above . D′ , a measure of LD that ranges from zero to one and normalizes D for overall allele frequencies [61] , was employed as the metric here ( Figure 6 ) . Very few regions of high interchromosomal D′ values common to both cross directions were observed in this analysis . However , discrete blocks of high D′ present only in one cross direction are seen , including a block containing markers with interchromosomal D′ = 1 . In this case , in the AF16×HK104 cross , AI-RIL whose genotypes are AF16/AF16 at cb22151 ( ChrIII ) are never also AF16/AF16 at cb4013 ( ChrIV ) . However , D′ is calculated under the assumption of Hardy-Weinberg equilibrium , which might not be appropriate for inbred lines . Indeed , this correlation is not significant ( chi-square , p = 0 . 058 ) , most likely due to the strong HK104-biased allele frequencies of the AI-RIL set . Similarly , in the opposite cross direction , no gametic class frequencies are significantly different from expected based on the allele frequencies at these markers ( chi-square , p = 0 . 773 ) . It is nevertheless interesting to note that the same block of ChrIII markers interacts with a small region of ChrV in one cross direction and with ChrIV in the other ( Figure 6 ) . These three blocks on ChrIII , ChrIV and ChrV overlap with ( but are much smaller than ) regions of significant MTRD ( the blocks are identified by shading in Figure 2 ) .
The previous C . briggsae genetic map was based on SNP genotyping of F2 RIL [38] . Because Caenorhabditis chromosomes generally experience one crossover event per meiosis [57] , these RIL have very large haplotype blocks . While this did not hinder assignment of sequence supercontigs to linkage groups , it often prevented the supercontigs from being ordered and oriented within a chromosome [38] . The five additional generations of mating beyond F2 used to produce the AI-RIL ( Figure 1 ) expanded the genetic map to 928 . 6 centimorgans total length , a 1 . 57-fold increase compared to the cb3 genetic map . In addition , we were able to substantially increase the map's resolution by more than tripling the number of scored SNPs ( 1 , 032 ) in almost twice ( 167 ) the number of inbred lines ( Table 1 ) . Our AI-RIL genetic map compares favorably with other contemporary maps in marker number ( 1 , 032 ) and density ( 0 . 6 cM average spacing when normalized to a 50 cM map length ) . Those recently estimated in the genera Bombyx , Apis , Nasonia , and Brassica contain between 1 , 000 and 2 , 000 markers , producing 0 . 3–2 . 05 cM average marker spacing [62]–[65] . Our map did not match the quality of the C . elegans AI-RIL-based genetic map [15] , however . This map captured 3 , 629 recombination breakpoints over 1 , 588 cM , while our AI-RIL captured 1 , 494 breakpoints . Four explanations might account for this difference . First , our cross design did not achieve the maximum potential of an AI-RIL design because exchange of worms between the pools of intercrossing worms was not performed as in [15] . Second , we genotyped fewer lines ( 167 compared to 236 ) . Third , pervasive selection against AF16 alleles that occurs over much of the genome in the AI-RIL might have caused rapid reduction of heterozygosity during line construction prior to inbreeding , resulting in fewer observable recombination breakpoints . Finally , any contribution of self-progeny to the mating pools during the sib-mating phase of line construction , for example matings of male cross-progeny with hermaphrodite self-progeny , would reduce the map length . Although several lines contained one or more chromosomes with no apparent recombination breakpoints , none lack AF16 alleles completely . We can thus be certain that no lines were inadvertently established wholly from self-fertilization . Despite these potential issues , our AI-RIL cross scheme was successful at improving the resolution of the C . briggsae genetic map length compared to the previous F2 RIL-based version , capturing approximately twice the number of recombination breakpoints ( Table 2 ) . Because the X chromosome is hemizygous in males during outcrossing ( Figure 1 ) , its map length in our design is expected to be 2/3 the length of the autosomal maps . Indeed , the expanded AI-RIL X map length , 100 . 0 cM , is similar to the expected value of 110 . 5 . Unexpectedly , however , significantly fewer than expected SNPs were genotyped on the X . Although we cannot rule out the possibility that the C . briggsae X chromosome has reduced SNP density compared to autosomes , the method by which SNPs were chosen for genotyping is the most likely cause ( Materials and Methods ) . Because only two markers are required both to order and to orient each supercontig within a chromosome assembly , chromosomes with larger supercontigs would have had fewer total SNPs genotyped per unit of length . Indeed , supercontigs assigned to ChrX are significantly larger on average than autosomal ones ( t test , P = 0 . 02448; Figure S1 ) , a possibility that had been noted earlier [38] . The increased marker coverage of our genetic map allowed the incorporation of previously-unassembled genomic sequence supercontigs into the chromosomal assemblies and facilitated the genetic orientation of many supercontigs that were previously not oriented . Additionally , inconsistencies between the cb3 assembly [38] and the cb25 physical map [37] , as well as three previously reported issues with cb3 , have been resolved ( Text S1 ) . The C . briggsae genome assembly is more complete than some recently-sequenced insect genomes , such as for Nasonia vitripennis [66] , whose genome assembly comprises 63 . 6% of 312 Mbp of sequence based on a genetic map with more markers ( 1 , 255 ) but greater average inter-marker physical distance ( 249 kbp ) [65] . The cb4 assembly now surpasses the Drosophila melanogaster genome assembly in completeness as well ( version R5 . 33 , flybase release FB2011_01 [67] ) . While 13 . 4% of the D . melanogaster genome sequence is unordered ( half comprising unordered sequence from heterochromatic regions ) , the unordered content of C . briggsae has decreased from 15 . 9% ( cb3 ) to 3% ( cb4 ) . However , compared to C . elegans , whose genome assembly is truly complete ( i . e . containing no unordered sequence contigs , no gaps , and no uncalled bases ) , much work remains to complete the assembly of C . briggsae . The absence of heterochromatic centromeres and heteromorphic sex chromosome likely accounts for the relatively high quality of the Caenorhabditis assemblies . Inter-species variation in recombination rate has been described in other taxa . In Helianthus , most intervals tested exhibited rate variation between species 0 . 75–1 million years ( MY ) diverged [68] . Variation among some Drosophila species also exists [69] , but fine-scale recombination rates do not differ between others , suggesting lineage-specific and/or scale-dependent recombination rate variation [70] . Comparison of the C . elegans [15] and C . briggsae AI-RIL genetic maps reveals both conservation and variation in physical and genetic lengths of some recombination domains ( Table 3 ) . In both species , chromosome arms are clearly distinct domains that experience the vast majority of recombination events , and the distributions of arm recombination rates overlap , ranging from ∼2 . 5–8 cM/Mbp for autosomes . C . elegans arms tend to have slightly higher rates than C . briggsae , but C . elegans chromosomes also tend to be slightly smaller , so the elevated recombination rates likely reflect the necessity of fitting obligate recombination events into a shorter physical space . Poor local synteny in the arm domains ( Figure 3 ) prevented their direct comparison between species . We therefore compared the ratios of attributes for the two arms of a given homologous chromosome , assuming that aspects of the domains might be conserved despite mixing of the sequence content . For the AI-RIL-based genetic maps of both species , the ratios of arm physical or genetic lengths only exceeded two in one case , for the arm genetic lengths of C . elegans ChrI . The ratio of recombination rates of arms also occupied the same range , only once exceeding two ( C . elegans ChrIV ) . However , this similarity should be interpreted carefully given the extent of intraspecies variation discussed below . An additional caveat to the interpretation of the genetic parameters ( map length and recombination rate ) of the domains is that the values reported ( Table 3 ) do not reflect recombination alone . Homozygosity resulting from selection acting on an allele during RIL construction would prevent the detection of future recombination events occurring in the domain and cause a deviation in the fixation of parental alleles in regions under selection . Evidence of such selection exists for chromosomes in C . elegans [15] , [29] . In our C . briggsae AI-RIL , MTRD on ChrIII , ChrIV and ChrV also likely signifies the action of selection ( discussed below ) . The regions experiencing MTRD are broad ( Figure 2 ) , but the arm whose allele fraction comes closest to the neutral expected value ( IIIA , IVB , VB ) is always genetically longer than the opposite arm . This matches the prediction that MTRD , possibly due to selection , results in a decrease in apparent recombination breakpoints and thus a reduction in genetic map length over part of a chromosome . In sum , each autosome exhibits a signature of selection , MTRD , in one of the two species . For this reason , the genetic values reported in Table 3 ( both genetic length and recombination rate ) might not represent the neutral recombination rate , especially for C . elegans ChrI and ChrII and for C . briggsae ChrIII , ChrIV and ChrV . In contrast to map lengths , comparisons of physical attributes do not suffer from the influence of selection . The low recombination center domains , which have maintained greater synteny ( Figure 3 ) over the roughly 18 MY since the common ancestor of C . elegans and C . briggsae [71] , also revealed some size variation . Our findings concur with those from C . elegans , that the center domains are not precisely centered physically on the chromosome [15] . We find that , of the domain features tested , the proportion of total chromosome physical length occupied by the center domain is the most correlated between the species , suggesting that some aspect of relative physical position on the chromosome influences the positions of the center/arm domain boundaries . Work in a number of taxa has shown that recombination rates can vary within a species . A recent study of the evolution of recombination rates within mice found evidence for widespread rate differences among members of the species complex across 19% of the genome [72] . A remarkable seven-fold difference in recombination fraction within a Drosophila species has been revealed [69] , and a detailed study of maps from intraspecific crosses in Nasonia revealed a slight ( 1 . 8% ) but statistically significant increase in recombination frequency compared with interspecific crosses on a genome-wide scale [73] . Our findings from C . briggsae fall in the middle of this range , with the apparent recombination rates in homologous arm domains varying up to 2 . 9-fold between the crosses . Our AI-RIL and F2 RIL paired parental strains between and within , respectively , C . briggsae clades that are estimated to have diverged about 90 , 000 years ago [26] . Examination of Figure 4 reveals that , for some chromosomes ( ChrII and ChrX ) , the genetic lengths of both center and arm domains are constant . In addition , for each chromosome , the arm with the larger AF16/HK104 genetic map length is always the genetically larger arm in the VT847×AF16 map . However , substantial divergence in the genetic lengths of both the center domains ( ChrIII and ChrIV ) and arm domains ( ChrI , ChrIV and ChrV ) exists . The most striking feature of the genetic map comparison is the divergence in arm length ratio for multiple autosomes in the VT847×AF16 F2 RIL ( Figure 4 ) . Taken at face value , these results suggest that recombination itself is unusually biased to one arm in this cross , but alternative explanations should be considered . For example , we did not quantitatively compare our VT847×AF16 F2 RIL Marey maps to those previously reported for AF16×HK104 F2 RIL [38] because of the many differences in genome assemblies and markers scored in the two studies . Instead , we used our AF16/HK104 AI-RIL maps for the inter-strain comparison . However , both AF16/HK104 maps exhibit symmetrical arm usage , and generally resemble each other ( except for total genetic length ) more than either resembles the VT847×AF16 F2 RIL map . This suggests that intra-species differences are not caused by an artifact related to comparison of different cross designs . Strong selection against individual loci or recombinant haplotypes could also account for asymmetrical apparent recombination rates in the two arms . However , evidence for both of these is lacking for the chromosomes that have arm genetic length ratios >2 ( ChrI , ChrIV , and ChrV; Figure 4 ) . First , the strong effect of genetic drift in the F2 RIL implies that any hypothetical deleterious recombinant genotypes would have to be severely debilitating to strongly bias breakpoint capture to one arm , yet no class of morbid progeny was observed during line construction . Also , no strong MTRD is evident in the F2 RIL ( Figure S2 ) , suggesting an absence of selection on individual loci . We therefore conclude that real differences in recombination are the most likely explanation for the asymmetric arm breakpoint capture in the VT847×AF16 F2 RIL . This suggests that recombination rate can vary over short periods of time but does not necessarily correlate with genomic divergence . Greater variation in broad-scale recombination rate within rather than between species has also been observed in Nasonia [73] . The diversity in rate among populations of C . briggsae was unexpected , particularly given the similarities in the above interspecies comparisons and previous assertions that the overall similarity of recombination pattern among species likely reflects conservation [25] . Our results suggest that although the physical sizes of high and low recombination domains are stable within C . briggsae , variation in the degree of bias in usage of one arm over another exists . Comparisons with more genetic maps from other C . briggsae and C . elegans strains will likely reveal more diversity and patterns relevant to the understanding of the forces shaping the evolution of recombination rate . The comparison of C . briggsae genetic maps also revealed three blocks of markers with inverted genetic order relative to flanking markers in one cross ( Table S2 ) . Because the AI-RIL and F2 RIL genetic maps share one parental strain , a physical difference in marker order in one of the strains , for example by physical inversion , would not be expected to produce this genetic effect . Possible explanations for this discrepancy include multiple recombination events that accumulated in a small physical interval and resulted in inaccurate estimations of genetic positions , or unappreciated copy number variation that created genotyping artifacts . However , a similar local reversal of marker order was observed in a study describing the behavior of genetic markers associated with polymorphic inversions in Anopheles gambiae [49] . The stereotyped recombination domains for each linkage group have stimulated investigations into factors that might dictate their boundaries . Repeat density correlates with the domain structure [38] and is also associated with recombination rate differences in other species [72] . Likewise , inspection of Figure 3 suggests that many recombination domain boundaries are associated with loss of synteny . This finding suggests that local signals direct the locations of boundaries [15] . However , for both repeat content and synteny , it remains unclear whether these are causes or consequences of domain differences . The molecular basis of the distribution of meiotic crossovers is only beginning to be understood . In C . elegans , DPY-28 acts in a classical condensin I complex to regulate the number and distribution of crossover events [74] , [75] . In addition , loss of the chromatin protein XND-1 inverts the typical crossover distribution so that recombination occurs more frequently in the centers of chromosomes than in the arms [76] . Histone modifications on the arm and center domains are also distinct [77] , suggesting an interplay between nucleosomes , condensins , and recombination in Caenorhabditis . C . elegans chromosomes contain pairing centers: regions that promote homolog pairing and synapsis [78] . It has been suggested that these features might themselves have a cis effect on the distribution of recombination events , although their genetic locations in C . elegans do not perfectly correlate with recombination domain features [15] . Pairing centers might promote recombination in their vicinity , but this hypothesis cannot yet be tested in C . briggsae because no pairing centers have been characterized . Site-specific , perhaps cis-acting , segregating recombination rate modifiers , as are thought to exist in C . elegans [15] and mice [72] , might also be responsible for observed variation . This might explain why variation in the extent of arm recombination asymmetry in the F2 RIL is restricted to a subset of chromosomes ( Figure 4 ) . An earlier comparison of the C . elegans genome with C . briggsae assembly cb3 , based on the positions of orthologous genes , revealed that the vast majority of rearrangements during divergence of these species were intrachromosomal and that syntenic blocks are larger on the X than on autosomes and also larger in center domains than on arms [38] . Our comparison using the cb4 assembly ( Figure 3 ) qualitatively agrees with these previous findings . Specifically , syntenic blocks are longer in the low-recombining chromosome centers and are reduced or absent on the arms; the X chromosome exhibits the most structural similarity between the species . The relatively few off-diagonal sequence alignments ( Figure 3 ) confirm the rarity of interchromosomal gene movement . We find no evidence of large interchromosomal translocations , although sequence divergence between C . elegans and C . briggsae might have obscured some that did occur . Although the ortholog content of chromosomes is generally conserved ( Figure 3 , [38] ) , inter-arm movement has greatly eroded arm synteny between C . elegans and C . briggsae . Even the better-conserved center domains of chromosomes lack strict co-linearity . As a result , the relative orientation of the genetic and sequence maps of C . elegans and C . briggsae is basically arbitrary ( Figure 3 ) , especially for ChrII and ChrIII . The similarity of the recombination profiles of the chromosomes is therefore quite striking , reinforcing the impression that something other than gene content dictates the positions of recombination domain boundaries . The comparison of two distinct C . briggsae genetic maps allowed us to ask whether the genetic signature of inversions exists . The strongest candidate region , within the B arm of ChrIV , provides the first genetic evidence of inversions distinguishing strains of C . briggsae . In this case , we conclude that an inversion of at most 666 kbp in HK104 relative to AF16 and VT847 likely exists . Given the hundreds of presumed translocations and/or inversions evident from the C . elegans and C . briggsae comparison ( Figure 3 ) and the approximately 18 MY of divergence between the species [71] , it is reasonable that a rearrangement distinguishing strains occurred during the divergence between the temperate and tropical clades of C . briggsae . The spacing of markers common to both the AI-RIL and F2 RIL genetic maps suggests that inversions up to 1 Mbp in size would often be undetectable in our analysis ( particularly on the X chromosome ) . As in mice [72] , it is possible that inversions unique to one strain or species are responsible for some of the recombination rate variation evident within and between species . Large regions on ChrIII , ChrIV and ChrV in the AI-RIL preferentially fixed HK104 alleles to a degree not explained by sampling error alone ( Figure 2 ) , and nearly two-thirds of all AI-RIL marker genotypes are homozygous for the HK104 allele . Unintentional selection operating on hybrid genotypes during the intercross phase of RIL production is the most likely explanation for this widespread bias . In principle , selection could begin to cause MTRD as early as the F1 generation if a heterozygote-by-cross direction effect exists , but is not a factor here because there was no competition between cross directions during line production . More relevant here , selection on hybrid genotypes starting in the F2 generation would bias the transmission of parental alleles . We provide corroborating evidence for such F2 selection against AF16 alleles on ChrIII . A modest bias of ChrIII toward HK104 was also evident in AF16×HK104 F2 RIL ( Figure 5G ) [38] , presumably due to the acute developmental delay described here , but no MTRD was observed on ChrIV or ChrV . Our study should be more sensitive to incompatibilities because recombinant genotypes had substantial opportunity to compete against each other , whereas for the F2 RIL individual F2 were isolated immediately . This would be expected to allow genetic drift to dominate over all but the most severe fitness effects , such as that on ChrIII . Additionally , the AI-RIL cross scheme produced smaller haplotype blocks , perhaps separating co-adapted complexes of linked genes and creating more maladapted combinations of alleles than in F2 RIL . The difference in cross schemes might also explain the higher extinction rate of AI-RIL lines compared to the F2 RIL ( 59 of 240 vs . 1 of 112 lines ) . Selection against a subset of hybrid genotypes is commonly ascribed to the presence of Dobzhansky-Muller incompatibilities ( DMI ) that arise when loci diverge in two strains experiencing reduced gene flow between them [79]–[81] . MTRD in hybrid Caenorhabditis genomes might also occur based on physical attributes of chromosomes regardless of the genes residing in the biased regions . In C . elegans males , homologous chromosomes differing by as little as 1 kb in length can segregate with biased frequencies , with the larger homolog included preferentially into the nullo-X gamete [82] . Homolog sizes could diverge between C . briggsae strains by expansion or contraction of repetitive sequences , which comprise over 22% of the genome [37] . Additionally , C . elegans isolates exhibit extensive copy number variation [83] , suggesting that C . briggsae strains might as well . Meiotic drive can also produce MTRD [84]–[86] . However , selection against delayed development is sufficient to explain the ChrIII bias ( see below ) , and neither size-based assortment bias nor meiotic drive would explain the cross-specific MTRD observed on ChrIV and ChrV . Thus , while these phenomena might occur to some extent , we conclude that they are not a major factor in determining AI-RIL genotypes compared to selection . The F2 developmental delay phenotype associated with ChrIII ( Figure 5 ) indicates that AF16 alleles at one or more loci in the central domain are dysfunctional when homozygous in a hybrid background . Delayed animals were unlikely to have been chosen for the next generation of the AI-RIL cross scheme , and this might entirely explain the MTRD seen on ChrIII ( Figure 2 ) . The lack of extensive LD between this distorted domain and other autosomal regions ( Figure 6 ) suggests it interacts with HK104 alleles at multiple loci . Neither the delay phenotype nor MTRD on ChrIII ( Figure 5H ) were apparent during production of the VT847×AF16 F2 RIL , suggesting that the incompatibility does not exist in this cross . The phylogenetic and geographic relationships of AF16 , HK104 and VT847 match the expectation that incompatibilities are more likely to arise between more divergent strains [28] , [87] , [88] . The smaller genetic map length of ChrIII relative to other autosomes in the AI-RIL ( 148 . 6 cM vs . 164 . 5–173 . 2 cM ) might be another consequence of strong selection on ChrIII , as rapid loss of AF16 haplotypes reduces the opportunity for additional recombination events to produce detectable breakpoints . The ChrIII locus ( or loci ) responsible for the developmental delay phenotype is unlikely to be the same region of ChrIII involved in interchromosomal LD . The maximum MTRD for ChrIII occurs at roughly 5 Mbp , while the region of maximal D′ is limited to a small portion at 12 Mbp that also contains an unusual divergence of parental allele fixation between the two cross directions ( Figure 2 ) . Although all autosomal loci in the F1 founders of the AI-RIL are heterozygous AF16/HK104 , cross direction alters the source of maternal cytoplasm and ChrX allele frequencies ( Figure 1 ) . These genetic distinctions between cross directions raise the possibility that an epistatic interaction between autosomal and either X chromosome or mitochondrial genome ( mtDNA ) alleles in a hybrid might cause MTRD on that autosome in only one cross direction , as seen on ChrIV and ChrV ( Figure 2 ) . If the mitochondrial and nuclear genomes have co-evolved through compensatory changes [89] , DMIs might be revealed when two strains or species hybridize [90] . In hybrid AI-RIL , cytonuclear epistasis might cause preferential transmission of the autosome involved that originated from the parental hermaphrodite . Negative cytonuclear epistatic interactions might eventually produce reproductive isolation [91] , although it has been argued that incompatibilities will rarely lead to the formation of independent species [92] . Such a model of cytonuclear coadaptation fits the pattern of MTRD on ChrIV in AF16×HK104 AI-RIL . These lines contain HK104 mtDNA and are overrepresented for ChrIV HK104 alleles ( Figure 2 ) . ChrX could also drive this bias , but the lack of LD between ChrX and ChrIV rules out this possibility ( Figure 6 ) . A coadaptation model cannot explain the biased fixation of HK104 alleles on ChrV in the HK104×AF16 AI-RIL ( Figure 2 ) , which bear AF16 mtDNA . A plausible alternative model here is cytonuclear transgressive segregation , in which a synergistic interaction between the mtDNA of one strain and a nuclear allele of the other produces fitness greater than either parental strain [93] . Consistent with this , we again see no evidence of LD between ChrV and ChrX ( Figure 6 ) . We therefore favor cytonuclear epistatic interactions ( either coadaptive or transgressive ) as the most likely explanations for the cross direction-specific MTRD on ChrIV and ChrV . Other studies have reported similar patterns of MTRD in hybrid crosses . In Mimulus , an interpopulation cross exhibits MTRD involving multiple linkage groups [94] , and in an interspecies cross , bias against the maternal genotype is seen [95] , much like the pattern of bias on C . briggsae ChrV ( Figure 2 ) that we tentatively attribute to transgressive segregation of mitochondrial and nuclear loci . Such patterns of MTRD are often attributed to cytonuclear incompatibility ( e . g . in Nasonia wasps [96] and a moss [97] ) . Further , regions exhibiting MTRD might be expected to overlap the positions of hybrid incompatibility loci , as found in a cross between Solanum species [98] . However , it is unclear at what point ( i . e . , at what allele fraction threshold ) an interchromosomal epistatic interaction might be classified as an incompatibility . Only when two incompatible loci are tightly linked , such as in the case of the zeel/peel lethal system on C . elegans ChrI , would allele fraction values be expected to approach unity . Even in that case , the allele fraction of linked markers in C . elegans AI-RIL do not reach unity [29] . Given the limited evidence for the presence of an extreme ( i . e . lethal ) incompatibility between AF16 and HK104 , at this point we conclude only that cytonuclear epistatic interactions are responsible for the MTRD on ChrIV and ChrV . This is further supported by the significant difference between allele fraction values for the two cross directions in a block of markers on ChrV ( Figure 2 , asterisk ) . The nuclear genome encodes mitochondrial proteins , some of which interact with mitochondrion-encoded proteins involved in oxidative phosphorylation [90] , [99] . The mitochondrial genome can co-adapt both with the nuclear genome [99] and with temperature [90] , [100] , and some hybrids in other taxa suffer from decreased oxidative phosphorylation efficiency [99] , [101] . The mitochondrial genome of C . briggsae evolves rapidly [27] and is polymorphic for large deletions [102] . As this degree of mtDNA variation can impact fitness [27] , [103] , we propose that cytonuclear epistasis between AF16 and HK104 becomes evident when the mitochondrial genome is separated from co-adapted nuclear genes and/or provided nuclear alleles from a different strain . Similar incompatibilities have been discovered between many species ( e . g . [104]–[106] ) and can have complex genetic architecture [107] . Incompatibilities , cytonuclear or not , can contribute to speciation when hybrid fitness is sufficiently reduced [91] , [108] , [109] . Fecundity in Caenorhabditis can be affected by temperature [110] , and the strains employed in this study experienced substantially different temperatures in nature . Strain AF16 was isolated in Ahmadabad , India , a lowland tropical city ( 23°N latitude ) where the average annual temperature is over 30°C ( http://www . fao . org/countryprofiles/Maps/IND/07/tp/index . html ) . In contrast , HK104 was isolated in Okayama , Japan , a more temperate locale ( 34°N latitude ) with an annual mean temperature of only 14°C ( http://www . data . jma . go . jp/obd/stats/data/en/smp/index . html ) . Our AI-RIL were raised at 20°C , a temperature possibly more optimal for temperate strains [111] . Thus , the bias for HK104 alleles ( 61% of genotypes ) in the AI-RIL might reflect selection for temperature-adapted genes . Furthermore , although 120 lines in each cross direction were initiated , only 95 AF16×HK104 and 86 HK104×AF16 lines survived . Line extinction might reflect selection against hybrid genotypes specifically unsuited to 20°C . Repetition of the hybrid crosses at higher temperatures might yield different results , yet at 20°C under lab conditions , HK104 individuals produce fewer offspring over their lifetime than AF16 [110] , [112] . This suggests that a temperature-dependent effect separate from total fecundity might explain the bias of HK104 alleles in the AI-RIL . Alternatively , line extinction might be due to generalized outbreeding depression between the strains [113] . The regions of significant MTRD coincide with the central recombination domains ( Figure 2 ) and associated blocks of LD ( Figure 6 ) . Thus , selection on loci in the central domain , which will rarely be separated by recombination , can affect the population genetics of half of a chromosome [114] . While the recombination profile of Caenorhabditis chromosomes amplifies the population genetic signals of selection , the near-absence of recombination in the central domain is an obstacle to fine-scale mapping of loci under selection . The genotyped AI-RIL described here serve as a powerful new resource for the mapping of divergent phenotypes , as has been accomplished using C . elegans RIL [35] . For example , they are being used to explore the genetic architecture of temperature tolerance of AF16 and HK104 ( A . Cutter , pers . comm . ) To continue improving resources for the study of C . briggsae , future efforts should identify genetic markers on remaining unassembled sequence supercontigs in order to incorporate them into the genome assembly . Further increasing the marker density might also identify yet more misassemblies that exaggerate the apparent genomic divergence between C . briggsae and related species . More biologically , we note that the genetic structuring of C . briggsae strains by latitudinal zone [17] , [25]–[28] is not seen in C . elegans . Whether the epistatic effects described here represent maladaptive loss of local adaptations in hybrids or more generalized incompatibilities , only a few intra-species hybrid incompatibility loci have been described at the molecular level in animals ( reviewed in [108] , [109] ) . Future efforts will focus on mapping the hybrid developmental delay locus on ChrIII and testing the hypothesis that cytonuclear epistasis exists among C . briggsae strains diverged roughly 100 , 000 years [26] . It has been known for some time that some species of Caenorhabditis are cross-fertile but post-zygotically reproductively isolated [115]–[118] . The recent identification of fertile interspecies hybrids between C . briggsae and C . species 9 , which shared a common ancestor as recently as one million years ago [26] , has facilitated the study of post-zygotic reproductive isolation [119] . Thus , C . briggsae provides unique opportunities to explore different stages of reproductive isolation in the nematode phylum .
Advanced-intercross recombinant inbred lines ( AI-RIL ) were produced from the C . briggsae strains AF16 from Ahmadabad , India [33] and HK104 from Okayama , Japan ( H . Kagawa ) . Crosses between males and sperm-depleted hermaphrodites were established in both directions , and several mated ( as determined by presence of a copulatory plug ) hermaphrodite F1 produced a large F2 population . Three plugged F2 hermaphrodites ( each having mated with one or more males ) were chosen to found 120 lines from each cross direction . Generations F3–F7 were similarly founded by a population of three plugged hermaphrodites . The exact relatedness between mates thus varied , but should have been no closer than biparental full-sibs . During the F3–F7 generations , matings would have occurred between progressively more restricted genotypes , such that by F8 substantial homozygosity might have already existed . From F8–F17 , the lines were intentionally inbred by complete selfing using a single virgin ( L4 stage ) founder hermaphrodite per generation . 95 lines were produced for the AF16×HK104 cross ( male×hermaphrodite ) , and 86 for the HK104×AF16 cross . The disparity between the number of lines initiated and that produced was due to the extinction of lines . Additionally , one AF16×HK104 line was not genotyped . F2 RIL were produced from AF16 and the C . briggsae strain VT847 from Hawaii [30] . Crosses between VT847 males and sperm-depleted AF16 hermaphrodites were performed as described [38] . Eighty-nine RIL were initiated from individual F2 hermaphrodites produced by sib-mated F1 individuals , then inbred by one L4 hermaphrodite per generation through F11 . DNA was extracted from AI-RILs with a QuickGene-Mini80 using the DNA tissue kit S ( Fujifilm Corp . , Tokyo , Japan ) . The genotypes of 180 AI-RIL , 93 F2 RIL , and parental strains were obtained using the GoldenGate genotyping assay ( Illumina , [120] ) . The DNA samples were genotyped with 1 , 536 single nucleotide polymorphism ( SNP ) marker assays distinguishing AF16 from HK104 and/or VT847 [39] . These SNP markers were chosen 1 ) on the basis of their distribution on sequence supercontigs in order to genotype at least one marker on as many of the largest supercontigs as possible , and also 2 ) to maximize the number of large supercontigs containing at least two markers , so that the supercontigs could be oriented . Because the chromosomal assignment of supercontigs containing the markers was not considered during marker selection , the genome-wide distribution of genotyped SNPs was expected to reflect the true distribution of SNPs . Autosomal and X chromosome supercontig lengths were analyzed via var . test and an unpaired two-sample t test in R . Genotypes of pools of delayed F2 hybrids were determined through sequence analyses of PCR amplification products derived from Cbr-egl-5 and Cbr-mab-20 . Forward and reverse primers for Cbr-egl-5 were ( 5′ to 3′ ) CCGAGATTCAGAAAACCCGAAG and CACTACAGTAAACCCCCTCAAGACC , respectively . Forward and reverse primers for Cbr-mab-20 were TGCTCTTCGGTTGGAATGCGAC and CGGTTTTTTGGTTTGATGGTGGG , respectively . Sequencing reactions for both genes were primed with the forward primers . Raw GoldenGate assay data were analyzed with GenomeStudio 2008 ( v . 1 . 0 . 2 . 20706 ) using the genotyping module ( v . 1 . 0 . 10 , Illumina ) . The data were required to exceed the following quality control thresholds in order to be analyzed . Numbers in parentheses represent the number of samples or assays not exceeding each threshold in the AI-RIL . The 172 , 344 AI-RIL genotype calls ( Table S1 ) were imported into Map Manager QTXb20 ( v . 0 . 30 ) [121] . A genetic map for each of the six linkage groups ( five autosomes and the X chromosome ) was estimated using the following parameters: probability of incorporation into a linkage group 1×10−6 , Haldane map function , and intercross linkage evaluation . The cb3 map , produced from F2 RIL , was estimated using self-RI linkage evaluation [38] . However , this approach infers per-meiosis recombination rates from breakpoints accumulated over multiple generations , and thus reports compressed map lengths inconsistent with the number of observed recombination breakpoints in the AI- RIL . Selecting intercross evaluation , similar to the approach of selecting backcross evaluation to estimate AI-RIL maps in [15] , forces Map Manager QTXb20 to regard all breakpoints as occurring in a single meiosis . The resulting longer map lengths reflect the numbers of recombination breakpoints observed ( Table 2 ) and are thus more directly comparable to other AI-RIL maps . Map Manager QTXb20 was also used to estimate genetic maps using the 18 , 601 VT847×AF16 F2 RIL genotype calls ( Table S1 ) with the same parameters as previously used for C . briggsae F2 RIL [38] . A strategy of relaxation of the probability of incorporation was employed to incorporate five markers into the six major linkage groups , as in [38] . As was the case for the AI-RIL , it was empirically determined that the presence of 50 heterozygote genotype calls prevented robust map estimation . Therefore , these calls were considered as missing data in Map Manager QTXb20 and are reported as such ( “ ? ” ) in Table S1 . Map Manager QTXb20 reported the numbers of recombination breakpoints per linkage group used to calculate average breakpoint capture ( Table 2 ) . However , because it does not count breakpoints associated with heterozygote calls under self-RI linkage analysis , the counts were manually increased to account for breakpoints necessary to produce heterozygote genotypes . We noticed an artifact introduced when map positions were calculated using Map Manager QTXb20: map positions were offset by one marker . Exports of some linkage maps gave the genetic position of the first marker in the map as non-zero; the position of the last marker in each map was never reported , and the last marker in any block of non-recombinant markers was always reported to have a map position different from the others in that block . Defining the position of the first marker in each linkage group as 0 centimorgans ( cM ) and then shifting each subsequent map position by one marker resolved these discrepancies . This artifact might explain why some markers in the cb3 linkage maps are nonrecombinant yet flank haplotype breakpoints and differ in allele fraction: the reported genetic positions of the markers might differ slightly from their true values . The orientations of linkage maps produced in this study were compared with the cb3 maps [38] and inverted when necessary to maintain the same relative map positions of markers . Based on our new genetic maps and the locations of the SNP markers on sequence supercontigs , we first reassembled the genome from the cb25 supercontigs [37] and then compared this assembly with cb3 [38] . For a few supercontigs ( see Text S1 ) , the cb3 genetic maps contained more information than the cb4 maps . In these cases , we supplemented our data with data from cb3 . Only where our data contradicted or improved upon the cb3 assembly did we make changes . Where necessary , cb25 supercontigs were split to resolve discrepancies between the genetic and physical order of markers ( see Text S1 ) . Figure S3 depicts the decision tree employed to resolve these discrepancies; the genetic and physical map data used to select locations at which to split supercontigs to resolve certain discrepancies are provided in Table S3 . Genome assembly version cb4 is available at http://www . wormbase . org . Each tip domain ( two per chromosome ) comprises the sequence between a chromosomal assembly terminus and the most internal genetic marker in the terminal block of non-recombinant markers . By definition , these domains have a recombination rate of zero . For the AI-RIL , the boundaries of the arm-center recombination domains were identified by segmented linear regression for each linkage group as in [15] using the “segmented” package implemented in R [122] . The genetic map positions of recombination domain boundaries were estimated for the AI-RIL by linear interpolation from the two markers flanking each boundary . The lower marker density in the F2 RIL genotype data set reduced confidence in the accuracy of boundaries estimated by segmented linear regression , so we imposed the physical positions of domain boundary estimates from the AI-RIL onto the F2 RIL genetic maps and estimated the genetic length of each domain as above . The recombination rates for C . elegans domains reported in Table 3 differ from those previously reported [15] , which were rate estimates based on the slopes of segmented linear regression . Here , we calculated C . elegans domain genetic lengths , as above , from the interpolated genetic positions of domain boundaries ( kindly provided by M . Rockman , unpublished; Table 3 ) . To facilitate comparison between maps , we used a unique correction factor for each linkage group to normalize the sum of estimated genetic lengths of the three domains to 50 cM , the expected per-meiosis length under selfing . C . elegans ( release ws185 , the assembly version used to define recombination domain boundaries in [15] ) and C . briggsae ( cb4 ) genome sequences were first masked using RepeatMasker 3 . 2 . 9 with default parameters and the June 4 , 2009 RepBase repeat libraries [123] . The masked sequences were then compared with MUMmer 3 . 22 [124] using nucmer to identify only maximal unique matches . We compared the observed number of AI-RIL fixed for the HK104 allele to the expectation of 50% with a Bonferroni-corrected chi-square test . Because linked markers are not truly independent tests , the effective number of independent tests was estimated as follows: The autocorrelation parameter at lag = 1 was estimated for the allele fraction data within each recombination domain for each cross direction using the acf ( ) function in the base package of R . The value of the autocorrelation parameter was then used to estimate the effective number of tests [125]–[127] . The significance threshold p = 0 . 05 was then Bonferroni-corrected by the genome-wide sum of effective number of tests for each cross direction and used to calculate the allele fraction value , plotted in Figure 2 , at which a marker would reach genome-wide significance for deviation from the expected value . To test for epistasis between cross direction and the ChrIV or ChrV center domain markers , the allele fraction values for both cross directions were compared using Fisher's exact test in R . The significance threshold p = 0 . 05 was then Bonferroni-corrected by the sum of the largest effective number of tests estimated above for the two center domains for both cross directions . After identifying the relative genetic order of markers , the genotype data from each AI-RIL cross direction were imported separately into Haploview v . 4 . 2 [128] . With the Hardy-Weinberg p-value cutoff set at 0 , intra- and inter-chromosomal linkage disequilibrium D′ values were plotted using the Standard color scheme ( Figure 6 ) . One pair of markers exhibiting D′> = 0 . 8 from each block of markers in interchromosomal LD was selected to test for significance using the chi-square test . Expected counts of AI-RIL fixed for the same parental allele at two loci were calculated according to the parental allele frequencies at each locus for each cross direction .
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The nematode Caenorhabditis briggsae is increasingly used for comparisons with its more famous relative , C . elegans . To improve genomic resources for C . briggsae , we created two sets of inbred lines derived from crosses between diverged C . briggsae strains . High-throughput genotyping of these has improved the resolution of the recombination map and genome assembly . It also allows detailed comparisons of recombination both within and between species . Unexpectedly , we found that alleles from one parental strain were much more likely to be fixed on three of the six chromosomes in one of the sets of lines . One of these biases is caused by a pronounced developmental delay in F2 progeny that is seen in both reciprocal crosses , whereas the other two manifest in only one of the two cross directions . This indicates that the parental strains have diverged in both nuclear and nuclear-cytoplasmic interactions , either because of local adaptation or restricted gene flow across much of the genome .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"genetics",
"biology",
"genomics",
"evolutionary",
"biology",
"population",
"biology",
"genetics",
"and",
"genomics"
] |
2011
|
Caenorhabditis briggsae Recombinant Inbred Line Genotypes Reveal Inter-Strain Incompatibility and the Evolution of Recombination
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Public health interventions based on distribution of anthelminthic drugs against lymphatic filariasis ( LF ) , onchocerciasis , soil-transmitted helminthiasis ( STH ) and schistosomiasis have been implemented separately to date . A better use of available resources might be facilitated by a more coordinated approach to control such infections , including the possibility of co-administering the three recommended anthelminthic drugs through a single , large-scale intervention . Ivermectin , albendazole and praziquantel were co-administered to 5 , 055 children and adults living in areas endemic for LF , STH and schistosomiasis in Zanzibar , United Republic of Tanzania , during a pilot intervention aimed at elucidating and quantifying possible side-effects . Subsequently , these drugs were co-administered to about 700 , 000 individuals during a countrywide intervention targeting a large part of the total population of Zanzibar . Passive and active surveillance measures carried out during both interventions showed that side-effects attributable to the three drugs given at the same time were mild and self-limiting events . Our data suggest that co-administration of ivermectin , albendazole and praziquantel is safe in areas where lymphatic filariasis , soil-transmitted helminthiasis and schistosomiasis are co-endemic and where several rounds of treatment with one or two drugs have been implemented in the past . Passive surveillance measures , however , should be continued and detection , management and reporting of possible side-effects should be considered a key component of any health intervention administering drugs .
Zanzibar comprises 2 main islands , Unguja and Pemba , with a population of around 1 . 2 million . LF , caused by Wuchereria bancrofti , and STH and schistosomiasis are considered major public health problems by the Zanzibar Ministry of Health and Social Welfare ( MoHSW ) . Transmission of W . bancrofti occurs in both Unguja and Pemba [17] . Such an epidemiological situation justifies the inclusion of both islands among the areas eligible for mass drug administration ( MDA ) with ivermectin and albendazole at yearly intervals . Data show that the whole archipelago is also at high risk for STH; with the exception of a limited area on Unguja where the infection is not transmitted , it is also at high risk for urinary schistosomiasis caused by Schistosoma haematobium ( MoHSW unpublished data , [18]–[21] ) . Control of schistosomiasis and STH through large-scale preventive chemotherapy interventions distributing praziquantel and albendazole started in 1994 . Schools represented the main delivery channel and schoolchildren the main target population , however , occasionally whole communities have been also targeted for treatment . This strategy is still on-going with a period of interruption of two years ( 2000 and 2001 ) during which activities did not take place due to problems in securing the drugs . There has been a reduction in prevalence and intensity of both schistosome and STH infections over the years ( MoHSW unpublished data ) , however such indicators suggest that continuation of treatment of schoolchildren is still required . The last school-based drug distribution before the implementation of the activities described in this survey was carried out in May 2006 . In 2001 Zanzibar adopted the WHO recommended strategy against LF , consisting of MDA for elimination as a public health problem , coupled with disability prevention and management . MDA in Zanzibar involves administering a once-yearly dose of a combination of ivermectin ( Mectizan , 200 µg/kg ) and albendazole ( 400 mg ) to its entire population , with the exception of those who are sick or infirm , of children <90 cm in height , of pregnant women , and of lactating women in the first week after birth . The last round before the implementation of the activities described in this article was conducted in August 2005 ( 5th round of MDA ) [17] . W . bancrofti was highly endemic in both Unguja and Pemba before MDAs , with a prevalence of microfilaraemia in all age groups ( children and adults ) ranging between 5% and 30% [17] . Whilst the evaluation of the impact of MDAs showed an overall decline in both prevalence and intensity of microfilaraemia , mean prevalence of infection in all age groups ( adults and children ) at one sentinel and in some randomly selected spot-check sites after the 5th round was still 1% and above . The MoHSW therefore decided to implement a further round ( 6th ) of MDA . This follows the WHO recommended processes leading to decision to stop MDA only after interruption of transmission ( prevalence of microfilaraemia <1% in the general population ) [22] . The 6th round of MDA for LF offered the opportunity to evaluate the feasibility and safety of triple drug co-administration with ivermectin , albendazole and praziquantel in communities where LF , STH and schistosomiasis are co-endemic . Ivermectin , albendazole and praziquantel are well suited for large-scale distribution in helminth control or elimination when administered individually or in double combination ( ivermectin and albendazole or albendazole and praziquantel ) at the recommended dosages ( ivermectin 200 µg/kg; albendazole 400 mg; praziquantel 40 mg/kg ) . Combination of ivermectin and albendazole is highly efficacious after a single administration for LF , and treatment rarely results in side-effects outside those commonly associated with a therapeutic effect [23] . Similarly , co-administration of praziquantel and albendazole is an efficacious and safe tool to control morbidity due to schistosomiasis and STH in areas where both infections are endemic [24] . However , side-effects do sometimes occur following administration of anthelminthic drugs , primarily as a result of the individual's immune inflammatory response to dying parasites; the greater the infection load in the patient , the greater are the frequency and severity of such reactions . These can include systemic responses ( e . . g . headache , myalgia , light-headedness , anorexia , malaise , nausea , vomiting and wheezing , abdominal discomfort , dizziness , drowsiness , rectal bleeding ) ; or , less commonly , localized reactions ( including lymphadenitis , funiculitis , epididymitis , lymphangitis and even abscess formation ) ; rarely , in case of administration of praziquantel for schistosomiasis , hypersensitivity reactions , fever , pruritus and eosinophilia may occur . Only seldom ( in heavily infected individuals ) are these post-treatment reactions severe or do they require more than just symptomatic treatment [25] . Triple co-administration of ivermectin , albendazole and praziquantel has never been carried out in large-scale interventions , however , pharmacokinetic studies performed in healthy ( i . e . non-infected ) individuals indicate that there are no pharmacological interactions between the three drugs and that triple co-administration does not enhance their toxicity [26] . However , because of the lack of documentation on such triple co-administration in real epidemiological scenarios , and considering that in those settings some of the individuals receiving drugs may carry high burden of multiple parasites , it is recommended that triple co-administration is carried out with caution and with adequate monitoring of potential side-effects [1] . As a first step it is advisable that in a population that has never been subjected to MDA with any of these drugs , the initial 1–2 rounds of treatment with praziquantel should be given separately from ivermectin and/or albendazole treatment; additionally , in a population that has previously been subjected to ( separate ) MDA with either ivermectin plus praziquantel or ivermectin+albendazole plus praziquantel , the three drugs should be co-administered in conjunction with additional safety monitoring for any unanticipated side-effects during the initial rounds . Since in Zanzibar separate MDAs had already been conducted in the past , it was decided to implement co-administration of the three drugs with the requisite precautionary measures . Before co-administering the drugs to the entire eligible Zanzibar population of around 1 million , it was therefore considered imperative that such intervention take place in a pilot population and that active and passive surveillance measures be implemented during and after treatment . Results of the pilot intervention were considered crucial to the initiation of a country-wide intervention . It was agreed that if side effects during the pilot intervention were mild and transitory , co-administration would take place throughout Zanzibar and that active and passive surveillance measures would be also implemented during such a country-wide interventions . The aim of the present paper is to report on the outcome of passive and active surveillance measures carried out to elucidate and quantify any side-effects experienced after co-administration of ivermectin , albendazole and praziquantel by a sample population of 5 , 055 and subsequently by about 700 , 000 individuals living in areas endemic for LF , STH and schistosomiasis in Zanzibar .
The pilot intervention was conducted in 2 highly endemic sites , one from each of the two islands forming Zanzibar: Kinyasini on Unguja ( resident population of approximately 4 , 000 ) and Mtambile on Pemba ( resident population of approximately 3 , 000 ) . Field assessments conducted in all age-groups before the survey in early November 2006 showed that at Kinyasini prevalence of LF antigenaemiaia ( assessed by an ImmunoChromatographic Test ICT ) [27] ) was 4 . 0% , of urinary schistosomiasis ( assessed by urine filtration ) was 63 . 5% and of STH infections ( assessed by Kato-Katz method ) [28] was 76 . 8%; at Mtambile , these figures were 13 . 0% , 43 . 0% and 73 . 0% , respectively ( MoHSW unpublished data ) . The major occupations of the community in both sites are linked to agriculture [29] . Both sites are surrounded by permanent water bodies . The whole population of both Kinyasini and Mtambile was considered for enrolment in the pilot intervention . Criteria for enrolment coincided with criteria for eligibility for administration of ivermectin and albendazole in LF disease-specific interventions , which are the most restrictive among the criteria used in interventions against one of the three diseases ( LF , STH , and schistosomiasis ) taken singularly . As such , we considered eligible all consenting residents of both sites , with the exception of those who were sick or infirm , of children <90 cm in height , of pregnant women , and of lactating women in the first week after birth . All consenting participants ( written and oral ) were interviewed in order to determine their health status before the intervention , and all their information were recorded . All participants in the study were given their respective dosages of ivermectin ( 200 µg/kg ) , albendazole ( 400 mg ) and praziquantel ( 40 mg/kg ) at the same time; treatment was directly observed by drug distributors to ensure that tablets were actually swallowed . The dosage for ivermectin and praziquantel was calculated using a two-sided tablet ( height ) pole that was the combination of the two poles currently used for separate administration of such drugs [1] , [30]–[32]: one side for determination of the number of ivermectin tablets and the other side for the number of praziquantel tablets . The two sides were clearly made distinguishable by the presence of the Kiswahili ( local language ) text “kichocho” ( schistosomiasis ) on one side and “matende” ( elephantiasis , LF ) on the other . One tablet of albendazole ( 400 mg ) was used as the standard dose for everybody irrespective of age or height [1] . Theoretical and practical training sessions were held during the weeks preceding the intervention so as to train drug distributors - who were familiar with single-drug poles - on the use of the two-sided poles and on the shape and strength of each drug administered , so as to avoid any risk of miscalculation of the dose of ivermectin and praziquantel to be administered . The strategy of drug distribution and the individuals responsible for drug distribution were the same used in those two sites during previous interventions of MDA with ivermectin and albendazole for elimination of LF . The pilot intervention took place on 18 November at Kinyasini 2006 and on 19 November 2006 at Mtambile . Both passive and active surveillance measures were implemented during the pilot intervention . Passive measures were aimed at ensuring rapid medical assistance for any individuals who might experience side-effects after treatment , while active measures were in place to elucidate the nature of and quantify any such event . Passive measures were established on the treatment day and the day after; two health centres at Kinyasini and two at Mtambile were kept open round the clock and equipped with first-line emergency drugs ( non-steroid anti-inflammatory drugs , anti-histaminic drugs , cortisone , intravenous fluids ) . Individuals who received drugs were invited to report to these first-line centres in the event of any side-effects ( “anything abnormal occurring in your body” ) , health centre personnel were trained on how to fill in the record forms and instructed to refer to second-line hospitals any individual presenting with side effects that they could not manage . In addition , vehicles/motor bikes patrolled the area to facilitate a rapid response should it be needed . Active surveillance measures were also carried out between the 5th and the 7th day after treatment . All treated individuals were interviewed on occurrence of side-effects by experienced professional health staff and/or researchers who had participated in previous health survey studies done in the country and who were not resident either in Kinyasini or Mtambile . The occurrence of any side-effects following the ingestion of the three drugs was investigated . A side-effect was defined as any abnormal event experienced by a treated individual within period of observation . A structured questionnaire listing the most common symptoms and signs usually reported after administration of anthelminthic drugs was used to record events , but these events were not read to the interviewee who was asked the following question: “How have you been feeling since taking the treatment ? ” and left free to answer and to grade the possible event as mild , moderate or severe . For standardization of the approach to be used when administering the questionnaires , health staff/ researchers received one day training , on how to ask the questions and fill up the form . The protocol of the pilot intervention was reviewed and approved by the Ethical Committee of the Liverpool School of Tropical Medicine , United Kingdom , and by the MoHSW , Zanzibar . All individuals participating in the pilot intervention or their parent/guardian in case of children provided a written informed consent to treatment . All records are available for scrutiny in the MoHSW , Zanzibar . The procedure regarding the administration of questionnaires to designated interviewees was the same for the pilot project and the nationwide intervention . The individuals gave consent prior to being interviewed for adverse events . It is the policy of the MOHSW to obtain consent from involved communities or involved individuals before carrying out activities in the field .
A total of 5 , 055 individuals of both sexes aged 5 years and above , participated in the pilot intervention: 2 , 509 from Kinyasini and 2 , 546 from Mtambile . The age-group 10–19 years old was the most represented , in line with current demographic trends in Tanzania and most developing countries [27] . The number of females was higher than that of males ( Table 1 , Figure 1 ) . This can be mainly explained by the fact that both Kinyasini and Mtambile are rural areas where young males are either farmers or have employment in town . Hence , they usually leave their houses early in the morning and return back late in the evening . Only 1 treated individual reported to a first-line health centre ( in Kinyasini ) complaining about vomiting that started following treatment; symptoms were , however , mild and successfully managed on spot without requiring referral to a second-line hospital facility . The results of the interviews carried between day 5 and 7 post triple drug administration are shown in Table 2 . Overall , a total of 615 events were reported by 504 individuals , i . e . by approximately 10% ( 504/5055 ) of those treated . Occurrence of side-effects was the same ( 10% ) in different sexes and peaked in the age-group 30–39 ( Table 2 ) . 87 . 3% of symptoms occurred within 24 hours of treatment , while a few were also reported to have occurred on the second ( 11 . 9% ) and on the third day ( 0 . 8% ) . The symptom most frequently reported was dizziness ( Table 3 ) . All symptoms were reported to be mild and subsided within a period of 24 hours after onset . As active surveillance for side-effects during the pilot intervention did not indicate any concern , two weeks after co-administration of the three drugs had taken place in Kinyasini and Mtambile , on December 2–3 , 2006 , the first large-scale triple drug co-administration was carried out in Zanzibar . This intervention was conducted under the newly established “Lymphatic Filariasis , Schistosomiasis and Soil-Transmitted Helminthiasis Integrated Programme” of the MoHSW . Every eligible individual in Zanzibar was targeted to receive the three drugs at the same time with the exception of those living in areas without transmission of schistosomiasis where only ivermectin and albendazole were administered . Such areas are restricted to Unguja island and include the whole Urban district of Stone Town , the whole South district , and some communities ( shehias ) in the North A district [18]–[20] . The same criteria for eligibility and ineligibility were applied as in the pilot intervention . Overall , about 700 , 000 individuals were administered three drugs ( ivermectin , albendazole and praziquantel ) and another 300 , 000 two drugs ( ivermectin and albendazole ) . As in the pilot intervention , the door-to-door strategy was chosen as the method of drug administration . For effective coverage , 4 , 161 drug distributors , used in previous LF-MDA interventions , were deployed and given extra training on how to use the two–sided drug pole in determining number of tablets . Each drug distributor was responsible for 50 households . All drug distributors were previously identified through a community-based participatory process , so as to guarantee their full acceptance by populations targeted . Many of them were health personnel or school teachers . Zanzibar was divided into 14 MDA operational units – 9 of the units followed the administrative divisions ( districts ) ; 3 were the result of subdividing the urban districts into more manageable units; and the remaining 2 units targeted special groups within special institutions ( SI ) ( soldiers , policemen , prisoners , etc . ) . The social mobilization component was given high priority in the campaign . Three important areas were emphasized: Similar to what had happened for the pilot intervention , both passive and active surveillance measures were taken during and after the country-wide drug administration . Passive surveillance was established during the intervention through the network of health centres and referral hospitals in both islands to monitor and respond to potential side-effects . One week after the drug distribution , active surveillance measures were carried out to quantify the occurrence of side-effects in a sub-sample of the target population; the activity was incorporated into the routine survey intended to assess and check drug coverage . 35 communities ( shehias ) out of the 250 that form Zanzibar were randomly selected ( 20 in Unguja and 15 in Pemba ) , and 600–1000 people per site were interviewed , for a total of 19 , 043 individuals . A researcher was randomly assigned to each of the 35 evaluation sites and entered houses following a random route in their area . The same questionnaire as in the pilot intervention was used , and each individual visited was interviewed to check drug intake and investigate side-effects experienced .
Overall , only 266 individuals , equivalent to 1 . 4% of the interviewees who swallowed the drugs reported any side-effects , none of which was judged to be significant enough to justify a visit to the nearest health centre . All the side-effects were mild , the most frequent being fatigue ( n = 102 ) , abdominal pain ( n = 67 ) , dizziness ( n = 57 ) , fever ( n = 27 ) and vomiting ( n = 13 ) . These side-effects were accepted and managed by those who reported them . They were transient and all counted for less than 24 hours . No difference in nature and frequency of side-effects was documented during the country-wide intervention between areas where ivermectin and albendazole only were distributed and areas where praziquantel was also added to the package .
The results of the pilot intervention in Kinyasini and Mtambile were considered representative of the worst possible epidemiological scenarios in Zanzibar and as such were deemed sufficient to justify the implementation of the first nationwide intervention , in which ivermectin and albendazole currently recommended for elimination of LF and praziquantel for control of schistosomiasis were administered at the same time . The first national scale triple therapy carried out in Africa or indeed globally . Passive and active surveillance measures implemented during both the pilot and the country-wide intervention showed that side-effects experienced by individuals co-administered with the three drugs were mild and self-limiting events . It was not possible or feasible to obtain individual data on parasitological status hence this data does not allow us to establish a clear relationship between infection status and side-effects experienced . However , we believe that our data show that triple drug co-administration is a feasible option in real epidemiological scenarios such as those exemplified by Kinyasini and Mtambile , where pre-intervention prevalence rates for schistosomiasis and STH infections were high and where W . bancrofti micrfilaria prevalence remained above the 1% cut off point for MDA [17] . The studies using the ICT cards to measure antigenaemia have limited value at this stage of an LF programme as they only measure the presecnec of adult worm antigen . Their use and value in post MDA evaluation is in measuring the transmission to children born since the first MDA commenced . The proportion of individuals reporting any side-effects in the pilot intervention phase ( 10% ) is higher than that in the nationwide intervention phase ( 1 . 4% ) . This can be explained by the fact that Kinyasini and Mtambile are both sites with particularly high prevalence of helminthic infections , while the nationwide intervention also covered areas with lower prevalence . The two sites were specifically selected in order to assess the occurrence of side-effects in places where they are expected to be most frequent and most severe , so as to use the results of the pilot intervention as indicators and make a judgment before the implementation of the nationwide intervention . It is also possible , however , that the sensitivity of the surveillance system during the pilot intervention was higher than during the nationwide intervention: individuals responsible for surveillance during the pilot intervention - which had a research-like outlook - might have paid more attention to recording side-effects . Overall , both in the pilot and the nationwide intervention , the number of individuals reporting side-effects following treatment registered a significant decline from that reported for distribution of ivermectin and albendazole only by 2002 ( 24% ) [33] , which could be explained by considering that the average wormload in infected individuals in 2002 may have been higher due to the fact that only two rounds of LF treatment had taken place , and in the two previous years ( 2000 and 2001 ) the second yearly round of albendazole for STH had not been implemented due to shortage of drugs . Data from such a large population under study in Zanzibar therefore suggests that co-administration of the three drugs is a safe intervention when carried out in an area where LF , STH and schistosomiasis are co-endemic and where several rounds of treatment with one or two drugs have been implemented in the past . However , it is necessary to emphasize the need for maintaining passive surveillance measures during similar interventions , and to ensure that detection , management and reporting of potential side-effects are a key component of any health intervention administering drugs [34] . There are opportunities arising from a coordinated approach to tackle multiple tropical diseases simultaneously . Currently many control/elimination programmes in Africa are constrained not by drug availability but by lack of the financial resources necessary for drug distribution , and it is expected that distribution costs will be lower when drugs are co-administered than in the case when several “vertical” interventions are conducted separately [35]–[38] . Meeting distribution costs would mean being able to implement control activities , since ivermectin and albendazole for LF elimination are donated . Praziquantel is not at presented donated on adequate scale to cover all the current needs . In countries where there is a significant overlap between LF , STH and schistosomiasis [1] , triple drug co-administration can be an option to cut down costs , boost control activities and improve the health status of neglected populations . Co-administration of anthelminthic drugs also offers an opportunity for integration of parasitic disease control programmes into the regular health system activities in Africa and elsewhere which has an appeal for most partners or donors . These interventions provide many benefits beyond purely disease elimination or control as they are relevant to the millennium development goals . MDA is a pro- poor non – discriminatory , and hence equitable intervention which reaches all eligible people irrespective of socio-economic status . This paper demonstrates co – administration of three highly efficacious antihelminthic drugs can be achieved at scale with very limited but acceptable side-effects . This work will pave the way for the next stage of studies in more intensely infected populations . This result will permit further expansion of the WHO policy of preventive chemotherapy [1] to needy populations for the control of neglected tropical diseases in sub Saharan Africa where extensive co-endemicity is the norm rather than the exception .
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This paper describes how the use of three drugs which are used separately in mass drug distribution programmes when given together appear safe for use in large populations which have been previously treated with the same drugs separately ( Mectizan [ivermectin] , albendazole and praziquantel ) . The target diseases—lymphatic filariasis , soil-transmitted worms and schistosomiasis—were prevalent in Zanzibar up to 2000 but have been largely controlled by mass drug administration . The Ministry of Health and Social Welfare , with the support of WHO , initiated a small scale trial in a population of triple therapy in over 5 , 000 people initially in two sites , and having found there were no severe adverse events associated with the combined treatment then upscaled to treat the whole of the eligible population of over 700 , 000 . Similarly , there were no severe adverse events . This is the first time the three drugs have been used together at the same time at scale in Africa and provide a basis for expansion of integrated preventive chemotherapy of helminths ( worms ) . The next steps need to be initiated in populations which have heavier worm loads and such interventions need to be subject to close monitoring and ethical review .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Results",
"Discussion"
] |
[] |
2008
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Triple Co-Administration of Ivermectin, Albendazole and Praziquantel in Zanzibar: A Safety Study
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Heat stress commonly leads to inhibition of photosynthesis in higher plants . The transcriptional induction of heat stress-responsive genes represents the first line of inducible defense against imbalances in cellular homeostasis . Although heat stress transcription factor HsfA2 and its downstream target genes are well studied , the regulatory mechanisms by which HsfA2 is activated in response to heat stress remain elusive . Here , we show that chloroplast ribosomal protein S1 ( RPS1 ) is a heat-responsive protein and functions in protein biosynthesis in chloroplast . Knockdown of RPS1 expression in the rps1 mutant nearly eliminates the heat stress-activated expression of HsfA2 and its target genes , leading to a considerable loss of heat tolerance . We further confirm the relationship existed between the downregulation of RPS1 expression and the loss of heat tolerance by generating RNA interference-transgenic lines of RPS1 . Consistent with the notion that the inhibited activation of HsfA2 in response to heat stress in the rps1 mutant causes heat-susceptibility , we further demonstrate that overexpression of HsfA2 with a viral promoter leads to constitutive expressions of its target genes in the rps1 mutant , which is sufficient to reestablish lost heat tolerance and recovers heat-susceptible thylakoid stability to wild-type levels . Our findings reveal a heat-responsive retrograde pathway in which chloroplast translation capacity is a critical factor in heat-responsive activation of HsfA2 and its target genes required for cellular homeostasis under heat stress . Thus , RPS1 is an essential yet previously unknown determinant involved in retrograde activation of heat stress responses in higher plants .
It is generally accepted that a temperature upshift , usually 10–15°C above an optimum temperature for growth , is considered as heat stress for leaf photosynthesis in higher plants [1] , [2] . Photosystem II ( PSII ) is the most heat sensitive apparatus within the chloroplast thylakoid membrane protein complexes involved in photosynthetic electron transfer and ATP synthesis [1]–[5] . Chlorophyll fluorescence , the ratio of variable fluorescence to maximum fluorescence ( Fv/Fm ) and the base fluorescence ( Fo ) are used as common indicators of heat stress-induced damages that have been shown to correlate with alterations of photochemical reactions in thylakoid lamellae of chloroplast [1] , [2] , [6] , [7] . Oxygen evolving complex ( OEC ) in PSII is highly thermolabile and heat stress may cause the dissociation of OEC , resulting in an imbalance in the electron flow from OEC toward the acceptor side of PSII in the direction of PSI reaction center [1]–[3] , [8] , [9] . Studies on spinach thylakoids subjected to heat stress have shown that heat stress causes cleavage of the reaction center-binding protein D1 of PSII and induces dissociation of a manganese ( Mn ) -stabilizing 33-kDa proteins from PSII reaction center complex [10] . Besides the disruption of OEC in PSII , heat stress also leads to dysfunction in the system of carbon assimilation metabolism in the stroma of chloroplast [5] . The rate of ribulose-1 , 5-bisphosphate ( RuBP ) regeneration is limited by the disruption of electron transport and inactivation of the oxygen evolving enzymes of PSII [7] , [11] . It is known that under heat stress , the decline in ribulose-1 , 5-bisphosphate carboxylase/oxygenase ( Rubisco ) activity is mainly due to inactivation of Rubisco activase that is extremely sensitive to elevated temperatures because the enzyme Rubisco of higher plants is heat stable [5] , [11] . In addition to the early effects on photochemical reactions and carbon assimilation , heat stress usually leads to alterations in the microscopic ultrastructures of chloroplast and the integrity of thylakoid membranes , including membrane destacking and reorganization [2] , [12]–[15] . Because temperature elevations represent a fundamental challenge to all sessile organisms , higher plants are capable of a variety of heat shock responses characterized by a rapid expression reprogramming of a set of proteins known as heat shock proteins ( HSPs ) [16] , [17] . Analysis of Arabidopsis genome-wide expression profiles to heat stress has shown that the transcripts of the well-characterized HSPs increased dramatically , including Hsp101 , Hsp70s and small HSPs , which are proposed to act as molecular chaperones in protein quality control under heat stress [18]–[23] . In addition to classical heat stress responsive genes , these studies have also revealed the involvement of factors in heat tolerance , including members of the dehydration-responsive element-binding transcription factor 2 ( DREB2 ) family of transcription factors , GALACTINOL SYNTHASE 1 ( GolS1 ) in the raffinose oligosaccharide ( RFO ) pathway , and ASCORBATE PERROXIDASE2 ( APX2 ) [18]–[27] . The accumulation of HSPs is assumed to counteract the detrimental effects of protein misfolding and aggregation that result from heat stress [28] , [29] . Genetic analyses demonstrate that Hsp101 is required for heat tolerance , functioning in cooperation with the small HSPs to resolubilize protein aggregates after heat stress in higher plants [30] , [31] . Small HSPs may function as membrane stabilizers and possibly as site-specific antioxidants to protect thylakoid membranes against heat stress [2] , [32] . Several small HSPs have been reported to protect thylakoid stability from heat or oxidative stresses in photosynthetic organisms such as higher plants [33]–[35] and cyanobacteria [36] , [37] . Expression of HSP genes is orchestrated mainly at the transcriptional level by heat shock transcription factors ( HSFs ) that recognize cis-elements ( heat shock elements; HSEs ) conserved in HSP gene promoters [16] , [17] . HSFs play a central role in heat shock response in many species . In contrast to Drosophila , Caenorhabditis elegans and yeast that have a single HSF , the Arabidopsis genome contains 21 HSFs that are assigned to 3 classes , A , B and C , based on the structural features of their oligomerization domains [38] . At least 23 and 18 HSF genes were identified in rice ( Oryza sativa ) and tomato ( Lycopersicon esculentum ) , respectively [39] , [40] . In comparison with class A HSFs , the members of class B lack the structural motif ( aromatic , hydrophobic and acidic amino acids ) present in the C-terminal domain crucial for the activator activity of class A HSFs [41] . In agreement with the structural difference between class A and B HSFs , the transient overexpression of several class B HSFs failed to activate heat shock responsive promoters in tobacco protoplasts [42] , [43] , indicating that certain class B HSFs may function as coactivators to enhance transcriptional levels of house-keeping genes during heat stress . Recently , consistent with having repressive activities [44] , Arabidopsis HsfB1 and HsfB2b were reported to act as repressors that negatively regulate the expression of HSFs , including HsfA2 , in response to heat stress , indicating that these two B class members may interact with class A HSFs in regulating the shut-off of the heat shock response [45] , [46] . As one of the most intensely studied HSFs , HsfA2 is considered as a key regulator of heat tolerance in tomato [41] , [47] , [48] and Arabidopsis [21] , [49] , [50] owing to its high activator potential for transcription of HSP genes and its continued accumulation during repeated cycles of heat stress and recovery [17] . In tomato , HsfA1a , a constitutively expressed HSF , regulates the transcriptional activation of HsfA2 and HsfB1 in response to heat stress , indicating that these three HSFs seem to form a regulatory network to regulate the expression of down-stream heat shock-responsive genes [40] , [51] . In contrast to tomato , Arabidopsis HsfA2 as a transcriptional activator can localize to the nucleus and is regulated by a complex “master switch” containing HsfA1a-e [52]–[54] . Interestingly , Arabidopsis ROF1 ( AtFKBP62 , a peptidyl prolyl cis/trans isomerase ) also modulates thermotolerance by interacting with HSP90 . 1 and affecting the accumulation of HsfA2-regulated sHSPs [55] . The major target genes regulated by HsfA2 in Arabidopsis have been identified by analyzing HsfA2 knockout mutant and overexpression transgenic plants [21] , [49] . These target genes encode APX2 , GolS1 , several small Hsps and individual isoforms of the Hsp70 and Hsp101 families . In addition to the induction by heat stress , the expression levels of HsfA2 were also up-regulated in response to high light and H2O2 [49] . Interestingly , a recent report has shown that sumoylation of HsfA2 by the small ubiquitin-like modifier protein ( SUMO ) regulates its activity in connection with heat stress response and heat tolerance in Arabidopsis [56] . Although the accumulating literatures on the functions of HSPs and HSFs have substantially extended our understanding of heat stress response in plants , its regulatory network is far from completely understood . In this study , we have identified chloroplast ribosomal protein S1 ( RPS1 ) as a heat-responsive protein through proteomic screening of heat-responsive proteins . In Escherichia coli , RPS1 , the largest ribosomal protein , is involved in the process of mRNA recognition and binding by the 30S ribosomal subunit to the translation initiation site [57]–[59] . The RPS1 in E . coli consists of six repetitions of a conserved structural domain , called S1 domain , which is found in many other proteins involved in RNA metabolism in all organisms [57] , [58] . In bacteria , RPS1 is believed to facilitate the binding of the 30S small ribosomal subunit near the initiation codon of the transcripts [59] , [60] . A homologue of the bacterial S1 protein was found in spinach chloroplast [61] , [62] , cyanobacteria [63] and Chlamydomonas reinhardtii [64] , [65] . With the identification of RPS1 as a heat-responsive protein , we have further demonstrated that knockdown of RPS1 expression leads to inhibition of transcriptional activation of HsfA2 and its target genes in the rps1 mutant , which confers a heat-sensitive phenotype . Furthermore , our findings support that the capacity of plastid protein translation is critical for retrograde activation of HsfA2-dependent heat tolerance pathway . Our findings shed new light on the mechanisms whereby plant cells modulate nuclear gene expression to keep accordance with the current status of chloroplasts in response to heat stress .
The objective of this study was the identification of novel genes and pathways that contributed to the regulatory networks involved in the development of heat tolerance in Arabidopsis . During our initial studies , we were particularly interested in the responsive proteins that are predicted to be targeted to chloroplast since photosynthesis housed in chloroplast is extremely sensitive to heat stress [1] , [2] . To uncover how plant cells modulate protein expression in response to heat stress , we performed a proteomic screen for heat-responsive proteins . One heat-responsive protein was identified as the chloroplast RPS1 ( Figure 1A , 1B , Figures S1 and S2 ) , equivalent to the plastid ribosomal protein S1 orthologues CS1 in spinach [61] , [62] and CreS1 in C . reinhardtii [65] ( Figure S3 ) , which have been reported to specifically bind chloroplast mRNA during translation initiation . Western blot analysis further confirmed that the protein levels of RPS1 gradually increased to peak at 2 h after heat treatment , indicating that RPS1 is a heat-inducible protein ( Figure 1C and Figure S4 ) . Interestingly , RPS1 responded to heat stress at protein level , but not at transcriptional level since the expression levels of RPS1 slightly decreased during 2-h heat treatment ( Figure S4 ) , suggesting that RPS1 may not be identified as a heat-responsive protein through the analysis of heat-responsive transcriptome because the correlation between mRNA and protein levels is not sufficient to predict protein expression levels from the quantitative mRNA data [66] , [67] . Given that RPS1 was induced by heat ( Figure 1A–1C and Figure S4 ) and its highly conserved orthologues are involved in the direct control of chloroplast gene expression , we reasoned that RPS1 might act as a retrograde communication coordinator to trigger nuclear gene expression critical for heat tolerance . We first examined whether RPS1 plays a role in heat tolerance by identifying a homozygous knockdown mutant of rps1 with a T-DNA insertion at 6 bp from the 5′-untranslated region ( 5′-UTR ) of the RPS1 gene ( Figure 2A and Figure S5 ) . The substantial reduction in RPS1 expression in the rps1 mutant compared with wild type was verified using RT-PCR , western blots and quantitative PCR with reverse transcription ( qRT-PCR ) ( Figure 2B and 2C ) . To analyze RPS1 expression , we generated transgenic Arabidopsis plants carrying pRPS1:GUS constructs and the GUS staining signals were highly observed in cotyledons and true leaves ( Figure S6 ) . The rps1 mutant plants appeared slightly pale green with a reduced plant size ( Figure 2A ) . When 2 . 5-d-old seedlings were exposed to transient increases in temperature , almost none of the mutant seedlings survived after a 7-d recovery , compared with a survival rate of greater than 90% for wild type seedlings ( Figure 1D ) . In addition , both mature plants and detached leaves of the rps1 mutant exhibited heat-sensitive phenotypes compared with wild type plants after heat treatment and recovery ( Figure 1E and 1F ) . Cell death was examined by Trypan blue staining in the detached leaves challenged with heat stress shown in Figure 1F , and the cell death phenotype of the rps1 mutant was considerably more severe than that of wild type ( Figure 1G ) . Given the diminished expression of RPS1 in the rps1 mutant , these results indicate that RPS1 is required for heat tolerance . To test whether RPS1 is generally involved in abiotic stress responses , we monitored the sensitivity of wild type and rps1 mutant seedlings to salt and osmotic stresses and observed no significant difference under either treatment between wild type and rps1 mutant plants ( Figures S7 and S8 ) . These data support the assumption that the alteration in RPS1 expression affects cellular heat stress response by disrupting specific machinery rather than through general physiological defects . To further confirm the relationship existed between the downregulation of RPS1 expression and the loss of heat tolerance observed in the rps1 mutant , we investigated whether RNA interference ( RNAi ) -mediated gene silencing of RPS1 alters the heat-responsive behavior of transgenic plants harboring RNAi constructs . As expected , we found that the RNAi lines , in which downregulation of RPS1 expression was validated using RT-PCR , western blots and qRT-PCR ( Figure 2B and 2C ) , appeared pale green like those of the rps1 mutant ( Figure 2A ) and exhibited a heat sensitive phenotype in detached leaves and whole plants in comparison with wild type plants ( Figure 2D and 2E ) . Furthermore , transforming genomic fragments of RPS1 complemented the defects of the rps1 mutant in heat tolerance ( Figure 2D and 2E ) . These results demonstrate that RPS1 is the gene responsible for the deficiency in heat tolerance exhibited in the rps1 mutant . In addition , three genomic complementation lines ( Comp rps1-2 , 1-3 and 1-4 ) were generated in which the expression level of RPS1 dramatically increased when compared with wild type ( Figure 2B , 2C and Figure S9 ) . To test if the increased expression levels of RPS1 could enhance the heat tolerance , we performed the heat tolerance assay using the seedlings of wild type and the complementation lines . The result showed that when 2 . 5-d-old seedlings were exposed to transient increases in temperature , almost none of the wild type seedlings survived after a 7-d recovery , compared with a survival rate of 40–50% for the complementation line seedlings ( Figure S9 ) . On the other hand , we also analyzed the translation efficiency of the representative thylakoid membrane proteins encoded by chloroplast DNA , including D1 , D2 , CP43 , CP47 , PsaA , PsaB and β-subunits of ATPase between wild type and the genomic complementation line Comp rps1-3 in which the transcript level and protein level of RPS1 increased dramatically compared with wild type ( Figure 2B and 2C ) . In agreement with the enhancement in heat-tolerance , the translation efficiency of the representative thylakoid membrane proteins in complementation line Com rps1-3 increased substantially in comparison with the wild type seedlings under both control and heat stress conditions ( Figure S9C ) . These data further support that RPS1 is required for heat tolerance . Based on heat-responsive transcriptional analysis , HsfA2 is the most inducible HSF gene and appears to play a key role not only in the triggering of cellular responses to heat stress , but also in the amplification of the signal in the responses [49] , [50] . HsfA2 knockout mutant displays a heat-sensitive phenotype [50] , indicating that HsfA2 is a key heat tolerance regulator that cannot be replaced by other HSF genes . We verified the expression pattern of HsfA2 in the rps1 mutant in response to heat by qRT-PCR . At a heat stress temperature ( 38°C ) , the levels of HsfA2 mRNA rapidly increased and peaked 1 h after treatment in wild type plants whereas the heat-activated expression of HsfA2 was severely inhibited in the rps1 mutant ( Figure 3A ) . In agreement with the HsfA2 expression pattern , the heat-responsive expression of a subset of representative HsfA2 target genes , including APX2 , GolS1 and several HSPs ( Hsp17 . 7-CII , Hsp18 . 1-CI , Hsp25 . 3-P , Hsp70 and Hsp101 ) [49] , was nearly abolished in the rps1 mutant and did not match the transcriptional activity of these genes in wild type plants ( Figure 3B and 3C ) . In addition , we examined the heat-responsive expression levels of 15 members in class A HSF by qRT-PCR analysis . In agreement with the previous reports [19] , [49] , we found that HsfA2 is the most inducible HSF gene among 15 members in class A and the mutation of RPS1 leads to the most pronounced inhibitory effect on heat-responsive transcriptional activation of HsfA2 in comparison with the rest of the class A members whose relative expression levels are less than 100 with no or marginal difference between wild type and the rps1 mutant after heat treatment ( Figure S10 ) . These results indicate that downregulation of RPS1 expression considerably inhibits the transcriptional activation of HsfA2 and its target genes in response to heat stress , which are required for establishing cellular heat tolerance . Many of HsfA2 target genes are involved in protective environmental stress responses , including APX2 encoding a enzyme scavenging stress-induced reactive oxygen species ( ROS ) [68] , GolS1 encoding a enzyme catalyzing the synthesis of protective osmolyte such as RFO [69] and several HSPs encoding chaperone proteins stabilizing damaged proteins [49] . In this view , the defects in heat tolerance observed in the rps1 mutant are likely to be due to the repressed expression of HsfA2 and its target genes in response to heat stress . To further define the role of HsfA2 as a mediator in the activation of RPS1-dependent heat-responsive processes , we generated transgenic rps1 plants with the HsfA2 gene under the control of constitutive CaMV35S promoter ( Figure 4A ) . The constitutive expression of HsfA2 in the 35S:HsfA2 rps1 mutant was verified using RT-PCR and qRT-PCR ( Figure 4B and 4C ) . Notably , constitutive expression of HsfA2 almost totally restored the heat-sensitive phenotype of the rps1 mutant compared with wild type in young seedlings , detached leaves and whole plants ( Figure 4D–4F ) . Furthermore , we have performed qRT-PCR and western blot analysis to examine the expression levels of HsfA2 target genes and the protein levels of thylakoid membrane proteins in 35S:HsfA2 rps1 plants , respectively . The results showed that the expression levels of a subset of representative HsfA2 target genes , including APX2 , GolS1 and several HSPs ( Hsp17 . 7-CII , Hsp18 . 1-CI , Hsp25 . 3-P , Hsp70 and Hsp101 ) , constitutively increased in 35S:HsfA2 rps1 plants compared with that in wild type and rps1 plants ( Figure 5A ) . These results further confirm that the reduced expression levels of HsfA2 and its target genes under heat stress are responsible for the heat-sensitive phenotype of the rps1 mutant . Previous studies indicate that HSP21 is targeted to chloroplast and functions in protecting chloroplasts from heat or oxidative stresses in higher plants [34] , [35] . Importantly , by performing western blot analysis , we further confirmed that the protein level of HSP21 , encoded by the HsfA2 target gene Hsp25 . 3-P , also increased dramatically in 35S:HsfA2 rps1 plants in comparison with WT and the rps1 mutant plants ( Figure 5C ) . On the other hand , we found that the protein levels of thylakoid membrane proteins represented by D1 , D2 , CP43 , CP47 , PsaA , PsaB and β-subunits of ATPase in 35S:HsfA2 rps1 plants substantially increased in comparison with the rps1 mutant , and were restored to near the wild type levels ( Figure 5B ) . These data reveal that HsfA2 acts downstream of RPS1 and plays an essential role in mediating chloroplast RPS1-initiated transcriptional reprogramming of downstream target genes critical for heat tolerance . It is well known that heat stress leads to a loss of thylakoid membrane integrity , especially destacking of thylakoid membranes [2] , [12]–[14] , suggesting that the maintenance of thylakoid stability in response to heat stress is a key sign of heat tolerance in plants . To confirm that RPS1 is the chloroplast orthologue of CS1 in spinach [61] , and CreS1 in C . reinhardtii [65] , we determined its localization in mesophyll cell protoplasts and guard cells prepared from the transgenic plant leaves harboring 35S:RPS1-GFP constructs and its role in synthesis of thylakoid membrane proteins encoded by chloroplast genes . As predicted , RPS1 is targeted to chloroplasts ( Figure 6A and Figure S11 ) and the downregulation of RPS1 in the rps1 mutant caused a substantial reduction ( 50–60% ) in the protein levels of thylakoid membrane proteins , represented by D1 , D2 , CP43 , CP47 , PsaA , PsaB and β-subunits of ATPase ( Figure 6B ) . To further determine the function of RPS1 in plastid protein translation , we examined the differences in translation efficiency of thylakoid membrane proteins encoded by chloroplast DNA between wild type and the rps1 mutant by employing the pulsed stable isotope labeling assay with amino acids [70] . As shown in Figure 6C , the translation efficiency of D1 and CP43 proteins in chloroplast was reduced by 56% and 45% respectively in rps1 mutant leaves incorporated with medium heavy isotope-labeled amino acids ( M ) , compared with that in wild type leaves incorporated with heavy isotope-labeled amino acids ( H ) . The ratio of peak intensities of M versus H peptides reflects difference in translation of the corresponding proteins D1 and CP43 between wild type and the rps1 mutant . These results demonstrate that RPS1 plays a critical role in biosynthesis of thylakoid membrane proteins encoded by chloroplast genes . Having established that RPS1 functions in synthesis of thylakoid membrane proteins , we next investigated whether the downregulation of RPS1 altered the stability of thylakoid membranes . We generated estrogen-inducible RPS1-RNAi and 35S:RPS1 cosuppressed transgenic lines ( CS1 and CS2 ) and in both cases the transgenic plants exhibited a variegated phenotype ( Figure 7A and 7C ) . We attempted to examine the phenotypes of RPS1 overexpression transgenic lines and were not able to obtain such overexpression lines mainly owing to co-suppression caused by overexpressing RPS1 under the control of constitutive CaMV35S promoter . Estrogen treatment-induced downregulation of RPS1 expression was validated in estrogen-inducible RPS1-RNAi lines using RT-PCR and qRT-PCR ( Figure 7B ) . Furthermore , western blots with polyclonal antisera against RPS1 confirmed the highly reduced levels of RPS1 in the white sectors but the relatively higher levels in the green sectors of the representative variegated CS1 leaves ( Figure 7D ) . Detailed examinations of a representative variegated leaf detached from a mature CS1 plant using transmission electron microscopy ( TEM ) revealed that chloroplast structures in the green sector had normally developed granal stacks , but granum-stroma thylakoid membranes were severely disrupted in the transition sector with broken stromal membranes and large , thick granal stacks; the configurations of thylakoid systems nearly disappeared in the white sector , with the thylakoids decomposed into vesicles ( Figure 7E ) . These results further support the conclusion that RPS1 plays a critical role in synthesis of thylakoid membrane proteins that are required for maintaining the stability and integrity of thylakoid membranes in a RPS1 expression level-dependent manner . As the most sensitive component to the inhibiting action of heat stress in chloroplasts , thylakoid membrane system is vulnerable to be destabilized under heat stress conditions [2] . We next addressed whether the restoration of heat tolerance in the rps1 mutant by HsfA2 overexpression would be correlated with the improvement in thylakoid membrane stability under heat stress . To this end , we conducted TEM examinations . The thylakoid membranes in the chloroplasts of the rps1 mutant appeared distorted ( 38°C for 1 h ) and began to decompose 4 h after heat stress , whereas the wild type thylakoid systems , including grana and stroma membranes , retained their initial configurations ( Figure 8A and 8B ) . More importantly , overexpressing HsfA2 restored thylakoid stability in the rps1 mutant to wild type levels ( Figure 8A and 8B ) . To further corroborate TEM ultrastructural findings , we studied the surface topography of thylakoids in de-enveloped chloroplasts by atomic force microscopy ( AFM ) . AFM images also revealed that heat stress led to a considerable loss of granum structures in de-enveloped chloroplasts from the rps1 mutant , observed as a substantial reduction in the size of de-enveloped chloroplasts , but little reduction was observed for wild type and the rps1 mutant with overexpressed HsfA2 ( Figure 8C ) . These observations further confirmed that the rps1 mutant thylakoid membranes are susceptible to heat stress , which is mainly caused by the inhibition of the heat-responsive activation of HsfA2-dependent heat tolerance pathway . Furthermore , the heat-induced dramatic decrease in Fv/Fm values in the rps1 mutant was reverted by overexpressing HsfA2 , reflecting a substantial improvement in thylakoid stability and indicating that HsfA2-dependent restoration of thylakoid stability in the mutant is physiologically relevant ( Figure 8D ) . Therefore , these findings have established a previously unrecognized genetic connection between the RPS1 expression in chloroplast and the activation of HsfA2-dependent heat-responsive gene expression in nucleus , which is required for heat tolerance in higher plants .
In recent years , proteomics has provided a powerful approach to discovering the genes and pathways that are crucial for heat stress responsiveness in a variety of plant species [71] . In contrast to many studies on analysis of Arabidopsis transcriptome in response to heat stress [18]–[23] , a few reports have focused on proteome analysis of heat stress-responsive proteins in Arabidopsis [72] , [73] . In this study , we have demonstrated that RPS1 is a heat-responsive protein based on two lines of evidence from proteomic screen and western blot analysis with a RPS1 polyclonal antibody . Although numerous studies on the proteomic response to heat shock were reported on a variety of plant species such as rice , wheat , barley and Arabidopsis [71] , the physiologically relevant roles of the proteins identified in these studies have hardly been examined by analyzing heat stress-related phenotypes of corresponding mutant plants . This difficult situation is probably due to the limited mutant resources and the functional redundancy for most of the heat-responsive genes such as HSPs [16] , [17] . Fortunately , we identified a homozygous knockdown mutant of rps1 , which enabled us to do reverse genetic analysis to define the entirely novel roles of RPS1 in cellular heat stress response . We have answered the question of whether downregulation of RPS1 expression alters plant responses to heat stress by studying the knockdown mutant of rps1 and RPS1-RNAi transgenic plants; both the mutant and RNAi plants displayed sensitivity to heat stress . These results provide strong genetic evidence to support that RPS1 is required for heat tolerance . It is generally accepted that the chloroplasts in modern plants and algae are the descendants of the ancient photosynthetic bacteria . The modern chloroplast maintains a circular genome and transcription and translation machinery similar to that of its evolutionary precursor [74] , [75] . In E . coli , ribosomal protein S1 contains six S1 domains that are essential for RNA binding and is an essential protein required for the translation of most transcripts [57] , [59] , [60] . Based on the molecular diversity analysis , RPS1s in prokaryotes have been classified into four types depending on their functional reliability of translation initiation [58] . According to the complete proteome of chloroplast ribosomes from higher plants [76] , [77] , a majority of the protein components of chloroplast ribosomes have clear homologs in bacterial 70S ribosomes . In this study , we have cloned Arabidopsis RPS1 that contains three S1 domains and shares high sequence similarity with CS1 in spinach [78] , but a much less similarity with CreS1 in C . reinhardtii [65] and RPS1 in cyanobacteria [63] ( Figures S3 and S12 ) . Up to the present , the studies on CS1 and CreS1 , the orthologues of RPS1 in spinach and C . reinhardtii , have been limited to their expression and RNA binding properties [62] , [65] , [78] . Considered that RPS1 , a chloroplast-localized protein , has previously not been associated with heat stress responses , we have highlighted RPS1 as a possible candidate protein for further functional analysis of its role in heat tolerance . With reference to the roles of RPS1 orthologues in prokaryotic and eukaryotic organisms , we had expected RPS1 to be essential in synthesis of photosynthetic proteins encoded by chloroplast genome in Arabidopsis . As expected , we have provided strong evidence of a functional role for RPS1 in synthesis of thylakoid membrane proteins that are needed for maintaining the stability of thylakoid membrane system in chloroplasts of plants under normal growth conditions . Importantly , TEM examination of chloroplast structures in the green , transition and white sectors sampled from a representative variegated leaf detached from cosuppressed transgenic line CS1 reveals that the protein level of RPS1 positively correlates with the de-organization degree of thylakoid membrane systems in chloroplasts ( Figure 7 ) . Knockdown of RPS1 impairs the integrity of chloroplast as evidenced by alterations in the microscopic ultrastructures of chloroplast in the rps1 mutant with the reduced Fv/Fm value under control condition ( Figure 8 ) . Throughout the molecular , biochemical and microscopic analysis , we conclude that RPS1 plays a critical role in maintaining the chloroplast integrity . Such a conclusion was drawn on the basis of reverse genetics analysis using the knockdown mutant of rps1 , RPS1-RNAi transgenic plants and 35S:RPS1 cosuppression lines . In addition to identification of RPS1 as a heat-responsive protein , it truly surprised us to find that knockdown of RPS1 expression almost eliminates the transcriptional activation of HsfA2 and its target genes in the rps1 mutant in response to heat stress . It is known that translation impairment in plastids leads to downregulation of nuclear photosynthetic genes in higher plants [79]–[81] . Given that RPS1 functions in the translation initiation of chloroplast proteins and determines the integrity of chloroplast , we have proposed that the maintenance of chloroplast integrity is required for initiating the many molecular processes that signal the transcriptional activation of HsfA2 and its target genes required for establishing cellular heat tolerance . Accordingly , the exchange of signals is required for coordination between the activities of organelles and the nucleus . However , the mechanisms that generate the retrograde signal ( s ) to activate the expression of heat-responsive genes in plants remain to be characterized . Numerous studies suggest the existence of plastid signals passing from the chloroplast to the nucleus [80] . Mg-protoporphyrin IX was identified as a negative signal generated from defective plastids to repress the expression of photosynthetic genes in the nucleus [82] , [83] . In C . reinhardtii , it was reported that Mg-protoporphyrin IX could induce the expression of nuclear chaperone genes HSP70A and HSP70B [84] . However , recent reports have shown that the repression of photosynthetic gene expression caused by defective plastids has no correlation with the steady-state levels of Mg-protoporphyrin IX [85] , [86] . Instead of the tetrapyrrole pathway , it is proposed that plastid signals could derive from various sources , including protein synthesis , reactive oxygen species , or the redox state of the organelle , but the identity of the putative organellar signaling molecules remains elusive [87] . Since the components of the photosynthetic apparatus housed in the chloroplasts , including the oxygen evolving complex along with the associated cofactors in PSII , carbon fixation by Rubisco and the ATP generating system , are the primary susceptible targets of thermal damage in plants , the chloroplasts were proposed as sensors to changes in the growth environment , especially to a shift up in temperature [2] , [88] . In this study , we have demonstrated that the retrograde activation of HsfA2 expression is required for maintaining the integrity of chloroplasts indicated as the stability of thylakoid membrane systems under heat stress . We have drawn this conclusion based on several lines of evidence . Firstly , knockdown of RPS1 inhibits the heat-responsive activation of HsfA2 and its target genes and leads to a heat-sensitive phenotype of the rps1 mutant plants . Secondly , the overexpression of HsfA2 is sufficient to reestablish the lost heat tolerance in the rps1 mutant plants ( Figure 4 ) . Thirdly , the overexpression of HsfA2 and its target genes in the rps1 mutant dramatically improves the stability of thylakoid membranes under heat stress , which contributes to the restoration of heat tolerance in the rps1 mutant plants ( Figure 5 and Figure 8 ) . Importantly , it should be noted that the transcriptional and protein levels of HSP21 , encoded by the HsfA2 target gene Hsp25 . 3-P , are enhanced dramatically in 35S:HsfA2 rps1 plants in comparison with wild type and the rps1 mutant plants ( Figure 5 ) . These data may explain why the heat-sensitive integrity of the rps1 mutant chloroplasts is reverted by overexpressing HsfA2 since previous studies indicate that HSP21 is targeted to chloroplast and functions in protecting chloroplasts from heat or oxidative stresses in higher plants [34] , [35] . In general , the central message of our study is that the translation defects caused by downregulation of RPS1 in chloroplast negatively modulate nuclear heat-responsive gene expression under heat stress , leading to a loss of heat tolerance in the mutant plants , which reveals the existence of a retrograde activation pathway for cellular heat response in Arabidopsis . Consistent with the model we propose for the chloroplast regulation of the cellular heat stress responses , we found that knockdown of RPS17 , an essential subunit of chloroplast ribosome since the knock-out mutant of its maize orthologue hcf60 is seedling-lethal [89] , also led to a significant reduction in the heat-responsive expression of HsfA2 and a heat-sensitive phenotype in the rps17 mutant plants ( Figure S13 ) . In addition , the treatment with lincomycin , an inhibitor of the chloroplast protein synthesis , severely inhibited the expression of HsfA2 in response to heat stress ( Figure S14 ) . These additional data have further confirmed that cellular heat responses are modulated by a retrograde activation pathway in Arabidopsis . Our findings have revealed that RPS1 is a key genetic connection between chloroplast translation capacity and the heat-responsive transcriptional activation of HsfA2 , which helps in better understanding of the complex regulatory network of HsfA2 with a new angle . As a key component of the HSF signaling network involved in cellular heat stress responses , the regulatory mechanisms of HsfA2 have been intensely studied . In Arabidopsis , recent studies indicate that HsfA1 transcription factors , including HsfA1a , HsfA1b , HsfA1d , HsfA1e , function as the main regulators in heat-responsive gene expression such as HsfA2 [52]–[54] . Interestingly , we found no significant difference in the expression levels of HsfA1s between wild type and the rps1 mutant in response to heat stress ( Figure S10 ) . According to existing literatures and our data presented in this study , we favor the model that the capacity of protein translation in chloroplasts plays a critical role in generating the retrograde signal ( s ) to activate the heat-responsive expressions of HsfA2 and its target genes . We have demonstrated that RPS1 determines the stability of thylakoid membranes ( Figure 7 ) by modulating the translational efficiency of thylakoid proteins encoded by the chloroplast genes ( Figure 6 ) . It is well known that the chloroplasts are major sites of the production of reactive oxygen species ( ROS ) [90] . ROS are proposed to diffuse away from their sites of production and consequently elicit a different set of signaling events under a wide range of biotic and abiotic stress conditions [91] , [92] . We speculate that the alterations of thylakoid membranes caused by the downregulation of RPS1 may affect the generation of ROS such as H2O2 under heat stress by inhibiting thylakoid membrane-associated physiological processes , which could repress the activation of ROS-mediated retrograde signal transduction . Indeed , H2O2 is thought to be a signaling molecule to activate the core transcription regulators in response to heat stress . Interestingly , the exogenous application of H2O2 induces the expression of HSP genes in plant cells [93] , [94] . It has been suggested that the HsfA4a acts as a H2O2 sensor in controlling the homeostasis of reactive oxygen species in higher plants [95] . In Class A HSFs , HsfA2 is shown to have the highest level of expression in response to heat stress and the treatments with H2O2 and ozone [49] . Studies have pointed to a critical role of the mitogen-activated protein kinase ( MAPK ) in H2O2-mediated expression of HSFs , including HsfA2 under heat stress [16] , [96]–[99] . In this view , it has been suggested that H2O2 diffuses freely across the chloroplast envelope to activate a cytosolic MAPK cascade [100] . It is assumed that H2O2 may regulate the activity of HsfA1s through the mitogen-activated protein kinase [97] , [98] or Calmodulin ( CaM ) -binding protein kinase 3 ( CBK3 ) [101] pathways . Consequently , the activated HsfA1s regulate the heat-responsive expression of HsfA2 and its target genes , which is required for heat tolerance . Although H2O2 is proposed as a possible retrograde signal molecule , the difficulty with this model lies in that how H2O2 could specifically communicate information on the state of chloroplasts to the nucleus because H2O2 is produced at different sites in the cell and in response to various different stresses and stimuli in higher plants [87] . Therefore , these proposed pathways remain to be further explored . The future studies should turn towards the identification of interconnecting components between the capacity of plastid protein translation and the nuclear heat-responsive gene expression of HsfA2 and its target genes . In summary , by integrating a variety of approaches , including proteomics , reverse genetics and microscopic analysis ( TEM and AFM ) , we have identified RPS1 as a previously unrecognized determinant regulator involving in plastid protein translation control and retrograde activation of heat-responsive genes . Our findings demonstrate the existence of a retrograde pathway in the regulation of the cellular heat stress responses . In this view , the maintenance of chloroplast integrity under heat stress is a highly coordinated process in which RPS1 is a previously unrecognized regulator that optimizes the adaptive value of the cellular heat stress response in correspondence to capacity of plastid protein translation .
Arabidopsis thaliana plants used in all experiments were of the ecotype Columbia ( Col-0 ) . Growth chambers were used for controlled temperature experiments . All seeds were surface-sterilized , plated on half-strength MS medium , and stratified at 4°C for 3 days or grown in soil-culture without sterilization . Plants were grown under long-day conditions , 16 h of white light ( 80 µmol m−2 s−1 ) and 8 h of dark , with 60% relative air humidity at 21°C . The rps1 mutant was isolated from the T-DNA insertion line ( CS874869 ) obtained from the Arabidopsis Biological Resource Center ( Ohio State University , USA ) . The rps1 mutant was backcrossed to wild type twice for removing background mutations and the heat sensitive phenotype of F2 backcrossed lines co-segregated with T-DNA insertion as a single recessive trait . For subcellular localization analysis , a cDNA clone containing the full-length RPS1 open reading frame was amplified by PCR with RGFP+ and RGFP- primers and inserted into XhoI and SpeI cloning sites of the 35S CaMV expression cassette of the p35S-GFP-JFH1 vector [102] , yielding a C-terminal GFP fusion construct . For the genomic complementation assay , a genomic fragment of RPS1 ( 4 , 597 bp in size ) , starting at 2 , 139 bp upstream of the ATG codon and ending at 496 bp after the stop codon , was amplified from genomic DNA by PCR with RComp+ and RComp− primers and cloned into KpnI and XbaI sites of the pCAMBIA1300 binary vector . For the expression pattern analysis , a promoter fragment extending 2139 bp upstream to 201 bp downstream of the translation initiation ATG codon of RPS1 was amplified using the primers RGUS+ and RGUS− and the resulting fragment was cloned into HindIII and BamHI sites of the binary vector pBI101 . 1 . To generate the constitutive RPS1-dsRNAi construct and estrogen-inductive RPS1-dsRNAi construct , a 120 nucleotide intron of the AtRTM1 gene [103] was subcloned into XbaI and NotI sites of the pBluescript SK+ ( Stratagene , La Jolla , CA ) vector to create pBS-RTM . A 485-bp sense fragment , starting at 25 bp upstream and ending at 457 bp downstream of the ATG codon of RPS1 , was amplified with FRNAi+ and FRNAi− primers , and the antisense fragment was amplified with RRNAi+ and RRNAi− primers . The amplified sense and antisense fragments were subcloned into pBS-RTM to yield the pBS-RPS1-RTM-1SPR vector . To generate the constitutive RPS1-dsRNAi construct , the RPS1-RTM-1SPR fragment was released from the pBS-RPS1-RTM-1SPR vector by digestion with SmaI and SacI and cloned into pCAMBIA1300s to generate pCAMBIA1300s-dsRPS1 . For the estrogen-inductive RPS1-dsRNAi construct , the RPS1-RTM-1SPR fragment was obtained by digesting the pBS-RPS1-RTM-1SPR vector with XhoI and cloned into pER8 to generate pER8-dsRPS1 . The pER8 vector [104] was kindly provided by N . -H . Chua ( Rockefeller University , New York , USA ) . For overexpressing HsfA2 in the rps1 mutant , a cDNA clone containing the full-length HsfA2 open reading frame was amplified by PCR with 121A2-F and 121A2-R primers and inserted into XbaI and SacI cloning sites in the 35S CaMV expression cassette of pBI121 . For overexpression of RPS1 in transgenic plants , a cDNA clone containing the full-length RPS1 open reading frame was amplified by PCR with ROX+ and ROX− primers , digested with BamHI and KpnI and inserted into BglII and KpnI cloning sites in the 35S CaMV expression cassette of pMON530 . The co-suppression line CS1 and CS2 were isolated from the resulting overexpression lines described above . The primer sequences for generating the indicated constructs are listed in Table S1 . Binary vectors harboring the desired constructs were transferred into Agrobacterium tumefaciens strain GV3101 . Transgenic plants were generated by a floral dip method and screened on solid plates containing 50 mg/L kanamycin or 25 mg/L hygromycin . Heat tolerance assays of seedlings , mature plants and detached leaves were performed as described previously [30] , [105] with modifications . All heat treatments were performed in dark . For the acquired heat tolerance test of seedlings , 2 . 5-d-old seedlings , grown on 1/2 MS medium , were initially acclimated to heat at 38°C for 1 h , returned to 22°C for 2 h , and then challenged at 45°C for 3 h . Challenged Seedlings recovered in a growth chamber at 22°C for 7 d under 16/8 h light-dark cycles . To evaluate the effect of continuous moderate heat stress on mature plants , 21-d-old plants grown in peat soil pots were heated in the incubator at 38°C for 9 h and the challenged plants were allowed to recover at 22°C for 3 d under continuous light conditions . For the heat tolerance assay of detached leaves , fully extended leaves detached from 21-d-old plants were placed on plastic square Petri dishes with three-layer Whatman filter paper at the bottom immersed in 20 ml of deionized water , incubated at 38°C for 6 h , and the challenged leaves were allowed to recover at 22°C for 3 d under continuous light conditions . For all heat treatments , plants were photographed following the recovery processes . Total RNA was isolated from leaf samples frozen in liquid nitrogen using the TRIzol reagent ( Takara ) according to manufacturer's protocol . For quantitative real-time RT-PCR analysis , DNA contaminated in total RNA samples was digested with RNase-free DNase ( Takara ) . Complementary DNA was produced using 1 µg total RNA and an oligo ( dT ) 18 primer . Quantitative real-time PCR was performed with SYBR Premix Ex TaqII ( Takara ) using a MyiQ5 single color Real-Time PCR Detection System ( Bio-Rad ) . The comparative threshold cycle ( Ct ) method was used for determining relative transcript levels ( iQ5 admin , Bio-Rad ) using ACTIN2 as an internal control . Three biological and three technical repeats were performed in the experiments . Primer names and sequences are listed in Table S2 . Thylakoid membranes were prepared as described previously [106] . Immunodetection of thylakoid membrane proteins was performed using the indicated primary antibodies against thylakoid membrane proteins ( Agrisera ) and Alkaline-phosphatase-conjugated goat anti-rabbit IgG ( Chemicon ) as a secondary antibody and reaction was revealed using an ECL kit ( Amersham ) . Samples were fixed with 2 . 5% ( v/v ) glutaraldehyde and 2% ( v/v ) paraformaldehyde for approximately 4 h at 4°C . Thin sections were examined by a transmission electron microscope ( H7650 , Hitachi ) using a voltage of 120 kV . Proteins were extracted from detached , fully-extended wild type leaves treated with control or heat treatment ( 38°C , 2 h ) in dark . Proteins were extracted and 2-DE analysis was performed as described previously [107] . Second dimension SDS-PAGE was performed using a 12% acrylamide gel in a PROTEAN II xi Cell system ( Bio-Rad ) . Silver-stained gels were digitized by an FLA-7000 imaging analyzer ( Fujifilm ) and analyzed using Multi Gauge software ( Fujifilm ) . Mass spectra were measured using a 4700 proteomic analyzer MALDI-TOF/TOF tandem system ( Applied Biosystems , Framingham , MA , USA ) . Gel pieces were detained with a solution of 15 mM potassium ferricyanide and 50 mM sodium thiosulfate ( 1∶1 ) for 20 min at room temperature , washed twice with deionized water , and shrunk by dehydration in ACN . The samples were swollen in a digestion buffer containing 20 mM ammonium bicarbonate and 12 . 5 ng/L trypsin at 4°C for 30 min and then digested more than 12 h at 37°C . Peptides in the samples were extracted twice using 0 . 1% TFA in 50% ACN . The extracts were dried under the protection of N2 . For MALDI-TOF-MS , the peptides were eluted onto the target with 0 . 7 µl matrix solution ( α-cyano-4-hydroxy-cinnamic acid in 0 . 1%TFA , 50%ACN ) . Samples were allowed to dry in air before subjected to the mass spectrometer . Data from MALDI-TOF MS/MS were searched by GPS Explorer using MASCOT as a search engine . Total protein from plants was extracted as described previously [108] . Western blotting was performed with equal amounts of protein extracts ( 5 µg ) , separated by SDS–polyacrylamide-gel electrophoresis , immunoblotted to polyvinylidene difluoride membranes ( Millipore ) and probed with affinity-purified RPS1 antibodies at a dilution of 1∶1 , 000 ( v/v ) in PBS buffer ( pH 7 . 4 ) containing 0 . 05% Tween 20 . Alkaline-phosphatase-conjugated goat anti-rabbit IgG ( Chemicon ) was used as a secondary antibody and reaction was revealed using an ECL kit ( Amasham ) . Anti-RPS1 rabbit polyclonal antisera were generated against the peptide of RPS1 ( from Ser17 to Leu248 ) by Abmart biomedical company ( Shanghai , China ) . Anti-HSP21 rabbit polyclonal antisera were purchased from Agrisera ( Sweden ) . In vivo analysis of chloroplast translation was examined according to [70] . Briefly , wild type and the rps1 mutant primary leaves detached from 15-d-old young seedlings grown in greenhouse , were vacuum-infiltrated with cycloheximide ( 20 mg/ml ) in the incubation buffer ( 10 mM Tris-HCl , pH 6 . 8 , 5 mM MgCl2 , 20 mM KCl , and 0 . 1% ( v/v ) Tween 20 ) in 9 cm petri dishes with three-layer Waterman filter paper at bottom , and incubated in dark for 30 min for blocking cytosolic translation . Next , wild type and the rps1 mutant leaves were pulse-labeled with 100 mg/L 13C615N4 L-arginine ( “heavy” , H ) and 100 mg/L 15N4 L-arginine ( “medium heavy” , M ) in the incubation buffer , respectively , and then transferred into light condition ( 80 µmol•quanta m−2•s−1 ) at room temperature for 4 h . Thylakoid membranes were prepared from the labeled leaves as described [106] . The extracted thylakoid membranes were separated by BN-PAGE as described [109] . The thylakiod membranes samples were washed with washing buffer ( 50 mM BisTris-HCl , pH 7 . 0 , 330 mM sorbitol ) and then suspended in suspension buffer ( 25 mM BisTris-HCl , pH 7 . 0 , 20% glycerol ) at 2 . 0 mg chlorophyll/ml . The samples of wild type and the rps1 mutant were mixed with equal chlorophyll quantity and the mixed sample was diluted with the equal volume of suspension buffer containing 2% ( w/v ) DM in a dropwise manner . After incubation at 4°C for 30 min , the insoluble material in the thylakoid samples was removed by centrifugation at 10 , 000 g for 30 min . The supernatant ( 5 ug chlorophyll ) was mixed with one-tenth volume of 5% Serva blue G solution ( 100 mM BisTris-HCl , pH 7 . 0 , 0 . 5 M 6-amino-n-caproic acid and 30% ( w/v ) glycerol ) and then applied to 0 . 75-mm-thick 5 to 13 . 5% acrylamide gradient gels in a Hoefer Mighty Small vertical electrophoresis unit connected to a cooling circulator . Gel slices in the expected molecular weight range of thylikiod complex proteins were excised , reduced , alkylated , and trypsin-digested . Extracted peptides were analyzed by LC-MS/MS on a high performance mass spectrometer ( LTQ-Orbitrap XL , Thermo Finnigan , San Jose , CA ) . Raw data were processed using the MaxQuant 1 . 1 . 36 software package for protein identification and quantitation . GFP images were visualized by a LSM510 laser scanning confocal microscope ( Zeiss , Jena , Germany ) with argon laser excitation at 488 nm and a 505- to 550-nm emission filter set for GFP fluorescence . Envelope-free chloroplasts were prepared according to the assay described previously [110] . Briefly , fully expanded leaves detached from 3-week-old plants were challenged with heat treatment ( 38°C ) in the indicated time , floated on icecold water for 30 min in dark and then blotted dry . The following experimental procedures were carried out in dark on ice . Next , the blotted leaves were blended in grinding buffer containing 0 . 4 M sorbitol , 5 mM EDTA , 5 mM EGTA , 5 mM MgCl2 , 10 mM NaHCO3 , 20 mM Tricine , pH 8 . 4 , and 0 . 5% ( w/v ) fatty acid–free BSA . The resulting slurry was filtered and centrifuged for 3 min at 2600 g ( 4°C ) . The half of the resulting pellet ( topmost ) was suspended in resuspension buffer ( RB; 2 mL ) containing 0 . 3 M sorbitol , 2 . 5 mM EDTA , 5 mM MgCl2 , 10 mM NaHCO3 , 20 mM HEPES , pH 7 . 6 , and 0 . 5% ( w/v ) fatty acid–free BSA . The suspension was centrifuged for 3 min at 200 g , ( 4°C ) and the collected supernatant was then centrifuged ( 2600 g for 3 min , at 4°C ) to form pellets that contained the de-enveloped chloroplasts . The resulting pellets were resuspended in RB buffer for experiments . Samples were attached to glass cover slips ( 10 mm of diameter ) coated with 0 . 01% ( w/v ) poly-L-lysine by gentle centrifugation ( 5 min at 1 , 000 g ) and fixed for overnight at 4°C in RB containing 2% ( v/v ) glutaraldehyde and 3% ( v/v ) paraformaldehyde . Signals were recorded in contact mode with the MultiMode-SPM ( Veeco Co . ) equipped with a 30-µm scanner , using oxide-sharpened Si3N4 cantilevered tips ( k = 0 . 12 N/m ) . Images were acquired with forces set minimally above lift-off values , at 1 to 2 Hz . Chlorophyll fluorescence emissions were detected with an LI-6400XT Portable Photosynthesis System ( LI-COR Biosciences , Lincoln , Nebraska USA ) . The fifth leaves were excised from 21-d-old plants , and challenged with heat treatment ( 38°C ) for the indicated time in dark . The maximum photochemical efficiency of PSII was determined from the ratio of variable ( Fv ) to maximum ( Fm ) fluorescence ( Fv/Fm ) . Measurements were performed by root-bending assay as described previously [111] , [112] and by seedling-growth assay as described previously [113] . Tissues were immersed into the staining solution ( 50 mM Na phosphate buffer , pH 7 . 0 , 10 mM EDTA , 0 . 5 mM potassium ferricyanide , 0 . 5 mM potassium ferrocyanide , 0 . 1% Triton X-100 , and 2 mM 5-bromo-4-chloro-3-indolyl-ß-D-glucuronide ) , vacuum- infiltrated for 5 min and incubated at 37°C overnight . Stained tissues were decolorized with 70% ethanol and examined with an Olympus BX51 microscopy or Olympus SZX7 stereomicroscopy ( Olympus , Japan ) . Seedlings were treated with lincomycin according to [114] . Sequence data from this article can be found in the Arabidopsis Genome Initiative or GenBank databases under the following accession numbers: RPS1 ( At5g30510 ) , Hsp101 ( At1g74310 ) , Hsp70 ( At3g12580 ) , Hsp25 . 3-P ( At4g27670 ) , Hsp18 . 1-CI ( At5g59720 ) , Hsp17 . 7-CII ( At5g12030 ) , APX2 ( At3g09640 ) , GolS1 ( At2g47180 ) , Actin2 ( At3g18780 ) . The National Center for Biotechnology Information accession numbers of the proteins used in Alignment analysis under the following accession numbers: CS1 in spinach ( M82923 ) and CreS1 in Chlamydomonas reinhardtii ( AJ585191 ) .
|
As a consequence of global warming , increasing temperature is a serious threat to crop production worldwide and may influence the objectives of breeding programs . As a universal cellular response to a shift up in temperature , the heat stress response represents the first line of inducible defense against imbalances in cellular homeostasis in the prokaryotic and eukaryotic kingdoms . Given that components of the photosynthetic apparatus housed in the chloroplast are the primary susceptible targets of thermal damage in plants , the chloroplasts were proposed as sensors to a shift up in temperature . However , the mechanism by which chloroplasts regulate the expression of nuclear heat stress–responsive gene expression according to the functional state of chloroplasts under heat stress remains unknown . In this study , we have identified chloroplast ribosomal protein S1 ( RPS1 ) as a heat-responsive protein through proteomic screening of heat-responsive proteins . We have established a previously unrecognized molecular connection between the downregulation of RPS1 expression in chloroplast and the activation of HsfA2-dependent heat-responsive genes in nucleus , which is required for heat tolerance in higher plants . Our data provide new insights into the mechanisms whereby plant cells modulate nuclear gene expression to keep accordance with the current status of chloroplasts in response to heat stress .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"chloroplast",
"plant",
"science",
"plant",
"biology",
"plant",
"cell",
"biology",
"plant",
"genetics",
"biology",
"plant",
"physiology"
] |
2012
|
Downregulation of Chloroplast RPS1 Negatively Modulates Nuclear Heat-Responsive Expression of HsfA2 and Its Target Genes in Arabidopsis
|
Heme oxygenase 1 ( HO-1 ) is an essential enzyme induced by heme and multiple stimuli associated with critical illness . In humans , polymorphisms in the HMOX1 gene promoter may influence the magnitude of HO-1 expression . In many diseases including murine malaria , HO-1 induction produces protective anti-inflammatory effects , but observations from patients suggest these may be limited to a narrow range of HO-1 induction , prompting us to investigate the role of HO-1 in malaria infection . In 307 Gambian children with either severe or uncomplicated P . falciparum malaria , we characterized the associations of HMOX1 promoter polymorphisms , HMOX1 mRNA inducibility , HO-1 protein levels in leucocytes ( flow cytometry ) , and plasma ( ELISA ) with disease severity . The ( GT ) n repeat polymorphism in the HMOX1 promoter was associated with HMOX1 mRNA expression in white blood cells in vitro , and with severe disease and death , while high HO-1 levels were associated with severe disease . Neutrophils were the main HO-1-expressing cells in peripheral blood , and HMOX1 mRNA expression was upregulated by heme-moieties of lysed erythrocytes . We provide mechanistic evidence that induction of HMOX1 expression in neutrophils potentiates the respiratory burst , and propose this may be part of the causal pathway explaining the association between short ( GT ) n repeats and increased disease severity in malaria and other critical illnesses . Our findings suggest a genetic predisposition to higher levels of HO-1 is associated with severe illness , and enhances the neutrophil burst leading to oxidative damage of endothelial cells . These add important information to the discussion about possible therapeutic manipulation of HO-1 in critically ill patients .
Heme oxygenase ( HO ) is the rate limiting enzyme that catabolizes free heme into carbon monoxide ( CO ) , ferrous iron , and biliverdin/bilirubin [1] . To date , two functional isoforms ( HO-1 , HO-2 ) have been described . While HO-2 is constitutively produced by most cells , HO-1 protein is induced by its substrate heme and a broad array of acute stress stimuli , many of which are associated with critical illnesses [2] . HO-1 induction produces cytoprotective and anti-inflammatory effects by reducing intracellular heme availability , through generation of CO and bilirubin , through stimulation of ferritin synthesis [3] , and possibly , by heme-independent mechanisms of transcriptional regulation [4] . HO-1 is an essential enzyme in humans and mice; deficiency in humans is deleterious , predominantly affecting endothelial cells and the reticuloendothelial system , and results in a greatly reduced life expectancy [5] . However , much of what is known about HO-1 function is derived from experiments in animal models or in in vitro experiments . The impact of HMOX1 over- or under-expression , silencing or knockout and the concomitant changes in protein levels in a physiological or homeostatic context [6] or in humans [7] is less clear . The blood stage of malaria infection is characterized by hemolysis and consequent release of hemoglobin and its heme moiety [8] . Elegant mechanistic studies in mice have shown that free heme has a profound pro-inflammatory and cytotoxic effect in malaria , increasing susceptibility to experimental cerebral malaria ( ECM ) , and hepatic failure . These adverse events can be prevented by HO-1 induction or administration of CO that can reduce the levels of free heme [9] , [10] . Marked differences amongst mouse strains in the kinetics of HO-1 in response to P . berghei ANKA infection appeared to determine susceptibility to ECM , suggesting that regulation of HMOX1 expression is a crucial factor in this model . However , higher HO-1 levels in the murine liver appeared to allow the development of liver stage parasites by reducing the host inflammatory response , indicating that optimal regulation of HO-1 must balance control of pathogen replication with protection from inflammatory damage during infection [11] . As expected , evidence of increased expression and activity of HO-1 has been observed in human malaria [12] , [13] , [14] , [15] , but its functional relevance has been far more difficult to establish . Other than inbred mice , the amount of HO-1 produced in response to a defined stimulus in humans may be influenced by a ( GT ) n repeat length polymorphism in the promoter region of the HMOX1 gene [16] . In various chronic inflammatory conditions and other diseases , long HMOX1 ( GT ) n repeats , associated with lower HO-1 protein have been identified as disease risk factors [17] . This has led to the hypothesis that the ability to mount a strong HO-1 response is beneficial for people living in malaria endemic areas , and that the disease may have applied selective pressure for shorter ( GT ) n repeats [17] . The potential role of HO-1 and CO has also been recognized in other critical illnesses [18] , and in a murine model free heme clearly contributed to the pathogenesis of severe sepsis [19] . If the protective effect of CO or other products of the enzymatic reaction catalyzed by HO-1 can be established in man , this could provide novel avenues for treatment using therapeutic CO inhalation , or systemic administration of CO releasing molecules ( CORM ) , capable of releasing CO in a controlled fashion [20] . HO-1 has thus moved to “center stage” for a variety of infectious diseases , not just for malaria [20] , [21] . A recent report on critically ill patients measuring CO bound hemoglobin ( COHb ) levels of which 85% can be ascribed to HO-1 mediated heme metabolism [22] indicates that both excessively low or high levels of COHb appear to be associated with death [23] . This indicates that the protective effects of HO-1 are limited to a narrow range of HO-1 concentrations [18] . While HO-1 uses the highly cytotoxic heme as a substrate , one of the products of the enzymatic reaction , ferrous iron , is released into the endoplasmic reticulum ( ER ) . In this form , iron is redox active and can catalyze the formation of organic and inorganic reactive oxygen species ( ROS ) [24] . HO-1 thus has both anti-oxidant and oxidant properties . In malaria its induction may be particularly enhanced by a pronounced intravascular hemolysis liberating considerable amounts of heme [25] that require degradation by HO-1 in endothelial cells , resulting in an increase of ferrous iron . Indeed , in vitro studies indicate that the equimolar production of anti-oxidant bilirubin and ferrous iron by HO-1 results in an overall pro-oxidant effect [26] , and that high HO-1 levels can lead to tissue damage [27] . In light of this , it has been hypothesized with regard to the effect of the ( GT ) n repeat length polymorphism in the HMOX1 gene promoter that – in contrast to what has been observed for chronic inflammatory conditions - short repeat array alleles may cause susceptibility to severe malaria in humans [28] . Consistent with this , short alleles were found to be associated with risk of cerebral malaria in Myanmar [29] , and Angola [30] . The functional duality is problematic with respect to developing adjuvant therapies for severe malaria based on induction of HO-1 or administration of CO , and highlights the need to understand better the regulation and function of HO-1 in humans in relation to both promoter polymorphisms and malaria . In the present study we characterized in detail the genetic and functional associations between HMOX1 promoter polymorphisms , HO- 1 inducibility , HMOX1 expression and severity of malaria in Gambian children exposed to seasonal malaria . We show that short ( GT ) n repeat alleles in the HMOX1 gene are associated with higher HMOX1 expression in white blood cells of this population , and that short repeat alleles are strongly associated with severe disease and death , whilst high HMOX1 mRNA and HO-1 protein levels are associated with severe disease . We establish that neutrophils are the main HO-1 expressing cell type in peripheral blood ex vivo , and demonstrate in vitro that HMOX1 mRNA expression in purified neutrophils can be upregulated further by lysed erythrocytes , or hemin . We provide mechanistic evidence that hemin-mediated HMOX1 expression potentiates the neutrophil respiratory burst , and propose that this may be part of a causal pathway driving the association between short ( GT ) n repeats and increased disease severity .
The study was reviewed and approved by the Gambian Government/MRC Joint Ethics Committee and the Ethics Committee of the London School of Hygiene & Tropical Medicine ( London , UK ) . Between September 2007 and January 2010 , after written informed consent was obtained from the parents or guardians , a total of 153 severe and 154 uncomplicated malaria cases were enrolled . ( see Table S1 in Text S1 for detailed information ) . Subjects enrolled in this study were recruited from an ongoing health centre based study comparing children with uncomplicated and severe malaria disease resident in a restricted peri-urban area of the Gambia described in more detail previously [31] . Uncomplicated malaria ( UM ) was defined as an episode of fever ( temperature >37 . 5°C ) within the last 48 hours with more than 5000 parasites/µl detected by slide microscopy . Severe malaria ( SM ) was defined using modified WHO criteria [32]: severe anaemia ( SA ) , defined as Hb<6 g/dl; severe respiratory distress ( SRD ) defined as serum lactate >7 mmol/L; cerebral malaria ( CM ) defined as a Blantyre coma score ≤2 in the absence of hypoglycaemia or hypovolaemia , with the coma lasting at least for 2 hours; severe prostration ( SP ) defined as inability to sit unsupported ( children>6 months ) or inability to suck ( children≤6 month ) . The term “disease severity” refers to comparisons between UM and SM , and , where indicated , to a comparison across disease entities grouped according to increasing severity . To avoid the confounding effects of other pathogens in children with concomitant systemic bacterial infections , children with clinical evidence of infections other than malaria were not enrolled into the study . For some experiments , healthy children ( HC , n = 6 ) of the same age were enrolled as controls . On admission ( D0 , also referred to as “acute disease” ) and after 4 weeks ( D28±3 days , also referred to as “convalescence” ) one ml of blood was collected in RNA stabilizing agent ( PAXgene Blood RNA system , Pre-AnalytiX ) and a maximum of 4 mls of blood ( mean: 3 . 2 mls CI 95%: 3 . 1–3 . 3 mls ) were collected into heparinized vacutainers ( BD ) . Four buccal swabs were performed using sterile mouth brushes ( Cytobrush plus , Henley's Medical , UK ) and stored in a DNA-stabilizing buffer containing 10 mM Tris , 10 mM EDTA , 0 . 5% Sarkosyl for subsequent DNA extraction . All patients received standard care according to the Gambian Government Treatment Guidelines , provided by the health centre staff . The children's health was reviewed 7 days after admission . Healthy adult volunteers were bled for the in vitro experiments after informed consent was obtained . P . falciparum parasites were identified by slide microscopy of 50 high power fields of a thick film . Full differential blood counts were obtained on days 0 and 28 using a Medonic instrument ( Clinical Diagnostics Solutions , Inc ) . Blood samples were processed within 2 hours of collection . Flow cytometry was performed on 300 µl of whole blood collected into heparinized tubes . HO-1 induction assays were performed on 200 µl of whole blood collected on D28 . From the remaining sample , plasma was removed , stored at −80°C and replaced by an equal volume of RPMI 1640 ( Sigma-Aldrich ) . PBMC were isolated after density centrifugation over a 1 . 077 Nycoprep ( Nycomed , Sweden ) gradient ( 800 g , 30 min ) and washed twice in RPM 1640 . PBMCs were used for other studies [31] . The remaining PBMC deficient blood suspension underwent a further density centrifugation over Histopaque 1119 ( Sigma Aldrich ) to isolate granulocytes that were used for Western blood analysis of HO-1 expression after a microscopic purity check with Giemsa stain . Whole blood was incubated for 35 min at 4° in the dark with the following cocktail of surface antibodies: 5 µl each of PE anti-CD16b , Per CP anti-CD14 , PE-Cy7 anti-CD4 , APC anti-CD19 ( all Becton Dickinson ) , Pacific blue anti-CD3 and 4 ul of APC-AF 750 anti-HLA-DR ( both Ebioscience ) , or a cocktail of manufacturer matched isotype controls . Thereafter , erythrocytes were lysed using FACS lysing buffer ( Becton Dickinson ) , and the remaining cells were fixed and permeabilized ( Cytofix/Perm reagent; Becton Dickinson ) . After a blocking step with 5% of mouse serum ( 4°C , 15 min ) intracellular staining ( 4°C , 30 min ) for HO-1 was performed with 3 . 5 µl of FITC anti-HO-1 ( Abcam ) . Samples were acquired on a 3 laser/9 channel CyAn ADP flowcytometer and analysed using FlowJo 7 . 25 ( Tree Star Inc . ) . For quantitative reverse transcription-polymerase chain reaction ( qRT-PCR ) , total RNA was extracted from PAX tubes , collected from study patients following the manufacturer's instructions and reverse transcribed into cDNA using TaqMan reagents for reverse transcription ( Applied Biosystems ) , according to the manufacturer's protocol . In addition , whole blood used for HO-1 induction assays from samples obtained on day 28 were collected into Trizol LS ( Invitrogen ) and the RNA precipitated by a chloroform/ethanol step . Isolation of RNA from neutrophils or whole blood used in the in vitro assays was performed with the RNeasy Mini kit ( Qiagen ) after collection and storage of the cells into RLT buffer . Gene expression profile for IL-10 was measured previously on a subset of samples from the clinical study and were used for correlation analysis [31] . HMOX1 gene expression was determined by qRT-PCR on a DNA Engine Opticon ( MJ Research ) using the TaqMan Probe kit with primers ( all Metabion ) as previously published [33] . 18S rRNA , amplified using a commercially available kit ( rRNA primers and VIC labeled probe , Applied Biosystems ) , was assayed as a housekeeping gene with a stable expression profile in this setting regardless of disease severity or time point [31] . Data were analysed using Opticon Monitor 3 analysis software ( BioRad ) and are expressed as the ratio of the transcript number of the gene of interest over the endogenous control , 18S rRNA . Levels of soluble HO-1 were determined in plasma ( 1∶50 diluted ) or cell culture supernatants ( neat ) by ELISA in duplicate wells of Immunolon HX4 plates , using the HO-1 human ImmunoSet Kit ( Stressgen ) . A commercial HRP-2 ELISA kit ( CELISA , Cellabs , Australia ) was used to quantify HRP-2 in plasma samples diluted 1∶20 , in duplicate wells of Immunolon HX4 plates . Some samples were out of range and were repeated at a 1∶2 dilution if below the bottom of the standard curve , or at a 1∶100 dilution if above the top of the standard curve . Free heme in plasma was quantified using a published method [9] . Briefly , plasma was centrifuged at 1000 g for 5 min and the supernatant passed through a Microcon YM-3 column ( Millipore , 14 , 000 g for 100 min at RT ) to remove proteins . Free heme from protein depleted plasma and heme content in lysates of infected and uninfected RBC as well as a solution of uninfected intact RBC was quantified by a chromogenic assay ( QuantiChrom Heme Assay Kit , BioAssay Systems ) . Immunodetection of HO-1 protein in lysates of isolated neutrophils was performed using a protocol adapted from [4] . Polyclonal rabbit anti-HO-1 antibodies obtained from StressGen Biotechnologies Corp . ( Victoria , BC , Canada ) were used . Polyclonal goat anti-actin ( Santa Cruz ) antiserum was used for staining as loading controls . Briefly , 10 µg of cell lysate proteins was separated by reducing sodium dodecyl sulphate polyacrylamide gel electrophoresis using precast Nupage gels and MOPs buffer in the X-cell mini electrophoresis chamber ( Life Technologies ) . Separated proteins were then transferred onto methanol treated PVDF membranes using the X-cell mini blotting system . Blotted membranes were rinsed in 1×PBS and blocked overnight at 4°C in blocking buffer containing 5% non-fat milk in 1×PBS and 0 . 1% Tween 20 ( Sigma Aldrich ) . After the blotted membranes were washed three times in PBS-Tween , they were incubated with constant shaking for 2 h at RT with anti-HO-1 , or anti-actin diluted 1∶1 , 000 in blocking buffer . The membranes were then washed with three changes of PBS-Tween and further probed with horseradish peroxidase-conjugated donkey anti-goat or goat anti-rabbit IgG ( Santa Cruz ) at a dilution of 1∶10 , 000 for 2 hours at room temperature with constant shaking . Following three washes in PBS-Tween , membranes were rinsed in 1×PBS and bound antibodies were revealed by chemiluminescent detection performed with the Amersham ECL detection kit according to the manufacturer's instructions . Material from mouth brushes was eluted into transport buffer and incubated with Proteinase K , guanidine hydrochloride , and ammonium acetate ( Sigma Aldrich , UK , at final concentrations of 262 µl/ml , 1 . 57M and 0 . 59M , respectively ) , for 1 hr at 60°C . Ice cold chloroform was added to each sample at a ratio of 1 to 1 . 9 followed by a 5 min centrifugation at 1000 g . The upper layer was transferred onto 10 mls pure ethanol and kept at −20°C for 1 hour to precipitate the DNA . After 15 min centrifugation at 1200 g the pellet was resuspended in 70% ethanol , washed again ( 1200 g , 5 min ) , resuspended in 100 µl 1X TE buffer ( Sigma Aldrich , UK ) , and stored at −20°C until processing . The 5′-flanking region of the HMOX1 gene containing a ( GT ) n repeat was amplified by PCR using a fluorescein-conjugated sense primer ( HMOX1_microsat_ ( 9/10 ) 5′-AGAGCCTGCAGCTTCTCAGA- 3′ ) and an antisense primer HeOP-1/R HMOX-1mi ( 1/3 ) 5′-ACAAAGTCTGGCCATAGGAC-3′ ) previously described [29] , [34] . Samples that did not amplify with these primers were amplified using a second set of primers; HMOX-2micro-Fwd ( 2/3 ) 5′ CTTTCTGGAACCTT CTGGGAC 3′ designed according to the published sequence [35] and the above antisense primer . Thirty-five cycles were performed under the following conditions; 96° for 1 minute , 95° for 30 seconds , 60° for 30 seconds , 72° for 3 minutes . The sizes of the microsatellites were determined by the use of a laser based automated DNA sequencer; ABI genetic analyser 3130xl ( Applied Biosystems , Forster City , Calif , USA ) , with a cloned fragment of 28 bp that was used as a size marker . Allele scoring was performed using GeneMapper version 4 . 0 ( Applied Biosystems , Forster City , Calif , USA ) , by 2 investigators blinded to the disease status of donors . For analysis purposes , alleles were subsequently divided into “S” ( for short <27 repeats ) , “M” ( for medium 27 to 32 repeats ) , and class “L” ( for long >32 repeats ) , using an established classification [33] , [34] , [36] . To determine the frequency of Glucose 6 Phosphate Dehydrogenase ( G6PD ) deficiency , genomic DNA was genotyped for SNPs A376G ( rs1050829 ) ( G6PD A ) , G202A ( rs1050828 ) ( G6PD A- ) , and T968C ( G6PD A- ) [37] that are mutations causing reduced enzyme activity [38] . In order to infer the frequency of individuals with blood group O , rs8176719 was typed to identify the frame shift deletion at this position that encodes the O allele [39] . Genotyping was performed on a Sequenom MassArray platform [40] . For each reaction 20 ng of gDNA was used and each genotype was replicated three times . Sickle cell status was determined by metabisulfite test and the genotype was confirmed by cellulose acetate electrophoresis [31] . From a subset of participants ( 12 SM , 20 UM ) , 200 µl of whole blood collected at D28 were kept for 3 hours at 37°C , at 40°C ( water bath ) , or stimulated with hemin ( 10 µM , Sigma Aldrich ) at room temperature , to determine inducibility of HO-1 mRNA . An additional 6 samples from healthy controls were processed similarly . After the incubation , samples were diluted 1∶1 in RNAse free water , and transferred into Trizol LS reagent ( Life Technologies ) . RNA processing and HMOX-1 gene expression was carried out as described under qRT-PCR . P . falciparum parasites ( 3D7 clone ) were cultured in vitro as described [31] , and were routinely shown to be mycoplasma free by PCR ( Bio Whittaker ) . Schizont-infected erythrocytes were harvested from synchronized cultures by centrifugation through a Percoll gradient ( Sigma-Aldrich ) . P . falciparum schizont extracts ( PfSE ) was prepared by three rapid freeze-thaw cycles between liquid nitrogen and a 37°C water bath . Lysates of uninfected erythrocytes ( uRBC lysate ) were prepared in the same way . Neutrophils were isolated from whole blood using CD15 beads ( Miltenyi , Germany ) . The purity of neutrophils was assessed by flow cytometry and found to be 95 . 4% ( 95%CI: 93 . 6% to 97 . 1% ) . Neutrophils were cultured for various times either with intact , uninfected red blood cells ( intact uRBC , containing 6 . 6 µM heme ) , uRBC lysate or PfSE ( containing 95 . 3 µM and 99 µM of heme , respectively ) , growth medium ( GM ) , or 100 µM hemin ( Sigma Aldrich ) . Cell supernatants were harvested and assayed for HO-1 by ELISA , and cells were collected into RLT buffer and processed for HMOX1 mRNA as described under qRT PCR . To investigate the impact of hemin-induced HO-1 on the neutrophil respiratory burst , 500 uL whole blood of 4 healthy adult donors was diluted 1∶1 in RPMI ( Gibco ) and incubated for 18 hours at 37°C , in 5% humidified CO2 atmosphere , with different concentrations of hemin ( 0 to 200 µM ) . Half of the cells were used to measure hemin-induced induction of HO-1 mRNA . A small aliquot of cells was stained with a neutrophil marker ( anti CD15ab labeled with APC , Miltenyi ) and the ‘live dead cell stain’ ( Invitrogen ) to assess the viability of neutrophils by flow cytometry after pre-incubation with hemin . The oxidative burst was measured using a validated flow cytometric assay on the remainder of the cells [41] . Briefly , samples were stimulated by adding PMA ( Sigma ) to a final concentration ranging from 0 to 1000 nM for another 15 minutes . Thereafter , dihydrorhodamine 123 ( DHR 123 ) ( final concentration 5 ug/ml ) was added for 5 min . Red cells were lysed ( with ammonium chloride lysis buffer ) and the remaining cells were stained with anti CD15 APC ( Miltenyi ) and the median fluorescence intensity of rhodamine , the fluorescent oxidation product of DHR 123 , was measured in CD15+ cells by flow cytometry . In a separate series of experiments 500 µl of whole blood from another 4 healthy adult donors was incubated with 0–200 µM hemin , either with or without addition of tin protoporhyrin IX dichloride ( SnPP; final concentration 10 µM ) , a non-substrate inhibitor of HO-1 activity [42] . A viability check was performed as described above , and the oxidative burst was induced by stimulation with PMA at a final concentration of 100 nM for 15 min , and the burst was measured as described above . Flow cytometric results , HMOX1 mRNA and HO-1 plasma levels obtained on D0 and D28 were compared using linear regression based on ranks , with a random effect to allow for repeated measurements over time . Significance ( measured at the 5% level ) tests for the effects of malaria group ( SM , UM ) , time ( D0 and D28 ) and their interaction were adjusted for the possible confounding effects of age , gender , duration of prior symptoms and Hb levels , as indicated . Further adjustment for neutrophils was performed for the analysis of WBC , and HO-1 mRNA . Where there was no significant malaria group and time interaction , p-values for the overall comparison of D0 vs D28 are given . Comparisons of SM vs UM are given for each time point separately if the malaria group and time interactions were significant . To allow for the multiple tests resulting from multiple responses and multiple comparisons within a response performed in the model , a false discovery rate ( FDR ) of 5% was assumed . Using the Benjamini and Hochberg approach [43] only tests with a p-value below 0 . 012 have an FDR of ≤5% . Comparison of HMOX1 mRNA and HO-1 plasma levels between different disease entities during acute disease was performed using linear regression based on ranks , adjusting for the confounding effects of age , gender , duration of symptoms , and for neutrophil counts and Hb levels where indicated . A multinomial logistic regression model was employed to explore the association between the exposure ‘L allele containing genotype’ and the outcome of different disease entities . Pearson Chi-squared tests were used to compare proportions amongst more than 2 groups . The magnitude of the differences of the long L allele frequencies reported for African , Asian and European populations was explored with fixation ( FST ) indices , using FSTAT [44] . For the analysis of in vitro induction of HMOX1 mRNA in neutrophils , pairwise comparisons using Wilcoxon matched pairs test were performed , with p values adjusted for multiple comparisons using Holm's step down procedure . Where more than two groups were compared , non-parametric one way ANOVA ( Friedman test for paired samples , Kruskal Wallis test for unpaired samples ) was used with Dunn's post test adjustment for multiple comparisons . Linear regression was performed to assess whether the magnitude of the oxidative burst induced by a given concentration of PMA increases with increasing concentrations of hemin used for pre-incubation . Analyses were performed using Stata version 10 , and Graph Pad PRISM version 5 . 01 .
To identify which leucocyte subsets express HO-1 protein , whole blood collected on days 0 and 28 from 16 SM and 21 UM cases was stained for lineage markers and intracellular HO-1 ( Figure 1A–D ) . In SM , both the proportion and the total number of white blood cells ( WBC ) expressing HO-1 was 2 . 2 and 1 . 3 fold higher during the acute phase compared to convalescence ( both with p<0 . 0001 , both adjusted and unadjusted ) . For UM cases , a smaller difference was observed between time-points that became non-significant after adjustment for percentage ( number ) of neutrophils . ( %WBC UM: p = 0 . 280 [unadjusted: p<0 . 0001]; WBC number UM: p = 0 . 31 [unadjusted: p = 0 . 01] ) . Both the percentage and total number of WBC expressing HO-1 were significantly higher in SM than UM cases on day 0 ( % WBC: p = 0 . 004 [unadjusted: p = 0 . 001]; total WBC count: p = 0 . 009 [unadjusted p = 0 . 008] ) , while no differences were observed on day 28 . Almost all neutrophils stained positive for HO-1 , both on D0 ( median: 93% , CI 95%: 90 . 5–96% ) and D28 ( median: 97% , CI95%: 97–99% ) , with no difference between SM and UM . Similarly , a median of 98% ( CI 95%: 86–99 . 8% ) of neutrophils from healthy controls ( HC ) stained positive for HO-1 ( Figure 1E ) . Western blot of isolated neutrophils from 4 cases confirmed the presence of HO-1 in purified cells ( Figure 1F ) . Monocytes , B cells , T cells and DCs also expressed HO-1 , albeit at lower levels , rarely exceeding 4% of the lymphocyte subset ( Figure 1E ) . In both SM and UM cases the proportions of monocytes , T cells and DCs expressing HO-1 were slightly but significantly higher on D0 compared to D28 ( p = 0 . 002 [unadjusted: p<0 . 0001] , <0 . 0001 [unadjusted: p<0 . 0001] , <0 . 0001 [unadjusted: p<0 . 0001] , respectively; Figure 1E ) . The total number of HO-1 positive neutrophils , monocytes and DCs was significantly higher on Day 0 compared to D28 for both SM and UM cases ( p<0 . 0001 [unadjusted: p<0 . 0001] , p = 0 . 005 , [unadjusted: p = 0 . 001] , p<0 . 0001[unadjusted: p<0 . 0001] , respectively; Figure S1 ) . Irrespective of disease status ( SM , UM , HC ) or time of sampling , a median of 98% ( CI95%: 97 . 3–98 . 6% ) of HO-1 expressing cells were neutrophils , whereas the other cell subsets accounted for less than 1% of HO-1 producing cells in peripheral blood ( Figure 1G ) . RNA was extracted from 128 SM and 134 UM cases at both D0 and D28 from blood collected into PAX tubes to assess HMOX1 mRNA levels by qRT-PCR . Considering that neutrophils were the major source of HO-1 in peripheral blood and that their numbers are slightly higher in acute malaria compared to convalescence [31] , the random effects model ( from which the p values are derived ) additionally adjusted for neutrophil counts to rule out that the observed difference merely reflects different numbers of HO-1 producing neutrophils . For both SM and UM cases a geometric mean 4 . 3 and 3 . 7 fold higher HMOX1 mRNA/18s rRNA ratio was found during acute disease compared to convalescence ( p<0 . 0001 [unadjusted: p<0 . 0001] , for both SM and UM , Figure 2A ) , while no significant difference was observed between SM and UM on D0 or D28 . When HMOX1 mRNA expression of peripheral blood cells was assessed for different disease entities during acute disease ( Figure 2B ) , linear regression with UM as a baseline group adjusting for age , gender duration of symptoms and neutrophil counts revealed a trend towards higher levels with increasing disease severity . This reached borderline significance for children classified as having SRD plus CM ( p = 0 . 04 ) [unadjusted: p = 0 . 19] . In the UM , SP , SA , CM and SRD groups HMOX1 mRNA levels at D0 were elevated similarly ( 3 . 1 to 4 . 8 fold higher [geometric means] than on D28 , p = 0 . 36 , for comparison among groups , Kruskal Wallis test ) , but a significantly higher , 10 . 1 fold increase was measured for the SRD+CM group ( p<0 . 05 compared to UM , Dunn's post test , adjusting for multiple comparisons ) . Considering that previous studies report increased HO-1 protein in plasma of critically ill patients , [47] , we measured HO-1 levels in plasma on days 0 and 28 for 138 SM and 137 UM cases . Similar low levels of HO-1 were observed during convalescence for both SM and UM , but HO-1 concentrations measured during acute disease ( D0 ) were 5 . 7 fold ( SM ) and 3 . 3 fold ( UM ) higher than on D28 ( p<0 . 0001 for both groups [unadjusted: p<0 . 0001 for both groups] , Figure 2C ) , with HO-1 levels in SM being significantly higher than in UM at D0 ( p<0 . 0001 ) [unadjusted: p<0 . 0001] , but not day 28 . Using uncomplicated cases as the baseline group , plasma concentrations of HO-1 measured on day 0 were significantly associated with disease severity in a linear regression model based on ranks adjusting for age , gender , and duration of symptoms ( p<0 . 0001 [unadjusted: p<0 . 0001] ) . In particular , patients with SA , SRD and SRD plus CM had significantly higher HO-1 plasma concentrations ( SA: p = 0 . 004 [unadjusted: p = 0 . 001] , SRD: p<0 . 0001 [unadjusted: p<0 . 0001] , and SRD+CM: p = 0 . 001 unadjusted: p<0 . 0001] ) . After additional adjustment for Hb concentration the overall association between severity and HO-1 levels remained significant ( p = 0 . 004 ) . However , while HO-1 remained significantly elevated in cases with SRD ( p = 0 . 003 ) and SRD plus CM ( p = 0 . 007 ) , the difference previously seen in the SA group was lost ( p = 0 . 12; Figure 2D ) . While the origin of plasma HO-1 remains unclear , the latter observation supports the hypothesis that it is derived at least in part from damaged tissues [47] . By definition , SA cases have lower Hb levels , and a higher degree of hemolysis , which is associated with considerable damage of endothelial cells due to release of iron and heme-containing moieties from hemolysed RBC [48] . Adjusting for Hb may even out the effect of hemolysis-driven damage of endothelial cells that may lead to HO-1 release into plasma . However , additional factors may be responsible for the high HO-1 levels found in patients with SRD , where a significantly higher increase of HO-1 plasma levels was observed between D0 and D28 in patients with SRD or SRD plus CM compared to other entities ( p<0 . 0001 , Kruskal Wallis test ) . While patients with SP , SA or CM had 4 . 8 , 7 . 7 and 5 . 5 fold higher values on D0 compared to D28 , a 10 . 2 and 8 . 9 fold difference between D0 and D28 was measured for patients with SRD plus CM or SRD , respectively . This was significantly higher than the 3 . 3 fold increase observed for UM ( p<0 . 05 , Dunn's post test ) . In summary , the data indicate that HO-1 production is induced during acute malaria in peripheral blood cells and probably in various other tissues , and the effect is greatest in cases with SRD . Interestingly , for both SM and UM , HO-1 levels in plasma correlated well with indirect bilirubin , one of the end products of the reaction catalysed by HO-1 , that is usually seen as an indirect measure of HO-1 activity , and has been established as a marker for disease severity [49] ( r: 0 . 69 , p<0 . 0001 [SM] and r: 0 . 77 , p = 0 . 0012 [UM]; Figure S2 ) . Considering that parasitaemia [%] correlated with HO-1 in plasma ( r: 0 . 5 , p<0 . 0001 ) and the observation that the majority of neutrophils contained HO-1 , we investigated whether encounter with P . falciparum antigens can induce HMOX1 expression in neutrophils . To this end , HMOX1 mRNA expression was determined by qRT-PCR in neutrophils purified from whole blood of 7 donors using magnetic beads and cultured for 3 hours with either growth medium ( GM ) ( negative control ) , 100 µM hemin ( positive control ) , intact uninfected red blood cells ( uRBC ) at 1×108/ml , or freeze – thaw lysates of either uRBC or P . falciparum Schizont extract ( PfSE ) at a concentration equivalent to 1×108 cells/ml . Heme concentrations were measured in all RBC preparations and were found to be 6 . 6 µM ( intact uRBC ) , 95 . 3 µM ( uRBC lysate ) or 99 µM ( PfSE ) . Culture with lysates of both uRBCs and PfSE resulted in a significant increase in median HMOX1 mRNA expression compared to culture in GM ( 2 . 3 and 2 . 7 fold with uRBC ( p = 0 . 04 ) and PfSE ( p = 0 . 01 ) lysate , respectively ) , while HMOX1 mRNA remained at baseline levels in neutrophils cultured with intact uRBCs ( Figure 3 ) . Culture in the presence of hemin led to a significant , 4 . 4 fold median increase in HMOX1 mRNA in neutrophils ( p = 0 . 023; all results adjusted for multiple comparisons ) . To evaluate whether neutrophils could contribute to plasma HO-1 levels by releasing HO-1 , we cultured bead-purified neutrophils from an additional 4 donors using the above described conditions for 3 , 6 , 12 , 24 and 36 hours , respectively , and tested the supernatants for HO-1 protein by ELISA . RNA was isolated from neutrophils for determination of HMOX1 mRNA by qRT-PCR . Although HMOX1 mRNA expression increased up to 6 hrs in response to uRBC , PfSE and hemin no significant amount of HO-1 could be measured in the supernatants for any of the conditions tested ( data not shown ) . Taken together , these data demonstrate that HMOX1 mRNA can be induced in neutrophils in response to hemin as well as RBC lysates containing significant amounts of heme , and suggest that heme released during RBC lysis rather than parasite-derived molecules contribute to this increase . Further , we demonstrate that neutrophils do not release HO-1 in response to these stimuli within 36 hours , and thus are unlikely to contribute to plasma HO-1 . In order to explore a correlation between free heme and HO-1 in plasma from our clinical samples , we attempted to quantify non-protein bound ( free ) heme . After filtration of the samples heme concentrations were barely measurable ( median 1 . 42 µM , CI95%: 1 . 37–1 . 48 µM ) , being 4 . 6 fold lower than that in washed preparations of intact uninfected RBCs . We therefore excluded these data from further analysis . However , both RBC counts and Hb levels that may be regarded as surrogates for the degree of hemolysis , and therefore free heme in acute malaria , showed a negative correlation with plasma HO-1 ( r = −0 . 34 , p<0 . 0001 in both cases ) . The observation that HMOX1 expression can be increased in neutrophils in response to heme prompted us to investigate the role of HO-1 for the neutrophil respiratory burst . The oxidative burst in neutrophils is essential for the host's ability to kill ingested microorganisms and parasites [50] , but intense oxidative stress has also been associated with severe forms of malaria , triggering unspecific tissue damage [10] . To assess the impact of hemin-mediated induction of HO-1 on the neutrophil function , the respiratory burst in response to PMA stimulation ( 0 , 0 . 05 , 0 . 1 and 1 µM ) was measured using a validated flow cytometric whole blood assay [41] after overnight incubation of blood from 4 healthy donors with several concentrations of hemin . As expected , pre-incubation with hemin induced HMOX1 mRNA expression in a dose dependent manner ( r2lin regression = 0 . 9 , p = 0 . 0052 , Figure 4A ) , and did not significantly affect the viability of neutrophils ( Figure 4B ) . While hemin pre-incubation alone did not induce the oxidative burst , stimulation with 0 . 05 , ( 0 . 1 ) or [1 . 0] µM PMA reliably induced an oxidative burst in 94 . 4% , 96 . 5% and 96 . 9% of neutrophils , respectively ( p = 0 . 052 , paired measures ANOVA ) . For each PMA concentration , pre-incubation with different hemin concentrations did not affect the proportion of neutrophils responding with an oxidative burst ( Figure 4C ) . However , the magnitude of the oxidative burst induced with 0 . 05 µM and 0 . 1 µM PMA in neutrophils increased significantly with increasing concentrations of hemin used during the pre-incubation ( r2lin regression 0 . 92 [0 . 05 µM PMA] and 0 . 84 [0 . 1 µM PMA] , with p = 0 . 037 [0 . 05 µM PMA] and 0 . 04 [0 . 1 µM PMA] , Figure 4D ) . When 1 µM PMA was used , the burst could be maximally stimulated without preincubation with heme . This suggests that hemin-mediated induction of HO-1 may prime neutrophils to mount a stronger oxidative burst . To further investigate whether the observed effect is mediated by hemin-induced HO-1 , we repeated the experiment in the presence and absence of 10 µM tin protoporphyrin ( SnPP ) , an inhibitor of HO-1 activity , using whole blood from another 4 healthy volunteers in separate experiments . At this concentration , SnPP did not significantly affect neutrophil viability compared to pre-incubation with hemin alone ( p = 0 . 125 [0 µM hemin] , 1 . 0 [0 . 05 µM hemin] , 0 . 125 [0 . 1 µM hemin] and 0 . 625 [1 µM hemin] , Wilcoxon signed rank test ) . Further , the addition of 10 µM SnPP did not affect the proportion of neutrophils responding with an oxidative burst to stimulation with 0 . 1 µM PMA , compared to pre-incubation with hemin alone ( p = 0 . 375 [0 µM hemin] , 0 . 25 [0 . 05 µM hemin] , 0 . 875 [0 . 1 µM hemin] and 0 . 625 [1 µM hemin] , Wilcoxon signed rank test ) . However , hemin pre-incubation in the presence of 10 µM SnPP abrogated the hemin dose-dependent increase of the oxidative burst ( r2lin regression 0 . 88 , p = 0 . 035 [no inhibitor] and r2 = 0 . 22 , p = 0 . 23 [with inhibitor] , Figure 4E ) . Taken together , the data indicate that heme-mediated induction of HO-1 primes the oxidative burst in neutrophils . Apart from the availability of its substrate heme , other factors may induce HO-1 . In animal models [51] , and human hepatoma cell lines [52] HO-1 could be induced by heat exposure . However , in human alveolar macrophages or erythroblastic cell lines [53] , as well as in PBMC [54] thermal stress failed to induce HO-1 . Since we observed a weak but significant positive correlation between temperature on admission to the clinic and HO-1 plasma levels ( r: 0 . 266 , p<0 . 0001 ) , we explored whether a temperature of 40°C maintained over 3 hours would induce HMOX1 mRNA in human whole blood , using samples collected on D28 from 12 SM , 20 UM cases and 6 HC . Samples kept at 37°C or cultured with hemin served as negative and positive controls , respectively . In all three groups ( SM , UM , HC ) both incubation at 40° as well as with hemin resulted in a significant upregulation of HMOX1 mRNA compared to cells kept at 37°C , with no significant differences observed between groups ( Figure 5A ) . In a separate experiment using blood from 5 healthy donors we verified that incubation at 40°C for 3 hours did not lead to a significant change in hemolysis markers such as heme , haptoglobin or LDH , compared to incubation at 37°C ( data not shown ) . For murine macrophages , IL-10 has been shown to induce HO-1 [55] . We therefore correlated HMOX1 mRNA to IL-10 mRNA from D0 samples for 58 SM and 59 UM cases for which IL-10 mRNA measurements were available from a previously reported study [31] . For both SM and UM a positive correlation ( SM: r = 0 . 59 , p<0 . 0001; UM: r = 0 . 37 , p = 0 . 0037 ) was found in whole blood , compatible with a role for IL-10 as an inducer of HO-1 in human blood cells ( Figure 5B , C ) . The extent to which HMOX1 is upregulated in an individual in response to a defined stimulus may be influenced by genetic polymorphisms in the promoter region of the HMOX1 gene of which several have been described , ( reviewed by [16] ) . Of particular interest , a ( GT ) n repeat length polymorphism regulates the promoter activity and gene expression , with short repeats ( <27 repeats ) resulting in an increased transcription of HMOX-1 compared to alleles with long repeats ( >32 repeats ) [33] , [56] . Associations of the ( GT ) n polymorphism with disease outcomes have been explored in numerous association studies for various diseases , recently reviewed in [17] . To investigate whether the ( GT ) n polymorphism is associated with disease severity in malaria , we genotyped this microsatellite for 142 SM and 151 UM cases for whom DNA samples were available . In the study population ( GT ) n variation ranged from 13 to 45 repeats , and the allele frequency distribution was trimodal with peaks at 26 , 30 and 39 repeats ( Figure 6A ) . Using a previously established classification [33] , [34] , [36] , alleles were divided into 3 groups: “S” ( <27 repeats ) , “M” ( 27 to 32 repeats ) , and “L” ( >32 repeats ) . The frequency of “S” alleles was significantly higher in SM cases ( 0 . 50 vs . 0 . 37 , p = 0 . 0021 ) , whereas the frequency of “L” alleles was significantly higher in UM cases ( 0 . 36 vs 0 . 26 , p = 0 . 009 , Figure 6B ) . The frequency of different alleles according to disease entities is shown in Figure 6C . Based on the “S-M-L” classification , six genotypes ( SS , SM , MM , ML , LL and SL ) were defined . As shown in Figure 6D , the “SS” genotype is significantly more frequent in SM cases compared to UM cases ( 27 . 5% vs . 8% , p<0 . 00001 ) . Conversely , the “SL” genotype is more prevalent in UM cases ( 35% vs . 21 . 8% , p = 0 . 012 ) . Figure 6E depicts the frequency of the 6 genotypes for each disease entity . When dichotomized as described previously [34] , [56] into genotypes containing at least one “L” allele ( LL , ML , SL = L-carriers; labeled green in Figure 6E ) versus non-L carriers ( SS , SM , MM; labeled red in Figure 6E ) , SM patients were 53% less likely to be L carriers than UM cases ( OR: 0 . 47 , CI 95%: 0 . 29 to 0 . 75 , p = 0 . 002 ) . When L carrier status was analysed in relation to different disease entities using multinomial logistic regression , cases with SRD and SRD plus CM were significantly less likely to be L carriers ( 85% and 74% less likely , respectively ) compared to uncomplicated cases ( Table 1 ) . Of note , 9 out of the 10 individuals who succumbed to malaria were non-L carriers , compared to 53 . 4% non-L carriers within the remaining severe cases ( p = 0 . 043 , Fisher's exact test ) , or 37% non-L carriers within UM cases ( p = 0 . 003 , Fisher's exact test ) . We further examined whether ethnicity was associated with either disease outcome , frequency of L alleles or L allele containing genotypes . We found that ethnicity was not associated with being a SM or UM case ( p = 0 . 294 ) , or with any of the particular disease entities ( p = 0 . 112 ) . There was also no difference in the frequency of the L allele ( p = 0 . 063 ) or of the L allele-containing genotypes ( p = 0 . 088 ) among ethnic groups . To determine a possible confounding effect of some of the major factors known to determine disease severity , we measured the frequency of sickle cell trait , blood group O and G6PD deficiency , and the level of HRP-2 in our study population . Hemoglobin S ( HbS ) confers protection from severe malaria in humans [57] , and was recently shown to induce HO-1 in murine hematopoietic cells [58] . Blood group O has been associated repeatedly with reduced risk of severe malaria [59] , and so has been G6PD deficiency [60] , [61] , as hypothesized by Allison [62] . In agreement with two previous studies using samples from this geographic area [37] , [63] , we confirmed the 968C/376G allele as the most common G6PD A- deficiency allele in our study population ( 6 . 26% ) . The latter study from the Gambia [37] suggested that heterozygous females and hemizygous males are relatively protected from severe disease . The histidine-rich-protein 2 ( HRP-2 ) has been proposed as a surrogate for parasite biomass and is considered to be associated with disease severity [64] . Figure S3 shows the frequency of these factors according to disease group and HMOX1 genotype . In our study population , carriage of the sickle cell trait , G6PDA− , or blood group O were neither associated with disease severity , nor with HMOX1 genotype . As expected , HRP-2 was associated with disease severity , but showed no association with HMOX1 genotypes . To examine whether the genotype of the ( GT ) n polymorphism was associated with the magnitude of HMOX1 mRNA induction in peripheral blood leucocytes in response to a defined stimulus , the data for hemin and heat-mediated induction of HMOX1 mRNA in whole blood collected on D28 shown in Figure 3B were plotted according to L carrier status ( Figure 7 ) . Both L and non L carriers had similar HMOX1 expression at baseline ( p = 0 . 65 ) , and showed a significant 2 . 5 fold ( L carriers , p = 0 . 0002 ) , or 4 . 3 fold ( non L carriers , p = 0 . 002 ) increase in HMOX1 mRNA levels in response to heat . When hemin induced HMOX1 mRNA levels were compared to baseline a 4 . 7 fold ( L carriers , p = 0 . 0002 ) , or 17 . 1 fold ( non L carriers , p = 0 . 0039 ) increase was observed . Importantly , the median HMOX1 mRNA measured in non-L carriers after hemin stimulation was 3 . 9 fold higher ( p = 0 . 0028 ) than was observed in L carriers ( Figure 7 ) . In response to heat stimulation , non L carriers had 1 . 9 fold higher mRNA levels compared to L carriers ( p = 0 . 183 ) . After Bonferroni's adjustment for multiple comparisons the significance threshold for these tests becomes 0 . 007 . The differential HMOX1 mRNA expression of L and non L carriers in response to hemin is in line with what has been reported from human lymphoblastoid cell lines treated with H2O2 [33] , and demonstrates that in our study population the magnitude of HMOX1 mRNA expression in peripheral blood leucocytes in response to a defined stimulus is associated with the length of the ( GT ) n repeat . To investigate the possibility that , in West Africans , the ( GT ) n microsatellite is tightly linked to ( or “tagging” ) unexplored functional variants in alternative genes , we analyzed the extent of linkage disequilibrium ( LD ) at and around the HMOX1 locus , using HapMap data for Nigerian Yoruba . In this West African population , the ( GT ) n microsatellite in the promoter lies in a 6KB LD block that extends from rs2071746 ( 5′ ) to rs11912889 ( 3′ ) , encompassing approximately half of the HMOX1 gene . According to these data , the ( GT ) n microsatellite would effectively tag only variants within HMOX1 , but no other genes . Moreover , the two genes immediately flanking the HMOX1 gene ( TOM1 33 kb 5′ and MCM5 6 kb 3′ of HMOX1 ) are not obvious candidates for malaria susceptibility ( Figure S4 ) . Future comparative studies of LD would be ideally conducted in the Gambian ethnic groups , and will benefit from whole genome sequence data likely to emerge from initiatives including the 1000 Genomes Project [65] . The frequency of the long ( >32 copy ) repeat alleles was similar to that recently reported from Angola [30] , but significantly higher than was reported from populations living in areas where malaria is not endemic , such as Europe ( French [66] , German [67] ) , and North America ( Caucasians , [68] ) or Asia ( Japanese [34] , [36] , [69] , Karen people from Myanmar [29]; see Table S2 in Text S1 ) . The magnitude of the differences was therefore explored with fixation ( FST ) indices . Differences between the Gambian and North American ( FST = 0 . 29 ) , or European populations ( Gambia vs France , FST = 0 . 21; vs Germany , FST = 0 . 14 ) were slightly higher than the average for a genome-wide sample of polymorphisms ( FST = 0 . 126 , [70] ) , whereas differences between Gambian and Asian populations ( FST for Gambia vs Myanmar , or vs Japan ) were slightly less than the genome-wide average . In the Angolan population allele frequency of the long repeat alleles was higher than in The Gambia , and therefore slightly more divergent from the non-African population samples ( Table S3 in Text S1 ) . When available data from each continent were pooled , the largest FST values were observed for comparisons between Africa and America ( FST = 0 . 33 CI 95%: 0 . 29 to 0 . 38 ) , Africa and Europe ( FST = 0 . 25 CI 95%: 0 . 2 to . 29 ) , and Africa and Asia ( FST = 0 . 21 CI 95%: 0 . 18 to 0 . 25; Table S4 in Text S1 ) .
Inspired by elegant studies in murine malaria models clearly demonstrating that the induction of HO-1 helps prevent severe forms of malaria [9] , [10] , and the intriguing possibility either to manipulate HO-1 activity pharmaceutically [71] , [72] or to mimic its effect by administering CO [20] , we explored the role of HO-1 in children with severe and uncomplicated P . falciparum infection . During acute disease , the number of WBC staining positive for HO-1 , the HMOX1 mRNA levels , and the HO-1 protein concentrations in plasma were significantly higher than during convalescence , being highest in the most seriously ill patients presenting with SRD . While the association between elevated HO-1 and severe illness we and others [47] , [68] , [73] observed might merely reflect an appropriate response insufficient in magnitude and/or occurring too late , the association between short ( GT ) n repeat alleles and increased inducibility of HO-1 in vitro , and more severe disease suggests that HO-1 levels above a certain threshold may be part of the causal pathway leading to severe disease and death . The association between short ( GT ) n repeat alleles in the HMOX1 gene promoter region ( resulting in enhanced HMOX1 mRNA expression ) with CM observed in a small study in Myanmar [29] , and more recently , in Angola [30] supports this notion . Intriguingly , both our study and the study carried out in Angola [30] observed a distinct peak around 39 ( GT ) n-repeats , which is in contrast to previous data from populations from non-malaria endemic areas [34] , [36] , [66] , [67] , [68] , [69] . We have noted that the FST indices for comparisons between these two African populations and those from non-malaria endemic areas were slightly above the average for a genome-wide sample of polymorphisms [70] , although more detailed study of polymorphism in this gene would be needed to test a neutral hypothesis . The possibility that the relatively high frequency of long ( GT ) n repeats in Africa may have resulted from a survival advantage from P . falciparum should encourage investigation to prospect more powerfully for evidence of selection on this locus , given that malaria has been one of the most powerful selective forces acting on the human genome [74] . The fact that increased levels of indirect bilirubin and COHb – both end products of the reaction catalyzed by HO-1 – are widely recognized as independent markers for mortality in critically ill patients [23] , [49] , and that long ( GT ) n alleles were associated with less frequent multi organ dysfunction in European ICU patients irrespective of the specific diagnosis [47] , make it tempting to speculate that a high HO-1 response is disadvantageous for acute inflammatory conditions in general . In fact , HO-1-induced CO may reduce oxygen carrying capacity in the blood and tissue oxygenation , ultimately leading to metabolic acidosis . Furthermore , increased HO-1 may result in low nitric oxide ( NO ) levels [75] . This may constitute another pathway by which over-expression of HO-1 contributes to severe disease based on the beneficial effects ascribed to inhaled NO on endothelial function in patients with adult respiratory distress syndrome ( ARDS ) [76] , and the accumulating evidence that depletion of NO contributes to severe malaria [77] . Considering that HO-1 overexpression in the liver leads to an increase in parasite liver load [11] , and that the major benefit of RTS , S ( a malaria vaccine that partially reduces the parasite burden in the liver ) is the reduction of severe disease , it is tempting to speculate that particularly high HO-1 levels in the liver might contribute to severe malaria in man . These findings differ from the role HO-1 plays in preventing severe disease in mice [8] , [10] . An attempt to reconcile these observations needs to take into account that mice in contrast to humans lack the ( GT ) n repeat polymorphism [18] . The functional relevance of the human ( GT ) n promoter length polymorphism indicated here and elsewhere [33] , [56] suggests that humans might have a greater genetically determined variability of HMOX1 expression than exists among inbred mouse strains . The infection of BALB/c mice with P . berghei ANKA , for example , results in a fairly homogeneous 3–4 fold upregulation of HMOX1 mRNA 6 days post infection [9] , comparable to what we observed in uncomplicated cases . However , a more than 10 fold difference was measured in the most seriously ill patients of the SRD plus CM group . In fact , HO-1 has both pro-and anti-oxidant properties [24] , and dependent on its amount , diametrically opposed effects have been described: Several in vitro studies have shown that moderate ( less than 5 fold ) induction of HO-1 is associated with protection against heme-mediated damage [78] , while higher levels ( greater than 10 fold ) resulted in loss of cytoprotection [79] . Using HO-1 transfected hamster fibroblasts with either low , moderate , or high HO-1 activity , Suttner et al . demonstrated how HO-1 related cytoprotection turns into HO-1 mediated oxidative injury with increasing HO-1 expression [27] . Importantly , ferrous iron accumulated in high HO-1 expressing cells , and the addition of iron chelators or specific HO-1 inhibitors significantly reduced all measures of oxidative tissue injury [27] . The notion that high levels of HO-1 activity may potentiate , rather than attenuate ROS toxicity , and that this is related to the increased availability of ferrous iron is further supported by several in vitro studies [80] , [81] , as well as studies in animals [82] , [83] . Thus , we hypothesize that , up to a certain level , induction of HO-1 is protective , while excessive upregulation of HO-1 in response to an inflammatory stimulus is deleterious . The clinical relevance of free iron in severe malaria infections has been investigated previously , and high transferrin saturation ( which indicates mobilization of ferrous iron ) was associated with delayed recovery from coma in CM patients [84] . While HO-1 was not measured in this trial , a more recent study in patients with ARDS established that transferrin saturation increased in parallel to HO-1 [85] , strengthening the idea that in vivo high HO-1 levels may result in a clinically relevant increase of ferrous iron . However , results of studies on the usefulness of iron chelation therapy with desferroxiamine in malaria patients have been inconclusive [86] , [87] . We also provide mechanistic evidence that hemin-mediated HMOX1 mRNA expression in neutrophils potentiates the magnitude of the neutrophil oxidative burst , and propose that a genetic predisposition to high levels of HO-1 may cause an otherwise protective response to become deleterious . By demonstrating how the neutrophil oxidative burst may influence disease severity , our data help to determine the role of this cell subset in the pathogenesis of severe malaria , which is currently ill-defined . Earlier in vitro studies established that iRBCs can be phagocytosed by neutrophils [88] , and can activate them to produce ROS [89] , which can kill parasites [50] , [90] . In line with this , the amount of ROS produced by neutrophils from children with P . falciparum infection was associated with faster parasite clearance [91] , and clinical protection from P falciparum correlated with neutrophil respiratory burst induced by merozoite antigens opsonized by antibodies [92] , proposing neutrophils as an efficient defense mechanism . However , in murine models of severe malaria , early depletion of neutrophils prevents experimental CM [93] , as well as sequestration of neutrophils to the lungs and reduces mortality [94] , demonstrating that neutrophil effector mechanisms are capable of contributing to severe disease . Taken together , this suggests that an early neutrophil oxidative burst may benefit the host by contributing to initial parasite control , while a genetic predisposition towards an enhanced oxidative burst as suggested by our data may result in enhanced damage of endothelial cells , especially in conditions where neutrophils become sequestered in capillaries . Consistent with our data , a genome-wide analysis of the host response to malaria recognized neutrophil-related gene expression responses as the principal pattern distinguishing convalescent from acute malaria patients , and the HMOX1 gene was amongst the genes showing a stepwise increase with increasing severity [14] . The nature of the association between HO-1 in plasma and severe disease , and whether or not soluble HO-1 has a causal role in the pathogenesis of severe disease isn't entirely clear , but we consider it unlikely that HO-1 is functional in plasma . HO-1 is an intracellular enzyme [95] , [96] , and a molecule transporting HO-1 into the extracellular compartment has not been described . Furthermore , enzymatic functionality of HO-1 requires its C terminal end to be located in the membrane of the endoplasmic reticulum ( ER ) [97] , and several electrons to be provided by an ER-bound NADPH cytochrome p-450 [98] , [99] . Like Saukkonen et al . [47] , we speculate that plasma HO-1 leaks from damaged tissue , and the association between plasma HO-1 and severe disease is primarily driven by the degree of tissue damage and not the degree of HO-1 induction itself . It is therefore not surprising that the HMOX1 genotypes show no clear association with plasma HO-1 ( Figure S5A ) . Based on the negative association we observed between plasma HO-1 and RBCs or Hb ( both can be seen as markers of hemolysis in malaria ) , and considering that the release of free iron and heme-containing moieties that occurs during hemolysis leads to considerable damage of endothelial cells [48] , [100] , [101] , we propose damaged endothelial cells as an important source of plasma HO-1 . This study had several limitations . In order to study HO-1 protein levels in WBCs according to disease entities or ( GT ) n repeat polymorphisms , flow cytometric examination of blood from more participants would have been required . In view of the results we obtained for the comparison of in vitro stimulated whole blood showing a significant difference in HMOX1 mRNA expression between L and non L carriers in response to a defined amount of hemin ( Figure 7 ) , the lack of an association between HMOX1 genotype and HMOX1 mRNA expression ex vivo ( Figure S5B ) or the lack of a clear difference in HMOX1 mRNA levels between SM and UM cases may be surprising . However , it is important to note that in contrast to the in vitro experiment where the nature and the strength of the stimulus is known , in vivo HMOX1 mRNA expression may be driven by a variety of stimuli . To explore this further , it would have been necessary to measure various factors known to induce HMOX1 mRNA expression in vivo . In this regard , our inability to measure free heme in plasma , known to be a major stimulus for HO-1 , was an unforeseen limitation . We can therefore only speculate that inter-individual differences in the nature and amount of HMOX1 mRNA inducing factors may have obscured the effect of the HMOX1 promoter polymorphism on HO-1 levels in vivo . With this caveat in mind , our data do indicate that a genetic factor affecting high HO-1 levels in response to heme is associated with more severe disease and death from malaria . We identified neutrophils as the predominant source of HO-1 in peripheral blood , provide evidence that increasing HMOX1 mRNA expression in these cells enhances the oxidative burst , and suggest that this may constitute a mechanism by which sequestered neutrophils cause tissue damage , thereby contributing to severe pathology . Considering that similar associations between high HO-1 and illness severity have been observed in other conditions [47] , [73] , limiting HO-1 activity pharmacologically with tin protoporphyrin IX [71] or other inhibitors may be an interesting therapeutic option worth considering . An alternative therapeutic strategy might alter the distribution of HO-1 induction to particular cell types by therapeutic administration of haptoglobin or hemopexin , which both might limit the toxicity of free heme and restrict the uptake of cell free-hemoglobin and heme , and consequently upregulation of HO-1 , to those cells bearing receptors for these molecules .
|
HO-1 is an important anti-inflammatory enzyme induced by several stimuli associated with critical illness . In humans , the amount of HO-1 produced is influenced by a genetic polymorphism in the gene promoter region . Using Plasmodium falciparum malaria that can cause a sepsis-like syndrome as an example , we characterize the associations between the ( GT ) n polymorphism , HO-1 protein levels and HMOX1-mRNA expression with severity of malaria in 307 Gambian children . Our results support the functionality of this polymorphism , demonstrate that P . falciparum infections increase HO-1 levels , and indicate that a genetic predisposition to strongly upregulate HO-1 is associated with severe forms of malaria and increased risk of dying . We identify neutrophils as the main HO-1-producing blood cells , and provide evidence that hemin-mediated induction of HMOX1 in neutrophils in vitro enhances the oxidative burst . In this way sequestered neutrophils may contribute to oxidative damage of endothelial cells , which may be part of a causal pathway explaining the association between short ( GT ) n repeats and increased disease severity . Our findings imply that the beneficial effects of HO-1 may be limited to a narrow window of concentrations , which should be born in mind when considering the therapeutic potential of manipulating HO-1 induction in critically ill patients .
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"medicine"
] |
2012
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HMOX1 Gene Promoter Alleles and High HO-1 Levels Are Associated with Severe Malaria in Gambian Children
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Enterococcus faecium , an ubiquous colonizer of humans and animals , has evolved in the last 15 years from an avirulent commensal to the third most frequently isolated nosocomial pathogen among intensive care unit patients in the United States . E . faecium combines multidrug resistance with the potential of horizontal resistance gene transfer to even more pathogenic bacteria . Little is known about the evolution and virulence of E . faecium , and genomic studies are hampered by the absence of a completely annotated genome sequence . To further unravel its evolution , we used a mixed whole-genome microarray and hybridized 97 E . faecium isolates from different backgrounds ( hospital outbreaks ( n = 18 ) , documented infections ( n = 34 ) and asymptomatic carriage of hospitalized patients ( n = 15 ) , and healthy persons ( n = 15 ) and animals ( n = 21 ) ) . Supported by Bayesian posterior probabilities ( PP = 1 . 0 ) , a specific clade containing all outbreak-associated strains and 63% of clinical isolates was identified . Sequencing of 146 of 437 clade-specific inserts revealed mobile elements ( n = 74 ) , including insertion sequence ( IS ) elements ( n = 42 ) , phage genes ( n = 6 ) and plasmid sequences ( n = 26 ) , hypothetical ( n = 58 ) and membrane proteins ( n = 10 ) , and antibiotic resistance ( n = 9 ) and regulatory genes ( n = 11 ) , mainly located on two contigs of the unfinished E . faecium DO genome . Split decomposition analysis , varying guanine cytosine content , and aberrant codon adaptation indices all supported acquisition of these genes through horizontal gene transfer with IS16 as the predicted most prominent insert ( 98% sensitive , 100% specific ) . These findings suggest that acquisition of IS elements has facilitated niche adaptation of a distinct E . faecium subpopulation by increasing its genome plasticity . Increased genome plasticity was supported by higher diversity indices ( ratio of average genetic similarities of pulsed-field gel electrophoresis and multi locus sequence typing ) for clade-specific isolates . Interestingly , the previously described multi locus sequence typing–based clonal complex 17 largely overlapped with this clade . The present data imply that the global emergence of E . faecium , as observed since 1990 , represents the evolution of a subspecies with a presumably better adaptation than other E . faecium isolates to the constraints of a hospital environment .
Once not recognized as clinically relevant microorganisms , enterococci currently are the third most frequently isolated nosocomial pathogen from intensive care unit patients in the United States [1] . The emergence of enterococci as nosocomial pathogens in the 1990s was associated with a gradual replacement of Enterococcus faecalis by Enterococcus faecium and an epidemic rise of vancomycin-resistant E . faecium [2] . In Europe , though , vancomycin-resistant enterococcus ( VRE ) initially was only found to colonize healthy individuals , and nosocomial VRE outbreaks have only recently begun to emerge . This epidemiological difference between the US and Europe presumably resulted from massive bioindustrial avoparcin usage in Europe , which created a VRE reservoir among farm animals with spillover via the food chain to consumers [3–8] . Abundant antibiotic use in hospitals , most notably of vancomcyin and cephalosporins , was the presumed cause of VRE emergence in US hospitals [9] . The emergence of VRE as a nosocomial pathogen in countries with polyclonal endemicity seems irreversible , despite enforced hygiene measures and restricted antibiotic prescription policies [10] . Nevertheless , despite unsuccessful eradication , a sustained reduction in prevalence rates has been reported [11] . Also , successful control of monoclonal outbreaks in countries with low VRE prevalence has been reported [12] . Recent reports on the transfer of vancomycin resistance from enterococci to methicillin-resistant Staphylococcus aureus [13–16] stressed the need to better understand molecular epidemiology , as well as transmissibility and virulence of enterococci , to control further spread and develop treatment and eradication strategies . Yet , little is known about the virulence and pathogenesis of E . faecium . Apart from antibiotic resistance genes , only the enterococcal surface protein ( esp ) gene and the hyaluronidase gene have been epidemiologically associated with infections and documented hospital outbreaks [17–20] . The esp gene is contained on a putative pathogenicity island ( PAI ) , but functional studies on any of these E . faecium genes have not been performed yet [18] . Previously , we described the population structure of E . faecium with multi locus sequence typing ( MLST ) , relying on the variation in silent mutations in short sequences from seven housekeeping genes [21 , 22] . This population shows host specificity , and a globally present hospital subpopulation , clonal complex ( CC ) 17 , is responsible for most outbreaks and colonization of hospitalized patients [22] . Apart from linkage with the putative PAI , not much is known about the gene content of this subset and whether , based on gene content , a similar population can be characterized . Microarray-based comparative genomic hybridization ( CGH ) has provided novel insights into the diversity and adaptability of several bacterial populations , such as the relevance of lateral gene transfer and recombination , which both result in mosaic genome structures in Helicobacter pylori [23 , 24] , Salmonella species [25] , Escherichia coli [26 , 27] and S . aureus [28–30] . In addition , CGH has been used to study evolution and to decipher bacterial virulence and host specificity [31–33] . In this respect , CGH has major advances over more conventional genotyping methods , as it also provides insights into the core genome and accessory genes , which may help to further disclose gross signatures of niche differentiation . Almost all CGH studies originate from PCR-based arrays of amplified open reading frames ( ORFs ) derived from one or multiple annotated sequenced strains , sometimes completed with additional genes not present in the sequenced strains . This approach , though expensive , ascertains coverage of a whole genome . Unfortunately , this approach is not possible for E . faecium , as there is no complete annotated genome sequence . Moreover , the partially sequenced , but still not annotated , E . faecium DO strain doesn't contain the putative PAI , one of the few known gene clusters associated with virulence and epidemicity . For all these reasons , a different approach is necessary for a broad and detailed genomic analysis of E . faecium . In the present study , we performed comparative phylogenomics to study the genome composition population-wide as well as population dynamics of E . faecium using a mixed whole-genome array constructed from a shotgun library of nine strains from different ecological and genetic backgrounds , including the sequenced E . faecium DO strain . DNA–DNA hybridizations of 97 epidemiologically and genotypically different isolates to the array identified a distinct , globally dispersed clade containing all epidemic isolates and the majority of clinical isolates . Isolates within this clade harbored a large content of accessory genes mainly concentrated on two contigs in E . faecium DO . Furthermore , hybridization data revealed high rates of recombination and deletion resulting in mosaic-structured genomic regions . Insertion sequence ( IS ) elements were predicted to be prominent loci in the bifurcation of this clade , and probably have played a major role in adaptation and diversification of hospital-associated E . faecium strains belonging to this clade .
In total , 3 , 474 spots ( n ( genomic[g] ) = 2 , 727 , n ( plasmid[p] ) = 712 , n ( extra spotted genes ) = 35 ) met the quality criteria ( see Materials and Methods ) and were included in this study . Since the microarray consists of a mixture of nine strains , only the genomic coverage of core genes can be determined . The total nucleotide and gene detection coverage of the E . faecium core genome was estimated to be 80% and 93% , respectively , using algorithms by Akopyants et al . and Moore et al . , respectively [34 , 35] . Obviously , the microarray coverage of strain-unique accessory genes will be lower . The detected Cy5/Cy3 ratios of the 3 , 474 spots were subjected to log2 transformation and GACK normalization ( see Materials and Methods ) . Duplo hybridizations of seven isolates clustered as nearest neighbors in hierarchical clustering , each with 92% identical GACK values ( 98% for binary output ) in spot profile , indicating that microarray results were highly reproducible . Log2-transformed data is available in Dataset S1 . Validation of six ORFs located on ten inserts by Southern hybridization followed the presence and absence of spots-transformed array data ( unpublished data; see Materials and Methods ) . Among a selection of the accessory genome of 437 clone inserts , a subselection of 146 inserts ( explained elsewhere in this section ) was partially sequenced for further analysis . Sequence alignments revealed 16 redundant genes from 42 inserts and seven redundant plasmid loci from 27 inserts ( represented by >100 base pair–overlap in two to four spots ) . Eight of these 16 genes ( 27 of 42 inserts ) were present in multiple copies in the E . faecium DO genome; therefore , actual redundancy among the libraries is limited . Phylogenomic analysis with the microarray data using a Bayesian-based phylogenic method identified a distinct clade ( Bayesian posterior probabilities [PP] = 1 . 0 ) containing all epidemic isolates ( n = 18 ) , 63% of clinical isolates ( n = 22/35 ) , 33% of hospital surveillance isolates ( n = 5/15 ) , no community survey isolates , 7% ( n = 1/15 ) of animal isolates , and 0% ( n = 0/3 ) of environmental isolates ( Figure 1 and Table 1 ) . E . faecium DO ( E1794 in Table 1 ) is also contained in this clade . Throughout the rest of the article this clade is referred to as hospital clade , and hospital-associated E . faecium strains belonging to this clade are referred to as hospital clade strains . The bifurcation was supported by complete linkage transversal hierarchical clustering with GACK-transformed data of graded output , and by maximum parsimony analysis on binary GACK-transformed data ( Table 1 ) . With the latter two techniques , only one isolate was clustered differently . Internal branching within and outside this specific clade was less reliable ( mostly PP = 0 . 50 ) . The identification of a distinct hospital clade indicates the successful evolution of an E . faecium clone that adapted to its niche and diversified . The E . faecium core genome defined as genomic spots present or divergent ( GACK > −0 . 50 ) in each of the strains consisted of 65% of all genomic spots ( n ( g ) = 1 , 772 ) ( Figure 2 ) . The clone inserts of 35 randomly selected spots were PCR-amplified , partially sequenced , and blasted to GenBank; these inserts encoded 37 ( partial ) genes ( Table S1 ) . Twenty-seven inserts showed highest similarity with 30 different E . faecium DO genes located on different contigs , two with two different E . faecium DO sequences with no corresponding ORF , and six with 12 E . faecalis V583 genes ( Table S1 ) . Because of array design ( random shearing ) , more than one ( partial ) gene could be located on one insert . Assigned functions by clusters of orthologous genes ( COGs ) defined genes to be involved in basic cell function ( Table S1 ) . Among all other spots ( n ( g ) = 955 , n ( p ) = 712 , n ( extra spotted genes ) = 35 ) representing the accessory genome , 437 spots ( n ( g ) = 165 , n ( p ) = 261 , n ( extra spotted genes ) = 11 ) were ≥80% specific for and significantly associated with the hospital clade ( χ2 test followed by false discovery rate [FDR] correction ( p < 0 . 01 ) ) ( Figure 2 ) . The sensitivities for presence of these spots in clade-specific strains varied from 20% to 98% , indicating that some spots were present in almost all isolates belonging to the hospital clade , while other inserts were only present in a small subset ( Table 2 ) . The inserts from a selection of 146 spots ( n ( g ) = 86 , n ( p ) = 60 ) ( criteria in Materials and Methods ) were partially sequenced and blasted in GenBank for significant similarity . Sequencing revealed 175 ORFs with varying similarity to genes present in the E . faecium DO genome ( 131 ORFs located on 104 inserts ) , on E . faecium plasmids ( 21 ORFs on 19 inserts ) , in E . faecalis V583 ( six ORFs on eight inserts ) , and in other bacterial species ( 17 ORFs ) ( see Table 2 ) . Nine sequences showed no significant similarity at all ( Table 2 ) . Furthermore , 11 separately spotted PCR products were identified as hospital clade–specific . Hospital clade–specific sequences were identical or similar to genes from 13 different COGs ( Table 2 ) . By far the largest COG , group L consists of 80 ORFs ( 46% of 175 ORFs ) and contains genes involved in DNA replication , recombination , and repair . This group mainly comprises IS elements and transposases ( n = 42 ) and plasmid DNA sequences ( n = 26 ) . COG groups R and S , representing genes with a general function prediction and unknown function , respectively , are the second most prominent COG groups and include 55 ( 31% ) of the ORFs . ORFs identical or similar to genes encoding metabolic pathways ( COG G , E , F , H , P ) , and to proteins involved in cell wall and membrane biogenesis ( M ) and transcription ( K ) , occurred less frequently ( 17 , 9 , and 12 times , respectively ) . Among all hospital clade–enriched ORFs , eight inserts represented five different antibiotic resistance genes ( streptomycine adenylyltransferase; aminoglycoside phosphotransferase , which is similar to aph ( 3′ ) -III; chloramphenicol O-acetyltransferase; an aminoglycoside-streptothricin resistance cassette [aadE and sat4 from the aadE-sat4-aphA cluster] , and an aminoglycoside resistance cassette [aac ( 6' ) -Ie-aph ( 2" ) -Ia and aac ( 6' ) -Ie-aph ( 2" ) -Ia2] ) . Eleven ORFs were identical or highly similar to six different ( putative ) phage genes . Thirty-four of the 261 ORFs that originated from the plasmid library ( 58% ) were similar to gene sequences on two enterococcal plasmids , pEFNP1 and pKQ10 . At least three different hybridization patterns could be recognized among hierarchical clustering of these plasmid-specific inserts , indicating existence of at least three different pKQ10/pEFNP1 variants . Four different approaches were used to identify recombination in the hospital clade strains . First , we studied patterns of presence and absence of hospital clade–specific genes within gene clusters on the bacterial chromosome . Second , reticular networks were identified with split decomposition analysis ( SDA ) . Third and fourth , guanine cytosine ( GC ) content and the Codon Adaptation Index ( CAI ) of hospital clade–specific genes were determined . Overall , 94 of the partially sequenced inserts that were hospital clade–specific were identical or similar to E . faecium DO genes located on 23 to 27 different contigs . Uncertainty in the number of contigs was explained by the presence of multiple copies of the same genes on different contigs , which are predominantly transposases . Most hospital clade–specific genes were dispersed over the different contigs ( mostly one gene per contig ) , but three contigs evidently represented hotspots for hospital–clade specific genes . Twenty-five genes with similarity to the hospital clade–specific ORFs were located on E . faecium DO contig 658 , 16 genes were located on contig 656 , and nine on contig 653 . Clustering of hospital clade–specific accessory genes on the genome may indicate that these gene clusters have been acquired through horizontal gene transfer and recombination . Phylogenetic analysis of hospital clade–specific genes within contigs 658 and 656 using SDA revealed networked structures consisting of nine parallelograms in contig 656 ( n ( strains ) = 13 ) and eleven parallelograms in contig 658 ( n ( strains ) = 9 ) , with reasonable bootstrap values for contig 656 ( 99 . 9 , 96 . 3 , 96 . 2 , 86 . 7 , 86 . 5 , 65 . 0 , 64 . 7 , 63 . 4 , and 23 . 9 ) , high bootstrap values for contig 658 ( 100 ) , and high fit for both contigs ( 100 ) ( Figure 3 ) . These findings demonstrate the frequent occurrence of recombination events . Several clade-specific genes showed a different GC content than the 36% to 40% found in the rest of the genome ( mean 37 . 9%; http://genome . ornl . gov/microbial/efae ) : the GC content of five of 16 genes within contig 656 ranged from 34% to 43% , whereas for contig 658 , the GC content for eight of 25 genes ranged from 27% to 42% ( Figure 4 ) . These findings suggest foreign origin of genes acquired through lateral gene transfer . Inserts that map on the same contig grouped in different clusters based on hierarchical clustering ( unpublished data ) . This indicates that physically linked genes were differentially present in different E . faecium isolates , which is also highly suggestive of genomic mosaicism and recombination events . This is further illustrated in more detail for contigs 658 and 656 in Figures 3 and 4 , respectively . Besides genomic mosaicism , difference in codon usage can support foreign acquisition of genes . The mean CAI in E . faecium core genes was 0 . 65 ( 95% confidence interval: 0 . 62 and 0 . 68 ) . Five of these genes were all located on contig 595 . CAI values of all genes on contig 595 were calculated in comparison with the calculated mean CAI of the E . faecium core , since the whole contig probably contains only E . faecium DO core genes . CAI values were even significantly higher than the E . faecium core CAI ( p = 0 . 001 , t-test ) , indicating that the calculated mean CAI based on a small number of core genes might be underestimated ( Figure S1 and Table S2 ) . Nevertheless , CAI distribution among the contig 656 hospital clade–associated genes and contig 658 hospital-associated genes was significantly lower than mean CAI core genes ( p < 0 . 001 , t-test ) . However , local variations in CAI in hospital clade–specific gene clusters were substantial ( Figure S1 ) . This is exemplified by the CAI of genes belonging to the previously identified putative PAI ( Table S3 ) . In this island , the CAI of the esp gene ( 0 . 71 ) was higher than the CAI of the other genes ( CAI: 0 . 52–0 . 62 ) ( Table S3 ) . In conclusion , CAI differences between genes expressed at high and low level as described for E . coli [36] were less pronounced . The relatively high CAI value of E . faecium core genes suggests that the codon usage of E . faecium is shaped towards optimal codon usage irrespective of cellular demands , but that the translational apparatus of the bacterium handled ( part of ) recruited DNA less efficiently than core DNA . Deviating CAI values and GC percentages of single genes implicate relatively recent acquisition through lateral gene transfer . In summary , these results in E . faecium DO support recent acquisition and recombination of accessory DNA , as defined in this study . Three inserts , all identical to the IS16 transposase gene ( mostly annotated in E . faecium DO as mutator-like transposase ) , were identified with 98% sensitivity and 100% specificity and validated by Southern blotting as the most clade-predictive locus present in the hospital clade ( Figure 5 and Table S4 ) . Multiple copies of this transposase were present in E . faecium DO , though not always likewise annotated . Two complete copies were present in contigs 658 and 646 with 100% and 97% sequence similarity , respectively . Contigs 630 , 625 , and 546 contained only the right-end side , and contigs 654 and 613 only the left-end side of the gene . IS16 , part of the IS256 family , is flanked by nonidentical inverted repeats , with the right inverted repeat resembling a −35 promoter region [37 , 38] . Sequences of 14 high-ranking hospital clade predictive inserts ( ≥94% predicted presence and ≤5% presence in the hospital and non–hospital clade ancestral strain , respectively ) revealed ≥98% similarity with genes encoding a transposase belonging to the IS30 family ( tra8 gene ) ( annotation E . faecium DO: integrase with catalytic region ) ( n ( inserts ) = 7 ) ; an extracellular solute-binding protein , a glycosyl hydrolase , and a conserved hypothetical protein ( which are all located on contig 638 ) ; chloramphenicol O-acetyltransferase; ROK ( Repressor , ORF , Kinase ) ; a phage terminase; and a phage portal protein ( Table S4 ) . Apart from the hospital clade–unique inserts , IS elements were also prominent among hospital clade–enriched inserts . Approximately 30% of all sequenced inserts were similar to genes encoding five additional different types of transposases/IS elements ( transposase ISIIIA/IS1328/IS1533; transposase IS110/IS116/IS902 , transposase IS3/IS911 , transposase IS256 , transposase IS204/IS1001/IS1096/IS1165 , and transposase IS66 ) . Character tracing predicted that the hospital clade acquired certain genes , like the putative PAI , only after initial branching . Absence of the variant esp gene in the ancestor of the hospital clade was 98% likely . Other genes acquired after development of the hospital clade include plasmid-derived genes , membrane proteins ( n = 6 ) , genes involved with carbohydrate transport and metabolism ( n = 7 ) , transcription-related genes ( n = 6 ) , defense mechanism genes , aminoglycoside resistance cassettes , and several solitary genes ( n = 5 ) not belonging to the same COG . The observation that IS elements were most specific and abundant for the hospital clade suggests that the acquisition of IS elements increased genome plasticity and the propensity of acquiring further adaptive mechanisms , thus facilitating adaptation to the hospital environment . In general , the genetic variability of isolates that are evolutionary-linked , e . g . , the hospital clade isolates , is expected to be less than the genetic variability of isolates that belong to different evolutionary lineages , like all the different non–hospital clade isolates . This difference , however , can be mitigated if specific mechanisms , like the enrichment of IS element , enhance the genetic variability of hospital clade isolates . To compare genetic variation between strains within the hospital clade to variation between all other strains , the genetic similarity among isolates was determined by pulsed-field gel electrophoresis ( PFGE ) , the outcome of which is affected by genome rearrangements , and MLST , which is not influenced by genome rearrangements . As expected , the average genetic similarities among 21 evolutionary-linked hospital clade isolates , based on MLST , was higher ( 60% ) than that among 23 non–hospital clade isolates ( 26 . 7% ) ( Tables S5 and S6 ) . However , the PFGE-based average genetic similarity among the hospital clade strains was 53 . 6 % ± 13 . 2 standard deviation ( SD ) , comparable to the average genetic similarity among the non–hospital clade strains ( 54 . 9 % ± 12 . 8 SD; not significant , t-test ) ( Table S7 ) . The resulting recombination/diversity indices of 1 . 12 ± 0 . 72 SD for the hospital clade and 0 . 51 ± 0 . 50 SD for the non–hospital clade strains supported frequent genome rearrangements in the hospital clade ( p < 0 . 001; t-test ) .
Using a mixed whole-genome microarray , we have identified with three different phylogenetic algorithms—Bayesian-based phylogenic analysis , maximum parsimony analysis , and hierarchical clustering—a globally dispersed E . faecium clade among an epidemiologically well-characterized strain collection . This clade is highly specific for nosocomial outbreaks and infections , and 146 clade-specific genes were identified , which were located scattered over 23 to 27 different contigs . Three contigs appeared to be hotspots of these clade-specific genes and were characterized by extensive genomic mosaicim . CAI values and GC content of hospital clade–specific genes on these contigs were slightly different from the rest of the genome . This may indicate rapid adoption of these genes to the translational apparatus of E . faecium or acquisition from closely related species . Among hospital clade–specific genes , IS elements were identified as the most predictive loci for this clade . Besides lateral gene transfer , these IS elements might have facilitated extensive genome rearrangements in the hospital clade as shown by PFGE results , a technique used previously to demonstrate heterogeneity in location of transposon-mediated transconjugation in enterococci [39] . These genomic events could have contributed to the transition of an avirulent commensal to a nosocomial pathogenic E . faecium subspecies . A random shotgun library of nine E . faecium genomes , selected upon different MLST profiles , was used to investigate population dynamics and genome content of 97 E . faecium isolates . In the absence of a finalized annotation of an E . faecium genome , mixed whole-genome microarray technology offers the optimal tool for comparative genomics . Nevertheless , data interpretation is a potential limitation of microarrays generated upon cloned random fragments rather than gene-specific primers , since multiple gene fragments may be present per insert [40] . This technical restriction stresses the need for validation . Since confirmatory hybridizations matched array data , we consider our microarray suitable for genomic comparisons of isolates . MLST of E . faecium previously identified host specificity and a globally dispersed subpopulation named CC17 , which was associated with hospital outbreaks and infections , and which had apparently replaced the more heterogeneous enterococcal bacterial population within hospitals [22 , 41 , 42] . Intriguingly , our microarray phylogenetic analyses , based on genome-wide presence and absence of genes , was comparable to our findings obtained by MLST . Two outbreak-related strains , which were not considered part of CC17 by MLST , clearly belonged to the hospital clade in CGH . Although these strains were evolutionary unrelated to CC17 based on allelic profiles of housekeeping genes , they probably acquired hospital clade–specific genes by horizontal gene transfer . Other E . faecium MLST clonal complexes were not identified by CGH , probably reflecting high recombination frequencies . Congruence between array distance trees and MLST trees has also been described for S . aureus and Neisseria meningitidis [43 , 44] . IS elements contributed prominently to the hospital clade–specific genes . In general , mobile genetic elements , such as ISs , transposons , phages , and genomic islands , are common components of microbial genomes and are driving forces for novel genotypic and phenotypic variants . Transposition of IS elements may disrupt genes , but may also activate downstream genes [37] and fine tune gene expression through transposition mediated genome inversions . Some IS elements contain a −35 promoter-like sequence in their terminal , which may result in formation of a functional promoter [37 , 38] . Mobile elements are often flanked by IS elements which facilitate recombination and mobilization . The most prominent marker indicative for the hospital clade was IS16 , which is present in multiple copies on different contigs of the E . faecium DO genome . In the unfinished annotation of E . faecium DO , IS16 is designated as a mutator type transposase , sharing high similarity with similar tranposases in other bacterial species and in maize [45] . This IS element seems to possess all transposing capacities: IS16 ( i ) was already identified in E . faecalis as flanking part of Tn1547 [46] , ( ii ) inserted in the vanY gene of Tn1546 , resulting in a VanD-like phenotype in a vanA genotype vancomycin-resistant E . faecium [47] , and ( iii ) contains a −35 promoter-like sequence . In addition , IS16 was found in multiple copies in several enterococcal strains [48] and in pRUM , an E . faecium plasmid containing a postsegregational killing system [49] . Our findings demonstrate that IS16 can be used as a specific marker of the hospital clade genotype . Enrichment of particular IS elements in the genome of bacterial ( sub ) species has been documented previously . In S . epidermidis , IS256 is present in multiple copies in clinical strains , where it might induce genome flexibility of multiresistant , biofilm-forming isolates [33] . Shigella species are enriched with 300 to 700 copies of IS elements [50] , and Bordetella pertussis is significantly enriched in IS elements compared with Bordetella bronchiseptica , from which B . pertussis is thought to have been evolved [51 , 52] . The observation that IS elements are among the most specific and abundant hospital clade–specific inserts suggests that acquisition of these elements has contributed to the ecological success of this clade in the hospital environment , through enhanced genome plasticity . A higher diversity index for the hospital clade compared with that of the non–hospital clade demonstrates higher levels of genetic variability , which could have resulted from enrichment with IS elements . IS elements may not only affect gene expression and enhance genome plasticity , but may also increase the propensity of acquiring further adaptive mechanisms . All of these IS element–induced events may have been pivotal for E . faecium to adapt and survive in highly competitive niches , such as the hospital environment . The structure and genetic makeup of the E . faecium pangenome shows many similarities with the sequenced E . faecalis V583 [53] . In concordance with the more than 25% mobile elements in V583 , 50 ( putative ) IS elements were contained among the 146 identified E . faecium hospital clade–specific genes . One of the most prominent V583 IS elements , IS256 , was also found among these . V583 plasmids seem to be complex mosaic structures compared with similar plasmids in GenBank [53] . The presence of multiple plasmid remnants and the three resident plasmids in V583 was hypothesized as being important for genome plasticity [53] . Our data for contigs 656 and 658 provide more evidence for this concept in E . faecium . Highly prevalent hospital clade–specific genes represent antibiotic resistance genes , present in 80%–83% of the hospital clade isolates , and genes involved in carbohydrate metabolism , present in 89%–93% of hospital clade isolates , in addition to IS elements . Interestingly , we found the aadE-sat4-aphA-3 aminoglycoside streptothricine resistance gene cluster highly associated with the hospital clade ( present in 84% of hospital clade isolates ) and not linked to a specific IS element . In a previous study , this gene cluster had been identified as part of a Tn5405-like structure in 70 . 1% of isolates [54] . The Tn5405-like structure is present in E . faecium DO , with IS1182 annotated as EfaeDRAFT_2457 cassette chromosome recombinase B1 on contig 656 , and ORFs X and Y ( EfaeDRAFT_2456 and 2455 ) and the aadE-sat4-aphA-3 cluster ( EfaeDRAFT_2452 , 2453 and 2454 ) located directly upstream . In contrast to our data , this gene cluster was found in German multiresistant animal and sewage isolates , as well as in human hospitalized patients and outpatients [55] . Most hospital clade–specific hypothetical proteins and other genes , including the putative PAI genes , were identified in only a smaller subset , reflecting acquisition after initial branching of the hospital clade . Previously , the PAI has also been identified only in a fraction ( approximately 60% ) of hospital outbreak and infection strains [22] . Frequent recombination resulted in genomic mosaicism , as exemplified by contigs 656 and 658 . Variation in the combination of accessory genes might supply the organism with a varying armamentarium to colonize or infect the host and escape the immune system . Our study is unique in that it identifies a single phylogenetic hospital clade of strains with epidemic potential in hospitals and with more than 100 genes specific to this clade . Among the 97 strains included in this study , a core genome of 65% of the inserts was identified , while 13% of spots were highly associated with the hospital clade . Genetic subpopulations strongly associated with virulent or epidemic potential have not been identified for many other species . Recently , a nonlivestock-associated clade that contained all infectious Campylobacter jejuni isolates and associated genetic factors was identified using an approach similar to ours [56] . In addition , Howard et al . confirmed by comparative phylogenomics three distinct clusters of Yersinia enterocolitica composed of a nonpathogenic clade , a low pathogenic clade , and a high pathogenic clade [57] . In contrast , population genetics of S . aureus repeatedly failed to identify virulence factors associated with enhanced virulence or a subpopulation adapted to the hospital , though overrepresentation of invasive isolates in certain ( sub ) clusters was identified [28 , 30 , 58] . In another study , factors associated with S . epidermidis invasiveness were identified , but a phylogenetic analysis failed to distinguish invasive isolates from controls [33] . Nevertheless , evolution of a pathogenic species from a less pathogenic species has been documented before ( i . e . , Shigella species from E . coli [59] , and Bacillus anthracis from Bacillus cereus [60] ) . A quantum leap of evolution in these bacteria occurs when new genes are acquired en bloc via horizontal gene transfer by plasmids and bacteriophages [61] . Acquisition of these genes enables the pathogen to colonize a new niche , and new selective constraints lead to progressive adaptation of the organism by pathoadaptive mutations [62] . When aligning the enterococcal plasmid pRUM to E . faecium DO , the plasmid was highly similar to parts of contig 658 , including the toxin–anititoxin system . This may reflect integration of a plasmid in the E . faecium genome . An important element of pathoadaptive evolution is selection of “black holes”: inactivation to pseudogenes or loss of genes , which leads to genome decay [62] . The inactivated and lost genes are often antivirulence genes [62] . This DNA may still be present in the nonpathogenic ancestor . Our results didn't show direct evidence for complete loss of many genes specific for hospital clade strains; however , identification of pseudogenes with this approach is not possible . The fact that hospital clade strains are only rarely found outside the hospital indicates reduced fitness of these strains in the ancestral niche , which possibly reflects antagonistic pleiotropy in which hospital specialization is detrimental in other niches [63] . From these evolutionary insights , one might conclude that worldwide emergence of the E . faecium hospital clade represents , in fact , evolution of a novel hospital-adapted subspecies from a nonpathogenic ( commensal ) E . faecium ancestor , which succeeded in competing with E . faecalis as causative agent of hospital infections .
The 97 bacterial isolates used in this study originated from different documented epidemiological niches: 18 mostly monoclonal , hospital epidemics; 35 clinical sites representing invasive human infections , including E . faecium DO ( E1794 in Table 1 ) ; 15 hospital surveys , representing asymptomatic carriage of hospitalized patients; 11 community surveys , representing asymptomatic carriage in healthy subjects; three environmental isolates; and 15 animals in 21 countries on six continents ( Table 1 ) [20 , 41 , 64–72] . These strains were a subset of a large , genotypically well-characterized collection , which represented the global E . faecium population . The subset was selected based on differences in geographic locations , hosts , and sequence types . All strains were cultured on tryptic soy agar sheep blood plates at 37 °C . DNA for labeling ( see below ) was prepared from cell suspensions by bead-beating and chloroform phenol extraction . DNA for Southern blots was isolated according to the manufacturer's instructions with DNeasy Tissue kit ( Qiagen , http://www . qiagen . com ) . The shotgun library was created from nine strains from different epidemiologic and genetic backgrounds according to MLST analysis ( Table 3 ) [21] . In order to prevent overrepresentation of inserts from high copy plasmids , plasmid DNA was separated from chromosomal DNA according to Willems et al . [73] with the modification that clumping high molecular chromosomal DNA , cured from plasmid DNA , was captured with a glass capillary . Plasmids were prepared from the library strains with the QIAprep Spin Miniprep Kit according to the manufacturer's instructions ( Qiagen ) and amplified with the TempliPhi Amplification Kit ( Amersham , http://www . amersham . com ) . Equal amounts of chromosomal DNA from nine genetically diverse E . faecium strains were mixed to create a shotgun library as described by Borucki et al . [74] ( Table 3 ) . The same procedure was repeated for the plasmid DNA preparations . Briefly , 10 μg of pooled DNA ( equal amounts from each strain ) was sonicated ( Branson 250/450 Sonifier , 6-mm microtip; http://www . sonifier . com ) , and fragments of approximately 0 . 8–1 . 2 kb for genomic DNA and 1 . 2–1 . 7 kb for plasmid DNA were gel isolated , extracted ( Qiaquick columns , Qiagen ) , and end-repaired ( DNA Terminator End Repair Kit; Lucigen Corporation , http://www . lucigen . com ) . End-repaired fragments were ligated to pSMART-HC-Kan ( Clone-SMART , Lucigen ) , and E . coli ( ElectroMAX DH10B Cells; Invitrogen , http://www . invitrogen . com ) were transformed with this recombinant plasmid . Next , 4 , 560 genomic and 1 , 140 plasmid recombinant clones were arrayed in 96-well plates . Clone inserts were amplified by PCR with amino-modified SMART primers . Additionally , fragments from one enterococcal housekeeping gene , 13 virulence genes , and 20 genes involved with antibiotic resistance were PCR–amplified and included in the microarray ( Table S7 ) [18 , 49 , 55 , 75–89] . PCR products were ethanol purified and resuspended in 1 × SSC ( 1 × SSC is 0 . 15 M NaCl plus 0 . 015 M sodium citrate ) . All genomic , plasmid , and additional gene PCR products were printed by using ESI three-axis DB-3 robot ( Versarray ChipWriter Pro; Biorad , http://www . bio-rad . com ) at a controlled humidity of 55% on CSS silylated slides ( European Biotech Network , http://www . euro-bio-net . com ) . Slides were printed in two batches , after which they were blocked following the manufacturer's instructions . Genomic coverage of the library on the nucleotide level was calculated using Formula 1 [35]: in which N = number of clones , P = probability of coverage , I = insert size and G = genome size . This formula , however , is based on the assumption that that every single nucleotide should be present in the library . In the present approach , there is no need for a complete ORF to be present: border sequences with a minimal size of 100 nucleotides should be sufficient to obtain positive hybridization signals ( Formula 2 ) [34]: in which T = transcript length and RO = required overlap . In this study , both algorithms are used to estimate genomic coverage . Total DNA ( 0 . 5 μg ) was labeled with fluorescent dyes by random priming with the Bioprime labeling system ( Invitrogen ) . To normalize the two channels for label incorporation , DNA concentration differences , and variation in slide scanning , equal amounts of the library strains were mixed as the reference pool and labeled with Cy3 dUTP . Tester strains were labeled with Cy5 dUTP . Ten tester strains were hybridized in duplo for control of reproducibility . For each hybridization , Cy5 and Cy3 probes were combined with yeast tRNA , speed vacuum dried , resuspended in 40 μl Easy hyb buffer ( Roche Diagnostics Netherlands B . V . , http://www . roche-diagnostics . nl ) , and denatured for 2 min at 100 °C . Silylated slides were prehybridized in prehybridization solution ( 1% BSA , 5 × SSC and 0 . 1% sodium dodecyl sulfate , filtered ) at 42 °C during 45 min while rotating , washed twice with filtered milli Q water , dried with N2 flow , and prewarmed at 42 °C . Easy hyb solution was pipetted on the microarray print of the slide , covered with a hybrislib , and placed in hybridization chambers ( Corning Life Sciences B . V . , http://www . corning . com/lifesciences ) . Hybridizations were performed overnight at 42 °C in a waterbath . Microarrays were then washed sequentially in ( i ) 1 × SSC/0 . 2% sodium dodecyl sulfate for 10 s at 37 °C , ( ii ) 0 . 5 × SSC for 10 s at 37 °C , and ( iii ) twice in 0 . 2 × SSC for 10 min at room temperature , and dried with N2-flow . A Scanarray Express 680013 Microarray Analysis System ( PerkinElmer Life and Analytical Sciences , http://las . perkinelmer . com ) was used for scanning slides . Microarray images were quantified with Imagene software version 4 . 2 ( Biodiscovery , http://www . biodiscovery . com ) . Inferior spots ( empty spots , exceeding SD of pixels , less than two times background in Cy3 channels ) , were excluded from normalization and data analysis . To correct for differences in labeling , hybridization conditions , slide quality , and scanning circumstances , each slide was normalized independently . At first , ratios of Cy5 minus background to Cy3 minus background were calculated and log2-transformed . Filtering was applied to exclude spots with flags; for estimating the correction factor in normalization , only spots were included with Cy3 values larger than two times background . Mean log2 ratios were calculated and applied to each independent ratio . Next , the data were transformed using GACK ( http://falkow . stanford . edu/whatwedo/software/software . html ) to assign a region of considerate absence and presence , corresponding with , respectively , minus 0 . 50 and plus 0 . 50 , and an interval with indefinite presence/absence , or divergence , to interpret the data . For Bayesian modeling , maximum parsimony analysis , SDA , and character evolution modeling data was transformed to binary output . Using a Nexus format matrix , the relationship of strains based on the presence and absence of hybridizing signal on spotted inserts was determined with Bayesian-based algorithms implemented through MR BAYES 3 . 0 software [90] , as explained by Champion et al . [56] . With samples and saves from every 40th tree , 1 , 100 , 000 generations of four incrementally heated Markov chain Monte Carlos were performed on the DNA–DNA microarray data by using the default annealing temperature of 0 . 5 , a burn-in of 100 , 000 Markov chain Monte Carlos generations , and an 8-category distribution . Ninety five percent majority rule consensus trees and clade credibility values were obtained by using TreeView ( http://taxonomy . zoology . gla . ac . uk/rod/treeview . html ) . In addition to the Bayesian-based approach , phylogeny was studied with hierarchical clustering and maximum parsimony analysis . [24] . Bootstrapped ( 1 , 000 iterations ) complete linkage transversal hierarchical clustering with Euclidian distance was performed and visualized with TIGR MeV version 3 . 1 software ( http://www . tm4 . org/mev . html ) . One thousand times bootstrapped maximum parsimony analysis was performed with PAUP* 4 . 0 software ( Sinauer Associates , http://paup . csit . fsu . edu ) . In order to select a maximal variety of differential genes and gain insight into the degree of redundancy , hierarchical clustering ( for details see above ) was used to generate a dendrogram of genes based on their patterns of absence and presence across the strains . Detection of clusters of acquired genes is based on the assumption that co-inherited genes can be found co-located on the bacterial genome . Subsequently , a subset of inserts was considered highly specific for a clade according to the following two criteria: First , insert specificity for the clade was higher than 80% , estimated with the χ2 test and followed by FDR correction [91] . Second , the insert clustered with a Euclidian distance of 1 . 1 or less for the genomic library and 0 . 8 or less for the plasmid library was selected for sequencing ( see below ) . To gain insight into the core genome; 35 randomly chosen inserts that gave a positive hybridization signal in all strains were sequenced . SDA based on the presence and absence of ORFs , with identity to genes belonging to contigs 658 and 656 in a selection of the most genetically diverse strains , was used to test for parallel changes in the gene order on these E . faecium DO contigs . The bootstrapping procedure for SDA was used as implemented in the SplitsTree program version 4 . 0 using Hamming correction ( http://www . splitstree . org ) . Recombination , hybridization , gene conversion , and gene transfer all lead to histories that are not adequately modeled by a single tree . They effectively cause lineages to coalesce forward in time , resulting in trees that have reticulations or a network structure rather than the simple branching structure seen with most phylogenies . Split decomposition does not force tree topologies to be strictly bifurcating or multibranching but permits network relationships . A split decomposition graph will look less tree-like and more net-like as the influence of recombination becomes more important in the history of a set of taxa . Since splits graphs were sufficiently complex and the distances among strains sufficiently great , data sets had to be simplified by removing strains representing the longest branches to allow visualization of central networks and improve the fit parameter , which is similar to the method described in [92] . The character evolution maximum likelihood–based model of Mesquite 1 . 06 software ( http://www . mesquiteproject . org ) was used to identify clade-predictive genes on binary data in nexus format . Tracing shows the most likely hypothesis of ancestral states , and indicates how presence and absence or divergence of certain genes in an ancestral strain has led to the formation of a new clade . Inserts selected for sequencing ( see above ) were PCR-amplified and sequenced single-stranded from one direction in combination with the BigDye Terminator reaction kit by using an ABI PRISM 3700 DNA analyzer ( Applied Biosystems , http://www . appliedbiosystems . com ) . All sequences were blasted in GenBank . COGs for E . faecium genes and proteins were assigned according to the Oak Ridge National Laboratory Web site ( http://maple . lsd . ornl . gov/cgi-bin/JGI_microbial/display_page . cgi ? page=cog&org=efae&chr=08jun04 ) . COGs for other species' genes and proteins were assigned according to GenBank . Microarray hybridization results from ten spots , including six different ORFs ( IS16 , esp , vanA , transposase IS111A/IS1328/IS1533; transposase IS110/IS116/IS902 , glycosyl hydrolase family 88 , and extracellular solute-binding protein ) , were validated by Southern hybridization . For this purpose , chromosomal DNA preparations were digested with EcoRI , separated by agarose gel electrophoresis ( 0 . 8% agarose gels ) , transferred onto a Hybond N+ nylon membrane ( Nycomed Amersham plc , http://www . amersham . com ) , and subsequently hybridized to six ECl-labeled PCR products specific for the six ORFs according to the manufacturer's protocol ( Amersham ) . Primers , if not already designed for the additional spots on the array ( Table S7; see “Microarray fabrication” section of Materials and Methods ) , were listed in Table S8 . Codon usage patterns may vary considerably among genes . It is generally assumed that codons that are best recognized by the most abundant tRNA are those that are translated optimally ( most accurate ) , and are often linked to genes expressed at high levels . The CAI measures codon bias and indicates the relative adaptiveness of the codon usage of a particular gene towards the codon usage of highly expressed genes . A gene that consists only of the most frequently used codons of a reference set of highly expressed genes has the maximal possible CAI value of 1 . 0 and is thought to be highly expressed . In general , highly expressed genes have high CAI values . The CAI adaptation index was calculated as described previously [36] . Briefly , a CAI calculator ( http://www . evolvingcode . net/codon/cai/cai . php ) was used to determine the relative synonymous codon usage ( RSCU ) —that is , the observed frequency of a particular codon divided by its expected frequency under the assumption of equal usage of the synonymous codons for an amino acid [36]—of analyzed genes . CAI is defined as the geometric mean of the RSCU values corresponding to each of the codons used in that gene , divided by the maximum possible CAI for a gene of the same amino acid composition [36] . A subset of E . faecium DO core genes representing genes encoding elongation factors and ribosomal proteins was supposed to be highly expressed in E . faecium and was used as a reference for RSCU ( Table S9 ) . CAI values were then calculated using the CAI calculator ( http://www . evolvingcode . net/codon/cai/cai . php ) . The DRAFT annotation of the E . faecium DO genes is from the Joint Genome Institute E . faecium Web site ( http://genome . jgi-psf . org/draft_microbes/entfa/entfa . home . html ) . The mean CAI value with SD was calculated from the sequenced core genome genes ( Table S1 ) . Furthermore , the known putative E . faecium PAI genes were included . The observed codon frequencies in the E . faecium genome were compared with the expected codon frequencies calculated from the GC content at the first , second , and third codon positions under the assumption of the same amino acid composition . The significance of the differences was evaluated by t-test statistics . PFGE analysis was performed as described previously [6] . Distance matrices of banding patterns between 339 . 5 kb and 97 kb were calculated with Bionumerics software ( version 3 . 5; Applied Maths , http://www . applied-maths . com ) by the Ward method for a subset of hospital clade strains ( n = 22 ) and a subset of non–hospital clade strains ( n = 24 ) with different sequence types and epidemiological origins . Distance matrices from previously identified MLST allelic profiles were calculated with the categorical coefficient ( Bionumerics software ) . In order to compare the level of similarity among isolates belonging to the hospital clade with non–hospital clade isolates based on PFGE and MLST , a so-called diversity index was calculated . For this , the average of similarities between all possible pairs of hospital clade and non–hospital clade isolates based on MLST was calculated and divided by the average of similarities between all possible pairs of hospital clade and non–hospital clade isolates based on PFGE . When the level of genetic diversity ( is 1− similarity ) based on MLST and PFGE is identical , the diversity index equals 1 . A diversity index greater than one indicates that the average pairwise similarity based on PFGE is higher than that based on MLST , and suggests enhanced genomic rearrangements .
The GenBank ( http://www . ncbi . nlm . nih . gov/Genbank/index . html ) accession numbers for the genes and gene products discussed in this paper are E . faecium isolate E300 pathogenicity island ( AY322150 ) , pEFNP1 ( AB038522 ) , and pKQ10 ( U01917 ) .
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Whole-genome sequencing has become instrumental in investigating the genome contents of bacteria . However , there is enormous diversity within bacterial populations , and annotation of multiple genomes is costly and elaborate . For investigating diversity and phylogeny within bacterial species , comparative genomic hybridization is an attractive alternative that may provide fundamental insights into the factors ( genes ) distinguishing bacterial subpopulations . Enterococcus faecium , a worldwide emerging nosocomial pathogen usually resistant to multiple antibiotics , causes infections in immunocompromised patients . Using comparative genomic hybridization of 97 E . faecium strains isolated from different epidemiological niches worldwide , a subpopulation of E . faecium strains was identified that was associated with invasive infections and hospital outbreaks . Approximately 13% of the E . faecium pangenome was highly specific for this subpopulation , and , based on phylogenetic clustering , it should be considered a subspecies . We hypothesize that extensive variation within specific functional genes and high prevalence of mobile elements , mostly insertion sequence elements , contributed to the success of this genetic subset in its competition with other enterococci in hospital settings , creating a novel globally dispersed nosocomial subspecies . These findings fully confirmed previous phylogenetic studies based on multi locus sequence typing that had also revealed a genetic subset of E . faecium , clonal complex 17 . Identification of genes specific for clonal complex 17 is a first step in elucidating how global spread and adaptation to the hospital environment of this emerging nosocomial pathogen has occurred .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods",
"Supporting",
"Information"
] |
[
"evolutionary",
"biology",
"molecular",
"biology",
"eubacteria",
"microbiology"
] |
2007
|
Insertion Sequence–Driven Diversification Creates a Globally Dispersed Emerging Multiresistant Subspecies of E. faecium
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In 2005 , the Government of Senegal embarked on a campaign to eliminate a Glossina palpalis gambiensis population from the Niayes area ( ∼1000 km2 ) under the umbrella of the Pan African Tsetse and Trypanosomosis Eradication Campaign ( PATTEC ) . The project was considered an ecologically sound approach to intensify cattle production . The elimination strategy includes a suppression phase using insecticide impregnated targets and cattle , and an elimination phase using the sterile insect technique , necessary to eliminate tsetse in this area . Three main cattle farming systems were identified: a traditional system using trypanotolerant cattle and two “improved” systems using more productive cattle breeds focusing on milk and meat production . In improved farming systems herd size was 45% lower and annual cattle sales were €250 ( s . d . 513 ) per head as compared to €74 ( s . d . 38 ) per head in traditional farming systems ( p<10−3 ) . Tsetse distribution significantly impacted the occurrence of these farming systems ( p = 0 . 001 ) , with 34% ( s . d . 4% ) and 6% ( s . d . 4% ) of improved systems in the tsetse-free and tsetse-infested areas , respectively . We calculated the potential increases of cattle sales as a result of tsetse elimination considering two scenarios , i . e . a conservative scenario with a 2% annual replacement rate from traditional to improved systems after elimination , and a more realistic scenario with an increased replacement rate of 10% five years after elimination . The final annual increase of cattle sales was estimated at ∼€2800/km2 for a total cost of the elimination campaign reaching ∼€6400/km2 . Despite its high cost , the benefit-cost analysis indicated that the project was highly cost-effective , with Internal Rates of Return ( IRR ) of 9 . 8% and 19 . 1% and payback periods of 18 and 13 years for the two scenarios , respectively . In addition to an increase in farmers' income , the benefits of tsetse elimination include a reduction of grazing pressure on the ecosystems .
Food security and safety remains a serious concern in Africa in general and in Senegal in particular . In the last century the human population has increased tenfold in West-Africa , and is expected to triple by 2050 [1] . The expansion of current agricultural production practices will not allow feeding this increasing population which may lead to violent social crises . Senegal in West Africa faces two global challenges , namely demographic changes [2] and climatic change with especially reduced precipitation being critical as it can be associated with lower production of natural forage ( ecosystem service ) that is a major limit for the maintenance of traditional cattle systems in West-Africa . Moreover , overgrazing is a major cause of land degradation in Senegal [3] . The Niayes area around Dakar ( Fig . 1 ) , where the study is conducted , is partially protected from the second challenge ( see below ) but exposed to the first with a human population density already exceeding 150 habitants/km2 . Fifty three percent of the Senegalese population lives in the Niayes making the competition for space severe . In the past , the prospective increase of the milk needs in Africa ( estimated to 52% over a period of ten years ) [4] and the low productivity of local breeds ( 1–4 L/day ) [5] favored the development of institutional programs for the intensification of the dairy industry in Senegal . This included embryo implants in Ndama cattle [6] and more importantly artificial insemination that first started in the area where groundnuts were the main crop but thereafter was extended to the whole country [5] . In 2010 , the national production of milk was estimated at 143 , 124 tons for 366 , 200 heads of cattle , corresponding to 1 . 3 L/cattle/day of lactation ( FAOSTAT ) . Milk imports have always been dominant on the Dakar market with local production only contributing 2 to 5% between 1993 and 2000 [7] . Powdered milk is 50 to 60% less expensive than local fresh milk despite the increase of taxes on this product . In 2009 , the milk imports could only satisfy 60% of the total national demand ( 95 . 6 million L ) [8] which was equivalent to ∼€76 million . In 2010 , these imports reached ∼€96 million [9] . The Niayes area is located along the Atlantic coast of Senegal and includes four administrative districts: Dakar , Thiès , Louga and Saint-Louis . Particular meteorological and ecological characteristics of this area provide great potential for agricultural development in general and animal production ( cattle , donkeys , horses , small ruminants , pigs and poultry ) in particular . However , in 2004 the dairy farms of the peri-urban area of Dakar produced less than 6 , 000 L of milk per day . In 2005 , intensified livestock production systems with exotic breeds such as Holstein , Montbéliarde , Jersey , Gir and Girolando , and cross-breeds between this breeds and local cattle were only found on 1% of the farms . Mean daily milk production was still limited to 6 . 9 L ( s . d . 3 ) despite much higher genetic potential of these exotic breeds and the use of large amounts of inputs ( food concentrates , drugs , … ) [10] . From 1984 to 1993 these farms received government support that included training , animal health care and feed ingredients . Despite this support , farmers were still disorganized in 2005 in terms of milk distribution and inputs . In 2008 , a project called “La Grande offensive agricole pour la nourriture et l'abondance ( GOANA ) ” ( http://www . gouv . sn/IMG/article_PDF/article_777 . pdf ) was launched which included a component of artificial insemination of local breeds with exotic dairy breeds and by December 2011 , more than 91 , 000 cattle had been inseminated . In view of its proximity to the Atlantic Ocean , the Niayes area is a particular eco-region that is more resilient to climate change as compared to other regions in Senegal e . g . the area only experienced a reduction of 150 mm in annual precipitation the last 20 years compared to 200 mm of precipitation in the rest of Senegal . Unfortunately , this microclimate also favours the presence of Glossina palpalis gambiensis Vanderplank , a riverine tsetse species . Tsetse flies ( Diptera: Glossinidae ) are the vectors of human African trypanosomosis ( HAT ) and African animal trypanosomosis ( AAT ) , the former a major neglected human tropical disease , and the latter considered among the greatest constraints to improved livestock production in sub-Saharan Africa [11] . Most domestic animals are susceptible to AAT which was until recently still highly prevalent in the Niayes area [12] . It was a major pathological problem especially for cattle crossed with exotic breeds and Gobra zebus which are very susceptible to trypanosomes . The sustainable removal of the vector , the tsetse fly , would be the most efficient way of managing AAT [13] . In 2001 , an African Union initiative called the Pan African Tsetse and Trypanosomosis Eradication Campaign ( PATTEC ) was launched following an historic decision by the African Heads of State and Government in Lome , Togo , July 2000 . In 2005 , the Senegalese Government joined this campaign , starting a tsetse control campaign that aimed at the elimination ( elimination is here considered as local eradication ) of G . p . gambiensis from the Niayes area ( Fig . 1 ) . The program is implemented by the Government of Senegal ( Direction of Veterinary Services ( DSV ) and the Senegal Institute for Agricultural Research ( ISRA ) ) and technically and financially supported by the International Atomic Energy Agency ( IAEA ) , the Food and Agriculture Organization of the United Nations ( FAO ) , the Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ) and the USA through the Peaceful Uses Initiative ( PUI ) ( www . fao . org/news/story/en/item/211898/icode/ ) . During the feasibility study of this project the limits of the G . p . gambiensis distribution were determined to be within a 1 , 000 km2 area ( Fig . 1 ) and it was demonstrated that this population was completely isolated from the main tsetse belt in the south-eastern part of Senegal [14] , [15] . Therefore , the Government of Senegal selected a strategy of elimination following area-wide integrated pest management ( AW-IPM ) principles [16] to create a sustainable zone free of G . p . gambiensis in the Niayes . The strategy combined insecticide-treated targets and cattle for initial fly suppression [17] with the aerial release of sterile male flies as the final elimination component [18] . The study area was divided in four operational blocks that are being treated sequentially . At the time of writing , 20% of the project area was already cleared of G . p . gambiensis ( no capture of wild flies during 18 months in the monitoring traps ) and the apparent density of the fly population had been reduced with 99% in an additional 40% of the project zone . This project constitutes a major governmental intervention that will have a great positive impact on the Niayes agro-ecosystem . The goal of this paper is to present an ex ante benefit-cost analysis of this project which includes an SIT component that is considered by many a costly control tactic [19] .
Since the project has not been completed at the time of writing , cost estimates were based on real expenditures until December 2013 , and anticipated expenditures until December 2016 . The general economic framework proposed by [19] was used to class the costs into three main areas: studies , field costs and administration . Administration costs from 2007 to 2011 were included in the cost of studies because the operational phase of the tsetse project ( control ) started only in January 2012 ( fig . 2 ) . The field costs were further subdivided into a core component ( traps , pour on , sterile flies , cost of aerial release ) and other expenditures such as vehicle running costs , salaries and field allowances . In this study , we assumed no increase in cattle numbers . The ex-post socio-economic survey conducted on Unguja Island , Zanzibar after the elimination of a Glossina austeni population showed an estimated initial replacement rate of 2% per year of traditional to improved livestock breeds [22] . In the absence of any other study of this type , we used this replacement rate to estimate the potential benefits of the elimination campaign in the Niayes . This was considered a very conservative scenario as innovation sociology dictates that the introduction dynamics of exotic or more productive breeds follows an S curve , i . e . the rate of adoption should increase after the first period spearheaded by the early innovators [23] . However , we also tested a second more realistic scenario where the replacement rate was set at 10% following an initial period of 5 years with a replacement rate of 2% . The monetary assessment of the benefits and costs of the benefit-cost analysis was based on the calculation of the Payback Period ( PP ) , the Net Present Values ( NPV ) , the Internal Rate of Return ( IRR ) and the benefit-cost ratios . The PP refers to the period of time required for the operational products minus the operational expenses to recover the funds placed in an investment . The NPV is the monetary surplus at the end of a project after refunding the invested capital on the total period of the project and the accounts balance initially invested according to the selected discount rate , with the annual cash flow , the initial investment and the duration of the project . The IRR corresponds to the discount rate I for which the NPV of a project is null , . We selected two main hypotheses for the analysis: In our study , prices were calculated based on a conversion rate of 655 . 956 FCFA for one Euro and constant 2013 prices were applied throughout the projection . All farmers provided informed consent before filling the forms . The consents were oral to ensure equal treatment of the subjects , since a large part of the farmers were illiterate . The survey was approved by the General Director of Vet Services and conducted by the agents of Veterinary Services , in charge of animal health in Senegal .
The sample comprised 8 , 488 cattle of which 5 . 4% were dairy cattle breeds . During preliminary surveys 44% ( 226 ) , 52% ( 267 ) and 4% ( 20 ) of the farmers were classed in the cattle herd categories <20 , 20–100 , and >100 respectively . From these , 39 , 131 and 16 farms took part in the socio-economic survey respectively , and they had a mean herd size of 13 , 44 and 133 animals respectively . Based upon this , the number of cattle in the farms surveyed during the preliminary survey was estimated at ∼44 , 111 animals which can be extrapolated to 80 , 000–90 , 000 resident cattle in the target area of the Niayes . Three clusters of livestock keeping systems were identified . The first one was traditional and based mainly on trypanotolerant cattle ( more than 70% ) called “Djakoré” in the study area . These cattle are a cross between “Gobra” , the main zebu breed originating from northern Senegal , and “Ndama” , a trypanotolerant breed originating from the main tsetse belt in south eastern Senegal ( fig . 3 ) . The two other livestock keeping systems used more productive breeds and were composed of meat producing farms with mainly Gobra cattle ( >70% ) , and farms targeting milk production where less than 10% of the cattle were Gobra ( fig . 3 ) . There was a strong impact of tsetse presence ( as assessed using the Maxent model ) and the frequency of the type of farming system ( X-squared = 10 . 1748 , df = 1 , p-value = 0 . 001 ) with 34% ( s . d . 4% ) of farmers owning improved breeds in the tsetse-free pixels compared to 6% ( s . d . 4% ) only in the tsetse-infested pixels . The farming systems are henceforth denoted trypanotolerant , improved meat and improved milk . The Fulani are an ancestral ethnic group of cattle breeders who were the predominant group in the sample ( 82% ) especially in the traditional trypanotolerant system ( 90% ) . They were dominant in the improved meat ( 69% ) but not in the improved milk ( 36% ) farming system where the Wolof ethnic group was the most frequent ( 43% ) . The other ethnic groups were the Sérères , the Toucouleurs and the Lebous . The Toucouleurs together with the Fulani constitute the larger ethnic group of the Al Pulaar who were dominant even in the improved milk farming system ( 50% ) . In general , 57% of the farmers considered AAT as the main animal health problem with a marked difference between the tsetse-free ( 49% ) and -infested area ( 92% ) . All farmers of the improved milk farming system that were located in the tsetse-infested area considered the AAT as the major animal health problem with ticks coming second . Despite increased competition for space in the main cities , there was no clustering of improved milk farming systems in Dakar or Thiès , where tsetse also occur ( fig . 1 ) . There was a significant effect of type of farming system on the annual cattle sales ( p<10−3 , fig . 4 ) . Despite the different production schemes in the improved milk and improved meat farming systems , the annual cattle sales were similar in the two systems ( t = −0 . 9577 , df = 50 . 999 , p-value = 0 . 3427 ) averaging € 250 ( s . d . 513 ) per head which was more than 3 times higher than in the trypanotolerant system ( €74 , s . d . 38 ) . The difference was significant for both the improved milk ( t = −1 . 815 , df = 13 . 088 , p-value = 0 . 046 ) and improved meat ( t = −2 . 164 , df = 38 . 086 , p-value = 0 . 018 ) farming systems . These increased sales were obtained through more animals being sold and higher prices obtained per head in the improved meat farming system and through increased milk production in the improved milk farming system ( table 1 ) . The price of the milk was similar for all farming systems , i . e . €0 . 73 per L ( s . d . 0 . 09 ) . The average herd size in the improved milk and meat farming systems was similar ( 28 . 6 , s . d . 25 . 5 ) but was on average 45% smaller than in the trypanotolerant farming system ( 52 . 4 , s . d . 37 . 5 ) . Concerning other cattle production parameters ( table 1 ) , the improved meat farming system was similar to the trypanotolerant system in terms of herd management ( free grazing in communal land , cropped areas , no employees ) but experienced higher cattle mortality and lower calving rates as compared to the trypanotolerant system , probably because of the higher sensitivity to trypanosomosis of Gobra cattle . The improved milk farming system showed better cattle production parameters , probably because much more inputs were used in this system , as demonstrated by the higher yearly cost of trypanocidal drugs . The declared mean amount of money spent on trypanocidal drugs was generally very low , but significantly higher in the improved milk than in the trypanotolerant system indicating some degree of exposure to trypanosomes even if most of them where located adjacent to the tsetse-infested pixels . They were significantly lower in the improved meat system than in the two other systems . The total cost of the tsetse elimination project was estimated at € 6 . 4 million ( table 2 ) contributed by the Ministry of Livestock of the Government of Senegal , the ISRA , the US Department of State , the FAO , the IAEA and the CIRAD . The total contribution from Senegal reached 37% of the total cost and the breakdown of the other contributions is presented in fig . 5 . The core component of the field costs ( table 3 ) corresponded to the insecticide impregnated monoconical traps ( n = ∼3600 with purchase value of each €3 ) , the insecticides to treat ∼25 , 000 cattle at monthly intervals during the suppression phase ( total of 6 times ) ( pour on cost of €0 . 30/treatment ) and the aerial release of sterile males ( ∼2 . 8 million sterile male pupae purchased from the CIRDES and the Institute of Zoology , Slovak Academy of Sciences , Bratislava , Slovakia at €0 . 15 and €0 . 17/pupae respectively , €0 . 04 transport cost/pupae from Bobo Dioulasso , Burkina Faso or Bratislava , Slovakia to Dakar , Senegal and 4 , 000 hours of flying time with gyrocopters to disperse the sterile flies at €320 per hour including airport costs ) . These costs corresponded to the following treatment schedules: ∼17 insecticide impregnated traps/km2 of suitable habitat ( total surface area of 231 km2 according to the Maxent predictions ) with a 50% replacement rate during the suppression phase of one year; 2 . 5 cattle/km2 treated 6 times with pour-on at monthly intervals; 27 sterile flies released per km2/week i . e . 117 per km2 of suitable habitat/week ( 2 releases by week ) with a swath of 500 m between release lines . Other field components included three 4*4 vehicles , their running costs ( fuel , spare parts ) and the field allowances for the field staff who implemented the suppression and the elimination phase from 2012 to 2016 ( fig . 2 ) . Entomological studies included the demarcation of the target population ( 2007–2009 ) [14] , the confirmation that the Niayes population was completely isolated from the remainder of the tsetse belt in South East Senegal through a population genetics study ( 2008 ) [15] , the monitoring of the population dynamics of the fly population ( 2009 to 2011 ) ( including apparent densities as revealed by trap catches , trypanosome infection rates in the flies , physiological age distribution , and natural abortion rates ) , the assessment of the survival , competitiveness and dispersal of sterile males in the different ecosystems of the target area during trial releases of more than 240 , 000 sterile male G . p . gambiensis . The costs of the SIT component of the entomological study ( competitiveness , survival and dispersal of sterile males ) represented 46% of the total entomological study costs . Other studies included a parasitological base line data collection in the entire target area ( 2007 ) [12] , a monitoring of the AAT incidence as of 2009 , an environmental monitoring using various ecological indicators ( as of 2010 ) [25] , a socio-economic study including the ex-ante transversal study presented here , an assessment of farmer innovation trajectories and an ex-post transversal study planned in 2016 . Finally , administrative costs included monthly coordination meetings , expert missions , external reviews and salaries of the staff and advisors . The staff of the project was composed of 2 doctors of veterinary medicine ( 35% of their time ) , 3 agricultural engineers ( 50% ) and 7 technical staff ( 50% ) of the DSV , 1 senior researcher ( 50% ) , 1 junior researcher ( 20% ) and 3 entomological technicians ( 100% ) of the ISRA and 1 senior researcher ( 50% ) of the CIRAD . There were in addition MSc ( 6 ) and PhD students ( 3 ) involved in various project activities . The first effect of the project on the sales of meat and milk was seen in year six of project implementation when elimination of the G . p . gambiensis population was obtained in the first block ( 20% of the area ) . In year seven and eight , the total area of elimination was assumed to reach 60% and 100% of the total target area respectively ( Fig . 6 ) . Except for scenario 1 that assumes a 2% annual replacement rate with a discounting rate of 10% , the project has a positive NPV and an IRR higher than average interest rates for financing the project ( table 4 ) . The payback period would be 18 years for the first scenario and 13 years for the more realistic scenario 2 ( corresponding to 2020 ) . The benefit-cost ratios ranged from 0 . 98 to 4 . 26 depending on the discount rates and scenarios ( table 4 ) . Depending on the scenario , 100% of the farmers will have shifted from trypanotolerant cattle to more productive breeds in 2048 ( scenario 1 ) or in 2022 ( scenario 2 ) and the annual increase of cattle sales will reach more than €2 . 8 million , i . e . a 54% increase in total sales . Over the same period , the total cattle population will be reduced by 45% .
The tsetse elimination project in the Niayes is considered by the Government of Senegal as an ecologically sound strategy to intensify cattle production that will result in a decrease in cattle density , and the use of more productive cattle in urban areas . The data of this study have indicated that the elimination of the G . p . gambiensis population from the Niayes will bring major overall socio-economic benefits for the farmer community that is composed of several farming systems , more or less exposed to the disease . However , the adoption of new technologies is generally difficult because it requires changes of the socio-technical regime including social norms and associated practices , for example the management of exotic breeds [46] , [47] . In the case of the improved meat system , practices and social norms are similar to the traditional system whereas in the case of improved milk systems , complete technological packages and associated norms must be changed ( for example the attractiveness of local milk for consumers in comparison to powdered milk ) . We are presently studying individual and collective trajectories of herders based on comprehensive analyses to better estimate the mutation rates [48] . Moreover , the benefits will have to be evaluated more accurately using ex-post socio-economic surveys .
|
In 2005 , the Government of Senegal embarked on a campaign to eliminate a tsetse population from the Niayes area ( ∼1000 km2 ) around Dakar in order to intensify cattle production . Three main cattle farming systems are present in this area: a traditional system using trypanotolerant cattle and two “improved” systems using more productive trypano-sensitive cattle breeds . Whereas the size of the herds in improved cattle farming systems is more than twice lower than in a traditional system , the annual sales per head are threefold higher . Improved systems are more than fivefold less frequent in the tsetse infested sites than in the surrounding ones , showing that the risk posed by trypanosomosis is a major constraint to the intensification and innovation processes . Based on two scenarios of shift from traditional to improved systems after tsetse elimination , the benefit-cost analysis shows that , despite its relatively high cost , the project is highly cost-effective and will allow a reduction of grazing pressure on the ecosystems .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"invertebrates",
"medicine",
"and",
"health",
"sciences",
"african",
"trypanosomiasis",
"development",
"economics",
"tropical",
"diseases",
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"agriculture",
"arthropoda",
"arthropod",
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"biology",
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"life",
"sciences",
"organisms"
] |
2014
|
Ex-ante Benefit-Cost Analysis of the Elimination of a Glossina palpalis gambiensis Population in the Niayes of Senegal
|
The Global Program to Eliminate Lymphatic Filariasis ( GPELF ) advocates for the treatment of entire endemic communities , in order to achieve its elimination targets . LF is predominantly a rural disease , and achieving the required treatment coverage in these areas is much easier compared to urban areas that are more complex . In Ghana , parts of the Greater Accra Region with Accra as the capital city are also endemic for LF . Mass Drug Administration ( MDA ) in Accra started in 2006 . However , after four years of treatment , the coverage has always been far below the 65% epidemiologic coverage for interrupting transmission . As such , there was a need to identify the reasons for poor treatment coverage and design specific strategies to improve the delivery of MDA . This study therefore set out to identify the opportunities and barriers for implementing MDA in urban settings , and to develop appropriate strategies for MDA in these settings . An experimental , exploratory study was undertaken in three districts in the Greater Accra region . The study identified various types of non-rural settings , the social structures , stakeholders and resources that could be employed for MDA . Qualitative assessment such as in-depth interviews ( IDIs ) and focus group discussions ( FGDs ) with community leaders , community members , health providers , NGOs and other stakeholders in the community was undertaken . The study was carried out in three phases: pre-intervention , intervention and post-intervention phases , to assess the profile of the urban areas and identify reasons for poor treatment coverage using both qualitative and quantitative research methods . The outcomes from the study revealed that , knowledge , attitudes and practices of community members to MDA improved slightly from the pre-intervention phase to the post-intervention phase , in the districts where the interventions were readily implemented by health workers . Many factors such as adequate leadership , funding , planning and community involvement , were identified as being important in improving implementation and coverage of MDA in the study districts . Implementing MDA in urban areas therefore needs to be given significant consideration and planning , if the required coverage rates are to be achieved . This paper , presents the recommendations and strategies for undertaking MDA in urban areas .
Lymphatic Filariasis ( LF ) is a significant health problem in many developing countries with over 1 billion people believed to be at risk in endemic areas [1 , 2] . LF is also the second leading cause of permanent disability after leprosy [3] and undermines the social and economic welfare of affected people and communities [4] . The World Health Assembly passed a resolution in 1997 to eliminate LF by the year 2020 . In the year 2000 , the World Health Organization launched the global programme to eliminate LF [5] . The strategy employed involves annual mass treatment with single-dose diethylcarbamazine ( DEC ) or Ivermectin ( IVM ) in combination with Albendazole ( ALB ) for 4–6 years . This is the principal strategy of LF elimination . The strategy is backed by studies that have shown that one or two annual treatments with antifilarial drugs exert only limited effects on microfilaria rates and intensities and multiple rounds of treatment are necessary to reduce the microfilaria prevalence to zero [6] . Drug distribution in urban areas , however , has become a major challenge for programs involved in the elimination of LF [2 , 7] . An adequate level of 65% epidemiologic coverage is needed to eliminate LF [8] , but this continues to remain a challenge in urban areas for most countries including Ghana . While there is little literature available on urban MDA [9–11] , the scarcity of information makes it even more difficult to solve the challenges presented . The Greater Accra Region ( GAR ) with Accra as the capital city of Ghana continues to get low coverage for its annual MDA . Accra Metropolitan district started treatment in 2006 and had a fluctuating epidemiologic coverage of 49 . 4% , 11 . 1% , 37 . 6% and then 60 . 2% respectively for 2006 , 2007 , 2008 and 2009 treatments . Urban areas are generally known to have a mix of diverse populations . They also tend to have very densely populated urban slums with large mobile populations . This phenomenon requires varied but specific strategies tailored for the different identifiable groups rather than a uniform distribution strategy . The design of interventions for specific groups in urban areas requires appropriate diagnosis of the problem . Thus , in the Greater Accra region there was need to identify the reasons for poor treatment coverage in order to design specific strategies to improve the delivery of MDA . As such , the main objective of this study was to identify the opportunities and barriers for implementing MDA in urban settings in order to develop appropriate strategies for MDA in these urban settings .
Approval for the study was received from the Ethics review Committee of the Ghana Health Service . Written consent was obtained from all individuals who participated in the study .
Many challenges to MDA were also reported following interviews with various providers and facilities heads . First among the challenges was the inadequate remunerations and motivation . Health providers were interested in knowing how much they will be paid before they attend training for MDA . Remuneration only after the training or work has been done was not appreciated . Below is a statement from one of the FGD members . Another challenge identified , in all three sub metro areas , was the lack of some logistics to assists in MDA , such as rain coats , vehicles for supervision , and stationery ( reporting forms , pen , and pencil ) . These were reported to be either inadequate or not available . Providers reported that often the program is poorly planned and impromptu arrangements are made , with training done on the spur-of- the moment , which was not ideal . As such , complaints about the delay in the provision of logistics as a result of poor planning are a challenge to drug distribution . Health providers indicated that their exclusion in the planning process for the drug distribution , and their involvement only when their services are needed was not the best and would prefer to be involved at all stages . The sentiment below reflects some of these views . The supervisors also reported that the dress code of some distributors was unacceptable to some community members and that may contribute to refusal of some people to accept volunteers in their homes and take the drugs . As such , they suggested T-shirts for volunteers rather than allowing them to wear their own clothes . Some of the supervisors were of the view that volunteers needed to be provided with some form of identification cards to ensure their acceptability and trust by community members . Even though the supervisors have been working with the drug distributors over the years there was suspicion that drug distributors throw away drugs when they are unable to distribute them , due to the large coverage targets they are to meet . Reasons for throwing away these drug are not clear . Providers however indicated that they encourage distributors to desist from such acts . These sentiments are captured in the sentence below . One of the main concerns of providers and distributors in some of the communities is the consumption of alcohol by community members making it difficult for distributors to give them drugs to take during MDA . Other impediments have to do with food and water . Some community members ask that they are provided with food and water or money to buy them when they have not taken in any food at the time of arrival of drug distributors . Finally , the providers reported that early awareness creation prior to the distribution of drugs is important for effective distribution and acceptability . Both health care providers and volunteers stressed the importance of creating awareness and public education and information using the mass media and other available communication strategies as key to a successful implementation of MDA . The volunteers also described their challenges with respect to the drug distribution . Remuneration was the main concern for volunteers . Volunteer allowances were considered insignificant . Volunteers explained that they experience difficulties in reaching communities of higher socio-economic status . Convincing them to take drugs was a challenge among community members . The feeling of disrespect to CDDs by residents in these communities was another challenge . Volunteers felt intimidated when they were not able to express themselves well in English and were not able to respond to questions posed by these residents adequately . In some of these communities school authorities asked for parental consent before any child was given the drug . This then means that school authorities need to be informed prior to any drug distribution . Without parental consent a child will not be allowed by school authorities to take the drug . Even with parental consent school authorities are reluctant to allow children from high-income communities to take the drug . Also , some community members want to be sure distributors are truly sent by the government to distribute drugs . Some families and school heads ask for introductory letters from distributors . Volunteers suggested that the program provide T-shirts or other form of identification when they visit such communities . Many people in the urban communities insist on knowing whether the volunteers are genuine before allowing drug distributors to give drugs to their households . Some concerns of the distributors are reflected in the comments below: Following the pre-intervention assessments , several recommendations were made with regard to improving MDA implementation in urban areas . Based on recommendations made by both health workers and community members interviewed during the pre-intervention survey , meetings were held with health workers at the regional , metropolitan/ and sub-metropolitan level . Many recommendations were made following the pre-intervention phase . It was operationally impossible to implement them all and therefore after discussions with the implementing districts , some of them were selected for implementation . Table 16 summarizes the issues identified , the solutions and interventions that were implemented . The study team and the national NTD program office provided direct support and guidance to the implementing districts at all stages of implementation . While the interventions were specifically implemented in Ashiedu Keteke and Ledzokuku , the study team made no input into the activities undertaken in Ayawaso . Any activity undertaken in Ayawaso , such as the use of mobile vans for social mobilization , was carried out at the discretion of the health workers . The findings of the pre-intervention survey were disseminated at the regional review and training of trainers for the 2012 MDA . Meetings were also held with the District Health Management Teams ( DHMTs ) to further discuss the details of the findings with them to ensure better understanding of the issues . Many meetings were held with the DHMTs to discuss and agree on which recommendations to implement and what is involved in carrying them out . The details of the issues to address and the overall scope of work were examined . The need to change some of the ways of routinely implementing the program was stressed .
The observations from this study showed that , generally knowledge , attitudes and practices of community members to MDA improved slightly from the pre-intervention phase to the post-intervention phase . However , the intervention did not result in an increase in the number of people receiving the drug in all districts . Many factors were identified as being important in improving implementation and improving coverage of MDA in urban areas . Significant among these are leadership , planning , funding , developing an ideal work force of both health workers and community drug distributors , involvement of community members and knowledge of the disease targeted by the MDA drugs . Implementing MDA in urban areas therefore needs to be given significant consideration and planning , taking into consideration quality improvement processes , if the aims of achieving the required coverage rates are to be achieved .
|
The control of lymphatic filariasis depends on the treatment of entire endemic communities , ensuring that a greater proportion of the population is treated . In urban areas , this can be very difficult to achieve . In Ghana , parts of the Greater Accra Region , where the capital city is located , are also endemic for lymphatic filariasis . Treatment in these areas started in 2006 , but the proportion of people treated has continuously been below the required programmatic coverage levels . To understand the reasons behind this , a study was undertaken in three endemic districts . The study was carried out in three stages; pre-treatment , treatment and post-treatment . Individuals and groups of people were interviewed in the pre-treatment phase , following which their concerns were used to plan and execute treatment activities . After treatment , some individuals were again interviewed to assess the effectiveness of the interventions . The results showed that the knowledge and behavior of community members towards the disease and treatment activities improved from the pre-treatment to the post-treatment reviews . Many factors were identified including , financial , management and leadership issues that should be considered when planning treatment activities in urban areas .
|
[
"Abstract",
"Introduction",
"Method",
"Results",
"Discussion"
] |
[
"medicine",
"and",
"health",
"sciences",
"tropical",
"diseases",
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"physical",
"activity",
"health",
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"pharmaceutics",
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"drug",
"distribution",
"pharmacokinetics",
"helminth",
"infections",
"physical",
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"education",
"and",
"awareness"
] |
2017
|
Improving drug delivery strategies for lymphatic filariasis elimination in urban areas in Ghana
|
The human liver fluke , Opisthorchis viverrini , infects millions of people throughout south-east Asia and is a major cause of cholangiocarcinoma , or cancer of the bile ducts . The mechanisms by which chronic infection with O . viverrini results in cholangiocarcinogenesis are multi-factorial , but one such mechanism is the secretion of parasite proteins with mitogenic properties into the bile ducts , driving cell proliferation and creating a tumorigenic environment . Using a proteomic approach , we identified a homologue of human granulin , a potent growth factor involved in cell proliferation and wound healing , in the excretory/secretory ( ES ) products of the parasite . O . viverrini granulin , termed Ov-GRN-1 , was expressed in most parasite tissues , particularly the gut and tegument . Furthermore , Ov-GRN-1 was detected in situ on the surface of biliary epithelial cells of hamsters experimentally infected with O . viverrini . Recombinant Ov-GRN-1 was expressed in E . coli and refolded from inclusion bodies . Refolded protein stimulated proliferation of murine fibroblasts at nanomolar concentrations , and proliferation was inhibited by the MAPK kinase inhibitor , U0126 . Antibodies raised to recombinant Ov-GRN-1 inhibited the ability of O . viverrini ES products to induce proliferation of murine fibroblasts and a human cholangiocarcinoma cell line in vitro , indicating that Ov-GRN-1 is the major growth factor present in O . viverrini ES products . This is the first report of a secreted growth factor from a parasitic worm that induces proliferation of host cells , and supports a role for this fluke protein in establishment of a tumorigenic environment that may ultimately manifest as cholangiocarcinoma .
Cholangiocarcinoma ( CCA ) , or cancer of the bile ducts , is prevalent in people from Thailand and Laos whose staple diet includes uncooked fish which harbour the liver fluke , Opisthorchis viverrini , the main risk factor for this cancer in the region [1] . There is no stronger link between a parasite and cancer than that between O . viverrini and CCA - indeed WHO data suggest that as many as one-third of the nine million infected people will contract cancer [2] . This is a striking figure compared to data from other carcinogenic microbes , such as Helicobacter pylori , human papilloma virus and the hepatitis viruses , where less than one percent of infected individuals develop infection-related cancers [2] , [3] . For opisthorchiasis , in vivo studies in hamsters and in vitro investigations have indicated that the fluke's excretory/secretory ( ES ) products , metabolic products excreted and secreted into the external environment from the excretory openings and epithelial surface ( tegument ) , include mitogens that likely play a role in the initiation of CCA in infected humans and experimentally infected hamsters [4] , [5] . To gain a better understanding of the host-parasite interactions underlying the molecular pathogenesis of opisthorchiasis , we screened both the transcriptome [6] and the ES proteome ( J . Mulvenna et al . , unpublished ) of the fluke for genes encoding proteins with ontologies that were associated with human cancers . A homologue of human granulin , a secreted growth factor implicated in many aggressive and invasive cancers , was identified . The granulin domain consists of 12 highly conserved cysteines and is found in diverse phyla from eubacteria to humans , and subsequently has many synonyms [7] . Compounding the confusion , the term granulin can also refer to the small 6–10 kDa granulin domain ( also named epithelins or GEM∶granulin/epithelin modules ) found in the majority of animals , or the vertebrate protein , progranulin ( PGRN ) , which in mammals is a large 60–90 kDa glycoprotein containing seven tandemly repeated granulin motifs [8] . PGRN protein is also known as PC cell-derived growth factor ( PCDGF ) , proepithelin ( PEPI ) , Granulin/epithelin precursor ( GEP ) , GP88 , acrogranin , granulin or epithelin precursor [9] . Herein we will refer to the large multihomodomain form from vertebrates as PGRN , and granulin ( GRN ) will refer to the individual granulin domains . There is a broad distribution of PGRN in human organs and tissues , and elevated levels of mRNA are found in organs with neuronal cells ( cerebellum ) , hematopoietic stem cells ( spleen ) and rapidly dividing epithelium ( skin , gastrointestinal tract and wounded epithelia ) [10] , [11] . Numerous functions for GRNs have been reported but the roles in cell cycle control and wound healing are noteworthy [8] . Numerous mutations have been observed within the human PGRN gene with many linked to psychiatric disorders including Alzheimer's disease and frontotemporal dementia [12] , [13] . Over-expression of PGRN is linked to tumorigenesis in numerous human tissues , including liver cancers , and is associated with an aggressive and invasive tumour phenotype [14] , [15] . GRN is a potent proliferative agent but has other pro-tumor qualities that are not yet well characterized . It may promote carcinoma progression by promoting angiogenesis , insensitivity to apoptosis , promotion of tumor invasion and anchorage independence which all support tumor expansion in the unfavorable interstitial environment [7] , [16] , [17] . Preventing over-expression of PGRN in a range of tumor types , either through gene silencing or neutralizing antibodies , reduces or entirely inhibits tumor progression [18] . Over-expression of PGRN is an indicator of poor prognosis for a range of cancer types , and anti-GRN antibodies have been successfully employed in mice as therapy for hepatocellularcarcinoma ( HCC ) [19] . Large-scale gene sequencing efforts have revealed GRN homologues in the majority of parasitic phyla [20] , [21] , [22] . Like free-living eukaryotes , parasitic helminths probably utilize GRN to regulate growth and development of their own cells . By contrast , here we describe the detection of GRN in the ES products of O . viverrini and its binding to mammalian biliary epithelial cells in situ . Furthermore , recombinant O . viverrini GRN stimulated proliferation of fibroblasts , whereas antibodies against the recombinant GRN inhibited the ability of ES products to promote proliferation . Together these findings support a role for this fluke protein in establishment of a tumorigenic environment that may ultimately manifest as CCA .
Characterization of the protein profile of O . viverrini adult worm ES products using LC-MS/MS revealed a 19 amino acid peptide , with a MOWSE score of 50 ( delta error -0 . 0464 ) ( Figure 1 inset ) , that matched to a single contig encoding a protein with sequence similarity to human granulin ( not shown ) . The cDNA was termed Ov-grn-1 and its protein product Ov-GRN-1; the sequences were submitted to GenBank under accession number FJ436341 . Verification of the MS/MS identification was then performed using multiple-reaction monitoring ( MRM ) transitions targeted against the peptide identified in the shotgun proteomics . Firstly , a tryptic digest of O . viverrini ES products , collected after one day of culture , was analyzed and the target peptide identified and fragmented . Next , recombinant Ov-GRN-1 in water was digested and analyzed in the same fashion . The target peptide from the ES sample was identified at the same elution time and with an identical product ion spectrum as that generated for recombinant Ov-GRN-1 ( Figure 1 ) . The peptide observed showed very abundant y-ion fragments , as expected , on the C-terminal side of the peptide . The peptide also revealed a missed trypsin cleavage at the Arg residue , due to the Pro residue on its C-terminal side . The combination of the initial MS/MS data , elution time of the target peptide in both samples and the similarity of MRM fragmentation patterns strongly supports the presence of Ov-GRN-1 in the ES products of O . viverrini . Ov-GRN-1 , like homologues from the related liver fluke Clonorchis sinensis and earthworms , has an N-terminal signal peptide followed by a single GRN core domain . Most other proteins containing a GRN domain consist of multiple GRN domains ( PGRN ) or at least one GRN domain fused to other domains including proteases , protease inhibitors and fibronectin ( Figure 2A ) . Ov-GRN-1 consists of a predicted secretion signal peptide followed by an 84 amino acid GRN domain of 9 . 04 kDa with twelve conserved cysteines . Whereas no N-linked glycosylation sites were predicted , four putative O-glycosylation sites were identified at Ser-26 , Thr-35 , Thr-41 and Ser-61 . The core GRN domain of Ov-GRN-1 shared 43 . 6% identity at the amino acid level with granulin F , the closest human homologue , and 85% identity with an EST from the related liver fluke , Clonorchis sinensis ( Figure 2B ) . Data from the few GRN structures available suggest that Ov-GRN-1 adopts the general GRN fold and disulphide bonding pattern akin to carp GRN , the only complete GRN structure available to date [23] . The NMR derived structure of carp ( Cyprinus carpio ) granulin [23] was used as the template on which to build a molecular model of Ov-GRN-1 ( Figure 2C ) . The two proteins shared 32% identity over their granulin core domains . The lowest energy structure from 50 calculated using MODELLER was selected as an approximation of the structure of Ov-GRN-1 . The model contained no violations of distance restraints and the Ramachandran plot , calculated with PRO-CHECK-NMR [24] , showed a single residue in the disallowed regions . Ov-GRN-1 grouped very closely with its orthologue from the related liver fluke , C . sinensis , a parasite that has also been implicated as a cause of human CCA [25] , and this clade obtained 100% bootstrap support ( Figure 3 ) . GRNs from the placozoan Trichoplax , slime mould , the free-living nematode Caenorhabditis elegans and human granulin B also formed a clade with the liver fluke GRNs , although this did not obtain bootstrap support of greater than 50% . Interestingly , the blood fluke ( Schistosoma ) GRNs did not group closely with Ov-GRN-1 – most O . viverrini genes share greater sequence identity with other platyhelminth genes [6] than they do with genes from other phyla , suggesting that the phylogeny presented here reflects functional protein relationships rather than taxonomic relationships . It is also noteworthy that the schistosome GRN domains were probably derived from a multi-domain PGRN . Reverse transcription PCR using RNA from different Opisthorchis life cycle stages amplified a product of the expected size , ∼300 bp , in all developmental stages tested ( Figure S1 ) , indicating that Ov-grn-1 was constitutively expressed throughout the developmental cycle of the liver fluke . An amplicon was not detected in the absence of reverse transcriptase enzyme ( not shown ) , confirming the absence of contaminating genomic DNA . The constitutively expressed actin gene served as a control and was expressed in all stages . Ov-GRN-1 was expressed in E . coli and in Sf9 insect cells . We herein refer to the E . coli-derived recombinant protein as Ov-GRN-1e and Sf9-derived protein as Ov-GRN-1s . Soluble 6×His tagged Ov-GRN-1s protein with a molecular mass of ∼14 kDa was expressed in Sf9 cells at a yield of ≤200 µg purified protein per litre of culture medium . A combination of cation exchange and Ni-NTA affinity chromatographies followed by a second Ni-NTA purification resulted in recombinant granulin that appeared to be greater than 95% pure based on SDS-PAGE gels ( not shown ) . Ov-GRN-1e was highly expressed ( up to 60 mg/L ) in each of three E . coli cell lines ( BL21 , Rosetta , Rosetta-gami ) but in each case the Ov-GRN-1e was insoluble and required urea ( or other chaotropic agents ) to solubilise . Different induction times and temperatures were assessed , and none of these variables promoted the solubility of the recombinant Ov-GRN-1e . To obtain denatured recombinant protein , BL21 E . coli cells transformed with pET41a encoding the Ov-GRN-1 ORF were grown at 37°C and induced for 16 h . Recombinant protein was purified on Ni-NTA resin under denaturing conditions to yield >95% pure protein ( Figure 4A ) . Refolding of the purified denatured protein was undertaken , and the best conditions identified yielded ∼15% recovery of soluble protein by refolding in 20 mM Tris pH 7 . 5 , 1 mM CaCl2 for 24 hr . IgG antibodies raised against recombinant Ov-GRN-1e and GRN-1s proteins in mice were employed to probe the recombinant immunogens and Opisthorchis somatic adult extract ( SAE ) by Western blotting under both native and denaturing/reducing conditions . Bands were only visible when SAE was probed under native conditions with both anti-GRN-1s and anti-GRN-1e IgGs , with a strong band visible at 38 kDa , higher than the predicted 9 kDa mass of the monomeric protein ( Figure 4B ) . Neither antibody bound to any proteins under reducing/denaturing conditions ( not shown ) , suggesting that conformational epitopes were the target of anti-GRN-1 antibodies , and that the native protein might form homo-multimers or form complexes with other proteins under native conditions . Control antibodies did not produce any bands under native or denaturing/reducing conditions . Anti-GRN-1s IgG was used to localize the sites of expression within adult O . viverrini and in the surrounding bile ducts of an experimentally infected hamster . Ov-GRN-1 exhibited ubiquitous expression through all tissues , particularly in the gut , tegument and tegument extrusions of the adult worm ( Figure 4C , right upper panel ) . Interestingly , the protein was also strongly detected in the bile duct epithelial cells in close proximity to the liver fluke . Control mouse IgG did not bind to any tissue or structures in the fluke or hamster tissues ( Figure 4C , left panel ) . Additionally anti-Ov-GRN-1s IgG showed no affinity for host granulin as indicated by a lack of staining in uninfected hamster liver ( Figure 4C , lower right panel ) Others have shown that O . viverrini causes proliferation of fibroblasts and the KKU-100 CCA cell line when these cells are co-cultured in the presence of live adult O . viverrini in a non-contact format [4] , [26] . We reproduced these findings ( Figures 5A and S2A ) and proceeded to show that soluble ES products from O . viverrini stimulated proliferation of NIH-3T3 fibroblasts ( Figures 5B , S2B and S3 ) and the KKU-100 CCA line ( not shown ) . Cell proliferation was measured using two distinct approaches . WST-1 is a measure of metabolic activity of cells , and although it is routinely used to measure cell growth over time , metabolic variations in cells exposed to different conditions ( e . g . in the presence of ES products ) can mask changes in real cell numbers . We also assessed the growth of cells using a real time index of measurement to corroborate the proliferation quantified by the WST-1 assay using an xCELLigence system . The cell index readout is a real time measure of conductivity which is indicative of cell surface area in contact with the gold electrodes covering the plate surface [27] . We optimised the conditions for ES-induced cell growth to permit a thorough assessment of the effects of ES products ( and other treatments ) over time . Cells were seeded at an adequate density to determine growth over 3 days in a reliable manner before reaching confluence . Conditions that resulted in a minimum of two-fold growth of NIH-3T3 fibroblasts between samples treated with and without ES over 3 days were determined in the presence of increasing concentrations of bovine calf serum ( BCS ) in a 96 well plate – final conditions were 0% BCS seeded at 6000 cells/well , 2% BCS at 2000 cells/well , 5% BCS at 700 cells/well and 10% BCS at 300 cells/well . The optimal conditions identified for detection of approximately two-fold proliferation of NIH-3T3 fibroblasts induced by addition of ES compared with an equal volume of PBS ( control ) were as follows: 2 , 000 cells seeded per well and cultured for 3–8 h in DMEM containing antibiotic/antimycotic at 37°C in 95% air/5% CO2 and 2% BCS prior to addition of ES products ( 20 µl ) to a final concentration of 20 µg/ml . Cells were cultured in the presence of ES or PBS and cell numbers were determined using the WST-1 dye procedure . Addition of ES to cells grown in all serum concentrations tested resulted in changes in cell growth and morphology; Figure 5C presents the results of cell growth in the presence of 2% BCS . The flattened fibroblastic shape of 3T3 cells changed upon addition of ES products , resulting in a longer , narrower and more refractive spindle shaped cell morphology . A range of concentrations of recombinant Ov-GRN-1e was included with cells under different culturing conditions , based on information from other investigations with ES , as described above . Nanomolar concentrations ( 50–200 nM ) of Ov-GRN-1e induced significant growth of cells above growth of control cells treated with either PBS or an irrelevant recombinant protein purified under the same conditions as for Ov-GRN-1e ( Figures 6 and S4 ) . Four hundred nM Ov-GRN-1e induced significant growth after one day ( P<0 . 05 ) , after which cell growth slowed and cell numbers were equivalent to cells treated with control protein by day 3 ( Figure 6A ) . At higher concentrations ( ≥800 nM ) the cells suffered adverse effects and did not survive beyond 24 hr ( not shown ) . Compared to control protein , 200 nM Ov-GRN-1e promoted significant growth after one day ( P<0 . 05 ) and 50–200 nM Ov-GRN-1e caused significant growth by day 3 ( P<0 . 05; Figure 6B ) . Cell proliferation induced by both ES products and recombinant Ov-GRN-1 was completely ablated in the presence of 10 µM U0126 , an inhibitor of Erk1/2 signalling , indicating that Ov-GRN-1 , like human PGRN , signals via the MAPK pathway . Intriguingly , refolded Ov-GRN-1e that was concentrated ( retentate ) using a 3 kDa cut-off centrifugal concentrator membrane did not induce cell growth , however the column flow through ( i . e . >3 kDa ) did induce proliferation . Indeed , the proliferation was greatly enhanced at lower concentrations ( 10 nM ) compared with refolded Ov-GRN-1e that had not undergone concentration ( 50–200 nM; measured in real time by xCELLigence - Figures 7 and S5 ) . Using both SDS PAGE and Western blotting with anti-6×His antibody we identified a small amount ( ∼5–10% of purified and refolded protein ) of refolded protein that reproducibly passed through a 3 kDa cut-off membrane . To determine whether Ov-GRN-1 was responsible for the mitogenic activity of ES , we attempted to neutralize the mitogenic activity of ES with anti-Ov-GRN-1 antibodies . Anti-GRN-1s IgG inhibited ES-induced proliferation of NIH-3T3 fibroblasts ( Figures 8A and S6A ) . After 3 days of cell culture , significant inhibition of proliferation was evident at concentrations of 20 and 40 µg/ml IgG in both 2% and 5% BCS cultures ( P<0 . 01 - <0 . 001 ) . Similar antibody-induced suppression of proliferation was obtained in the absence of BCS over two days ( not shown ) , but after two days control cells ( treated with PBS ) began to die . NIH-3T3 cells were grown under identical conditions as described above −20 µg/ml ES , 20 µg/ml test or control IgGs and 2% BCS over 3 days - and monitored with the xCELLigence system ( Figures 8B and S6B ) . Cells treated with ES alone or ES in the presence of control IgG grew at the same rate ( F ( 2 , 186 ) P = 0 . 65 ) with a steady increase of 0 . 2–0 . 25 units over 24 hours and then a reduced rate of increase of 0 . 05–0 . 1 units for the subsequent two days . This was similar to the growth rates measured with WST-1 . When ES in the presence of either anti-Ov-GRN-1e or anti-Ov-GRN-1s IgGs were incubated with cells , growth slowed significantly ( F ( 2 , 186 ) P<0 . 0001 ) compared to cells treated with ES alone or ES plus control IgG and showed only minor variations from the growth profile of NIH-3T3 cells treated with PBS alone ( Figure 8B ) . The inhibitory effect of anti-Ov-GRN-1 IgG on the growth of the KKU100 CCA cell line induced by ES products was also assessed . Cells were cultured for 3 days in RPMI 1640/2% BCS with a final concentration of 20 µg/ml ES . Cell growth is presented as absorbance at 450 nm rather than as a growth ratio because of the differences in growth characteristics between this cell line and NIH-3T3 fibroblasts . The same general trend was observed , whereby anti-GRN-1e and to a lesser but still significant extent , anti-GRN-1s , IgGs inhibited proliferation induced by ES in an antibody dose-dependent fashion ( Figure 8C ) . Significant inhibition was observed with 16 µg/ml ( P<0 . 05 ) and 24 µg/ml ( P<0 . 001 ) anti-GRN-1e IgG . Addition of IgGs to cells in the absence of ES had no effect on cell growth ( not shown ) .
Initiation of CCA in chronic opisthorchiasis in humans [28] and experimentally infected hamsters [29] is thought to be multi-factorial , involving ( 1 ) infection-induced inflammation , particularly the release of reactive oxygen and nitrogen species from inflammatory cells , ( 2 ) dietary nitrosamines consumed by endemic populations , ( 3 ) secretion by the fluke of mitogens into the biliary tree [5] . Co-culture of O . viverrini adult worms with mouse fibroblasts ( NIH-3T3 ) where parasites and cells are separated by a porous membrane results in cell proliferation [4] . Here we show that soluble ES products , in the absence of live O . viverrini parasites , and recombinant Ov-GRN-1e cause proliferation of mouse fibroblasts and a human CCA cell line , and that proliferation caused by ES products can be blocked with anti- Ov-GRN-1e antibodies . This data implies that Ov-GRN-1 is perhaps the major mitogenic factor in ES , and this protein contributes to the development of an environment that is conducive to CCA . The GRN protein family is found in a diverse range of organisms including bacteria , plants and animals . Our phylogenetic analysis of the protein family suggested that a majority of GRN proteins do not form clades based on taxonomic groupings but rather group according to protein functions . The individual GRN domains from human PGRN form distinct clades with homologues from other species , supporting the notion that these proteins have evolved to perform distinct functions in different organisms , and furthermore , individual GRN domains released after processing of the multi-domain PGRN have also evolved to perform discrete functions . A range of organisational archetypes are seen within the family , ranging from single GRN domains behind a secretory signal peptide , as seen in earthworms and the liver flukes , to multi-homodomain PGRNs and even single GRN domains fused to other protein domains [7] . The structure of GRN is unique , although it can be partially superimposed on the 3-dimensional fold of epidermal growth factor ( EGF ) , despite the absence of primary sequence identity [30] . Furthermore , Ov-GRN-1 and human PGRN , like EGF , triggers similar signalling cascades , including the MAPK pathway [31] . When NIH-3T3 fibroblasts were co-cultured with O . viverrini adult worms without serum , only mRNAs associated with EGF and TGF-beta signalling pathways were significantly upregulated , further supporting a role for Ov-GRN-1 in parasite-induced proliferation and downstream signalling of host cells [32] . Granulin-induced cell proliferation can result in upregulation of EGF family members , such as VEGF , which could account for upregulation of genes involved in the EGF pathway [31] . Ov-GRN-1 was expressed at very low levels in lepidopteran ( Sf9 ) cells , limiting more thorough investigation of this form of the protein . By contrast , Ov-GRN-1 was expressed at high yield in E . coli and could be refolded into an active form that induced proliferation at nanomolar concentrations . This is the first report , to our knowledge , of a secreted growth factor from a parasite that induces proliferation of host cells . This is also the first report of functional recombinant expression of a single domain granulin . Tolkatchev expressed all 7 granulin domains individually from human PGRN but only three , granulins A , C and F , appeared to adopt at least partially correct fold and induced growth [33] . Despite refolding denatured Ov-GRN-1e to generate a functional recombinant protein that induced cell proliferation , the majority of functional recombinant protein passed through a 3 kDa cut-off membrane . If Ov-GRN-1 does indeed adopt a similar fold to carp granulin ( Figure 2C ) , the super helical structure held tightly together by 6 disulphide bonds might well pass through a 3 kDa membrane ( Figure 7 ) . Furthermore , the apparent molecular weights of native human granulins purified from leukocytes range from 1 . 7–3 . 2 kDa and would likely pass through a 3 kDa membrane , as we observed here with functionally active Ov-GRN-1 [34] . The low nanomolar activity displayed by refolded Ov-GRN-1 is comparable to the activity of purified human granulins [15] . GRN is associated with many aggressive cancers . It is over-expressed in human liver [14] , [19] , renal [35] , breast [31] , [36] , [37] , bladder [16] and brain [15] tumors . It may promote cancer progression by stimulating angiogenesis , suppressing anoikis ( a form of apoptosis ) , promotion of tumor invasion and anchorage independence , all of which support tumor expansion in the unfavourable interstitial environment [7] , [16] , [17] . Preventing the activity of PGRN in a range of tumor types , either through gene silencing or antibody neutralization , reduces or entirely inhibits tumor progression [18] . Transfection of fibroblasts with PGRN induces serum independent proliferation but does not transform them into neoplastic cells , suggesting that the protein is probably not oncogenic by itself , but over-expression of PGRN in the SW-13 non-malignant adrenal carcinoma cell line made it highly tumorigenic [38] . Indeed , PGRN is a therapeutic target for liver cancer , particularly HCC . An anti-PGRN monoclonal antibody inhibited tumor growth in vivo in nude mice transplanted with human HCC [19] . The anti-PGRN antibody also inhibited growth of hepatoma cells but had no significant effect on normal liver cells , and inhibited the growth and proliferation of established tumors via the p44/42 MAPK and Akt pathways . These findings demonstrate that GRN is an important factor in the initiation of liver cancer and the migration of cancerous cells . We showed here that Ov-GRN-1 signals via the MAPK pathway , further accentuating the potential role of this parasite protein in the initiation of CCA in people with chronic opisthorchiasis . Increased PGRN expression has not been reported in CCA , however , when gene expression profiles from intrahepatic CCA associated with or without O . viverrini were compared , genes associated with growth factor signalling were the most highly upregulated ontology in the non-fluke associated CCA , whereas genes involved in xenobiotic metabolism were the most highly upregulated genes in fluke associated CCA [39] . It is intriguing that genes involved in growth factor signalling pathways were selectively upregulated in non-fluke associated CCA . This prompts the speculation that Ov-GRN-1 causes excessive proliferation and migration of pre-cancerous and cancerous cells in the bile ducts of infected people , obviating the necessity for local upregulation of the host growth factors and associated signalling molecules during tumorigenesis . Why O . viverrini secretes such a potent growth factor that acts on host cells is unclear . One potential role for fluke GRN is in the wound repair . Inflammatory cells secrete peptides derived from PGRN [34] , and PGRN mRNA is highly induced in dermal fibroblasts and epithelial cells following transcutaneous puncture wounds [8] . Furthermore , recombinant PGRN increased the accumulation of inflammatory cells , blood vessels and fibroblasts at puncture sites , implying a direct role as a wound-healing growth factor [9] . O . viverrini adult worms grasp the bile duct wall with their suckers and feed on the biliary cells , often severely damaging the epithelium . Additional inflammation occurs as a result of the local immune response to resident worms ( reviewed in [5] ) . Ov-GRN-1 might therefore play a role in wound repair at and around the feeding site to minimize the pathology that the parasite causes to the host . Another potential role for Ov-GRN-1 is in the “farming” of host cells for nutritional purposes . By promoting growth of cells at the feeding site , the parasite is ensured of a steady supply of nutrients . Blood-feeding leeches secrete a GRN that inhibits thrombin activity [40] , and Ov-GRN-1 might also perform a similar function to interfere with clot formation while feeding . Like some other O . viverrini proteins , Ov-GRN-1 was identified on the surface of and inside host biliary epithelial cells . O . viverrini ES products adhere to and are internalised by hamster biliary epithelial cells in the first order bile ducts as well as the small extra-hepatic bile ducts where the parasite is too large to reside [41] . Until now , only one ES product that is internalized by host cells had been identified - thioredoxin peroxidase [42] . The mechanism of uptake of O . viverrini ES components by host cells is unknown . With a related fluke , Schistosoma japonicum , fluke glutathione transferase ( GST ) is translocated from the medium into a variety of mammalian cell types via an endocytotic pathway involving clathrin-coated pits [43] . Like most helminth parasites , O . viverrini secretes a GST ( J . Mulvenna et al . , unpublished ) , which along with other ES proteins ( such as Ov-GRN-1 ) , might enter host cells via a similar endocytotic mechanism . Translocation of O . viverrini proteins into host biliary epithelial cells is particularly important due to the carcinogenic nature of this parasite and the putative roles that internalised ES play in transforming host cells [5] . Helicobacter pylori delivers the CagA protein into gastric epithelial cells where it interacts with a kinase involved in cell polarity , resulting in disorganization of gastric epithelial architecture , inflammation and carcinogenesis [44] . Translocation of O . viverrini ES products such as Ov-GRN-1 , into biliary epithelial cells might likewise interfere with signalling , promoting carcinogenesis . Moreover , liver fluke ES products inhibit apoptosis ( B . Sripa , unpublished; [45] ) , further contributing to a tumorigenic environment . Despite the deployment of mass drug administration programs throughout Thailand , opisthorchiasis is still a major public health concern , and the prevalence of the infection in some areas is increasing [5] , [46] . Like other neglected tropical diseases , an integrated control program is required to have a lasting impact on reducing transmission and disease burden . To this end , a vaccine for opisthorchiasis is desperately needed to reduce worm burdens and minimize pathology . A recombinant vaccine based on Ov-GRN-1 is particularly attractive because of the potential role of this protein in establishing a pro-tumorigenic environment in the bile ducts . Such a vaccine would therefore have a major impact on reducing both parasite burdens and the incidence of CCA , the most prevalent and fatal of the liver cancers in north-east Thailand .
Hamsters used in this study were maintained at the animal research facility of the Khon Kaen University Faculty of Medicine; all work was conducted in accordance with protocols approved by the Khon Kaen University Animal Ethics Committee . Mice used in this study were housed at the Queensland Institute of Medical Research ( QIMR ) animal facility; all work was conducted in accordance with protocols approved by the QIMR Animal Ethics Committee . O . viverrini metacercariae were obtained from naturally infected cyprinoid fish in Khon Kaen province , Thailand . The fish were digested with pepsin-HCl , washed and used to infect hamsters ( Mesocricetus auratus ) by stomach intubation . Adult O . viverrini worms were recovered from bile ducts of euthanized hamsters infected for 3 months . Somatic adult worm extract ( SAE ) was prepared from frozen and homogenized adult worms resuspended in PBS with a cocktail of protease inhibitors covering serine , aspartic , cysteine and metallo-proteases ( protease inhibitor cocktail set #5 , Roche ) . ES products were prepared from live adult worms washed in antibiotics and incubated in modified RPMI-1640 ( Invitrogen ) at 37°C/5% CO2 . Supernatant containing the ES products was harvested daily for 7 days [41] . The supernatant was concentrated 20-fold to 100–300 µg/ml with 3 kDa Jumbosep spin concentrators ( Pall ) and aliquoted for storage at −80°C . Ov-GRN-1 was identified in the ES products of adult O . viverrini using liquid chromatography tandem mass spectrometry ( LC-MS/MS ) . The proteins present in ES products were identified by trypsin digestion followed by a combination of off-gel electrophoresis and LC-MS/MS as described by us for the analysis of ES products from the hookworm , Ancylostoma caninum [47] . For multiple reaction monitoring ( MRM ) , recombinant Ov-GRN-1 in water and O . viverrini ES were digested as described [47] . A Dionex 3000 HPLC system ( Dionex ) was used to perform reversed phase separation of the samples using a C18 300A column ( 150 mm×2 mm ) with a particle size of 5 µm ( Phenomenex ) . Twenty microliter aliquots of samples were dissolved in 5% formic acid ( aq ) and injected onto the HPLC column . The mobile phase consisted of solvent A ( 0 . 1% formic acid ( aq ) ) and solvent B ( 90/10 acetonitrile/0 . 1% formic acid ( aq ) ) . Tryptic peptides were eluted using a gradient elution programme of 0–40% B in 40 min , 40–80% B in 10 min and finally a 5-min hold at 80% B , followed by a return to 0% B for a 10-min equilibration . The flow rate was 250 µl/min . Eluate from the RP-HPLC column was directly introduced into the TurboIonSpray source . Mass spectrometry experiments were performed on a hybrid quadrupole/linear ion trap 4000 QTRAP MS/MS system ( Applied Biosystems ) . All analyses were performed using MRM , Information Dependant Acquisition Initiation Enhanced Product Ion experiments using both the triple quadrupole and the linear ion trap acquisition modes . Analyst 1 . 5 . 1 software was used for data analysis . The acquisition protocol to provide mass spectral data for both identification and characterization involved monitoring the HPLC eluant using MRM scans; ions over the background threshold of 200 counts per second were subjected to examination using the enhanced resolution scan to confirm charge states of the multiply charged molecular ions . The most and next most abundant ions in each of these scans with a charge state of +2 to +4 or with unknown charge were subjected to collision induced disassociation using a rolling collision energy dependent upon the m/z and the charge state of the ion . An enhanced product ion scan was then used to acquire the product ion spectrum . The 4000 QTRAP equipped with a TurboIonSpray Source was operated in the positive electrospray ionization mode . Sequences were edited and analysed with assistance from the MacVector software package . Homology searches were performed using Blast search at NCBI ( http://blast . ncbi . nlm . nih . gov/Blast . cgi ) . ORFs were analysed for signal peptides/anchors using SignalP-NN prediction and SignalP-HMM prediction at http://www . cbs . dtu . dk/services/SignalP/ . The O . viverrini cDNA encoding for GRN was termed Ov-grn-1 and was submitted to GenBank under accession number FJ436341 . The structural architecture of GRN family members was obtained from entry IPR000118 at the Interpro 18 . 0 database [48] . Prediction of potential glycosylation sites was determined using the YingOYang server [49] . Using version 3 of MODELLER , the three-dimensional structure of Ov-GRN-1 was predicted based on comparative modelling to carp granulin [23] . The covalent geometry of the modelled structure was in agreement with the template structures with all but one of the residues occupying the allowed regions of the Ramachandran plot . The quality of the stereo-chemical structures of the models was determined using PRO-CHECK-NMR [24] . Pymol was used to view the homology models ( http://www . pymol . org ) The phylogenetic relationship of Ov-GRN-1 with other GRN family members was inferred using a neighbor joining analysis in PAUP beta version 8 . 0 for Macintosh . Bootstrap values were determined from 1000 replicates . Where bootstrap values were below 50% , clades were collapsed to form polytomies . Where multiple GRN domains were observed within one PGRN protein ( e . g . , vertebrates and schistosomes ) , individual GRN domains sharing the greatest identity with Ov-GRN-1 were selected and numbered 1–3 in order of their identities . The individual GRN domains of human PGRN , however , have been alphabetically designated A–G in the order GFABCDE , based on their description in the literature . Extraction of O . viverrini RNA and subsequent reverse transcription PCR ( RT-PCR ) was carried out as described [50] , with minor modifications . Total RNA from each developmental stage of O . viverrini was extracted with Trizol ( Invitrogen ) according to the manufacturer's instructions . Contaminating genomic DNA was removed by treatment of RNA with DNase I ( Promega ) . For RT-PCR , first-strand cDNA was synthesized from 1 . 0 ug of total RNA using avian myeloblastosis virus reverse transcriptase ( Promega ) and an oligo ( dT ) primer at 42°C for 60 min . A 1 . 0 µl aliquot of the cDNA was amplified using primers specific for the control beta-actin mRNA ( Forward CGAGGTATCCTCACCCTCAA , Reverse GCGACTCGCAACTCATTGTA ) and the target Ov-grn-1 mRNA ( Forward CGCGCGCCATGGATACTTTGCAGCCAATT , Reverse GCGCGCCTCGAGTGCGACCTTTCGAGCGTT ) based on the following conditions: 30 sec denaturation at 94°C , 30 sec annealing at 55°C , and 30 sec extension at 72°C for 30 cycles . Control RT-PCR reactions were performed without reverse transcriptase to ensure that amplified products were derived from cDNA and not contaminating genomic DNA . PCR products were sized by electrophoresis through 1% agarose and visualized under UV light after staining with ethidium bromide . Ov-GRN-1 was expressed in both bacterial and insect cell expression systems . The complete ORF minus the predicted signal sequence was amplified using Expand polymerase ( Roche ) from an adult O . viverrini cDNA library [6] using primers described below and cloned into the plasmid pMIB/V5-His ( Invitrogen ) for insect ( Spodoptera frugiperda ) cell expression or cloned into the NdeI and XhoI sites of the pET41a vector ( Novagen ) for E . coli expression , thereby removing the GST fusion tag but retaining the 6×His tag and allowing for native N-terminal protein expression . Primers for insect cell expression were: pMIB F3 HindIII CGCGCGAAGCTTAATGGATACTTTGCAGCCAATT; pMIB R3 XbaI GCGCGCTCTAGATGCGACCTTTCGAGCGTT . Plasmid preparation , cell transfection , colony selection and growth of Sf9 cells ( Invitrogen ) was as previously described [51] . Primers for E . coli expression were: pet41 NcoI F7 CGCGCGCCATGGATACTTTGCAGCCAATT; pet41 XhoI R7 GCGCGCCTCGAGTGCGACCTTTCGAGCGTT . Plasmids were prepared using standard techniques and used to transform E . coli cell lines ( BL21 , rosetta , rosetta-gami cells – Novagen ) followed by selection with kanamycin and other appropriate antibiotics according to the manufacturer's instructions . Cells were grown in LB medium at temperatures between 16–37°C in 1 L Schott bottles at 220 rpm . Cultures were induced with 1 mM IPTG upon reaching an OD600 of 0 . 5 and grown overnight before harvesting the cell pellet . Since both recombinant proteins ( derived from E . coli and Sf9 insect cells ) contained C-terminal 6×His tags , the purification procedures included immobilized metal ion affinity chromatography ( IMAC ) . Purification was undertaken using an AKTA basic purification system ( GE ) at 4°C . Henceforth we refer to the E . coli-derived recombinant protein as Ov-GRN-1e and Sf9-derived protein as Ov-GRN-1s . For Ov-GRN-1s , 3 L of culture supernatant was passed across a 5 ml Hitrap HS HP cation exchange column ( GE ) with a gradient of 0–1 M NaCl over 10 column volumes . Fractions enriched for recombinant protein were detected using an anti-V5 affinity tag antibody ( Invitrogen ) . Further purification of these fractions was achieved by a subsequent IMAC step; protein was bound to 1 ml Ni-NTA resin ( Qiagen ) in 10 mM imidazole/sodium phosphate ( pH 8 ) and washed with 10 column volumes of 20 , 40 and 60 mM imidazole , followed by elution in 250 mM imidazole . Fractions containing recombinant protein were subjected to a second round of IMAC as above , followed by concentration to 1 mg/ml and buffer exchange into PBS using 3 kDa microsep spin columns ( Pall ) . For purification of Ov-GRN-1e , 3 g of E . coli cell pellet was resuspended in 30 ml binding buffer ( 50 mM Tris-HCl , 300 mM NaCl , 0 . 1% Triton X-100 ) followed by three disruption cycles through a chilled French press at 16–18000 psi . The sample was centrifuged at 4000 g and the pellet was dissolved in 6 M urea in nickel ( Ni ) -NTA binding buffer with 40 mM imidazole overnight at 4°C with gentle mixing . The supernatant was collected by centrifugation as above and purified by denaturing IMAC , with 6 M urea in all buffers , over a 5 ml His-trap Ni-IDA column ( GE ) . The column was washed with 100 mM imidazole and recombinant protein eluted with 500 mM imidazole/6 M urea . The eluate was concentrated to 20 mg/ml using 3 kDa 15 ml Amicon Ultra centrifuge concentration devices ( Millipore ) and refolded by drop wise addition to a 20-fold greater volume of a range of refolding buffers [52] . The soluble material was buffer-exchanged into PBS using a PD10 column ( GE ) . Ov-GRN-1e and GRN-1s were adjusted to 0 . 4 mg/ml and diluted 1∶1 with Freund's adjuvant and emulsified . Twenty micrograms of protein ( 100 µl of protein∶adjuvant ) was injected subcutaneously into each of four BALB/c female mice every two weeks , using Freund's complete adjuvant for the first immunization and Freund's incomplete adjuvant for the second and third immunizations . Two weeks after the final immunization , mice were euthanized , blood collected by cardiac puncture , and sera recovered from the clotted blood . Control sera were obtained from mice that were either ( 1 ) unimmunized or ( 2 ) immunized with an irrelevant control protein ( recombinant Na-GST-1 glutathione-S-transferase from Necator americanus ) [53] . Sera were pooled and diluted 1∶20 with PBS for affinity purification of IgG on Hitrap protein G ( GE ) at 4°C using an AKTA basic FPLC . Eluted fractions were concentrated with 30 kDa nanosep spin concentrators ( Pall ) , buffer exchanged into PBS and stored at −80°C . Denaturing and native polyacrylamide gel electrophoresis ( PAGE ) was performed using 15% gels . Proteins were electro-transferred to Biotrace nitrocellulose membranes ( Pall ) , which were then sliced into 3 mm wide strips . Membranes were blocked in 5% skimmed milk powder ( SMP ) /PBS with 0 . 05% Tween 20 ( PBST ) for 60 min at room temperature ( RT ) with gentle shaking and probed overnight with 8 µg/ml mouse IgG diluted in 2% SMP/PBST at 4°C . Subsequently , membranes were washed ( 3×10 min each ) in PBST at RT followed by probing with horse radish peroxidase ( HRP ) -conjugated goat anti-mouse IgG ( Zymed Laboratories ) diluted 1∶300 in 2% SMP/PBST at RT with gentle rocking for 60 min . After washing to remove the secondary antibody , colorimetric signals were developed in the presence of hydrogen peroxide and diaminobenzidine ( DAB ) ( Pierce ) . O . viverrini adult worms or liver tissue from hamsters infected with O . viverrini ( weeks 12–16 weeks ) were fixed and cut by microtome into sections of 4 µm [41] . The sections were deparaffinised in xylene , hydrated in a series of ethanol and distilled water , respectively . Endogenous peroxidise was eliminated by incubating sectioned tissues in 5% H2O2 in methanol for 30 min , after which the sections were rehydrated in water and PBS . Non-specific staining was blocked by incubation in 5% normal mouse serum in PBS for 30 min . The sections were probed with pooled mouse purified IgG diluted 1∶100–1∶500 ( v/v ) in PBS and incubated overnight at 4°C . After rinsing 3×5 min with PBS the sections were incubated with horseradish peroxidase-conjugated goat anti-mouse IgG ( Zymed Laboratories ) for 1 h . Sections were rinsed with PBS 2×10 min , after which the slides were developed with DAB . The sections were counterstained with Mayer's haematoxylin , dehydrated , cleared in xylene and mounted in Permount® ( Cen-Med ) . The sections were examined by light microscopy and images captured with a digital camera . ES products , recombinant proteins and IgG antibodies that were included in cell culture were filtered under sterile conditions with 0 . 22 µM syringe filters ( Pall ) . Dilutions were carried out in sterile PBS in Twintec 96 well plates ( Eppendorf ) . Samples were prepared so that 20 µl of ES protein or antibody in sterile PBS was added to 100 µl of cell culture media . Protein concentrations described hereafter refer to the final concentration in cell culture after dilution in media . All assays were conducted either in triplicate or duplicate , as specified in figure legends . Controls were relevant for the sample tested: expression matched recombinant proteins were included to assess effects of recombinant granulin – a hookworm protein , Na-ASP-2 , expressed in insect cells [51] served as the control protein for Ov-GRN-1s; Sm-TSP-2 EC2 expressed in E . coli [54] served as the control protein for Ov-GRN-1e . Antibodies against recombinant proteins for use in cell culture were purified as above . The Erk1/2 ( MAPK ) kinase inhibitor , U0126 ( Cell Signalling Technology ) was used at a final concentration of 10 µM in some cell cultures to assess its ability to block signalling induced by ES products or recombinant Ov-GRN-1 . NIH 3T3 mouse embryonic fibroblast cells ( ATCC ) were maintained as specified by ATCC protocols . Briefly , cells were maintained with regular splitting using 0 . 25% trypsin every 2–5 days in DMEM ( Sigma ) with 10% bovine calf serum ( BCS ) and 1×antibiotic/antimycotic ( Invitrogen ) at 37°C under 5% CO2 . To assess the effects of ES on cell growth , multiple culture conditions were investigated in 96 well plates including seed densities ( 1 , 000–10 , 000 cells/well ) , cell attachment times before sample addition ( 3 h , 6 h , 16 h ) , BCS concentration ( 0 , 2 , 5 and 10% ) , ES concentration ( 10–80 µg/ml ) and duration of culture after sample addition ( 1–3 days ) . The ability of live O . viverrini flukes to stimulate cell proliferation was assessed using a non-contact co-culture technique as described [4] . KKU-100 is a cell line derived from a human CCA and was maintained as described [55] . Cell proliferation was determined using two different approaches . First , cell numbers were assayed using the WST-1 cell proliferation reagent ( Roche ) as per product manual . Briefly the procedure involves incubating the cells with 10 ul of WST-1 for up to four hours at 37°C . During this period viable cells , which contain mitochondrial dehydrogenases , convert WST-1 to a water soluble formazan dye which has a peak absorbance at 450 nm which is measured on a Benchmark Plus plate reader ( BioRad ) and data were converted into cell numbers per well via comparison to standard curves . Cell proliferation was also assessed by counting cell numbers in real time using a xCELLigence system and E plates ( Roche ) which monitors cellular events in real time by measuring electrical impedance across interdigitated gold micro-electrodes integrated on the bottom of tissue culture plates . The impedance measurement provides quantitative information about the biological status of the cells , including cell number , viability , and morphology [27] . Cell culture conditions tested were the same as those tested with the WST-1 dye ( 2% BCS , 20 µg/ml ES , 20 µg/ml IgG ) .
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The oriental liver fluke is endemic through South-East Asia and is the major cause of cause of liver cancer in north-eastern Thailand . The molecules that are secreted by the parasite cause cells to multiply quicker than they normally would , and excessive cell growth is a key stage in the initiation of many cancers . We identified a secreted protein from the fluke , termed granulin , which has a similar structure to a human growth factor associated with many aggressive cancers . Granulin is secreted by the parasite into the bile ducts where it causes host cells to proliferate . The proliferative activity of fluke secreted proteins was blocked by antibodies against granulin , indicating that it is the major cell growth-inducing molecule released by the parasite . Identifying the function of granulin will enable us to understand how and why this debilitating yet neglected pathogen causes cancer in so many people in South-East Asia . This and future work will contribute towards the development of new strategies to reduce both parasite prevalence and the incidence of the most fatal of liver cancers in Thailand .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/helminth",
"infections",
"microbiology/parasitology"
] |
2009
|
A Granulin-Like Growth Factor Secreted by the Carcinogenic Liver Fluke, Opisthorchis viverrini, Promotes Proliferation of Host Cells
|
Population-wide oscillations are ubiquitously observed in mesoscopic signals of cortical activity . In these network states a global oscillatory cycle modulates the propensity of neurons to fire . Synchronous activation of neurons has been hypothesized to be a separate channel of signal processing information in the brain . A salient question is therefore if and how oscillations interact with spike synchrony and in how far these channels can be considered separate . Experiments indeed showed that correlated spiking co-modulates with the static firing rate and is also tightly locked to the phase of beta-oscillations . While the dependence of correlations on the mean rate is well understood in feed-forward networks , it remains unclear why and by which mechanisms correlations tightly lock to an oscillatory cycle . We here demonstrate that such correlated activation of pairs of neurons is qualitatively explained by periodically-driven random networks . We identify the mechanisms by which covariances depend on a driving periodic stimulus . Mean-field theory combined with linear response theory yields closed-form expressions for the cyclostationary mean activities and pairwise zero-time-lag covariances of binary recurrent random networks . Two distinct mechanisms cause time-dependent covariances: the modulation of the susceptibility of single neurons ( via the external input and network feedback ) and the time-varying variances of single unit activities . For some parameters , the effectively inhibitory recurrent feedback leads to resonant covariances even if mean activities show non-resonant behavior . Our analytical results open the question of time-modulated synchronous activity to a quantitative analysis .
To date it is unclear which channels the brain uses to represent and process information . A rate-based view is argued for by the apparent stochasticity of firing [1] and by the high sensitivity of the network dynamics to single spikes [2] . In an extreme view , correlated firing is a mere epiphenomenon of neurons being connected . Indeed , a large body of literature has elucidated how correlations relate to the connectivity structure [3–14] . But the matter is further complicated by the observation that firing rates and correlations tend to be co-modulated , as demonstrated experimentally and explained theoretically [4 , 5] . If the brain employs correlated firing as a means to process or represent information , this requires in particular that the appearance of correlated events is modulated in a time-dependent manner . Indeed , such modulations have been experimentally observed in relation to the expectation of the animal to receive task-relevant information [15 , 16] or in relation to attention [17] . Oscillations are an extreme case of a time-dependent modulation of the firing rate of cells . They are ubiquitously observed in diverse brain areas and typically involve the concerted activation of populations of neurons [18] . They can therefore conveniently be studied in the local field potential ( LFP ) that represents a complementary window to the spiking activity of individual neurons or small groups thereof: It is composed of the superposition of the activity of hundreds of thousands to millions of neurons [19 , 20] and forward modeling studies have confirmed [21] that it is primarily driven by the synaptic inputs to the local network [22–24] . As the LFP is a quantity that can be measured relatively easily , this mesoscopic signal is experimentally well documented . Its interpretation is , however , still debated . For example , changes in the amplitude of one of the components of the spectrum of the LFP have been attributed to changes in behavior ( cf . e . g . [25] ) . A particular entanglement between rates and correlations is the correlated firing of spikes in pairs of neurons in relation to the phase of an ongoing oscillation . With the above interpretation of the LFP primarily reflecting the input to the cells , it is not surprising that the mean firing rate of neurons may modulate in relation to this cycle . The recurrent network model indeed confirms this expectation , as shown in Fig 1A . It is , however , unclear if and by which mechanisms the covariance of firing follows the oscillatory cycle . The simulation shown in Fig 1B indeed exhibits a modulation of the covariance between the activities of pairs of cells . Such modulations have also been observed in experiments: Denker et al . [26] have shown that the synchronous activation of pairs of neurons within milliseconds preferentially appears at a certain phase of the oscillatory component of the LFP in the beta-range—in their words the spike-synchrony is “phase-locked” to the beta-range of the LFP . They explain their data by a conceptual model , in which an increase in the local input , assumed to dominate the LFP , leads to the activation of cell assemblies . The current work investigates an alternative hypothesis: We ask if a periodically-driven random network is sufficient to explain the time-dependent modulation of covariances between the activities of pairs of cells or whether additional structural features of the network are required to explain this experimental observation . To investigate the mechanisms causing time-dependent covariances in an analytically tractable case , we here present the simplest model that we could come up with that captures the most important features: A local network receiving periodically changing external input . The randomly connected neurons receive sinusoidally modulated input , interpreted as originating from other brain areas and mimicking the major source of the experimentally observed LFP . While it is obvious that the mean activity in a network follows an imposed periodic stimulation , it is less so for covariances . In the following we will address the question why they are modulated in time as well . Extending the analysis of mean activities and covariances in the stationary state [13 , 27 , 28] , we here expose the fundamental mechanisms that shape covariances in periodically driven networks . Our network model includes five fundamental properties of neuronal dynamics: First , we assume that the state of low and irregular activity in the network [1] is a consequence of its operation in the balanced state [29 , 30] , where negative feedback dynamically stabilizes the activity . Second , we assume that each neuron receives a large number of synaptic inputs [31] , each of which only has a minor effect on the activation of the receiving cell , so that total synaptic input currents are close to Gaussian . Third , we assume the neurons are activated in a threshold-like manner depending on their input . Fourth , we assume a characteristic time scale τ that measures the duration of the influence a presynaptic neuron has on its postsynaptic targets . Fifth , the output of the neuron is dichotomous or binary , spike or no spike , rather than continuous . As a consequence , the variance of the single unit activity is a direct function of its mean . We here show how each of the five above-mentioned fundamental properties of neuronal networks shape and give rise to the mechanisms that cause time-dependent covariances . The presented analytical expressions for the linear response of covariances expose two different paths by which a time-dependence arises: By the modulation of single-unit variances and by the modulation of the linear gain resulting from the non-linearity of the neurons . The interplay of negative recurrent feedback and direct external drive can cause resonant behavior of covariances even if mean activities are non-resonant . Qualitatively , these results explain the modulation of synchrony in relation to oscillatory cycles that are observed in experiments , but a tight locking of synchronous events to a particular phase of the cycle is beyond the mechanisms found in the here-studied models .
To address our central question , whether a periodically-driven random network explains the experimental observations of time-modulated pairwise covariances , we consider a minimal model here . It consists of one inhibitory ( I ) population and , in the latter part of the paper , additionally one excitatory population ( E ) of binary model neurons [6 , 27 , 29 , 32] . Neurons within these populations are recurrently and randomly connected . All neurons are driven by a global sinusoidal input mimicking the incoming oscillatory activity that is visible in the LFP , illustrated in Fig 2 . The local network may in addition receive input from an external excitatory population ( X ) , representing the surrounding of the local network . The fluctuations imprinted by the external population , providing shared inputs to pairs of cells , in addition drive the pairwise covariances within the network [13 , c . f . especially the discussion] . Therefore we need the external population X to arrive at a realistic setting that includes all sources of covariances . In the following , we extend the analysis of cumulants in networks of binary neurons presented in [6 , 13 , 27 , 28 , 33] to the time-dependent setting . This formal analysis allows us to obtain analytical approximations for the experimentally observable quantities , such as pairwise covariances , that expose the mechanisms shaping correlated network activity . Binary model neurons at each point in time are either inactive ni = 0 or active ni = 1 . The time evolution of the network follows the Glauber dynamics [34]; the neurons are updated asynchronously . At every infinitesimal time step dt , any neuron is chosen with probability d t τ . After an update , neuron i is in the state 1 with the probability Fi ( n ) and in the 0-state with probability 1 − Fi ( n ) , where the activation function F is chosen to be F i ( n ) = H h i - θ i h i = ∑ k = 1 N J i k n k + h extsinω t + ξ i H ( x ) = 1 if x ≥ 0 0 if x < 0 . ( 1 ) We here introduced the connectivity matrix J with the synaptic weights J i j ∈ ℝ describing the influence of neuron j on neuron i . The weight Jij is negative for an inhibitory neuron j and positive for an excitatory neuron . Due to the synaptic coupling the outcome of the update of neuron i potentially depends on the state n = ( n1 , … , nN ) of all other neurons in the network . Compared to the equations in [13 , page 4] , we added an external sinusoidal input to the neurons representing the influence of other cortical or subcortical areas and Gaussian uncorrelated noise with vanishing mean 〈ξi〉 = 0 and covariance 〈 ξ i ξ j 〉 = δ i j σ noise 2 . The threshold θi depends on the neuron type and will be chosen according to the desired mean activity . We employ the neural simulation package NEST [35 , 36] for simulations . Analytical results are obtained by mean-field theory [6 , 13 , 27 , 28 , 37 , 38] and are described for completeness and consistency of notation in the section “Methods” . In the main text we only mention the main steps and assumptions entering the approximations . The basic idea is to describe the time evolution of the Markov system in terms of its probability distribution p ( n , t ) . Using the master Eq 14 we obtain ordinary differential equations ( ODEs ) for the moments of p ( n , t ) . In particular we are interested in the population averaged mean activities mα , variances aα , and covariances cαβ m α t ≔ 1 N α ∑ i ∈ α n i t ( 2 ) a α t ≔ 1 N α ∑ i ∈ α n i t - n i t 2 ( 3 ) c α β t ≔ 1 N α N β ∑ i ∈ α , j ∈ β , i ≠ j n i t n j t - n i t n j t , ( 4 ) which are defined as expectation values 〈〉 over realizations of the network activity , where the stochastic update of the neurons and the external noisy input presents the source of randomness in the network . The dynamics couples moments of arbitrarily high order [33] . To close this set of equations , we neglect cumulants of order higher than two , which also approximates the input by a Gaussian stochastic variable with cumulants that vanish for orders higher than two [39] . This simplification can be justified by noticing that the number of neurons contributing to the input is large and their activity is weakly correlated , which makes the central limit theorem applicable . In a homogeneous random network , on expectation there are Kαβ = pαβ Nβ synapses from population β to a neuron in population α . Here pαβ is the connection probability; the probability that there is a synapse from any neuron in population β to a particular neuron in population α and Nα is the size of the population . Mean Eq ( 2 ) and covariance Eq ( 4 ) then follow the coupled set of ordinary differential equations ( ODEs , see section II A in S1 Text for derivation ) τ d d t m α t = - m α t + φ ( μ α ( m t , h extsinω t ) , σ α ( m t , c t ) ) ( 5 ) τ d d t c α β t = { - c α β t + ∑ γ [ S μ α m t , h extsinω t , σ α m t , c t × K α γ J α γ c γ β t + δ γ β a β t N β ] } + α ↔ β , ( 6 ) where α ↔ β indicates the transposed term . The Gaussian truncation employed here is parameterized by the mean μα and the variance σ α 2 of the summed input to a neuron in population α . These , in turn , are functions of the mean activity and the covariance , given by Eqs ( 18 ) and ( 19 ) , respectively . Here φ is the expectation value of the activation function , which is smooth , even though the activation function itself is a step function , therefore not even continuous . The function φ fulfills limm → 0 φ = 0 and limm → 1 φ = 1 and monotonically increases . Its derivative S with respect to μ has a single maximum and is largest for the mean input μ within a region with size σ around the threshold θ . S measures the strength of the response to a slow input and is therefore termed susceptibility . The definitions are given in “Methods” in Eqs ( 17 ) and ( 20 ) . The stationary solution ( indicated by a bar ) of the ODEs Eqs ( 5 ) and ( 6 ) can be found by solving the equations m ¯ = φ m ¯ ( 7 ) 2 c ¯ = S K J c ¯ + a ¯ N + transposed ( 8 ) numerically and self-consistently , as it was done in [13 , 27 , 33] . The full time-dependent solution of Eqs ( 5 ) and ( 6 ) can , of course , be determined numerically without any further assumptions . Besides the comparison with simulation results , this will give us a check for the subsequently applied linear perturbation theory . The resulting analytical results allow the identification of the major mechanisms shaping the time-dependence of the first two cumulants . To this end , we linearize the ODEs Eqs ( 5 ) and ( 6 ) around their stationary solutions . We only keep the linear term of order hext of the deviation , justifying a Fourier ansatz for the solutions . For the mean activities this results in m α ( t ) = m ¯ α + δ m α ( t ) = m ¯ α + M α 1 e i ω t with M α 1 = ∑ β U α β M β 1 = ∑ β U α β h ext U - 1 S μ ¯ , σ ¯ β - i τ ω + 1 - λ β τ ω 2 + 1 - λ β 2 . ( 9 ) The time-dependence of σ was neglected here , which can be justified for large networks ( “Methods” , Eqs ( 22 ) and ( 30 ) ) . The matrix U represents the basis change that transforms W ¯ α β ≔ S ( μ ¯ α , σ ¯ α ) K α β J α β into a diagonal matrix with λα the corresponding eigenvalues . We see that , independent of the number of populations or the detailed form of the connectivity matrix , the amplitude of the time-dependent part of the mean activities has the shape of a low-pass-filtered signal to first order in hext . Therefore the phase of δm lags behind the external drive and its amplitude decreases asymptotically like 1 ω , as can be seen in Fig 3A and 3B . If we also separate the covariances into their stationary part and a small deviation that is linear in the external drive , c α β ( t ) = c ¯ α β + δ c α β ( t ) , expand S ( μα ( t ) , σα ( t ) ) and a ( t ) around their stationary values , keeping only the terms of order hext and neglect contributions from the time-dependent variation of the variance of the input σ2 ( see “Methods” , especially Eq ( 30 ) for a discussion of this point ) , we get the ODE τ d d t δ c t + 2 δ c t - W ¯ δ c t - W ¯ δ c t T = { W ¯ diag 1 - 2 m ¯ N diag δ m t ︸ modulated-autocorrelations-drive + diag K ⊛ J δ m t ︸ recurrent drive + h extsinω t ︸ direct drive diag ∂ S ∂ μ t K ⊛ J c ¯ total } + . . . T , ( 10 ) where we introduced the point-wise ( Hadamard ) product ⊛ of two matrices A and B [see 40 , for a consistent notation of matrix operations] as ( A ⊛ B ) ij ≔ AijBij , defined the matrix with the entries diag ( x ) ij := δij xi for the vector x = ( x1 , ‥ , xn ) and set c ¯ t o t a l ≔ c ¯ + d i a g ( a ¯ N ) to bring our main equation into a compact form . We can now answer the question posed in the beginning: Why does a global periodic drive influence the cross covariances in the network at all and does not just make the mean activities oscillate ? First , the variances are modulated with time , simply because they are determined via Eq ( 3 ) by the modulated mean activities . A neuron i with modulated autocorrelation ai ( t ) projects via Jji to another neuron j and therefore shapes the pairwise correlation cji ( t ) in a time-dependent way . We call this effect the “modulated-autocovariances-drive” , indicated by the curly brace in the second line of Eq ( 10 ) . Its form in index notation is [ W ¯ d i a g ( ( 1 − 2 m ¯ ) / N ) d i a g ( δ m ( t ) ) ] α β = W ¯ α β ( 1 − 2 m ¯ β ) / N β δ m β ( t ) . This is the low-pass-filtered input . The other contributions are a bit more subtle and less obvious , as they are absent in networks with a linear activation function . The derivative of the expectation value of the activation function , the susceptibility , contributes linearly to the ODE of the covariances . As the threshold-like activation function gives rise to a nonlinear dependence of φ on the mean input μ , the susceptibility S = φ′ is not constant , but depends on the instantaneous mean input . The latter changes as a function of time by the direct external drive and by the recurrent feedback of the oscillating mean activity , indicated by the terms denoted by the curly braces in the third line of Eq ( 10 ) . Together , we call these two term the “susceptibility terms” . Both terms are of the same form [ diag δ μ ( t ) diag ∂ S ∂ μ t K ⊛ J c ¯ total ] α β= δ μ α ( t ) ∂ S α ∂ μ α ∑ γ K α γ J α γ ( c ¯ γ β + δ γ β a ¯ β N β ) , ( 11 ) but with different δμα . This form shows how the time-dependent modulation of the mean input δμα , by the second derivative of the gain function ∂ S α ∂ μ α = φ ″ , influences the transmission of covariances . The sum following ∂ S α ∂ μ α is identical to the one in the static case Eq ( 8 ) . For the “recurrent drive” , the time-dependent input is given by δμα ( t ) = ∑β Kαβ Jαβ δmβ ( t ) , which is a superposition of the time-dependent activities that project to population α and is therefore low-pass-filtered , too . The term due to “direct drive” is δμα ( t ) = hext sin ( ωt ) . We solve Eq ( 10 ) by transforming into the eigensystem of W ¯ and inserting a Fourier ansatz , δ c α β ( t ) = C α β 1 e i ω t . The solution consists of a low-pass filtered part coming from the direct drive and two parts that are low-pass filtered twice , coming from the recurrent drive and the modulated-autocovariances-drive . For a detailed derivation , consult the section “Covariances: Stationary part and response to a perturbation in linear order” . We have calculated higher Fourier modes of the simulated network activity and of the numerical solution of the mean-field equations to check if they are small enough to be neglected , so that the response is dominated by the linear part . Of course , it would be possible to derive analytical expressions for those as well . However , we will see that the linear order and the corresponding first harmonic qualitatively and for remarkably large perturbations even quantitatively gives the right predictions . The limits of this approximation are analyzed in Fig D in S1 Text . We will therefore constrain our analysis to controlling the higher harmonics through the numerical solution . In the following we will study three different models of balanced neuronal networks to expose the different mechanisms in their respective simplest setting .
We have left out so far several steps in the derivation of the results that were not necessary for the presentation of the main ideas . In this section , we will therefore give a self-contained derivation of our results also necessitating paraphrases of some results known from earlier works . The starting point is the master equation for the probability density of the possible network states emerging from the Glauber dynamics [34] described in “Binary network model and its mean field equations” ( see for the following also [13 , 37] ) ∂ p ∂ t ( n , t ) = 1 τ ︸ update rate ∑ i = 1 N ( 2 n i - 1 ) ︸ ∈ { - 1 , 1 } , direction of flux ϕ i ( n ∖ n i , t ) ︸ net flux due to neuron i ∀ n ∈ { 0 , 1 } N , ( 14 ) where ϕ i ( n ∖ n i , t ) = p ( n i - , t ) F i ( n i - ) ︸ neuron i transition up - p ( n i + , t ) ( 1 - F i ( n i + ) ) ︸ neuron i transition down = - p ( n i + ) + p ( n i - , t ) F i ( n i - ) + p ( n i + , t ) F i ( n i + ) . The activation function Fi ( n ) is given by Eq ( 1 ) . Using the master equation ( for details cf . section II A in S1 Text ) , one can derive a differential equation for the mean activity of the neuron i , 〈ni〉 ( t ) = ∑n p ( n , t ) ni and the raw covariance of the neurons i and j , 〈ni ( t ) nj ( t ) 〉 = ∑n p ( n , t ) ninj [6 , 13 , 27 , 34 , 37] . This yields τ d d t n k t = - n k t + F k t d d t n k t n l t = - n k t n l t + n l t F k t + k ↔ l . ( 15 ) As mentioned in “Binary network model and its mean field equations” , we assume that the input hi coming from the local and the external population is normally distributed , say with mean μi and standard deviation σi given by μ i ( t ) ≔ h i = J n i + h ext sin ( ω t ) σ i 2 ( t ) ≔ h i 2 - h i 2 = ∑ k , k ′ = 1 N J i , k J i , k ′ n k n k ′ - n k n k ′ + σ i noise 2 = J T c J i i + J ⊛ J n ⊛ 1 - n + σ i noise 2 , ( 16 ) where the average 〈〉 is taken over realizations of the stochastic dynamics and we used the element-wise ( Hadamard ) product ( see main text ) . The additional noise introduced in Eq ( 1 ) effectively leads to a smoothing of the neurons’ activation threshold and broadens the width of the input distribution . It can be interpreted as additional variability coming from other brain areas . Furthermore , it is computationally convenient , because the theory assumes the input to be a ( continuous ) Gaussian distribution , while in the simulation , the input ∑ l = k N J i k n k , being a sum of discrete binary variables , can only assume discrete values . The smoothing by the additive noise therefore improves the agreement of the continuous theory with the discrete simulation . Already weak external noise compared to the intrinsic noise is sufficient to obtain a quite smooth probability distribution of the input ( Fig 8 ) . The description in terms of a coupled set of moment equations instead of the ODE for the full probability distribution here serves to reduce the dimensionality: It is sufficient to describe the time evolution of the moments on the population level , rather than on the level of individual units . To this end we need to assume that the synaptic weights Jij only depend on the population α , β ∈ {exc . , inh . , ext . } that i and j belong to , respectively , and thus ( re ) name them Jαβ ( homogeneity ) . Furthermore , we assume that not all neurons are connected to each other , but that Kαβ is the number of incoming connections a neuron in population α receives from a neuron in population β ( fixed in-degree ) . The incoming connections to each neuron are chosen randomly , uniformly distributed over all possible sending neurons . This leads to expressions for the population averaged input hα , mean activity mα and covariance cαβ , formally nearly identical to those on the single cell level and analogous to those in [13 , sec . Mean-field solution] .
The present work offers an extension of the well-known binary neuronal network model beyond the stationary case [6 , 13 , 27 , 28 , 33] . We here describe the influence of a sinusoidally modulated input on the mean activities and the covariances to study the statistics of recurrently generated network activity in an oscillatory regime , ubiquitously observed in cortical activity [18] . Comparing with the results of the simulation of the binary network with NEST [35 , 36] and the numerical solution of the full mean-field ODE , we are able to show that linear perturbation theory is sufficient to explain the most important effects occurring due to sinusoidal drive . This enables us to understand the mechanisms by the help of analytical expressions and furthermore we can predict the network response to any time-dependent perturbation with existing Fourier representation by decomposing the perturbing input into its Fourier components . We find that the amplitude of the modulation of the mean activity is of the order h ext / ( ( 1 − λ α ) 2 + ( τ ω ) 2 ) 1 2 , where λα , α ∈ {E , I} are the eigenvalues of the effective connectivity matrix W , i . e . the input is filtered by a first order low-pass filter and the amplitude of the modulation decays like ∝ ω−1 for large frequencies . This finding is in line with earlier work on the network susceptibility [27 , esp . section V] . The qualitatively new result here is the identification of two distinct mechanisms by which the covariances δc are modulated in time . First , covariances are driven by the direct modulation of the susceptibility S due to the time-dependent external input and by the recurrent input from the local network . Second , time-modulated variances , analogous to their role in the stationary setting [13] , drive the pairwise covariances . Our setup is the minimal network model , in which these effects can be observed—minimal in the sense that we would lose these properties if we further simplified the model: The presence of a nonlinearity in the neuronal dynamics , here assumed to be a threshold-like activation function , is required for the modulation of covariances by the time-dependent change of the effective gain . In a linear rate model [10 , 46] this effect would be absent , because mean activities and covariances then become independent . The second mechanism relies on the binary nature of neuronal signal transmission: the variance a ( t ) of the binary neuronal signal is , at each point in time , completely determined by its mean m ( t ) . This very dependence provides the second mechanism by which the temporally modulated mean activity causes time-dependent covariances , because all fluctuations and therefore all covariances are driven by the variance a ( t ) . Rate models have successfully been used to explain the smallness of pairwise covariances [6] by negative feedback [10] . A crucial difference is that their state is continuous , rather than binary . As a consequence , the above-mentioned fluctuations present due to the discrete nature of the neuronal signal transmission need to be added artificially: The pairwise statistics of spiking or binary networks are equivalent to the statistics of rate models with additive white noise [46] . To obtain qualitative or even quantitative agreement of time-dependent covariances between spiking or binary networks and rate models , the variance of this additive noise needs to be chosen such that its variance is a function of the mean activity and its time derivative . The direct modulation of the susceptibility S due to the time-dependent external input leads to a contribution to the covariances with first order low-pass filter characteristics that dominates the modulated covariances at large frequencies . For small—and probably biologically realistic—frequencies ( typically the LFP shows oscillations in the β-range around 20 Hz ) , however , the modulation of the susceptibility by the local input from the network leads to an equally important additional modulation of the susceptibility . The intrinsic fluctuations of the network activity are moreover driven by the time-dependent modulation of the variance , which is a function of the mean activity as well . Because the mean activity follows the external drive in a low-pass filtered manner , the latter two contributions hence exhibit a second order low-pass-filter characteristics . These contributions are therefore important at the small frequencies we are interested in here . The two terms modulating the susceptibility , by the direct input and by the feedback of the mean activity through the network , have opposite signs in balanced networks . In addition they have different frequency dependencies . In networks in which the linearized connectivity has only real eigenvalues , these two properties together lead to their summed absolute value having a maximum . Whether or not the total modulation of the covariance shows resonant behavior , however , depends also on the third term that stems from the modulated variances . We find that in purely inhibitory networks , the resonance peak is typically overshadowed by the latter term . This is because inhibitory feedback leads to negative average covariances [13] , which we show here reduce the driving force for the two resonant contributions . In balanced E-I networks , the driving force is not reduced , so the resonant contribution can become dominant . For the biologically motivated parameters used in the last setting studied here , the effective coupling matrix W has complex eigenvalues which cause resonant mean activities . If the inhomogeneity was independent of the driving frequency , δc would have resonant modes with frequency fres and 2fres . Due to the mixing of the different modes and by the frequency dependence of the inhomogeneity driving the modulation of covariances , these modes determine only the ballpark for the location of the resonance in the covariance . Especially the resonances are not sharp enough so that each of them is visible in any combination of the modes . Different behavior is expected near the critical point where ℜ ( λ ) ≲ 1 . For predictions of experimental results , however , a more careful choice of reasonable biological parameters would be necessary . In particular , the external drive should be gauged such that the modulations of the mean activities are in the experimentally observed range . Still , our setup shows that the theory presented here works in the biologically plausible parameter range . The goal of extracting fundamental mechanisms of time-dependent covariances guides the here presented choice of the level of detail of our model . Earlier works [6 , 28 , 29] showed that our setup without sinusoidal drive is sufficient to qualitatively reproduce and explain phenomena observed in vivo , like high variability of neuronal activity and small covariances . The latter point can be explained in binary networks by the suppression of fluctuations by inhibitory feedback , which is a general mechanism also applicable to other neuron models [10] and even finds application outside neuroscience , for example in electrical engineering [47] . The high variability observed in binary networks can be explained by the network being in the balanced state , that robustly emerges in the presence of negative feedback [29 , 30] . In this state , the mean excitatory and inhibitory synaptic inputs cancel so far that the summed input to a neuron fluctuates around its threshold . This explanation holds also for other types of model networks and also for biological neural networks [48] . We have seen here that the operation in the balanced state , at low frequencies , gives rise to a partial cancellation of the modulation of covariances . Our assumption of a network of homogeneously connected binary neurons implements the general feature of neuronal networks that every neuron receives input from a macroscopic number of other neurons , letting the impact of a single synaptic afferent on the activation of a cell be small and the summed input be distributed close to Gaussian: For uncorrelated incoming activity , the ratio between the fluctuations caused by a single input and the fluctuations of the total input is N − 1 2 , independent of how synapses scale with N . However , the input to a neuron is actually not independent , but weakly correlated , with covariances decaying at least as fast as N−1 [6 , 29] . Therefore this additional contribution to the fluctuations also decays like N − 1 2 . The Gaussian approximation of the synaptic input relies crucially on these properties . Dahmen et al . [39] investigated third order cumulants , the next order of non-Gaussian corrections to this approximation . They found that the approximation has a small error even down to small networks of about 500 neurons and 50 synaptic inputs per neuron . These estimates hold as long as all synaptic weights are of equal size . For distributed synaptic amplitudes , in particular those following a wide or heavy-tailed distributions ( e . g . [49 , 50] , reviewed in [51] ) , we expect the simple mean-field approximation applied here to require corrections due to the strong effect of single synapses . The generic feature of neuronal dynamics , the threshold-like nonlinearity that determines the activation of a neuron , is shared by the binary , the leaky integrate-and-fire and , approximately , also the Hodgkin-Huxley model neuron . An important approximation entering our theory is the linearity of the dynamic response with respect to the perturbation . We estimate the validity of our theory by comparison to direct simulations . To estimate the breakdown of this approximation we compare the linear response to the first non-linear correction . We observe that the second order harmonics in the considered range of parameters remains as small as about 10 percent of the first harmonics . The quadratic contribution to the transfer properties of the neurons stems from the curvature of the effective gain function φ ( Eq ( 17 ) ) . The linear portion of this gain function , in turn , is controlled by the amplitude σ of the synaptic noise . One therefore expects a breakdown of the linear approximation as soon as the temporal modulation of the mean input is of the order of this amplitude . Fig D in S1 Text shows that with the parameters hext = 1 and σexc , inh ≈ 10 , used in the plots Figs 5 and 6 and Fig . B and Fig . C in S1 Text , the linear approximation is good , whereas in Fig 7 , we used hext = 6 , for which the linear perturbation theory already begins to break down . The latter figure is mainly supposed to give an intuitive impression . A generic property that is shared by nearly all neuron models is the characteristic duration τ during which the activity of a sending cell affects the downstream neuron . For the binary neuron model , this time scale is identical to the mean interval τ between updates , because , once active , a neuron will stay active until the next update . It most certainly deactivates at that point , because we here consider low activity states prevalent in cortex [1] . In the leaky integrate-and-fire model the exponentially decaying membrane voltage with time constant τ is qualitatively similar: it sustains the effect that an input has on the output for this time scale . As a consequence , neurons transmit their input in a low-pass filtered manner to their output . This feature persists for more realistic spiking models , as shown for the leaky integrate-and-fire model [52 , 53] , the exponential integrate-and-fire model [52 , 53] , and the quadratic integrate-and-fire model [54] . We therefore expect that the qualitative properties reported here will carry over to these models . A possible application of the framework developed in this paper is a quantitative comparison of the neuronal activity in the model network to the analysis of data measured in cortex [26] . Detecting the occurrence of so called Unitary Events ( UE , [55–57] , see also Sec . I in S1 Text ) , the authors observed that the simultaneous activation of neurons above the level expected for independence is locked to certain phases of the LFP . They hypothesized that the reason for this observation is the activation of cell assemblies . The results presented here show that the correlated activation of pairs of neurons is modulated by a sinusoidal drive even in a completely unstructured random network . In consequence , the locking of pairwise events to the cycle of the LFP is more pronounced for correlated events than for single spikes . Future work needs to quantitatively compare experimental data to the results from the model presented here . The closed form expressions for the modulations of the mean activities and covariances enable such an approach and the effective study of the dependence on the model parameters . A quantitative comparison needs to convert mean activities and pairwise covariances for binary neurons into the probability to measure a unitary event , interpreting the binary neuron states as binned spike trains . Preliminary results indicate that already the homogeneous network presented in this work can show some features described in [26] . In Sec . I in S1 Text , we apply the Unitary Event analysis to our setting . The presented methods will be helpful to analyze the modulation of synchrony in the presence of cell assemblies [58] in the model . This can be done by enhancing the connection probability among groups of excitatory neurons , similar as in [59] and will yield a more realistic model , which captures also nonlinear effects in the perturbation . Technically this extension amounts to the introduction of additional populations and the change of the connectivity matrix to reflect that these populations represent cell assemblies . The relation of spiking activity to mesoscopic measures , such as the LFP , is still an open question . These population measures of neuronal activity naturally depend on the statistics of the microscopic activity they are composed of . Pairwise covariances , the focus of the current work , in particular tend to dominate the variance of any mesoscopic signal of summed activity: The contribution of covariances grows quadratically in the number of components , the contribution of variances only linearly [60 , Box 2][10 , eq . ( 1 ) ][21 , eq . ( 1 ) , ( 2 ) ] . Under the assumption that the LFP mainly reflects the input to a local recurrent network [21 , 24] , we have shown here that these two signals—spikes and LFPs—are intimately related; not only does the afferent oscillatory drive trivially modulate the propensity to produce spikes , their firing rate , but also the joint statistics of pairs of neurons by the three distinct pathways exposed in the present analysis . Forward modeling studies have shown that the spatial reach of the LFP critically depends on covariances , with elevated covariances leading to larger reach [21] . In this light our work shows that a local piece of neuronal tissue driven by a source of coherent oscillations will more effectively contribute to the local field potential itself: not only the spiking rate is modulated accordingly , but also the covariances are increased and decreased in a periodic manner , further amplifying the modulation of the generated local field potential and temporally modulating the spatial reach of the signal . Functional consequences of the findings presented here deduce from the hypothesis that communication channels in cortex may effectively be multiplexed by the selective excitation of different areas with coherent oscillations [61 , 62] . The presented analysis exposes that oscillatory drive to a local piece of cortex alone already effectively enhances coherent firing beyond the level expected based on the assumption of independence . If synchronous activity is employed as a dimension to represent information , it is hence tightly entangled with time-dependent changes of the mean activity . A similar conclusion was drawn from the observation that covariance transmission in feed-forward networks is monotonously increasing with firing rate [4 , 5] . Any information-carrying modulation of synchronous activity must hence go beyond the here investigated effects , which can be regarded the baseline given by the non-stationary activity in networks without function . Since the mechanisms we have exposed only depend on generic features of cortical tissue—networks of non-linear neurons , connectivity with strong convergence and divergence , and dynamic stabilization by inhibition—the time-dependent entanglement of mean activity and covariances qualitatively exists in any network with these properties . In this view , our analysis can help to distinguish the level of time-modulated covariances in neural tissues that are surprising , and are therefore candidates to be attributed to function , from those that need to be expected in networks due to their generic properties .
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In network theory , statistics are often considered to be stationary . While this assumption can be justified by experimental insights to some extent , it is often also made for reasons of simplicity . However , the time-dependence of statistical measures do matter in many cases . For example , time-dependent processes are examined for gene regulatory networks or networks of traders at stock markets . Periodically changing activity of remote brain areas is visible in the local field potential ( LFP ) and its influence on the spiking activity is currently debated in neuroscience . In experimental studies , however , it is often difficult to determine time-dependent statistics due to a lack of sufficient data representing the system at a certain time point . Theoretical studies , in contrast , allow the assessment of the time dependent statistics with arbitrary precision . We here extend the analysis of the correlation structure of a homogeneously connected EI-network consisting of binary model neurons to the case including a global sinusoidal input to the network . We show that the time-dependence of the covariances—to first order—can be explained analytically . We expose the mechanisms that modulate covariances in time and show how they are shaped by inhibitory recurrent network feedback and the low-pass characteristics of neurons . These generic properties carry over to more realistic neuron models .
|
[
"Abstract",
"Introduction",
"Results",
"Methods",
"Discussion"
] |
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2017
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Locking of correlated neural activity to ongoing oscillations
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Vesicular stomatitis virus ( VSV ) suppresses antiviral responses in infected cells by inhibiting host gene expression at multiple levels , including transcription , nuclear cytoplasmic transport , and translation . The inhibition of host gene expression is due to the activity of the viral matrix ( M ) protein . Previous studies have shown that M protein interacts with host proteins Rae1 and Nup98 that have been implicated in regulating nuclear-cytoplasmic transport . However , Rae1 function is not essential for host mRNA transport , raising the question of how interaction of a viral protein with a host protein that is not essential for gene expression causes a global inhibition at multiple levels . We tested the hypothesis that there may be multiple M protein-Rae1 complexes involved in inhibiting host gene expression at multiple levels . Using size exclusion chromatography and sedimentation velocity analysis , it was determined that Rae1 exists in high , intermediate , and low molecular weight complexes . The intermediate molecular weight complexes containing Nup98 interacted most efficiently with M protein . The low molecular weight form also interacted with M protein in cells that overexpress Rae1 or cells in which Nup98 expression was silenced . Silencing Rae1 expression had little if any effect on nuclear accumulation of host mRNA in VSV-infected cells , nor did it affect VSV's ability to inhibit host translation . Instead , silencing Rae1 expression reduced the ability of VSV to inhibit host transcription . M protein interacted efficiently with Rae1-Nup98 complexes associated with the chromatin fraction of host nuclei , consistent with an effect on host transcription . These results support the idea that M protein-Rae1 complexes serve as platforms to promote the interaction of M protein with other factors involved in host transcription . They also support the idea that Rae1-Nup98 complexes play a previously under-appreciated role in regulation of transcription .
The antiviral responses mounted by virus-infected cells include potent mechanisms to prevent virus replication . Thus , in order for viruses to effectively propagate , most viruses have developed mechanisms to inhibit or evade these host antiviral responses . Many RNA viruses that replicate in the cytoplasm suppress antiviral responses by inhibiting host nuclear functions , such as transcription and nuclear-cytoplasmic transport . Vesicular stomatitis virus ( VSV ) is a widely studied prototype of the negative strand RNA viruses and is a potent suppressor of host antiviral responses [1] . This suppression is mediated by the viral matrix ( M ) protein , which inhibits multiple steps in the expression of host genes [2] , [3] , [4] , [5] , [6] , [7] including expression of genes that code for production of antiviral cytokines such as interferons [3] , [8] , [9] . M protein is a major structural component of the virus particle and plays several important roles in virus assembly [10] . However , the ability of M protein to suppress host gene expression is genetically separable from its function in virus assembly [3] , [11] . M protein causes a global inhibition of host gene expression at multiple levels . M protein inhibits host transcription [2] , [3] , [4] , [12] , and inhibits nuclear-cytoplasmic RNA transport [6] , [7] , [13] , [14] when expressed in transfected cells in the absence of other VSV components . M protein cannot inhibit host translation in the absence of other viral components [15] . However , in VSV-infected cells , host mRNA translation is inhibited and this inhibition is correlated with the ability of M protein to inhibit host transcription and transport [3] , [5] , [16] . One of the central questions in VSV pathogenesis is how does a relatively small ( 26 kDa ) M protein cause such a profound inhibition of host gene expression ? Since M protein lacks any enzymatic activity , it probably interferes with host gene expression by interacting with cellular proteins to alter their function . VSV M protein has been shown to interact with the host protein Rae1 , which in turn interacts with the nucleoporin Nup98 [7] , [14] . Rae1 had previously been thought to be involved in nuclear-cytoplasmic transport . Therefore , the global inhibition of host gene expression was attributed to a block in mRNA transport . However , other data show that Rae1 is not essential for nuclear-cytoplasmic mRNA transport , and silencing Rae1 expression does not inhibit cellular gene expression [17] , [18] . Furthermore , a block in mRNA transport by M protein would not be consistent with earlier data showing that VSV inhibits host gene expression in mammalian cells primarily at the levels of transcription and translation rather than mRNA transport [2] , [19] , [20] , [21] . With these discrepancies in mind , we decided to re-examine the interaction of M protein with Rae1 and Nup98 and the level of host gene expression in which they are involved . Rae1 is localized in the cytoplasm and the nucleoplasm , as well as around the nuclear rim [18] , [22] , [23] , [24] . Given its multiple sites of localization and the uncertainty about its function , we hypothesized that there may be multiple forms of Rae1 and that VSV M protein interacts with Rae1 to form multiple M protein-Rae1 complexes involved in inhibition of host gene expression . Indeed , we found that cellular Rae1 was present in high , intermediate , and low molecular weight complexes . The intermediate molecular weight complex with Nup98 was the form that interacted most effectively with M protein , but the low molecular weight form also interacted effectively with M protein in cells that overexpress Rae1 or cells in which expression of Nup98 was silenced . Silencing Rae1 expression did not affect host gene expression , but instead increased cellular resistance to the inhibitory effects of M protein . Furthermore , silencing Rae1 expression primarily affected the inhibition of host transcription , and had little if any effect on nuclear accumulation of host mRNA or translation of host proteins . These results support the idea that M protein-Rae1 complexes serve as platforms to promote the interaction of M protein with other factors involved in host transcription . They also support the idea that Rae1-Nup98 complexes play a previously under-appreciated role in regulation of cellular transcription .
The purpose of the experiments in Figure 1 was to compare the ability to interact with Rae1 and Nup98 of wild type ( wt ) M protein to that of mutant M proteins that are defective in their ability to inhibit host gene expression . Viruses containing an arginine for methionine substitution at M protein amino acid 51 ( M51R mutation ) are fully functional in virus assembly [11] , but are defective in inhibiting host transcription [3] , [12] , translation [16] , and nuclear-cytoplasmic RNA transport [9] . Mutant M protein , M ( D ) , which has three amino acid substitutions ( D52A , T53A , and Y54A ) , has been shown to be defective in interacting with Rae1 and Nup98 [14] . This mutant M protein is defective in inhibiting host mRNA transport [7] , [14] , but has not been tested in its ability to inhibit host transcription and translation . Recombinant wt or mutant M proteins were expressed in bacteria as fusion proteins with glutathione-S-transferase ( GST ) and purified on glutathione beads ( Figure S1A ) . GST not fused to M protein was used as a negative control . Lysates from HEK 293 cells were incubated with recombinant GST-M proteins bound to glutathione beads , and bound fractions were analyzed by SDS-PAGE and immunoblotting using antibody against Rae1 ( Figure 1A ) or Nup98 ( Figure 1B ) . Wt M protein interacted with Rae1 and Nup98 , while no interaction was detected with M51R mutant M protein , similar to the negative controls . The unbound fractions also contained another band with slower electrophoretic mobility that was immunoreactive with the antibody against Rae1 ( arrow in Figure 1A ) . Transfecting cells with Rae1 siRNA reduced Rae1 expression compared to control non-targeting siRNA , but had little if any effect on expression of the slower migrating band ( Figure S1B ) , indicating that this band was not derived from Rae1 . Similar to endogenous Rae1 , epitope-tagged Rae1 ( HA-Rae1 ) expressed in transfected cells interacted with wt , but not mutant M protein ( Figure S1C ) , and immunoprecipitation of HA-Rae1 from VSV-infected cells co-precipitated M protein ( Figure S1D ) . Collectively , results in Figures 1 and S1 are in agreement with published reports that M protein interacts with Rae1 and Nup98 [7] , [14] . In addition , the results with the M51R mutant M protein provide a genetic correlation between the interaction of M protein with these host proteins and the ability of recombinant viruses containing wt versus mutant M protein to inhibit host transcription and translation as well as nuclear-cytoplasmic transport . While the lack of interaction of the mutant M proteins with Rae1 correlates with their inactivity , these may not be causally related , as M protein could also interact with and inhibit other targets as well . Rae1 interacts with multiple proteins involved in regulating mRNA transport [22] , [25] , [26] , and in mitotic spindle [27] and checkpoint regulation [28] . To determine whether M protein interacts with Rae1 in different complexes , size exclusion chromatography was used to first separate complexes containing Rae1 , then the Rae1 in these column fractions was tested for its ability to interact with M protein . In the experiment shown in Figure 2A , cell lysates were chromatographed on a Superdex 200 column , and fractions were analyzed using SDS-PAGE and immunoblotting with antibodies against Rae1 and Nup98 . Rae1 was present in fractions 10–13 and in fractions 16–18 , whereas Nup98 was present primarily in fractions 11–12 . These data suggest that Rae1 exists in multiple forms: as high molecular weight complexes containing little if any Nup98 ( corresponding to fraction 10 ) , intermediate molecular weight complexes containing Nup98 ( corresponding to fractions 11–12 ) , and a low molecular weight form ( corresponding to fractions 16–18 ) . Approximately 30% of Rae1 was present in the low molecular weight form . The monomeric molecular weights of Nup98 and Rae1 are 98 and 42 kD , respectively . However , the low molecular weight form of Rae1 eluted in later fractions than would be expected compared to the ovalbumin standard which has a similar molecular weight . This is most likely due to the low molecular weight form of Rae1 adsorbing non-specifically to the chromatography matrix . To determine which Rae1 complexes are competent to interact with M protein , the fractions containing Rae1 10–13 and 16–18 were tested for interaction with GST-M protein on glutathione beads . Shown in Figure 2B are immunoblots of the bound fractions obtained after incubation with GST-M protein or GST alone probed with antibodies against Rae1 or Nup98 . Rae1 and Nup98 in fractions 11–13 were competent to interact with GST-M protein . However , the amount of Rae1 in fraction 10 that interacted with GST-M protein was much less than that in fractions 11–13 , indicating that the high molecular weight complex was relatively ineffective in interacting with M protein , compared to the intermediate molecular weight complexes ( corresponding to fractions 11–13 ) . Very little Rae1 in fractions 16–18 interacted with GST-M protein . However , the interaction was detectable on longer exposures ( data not shown ) . To determine whether overexpression of epitope-tagged Rae1 alters the complexes competent to interact with M protein , HEK293 cells were transfected with plasmid DNA encoding HA-Rae1 as described [14] , and cell lysates were analyzed by gel filtration and immunoblotting with anti-HA antibody . As shown in Figure 2C , HA-Rae1 was present in fractions 10–13 and 16–18 , similar to endogenous Rae1 . However , most of the HA-Rae1 was in the low molecular weight fractions ( approximately 80% ) . HA-Rae1 in the low molecular weight fractions ( 16–18 ) was competent to interact with GST-M protein ( Figure 2D ) , as was the HA-Rae1 in the intermediate molecular weight fractions ( 11–13 ) . The interaction of GST-M protein with Rae1 or HA-Rae1 was not affected by post-translational modifications that alter the charge of Rae1 , as shown by isoelectric focusing of bound and unbound fractions followed by immunoblotting for Rae1 or HA-Rae1 ( Figure S2 ) . Collectively , the data in Fig . 2A–D indicate that M protein can interact with Rae1 in the low molecular weight form as well as the intermediate molecular weight complex with Nup98 . Cell lysates were subjected to rate zonal centrifugation using sucrose gradients to further estimate the sizes of complexes containing Rae1 . After centrifugation twenty fractions were collected and analyzed by SDS-PAGE and immunoblotting . Shown in Figure 2E are fractions 1–11 collected from the top of the gradient . Rae1 was present in a broad peak from fractions 3–9 , with a peak in fractions 5–6 , which corresponds to an s20 . w value of 5±1S ( average ± SD for 5 experiments ) . This peak was composed primarily of the Rae1 complexes containing Nup98 , which interacted effectively with GST-M protein ( Figure 2F ) , whereas GST-M protein did not interact efficiently with Rae1 in fraction 8 of the sucrose gradients which had much less Nup98 . Rae1-Nup98 complexes were not well-resolved from the low molecular weight form of Rae1 by sedimentation analysis . The observation that the Rae1-Nup98 complexes eluted close to the high molecular weight complexes in gel filtration but close to the low molecular weight form in sedimentation is typical of proteins with a larger Stokes radius than similarly sized compactly folded globular proteins , suggesting that these complexes have either elongated structures or intrinsically disordered regions ( see Discussion ) . The impact of silencing expression of Rae1 or Nup98 on complexes that interact with M protein was determined by transfecting HeLa cells with siRNAs specific for each mRNA or nontargeting ( NT ) control siRNA . By selecting the most effective among four Rae1 siRNAs and four different transfection reagents , Rae1 expression levels were reduced to less than 2% of those in NT siRNA controls , but had little if any effect on expression of Nup98 ( Figure 3A ) . Silencing the expression of Nup98 ( Figure 3B ) reduced Nup98 protein levels to 10% of those in NT siRNA controls . There was a slightly lower level of expression of Rae1 in lysates from Nup98 siRNA cells ( 70±9% of NT siRNA cells , as determined by densitometry of 5 separate experiments ) . As reported previously [26] , silencing the expression of Rae1 was not lethal to the cells , and silencing the expression of Nup98 also had little if any effect on cell viability in the time period of these experiments ( 48–72 hours post-transfection ) . In the experiments shown in Figure 3 , cell extracts were prepared 48 hours post-transfection and were incubated with GST-M protein or GST alone on glutathione beads . Cell extracts and the bound fractions were analyzed by immunoblotting with antibodies against Rae1 and Nup98 . In lysates from Rae1 siRNA cells , the amount of Nup98 that interacted with M protein was considerably less than that in lysates from NT siRNA cells ( Figure 3A ) . Quantification of immunoblots from multiple experiments indicated that the amounts of Nup98 that interacted with M protein in lysates from Rae1 siRNA cells were <10% of those in lysates from NT siRNA cells . These results are consistent with previous mutagenesis experiments [14] indicating that Rae1 is required for the interaction of M protein with Nup98 . The amount of Rae1 in lysates from Nup98 siRNA cells that interacted with M protein was reduced slightly ( Figure 3B ) , but this could be attributed to the lower levels of Rae1 expression . These results suggest that Nup98 is not required for Rae1 to interact with M protein , although it is also possible that residual Nup98 expression in Nup98 siRNA cells could mediate the interaction . To distinguish these possibilities , and to determine whether silencing of Nup98 expression affected the distribution of Rae1 complexes , the elution profile of Rae1 in cells transfected with Nup98 siRNA was determined ( Figure 4A ) . In Nup98 siRNA cells , Rae1 eluted primarily in fractions corresponding to the low molecular weight form ( 16–18 ) . When the fractions containing Rae1 were incubated with GST-M protein , the low molecular weight form of Rae1 was competent to interact with M protein , as were the residual intermediate molecular weight complexes containing Rae1 and Nup98 ( Figure 4B ) . These data indicate that with the low levels of Nup98 expression , Rae1 primarily exists in a low molecular weight form that is competent to interact with M protein . In Rae1 siRNA cells , Rae1 could not be detected in the intermediate or low molecular weight forms . Following concentration of cell lysates , the residual Rae1 could be detected primarily in the high molecular weight form ( Figure 4C , fractions 10–11 ) . There was little if any effect of silencing Rae1 expression on elution of Nup98 , which was similar to that in NT siRNA cells ( Figure 4D ) . Similar to the data in Figure 2 , in siNT cells the intermediate molecular weight Rae1 complexes containing Nup98 bound efficiently to M protein ( Figure 4E ) . The effects of silencing Rae1 and Nup98 on VSV's ability to inhibit host transcription were determined . Host transcription was quantified by incorporation of [3H] uridine into RNA . This approach measures RNA synthesis by all three host RNA polymerases , with RNA polymerase I making the largest contribution . HeLa cells were transfected with siRNA against Rae1 or Nup98 or with NT siRNA . At 72 hours post-transfection , cells were mock infected or infected with recombinant wild-type ( rwt ) virus in the presence or absence of actinomycin D , an inhibitor of host transcription , which does not affect transcription by the viral RNA-dependent RNA polymerase . At 6 hours postinfection , cells were pulse labeled with [3H] uridine , and cell lysates were analyzed for trichloroacetic acid-precipitable radioactivity . Data from a representative experiment for Rae1 and Nup98 siRNA is shown in Table 1A and B , respectively , and results of multiple experiments are summarized in Figure 5A and B . In virus-infected cells , RNA synthesis in the absence of actinomycin D represents synthesis of both host RNA and viral RNA . Synthesis in the presence of actinomycin D represents viral RNA synthesis . Thus host RNA synthesis was determined by subtracting the amount of RNA synthesized in the presence of actinomycin D from the amount in the absence of actinomycin D . Both host ( actinomycin D sensitive ) and viral ( actinomycin D resistant ) RNA synthesis were expressed as a percentage of total RNA synthesis in mock-infected controls in order to normalize data among multiple experiments . Host RNA synthesis in NT siRNA cells or non-transfected control cells infected with rwt virus was reduced to approximately 10% of that in mock-infected cells . However , host RNA synthesis in Rae1 siRNA cells infected with rwt virus continued at approximately 40% of that in mock-infected cells . Viral RNA synthesis was similar in all three cell types . These results indicate that cells transfected with Rae1 siRNA are more resistant to inhibition of host transcription by VSV , and thus the expression of Rae1 is important for the ability of VSV to inhibit host transcription . In contrast to Rae1 , silencing the expression of Nup98 had no significant effect on host transcription inhibition by VSV ( Figure 5B ) . Labeling with 3H-uridine ( Figure 5 ) measures RNA synthesis by all three host RNA polymerases . RNA polymerases I , II , and III , have similar sensitivities to the inhibitory activity of M protein [2] , [19] , [20] , [21] , so it was expected that RNA polymerase II-dependent transcription would be affected by silencing Rae1 to an extent similar to total RNA synthesis . To specifically test the effect of silencing Rae1 expression on RNA polymerase II transcripts , host mRNAs were analyzed by cDNA microarrays . If the principal effect of M protein is to inhibit transcription , synthesis of mRNAs encoding antiviral proteins that would otherwise be induced by virus infection will be prevented , and the levels of mRNAs that are rapidly turned over will be reduced . Conversely , if silencing Rae1 expression increases cellular resistance to inhibition of transcription by M protein , mRNAs characteristic of host antiviral responses should be increased , and mRNAs that are rapidly turned over should be reduced to a lesser extent than in cells transfected with control siRNA . Figure 6 and Table S1 show the probe sets for genes that were reproducibly increased or decreased by greater than 3-fold at 6 hr postinfection with VSV compared to mock infection of siNT cells and siRae1 cells . To minimize the false discovery rate , the selection criteria for Figure 6 and Table S1 were that the pooled variance in the probe set in repeat experiments gave p<0 . 005 in comparing VSV-infected to mock-infected cells . In siNT cells , 880 probe sets met this criterion , most of which were only slightly different . The geometric mean intensity ratio ( VSV/mock ) of all the probe sets that met the selection criteria was 0 . 849 , indicating that the primary effect of VSV infection was a reduction in mRNA levels . In siRae1 cells , 970 probe sets met the selection criterion , with a geometric mean intensity ratio of 1 . 016 , which was significantly different from that of siNT cells ( p<10−12 by Students t-test ) . The selection of a 3-fold difference as a criterion for Figure 6 and Table S1 was based on a comparison of mock-infected siRae1 versus mock-infected siNT cells . In this comparison , 713 probe sets had p<0 . 005 . Of these only 3 were decreased >3-fold ( Table S1 E ) , including Rae1 itself . Thus , using a 3-fold difference as a selection criterion focused attention on gene expression changes in response to virus infection that were greater than the effects of silencing Rae1 expression in mock-infected cells . However , the same conclusions could be drawn by using a 2-fold increase or decrease as a selection criterion ( not shown ) . Few host mRNAs were decreased by more than 3-fold during the 6 hr timecourse of VSV infection , since the typical half-life of HeLa cell mRNAs is 6–12 hr [29] . However , those that were reduced >3-fold in siNT cells were reduced to a much lesser extent in siRae1 cells ( Figure 6A ) . Also fewer genes were reduced >3-fold in siRae1 cells ( Figure 6B ) compared to siNT cells ( Figure 6A ) . Infection with VSV increased expression of relatively few genes >3-fold in siNT cells ( Figure 6C ) , which is consistent with the inhibition of host transcription . The ones that were induced include stress-induced mRNAs such as those encoding c-Jun and homocysteine-inducible , endoplasmic reticulum stress-inducible , ubiquitin-like domain member 1 ( HERPUD1 ) . In siRae1 cells , many more genes were induced >3-fold than in siNT cells ( Figure 6D ) . The striking result is that many of these genes encode cytokines and other antiviral proteins that are typically induced by virus infection , such as IL-6 , CXCL2 , CCL5 , CXCL10 , and IFIT1 , 2 and 3 . The results with c-Jun and IL-6 were confirmed by real-time RT-PCR . As an additional control , silencing Rae1 expression had no effect on induction of IL-6 mRNA in cells infected with an M protein mutant virus ( rM51R-M virus [3] , [30] ) as determined by real-time RT-PCR ( not shown ) . Collectively , the results in Figure 6 are fully consistent with the conclusion that silencing Rae1 expression increases cellular resistance to the inhibitory effects of M protein at the level of host transcription . Furthermore , they emphasize the importance of the M protein-Rae1 complex in suppressing the antiviral response of host cells . To determine the effect of silencing Rae1 expression on the accumulation of host mRNA in the nucleus , the amount of host mRNAs in the nucleus versus cytoplasm was measured by real time RT-PCR in cells transfected with siRNA against Rae1 or with NT siRNA . At 72 hours post-transfection , cells were mock infected or infected with rwt virus . At 6 hours postinfection , cells were lysed and separated into nuclear and cytoplasmic fractions , and RNA was isolated from each fraction . The nuclear fractions were largely free of cytoplasmic contamination , since 28S and 18S rRNAs were undetectable by gel electrophoresis and ethidium bromide staining ( data not shown ) . As a control to monitor the efficiency of RNA recovery in the nuclear and cytoplasmic fractions , a known quantity of E . coli mRNA was added to the cytoplasmic and the nuclear fractions before harvesting RNA . The amounts of host mRNAs measured by real time RT-PCR in the cytoplasmic and nuclear fractions were normalized to the amount of E . coli uidA transcript measured in the same samples , and the percentage of total mRNA in the nucleus was calculated ( Figure 7 ) . Three different host mRNAs were analyzed . Actin mRNA was assayed as a representative mRNA for housekeeping genes , and IL-6 and c-Jun mRNAs were assayed as representative mRNAs induced during VSV infection . The amounts of actin mRNA in nuclei of mock-infected Rae1 siRNA cells and NT siRNA cells were similar , approximately 40% of total actin mRNA , similar to previous data for this cell type [31] , [32] . This result is consistent with the idea that Rae1 is not required for transport of actin mRNA . There was no significant difference in the levels of actin mRNA in the nuclei of rwt virus-infected cells compared to mock-infected cells for either Rae1 siRNA or NT siRNA cells . This result is consistent with earlier data indicating that there is little if any net accumulation of housekeeping mRNAs in the nuclei of VSV-infected cells , due to the inhibition of host transcription [20] , [21] . However , nearly all ( >99% ) of the IL-6 and c-Jun mRNA was in the nuclear fraction following infection with rwt virus . There was no significant difference between Rae1 siRNA cells versus NT siRNA cells in the nuclear accumulation of any of the host mRNAs assayed following virus infection . Collectively these results indicate that silencing Rae1 expression has little if any effect on the nuclear accumulation of host mRNA in VSV-infected cells . To determine the effects of silencing the expression of Rae1 on the ability of VSV to inhibit host translation , cells were transfected with Rae1 siRNA or with NT siRNA for 72 hours , and the rates of host and viral protein synthesis were determined at varying times postinfection . Cells were pulse-labeled with [35S] methionine , and lysates were analyzed by SDS-PAGE and phosphorescence imaging . Figure 8A shows a phosphoimage that compares protein synthesis in Rae1 siRNA cells versus NT siRNA cells that were mock infected or infected with rwt virus for 2 , 4 , and 6 hours . The ladder of bands in mock infected cells represents synthesis of host proteins . Host protein synthesis was quantified from regions of the gel devoid of viral proteins in three separate experiments and is shown in Figure 8B expressed as a percentage of that in mock-infected cells . Viral protein synthesis was quantified from radioactivity in all the viral bands and is expressed as a percent of synthesis at 6 hours postinfection ( Figure 8C ) . During infection with rwt virus , the synthesis of host proteins was inhibited in both Rae1 siRNA and NT siRNA cells , and was almost completely inhibited at 6 hours post infection . In rwt virus-infected cells , the synthesis of viral proteins L , G , N , P and M can be observed at 2 hours postinfection and by 6 hours the synthesis has reached its maximum [5] . There was no significant difference between Rae1 siRNA cells and NT siRNA cells in either the inhibition of host protein synthesis or the levels of viral protein synthesis . These data indicate that silencing expression of Rae1 does not affect the ability of VSV to inhibit host translation . Similarly , silencing expression of Nup98 did not affect the ability of VSV to inhibit host translation or affect viral protein synthesis ( Figure S3 ) . The results shown above indicate that Rae1 is required for efficient inhibition of host transcription in VSV- infected cells , but has little if any effect on nuclear accumulation of host mRNA or the shut-off of host translation . To further address whether M protein's interaction with Rae1 is required for M-protein-induced inhibition of host gene expression , M protein's ability to inhibit gene expression in transfected cells in the absence of other viral components was measured in cells silenced for the expression of Rae1 . Host-directed gene expression in transfected cells was measured using a luciferase reporter driven by the SV40 early promoter , which is dependent on the host transcriptional apparatus . Rae1 siRNA cells , NT siRNA cells , or cells that received no siRNA were cotransfected with luciferase plasmid DNA together with varying amounts of in vitro-transcribed mRNA encoding M protein or control RNA . The cells were transfected with M mRNA rather than plasmid DNA encoding M protein to promote optimal expression of M protein , because M protein inhibits transcription of its own mRNA from plasmid DNA that depends on host transcription machinery [4] , [15] . At 24 hours post-transfection cells were lysed and luciferase activity was measured . Shown in Figure 9 is luciferase activity that was normalized to the activity in the absence of M mRNA . In control cells transfected with NT siRNA or no siRNA , expression of M protein inhibited luciferase expression in a dose-dependent manner to approximately 10% of control with 500 ng of M mRNA , similar to previous results [15] , [33] . However , in Rae1 siRNA cells , there was significantly higher luciferase expression at both doses of M mRNA , with luciferase activity approximately 50% of control in cells transfected with 500 ng of M mRNA . This result is consistent with the results in Figures 5 and 6 that silencing the expression of Rae1 increases the resistance of cells to M protein's inhibitory effects on host gene expression . It has recently been shown that Nup98 plays a role in regulation of transcription and is associated with transcriptionally active chromatin in the nucleoplasm as well as nuclear pores [34] , [35] . The observation that silencing Rae1 expression primarily affects the ability of VSV to inhibit host transcription suggests that M protein binds to Rae1-Nup98 complexes associated with chromatin in the nucleus . This hypothesis was tested by isolating chromatin-associated Rae1-Nup98 complexes from nuclei of HeLa cells lysed in hypotonic buffer and fractionated as described in [36] . Nuclei were treated with DNase and RNase followed by heparin , a negatively charged polyanion , to solubilize chromatin and chromatin-associated proteins . The pellet largely represents the nuclear envelope . These fractions were probed for the presence of Rae1 and Nup98 and for their ability to interact with GST-M protein ( Figure 10 ) . The cytoplasmic fraction as well as the pellet and supernatant fractions obtained after each treatment of the nuclei were analyzed by SDS-PAGE and immunoblotting with antibodies against Rae1 and Nup98 ( Figure 10A ) . As a control to monitor the effectiveness of the solubilization of chromatin-associated proteins , the fractions were also probed for the transcription factor TATA-binding protein ( TBP ) . Rae1 and Nup98 were present in the cytoplasmic fraction as well as the supernatant fractions after treatment with DNase/RNase and heparin that contain proteins associated with chromatin , as expected from previous data [7] , [18] , [22] , [23] , [24] , [37] , [38] . The fact that both Rae1 and Nup98 are in the chromatin-containing fractions does not show that they function in concert in that environment . However , they do appear to be present as a complex that is competent to bind M protein , since GST-M protein co-precipitated Rae1 and Nup98 from both the cytoplasmic fraction and nuclear fractions containing chromatin-associated proteins ( Figure 10B ) . These data indicate that M protein can interact with Rae1-Nup98 complexes in these compartments , and are consistent with the idea that Rae1-Nup98 complexes are involved in the inhibition of transcription in VSV-infected cells .
One of the remarkable aspects of VSV pathogenesis is the ability of M protein to induce pleiotropic effects in infected cells . M protein plays multiple roles in both virus assembly and in the inhibition of host gene expression [10] . M protein inhibits transcription by all three host RNA polymerases [2] , [3] , [4] , [12] , inhibits nucleo-cytoplasmic RNA transport [6] , [7] , [13] , and plays a role in inhibition of translation of host mRNA [3] , [5] , [16] . One of the mechanisms by which M protein may serve these diverse functions is through interaction with host proteins , such as Rae1 , that may also serve multiple functions in a cell . Previous data had shown that M protein interacts with Rae1-Nup98 complexes , but did not address the ability of M protein to interact with other forms of Rae1 . It was originally thought that interaction of M protein with Rae1-Nup98 complexes was responsible for blocking nuclear-cytoplasmic transport . Therefore our hypothesis was that M protein interacts with other forms of Rae1 to inhibit other steps in host gene expression , such as transcription and translation . However , the data presented here show that Rae1-Nup98 complexes are the major form of Rae1 capable of interacting with M protein . In situations where the cellular levels of Rae1 or Nup98 are altered , either by overexpressing Rae1 or silencing expression of Nup98 , the low molecular weight form of Rae1 also interacts with M protein . Furthermore , rather than affecting the accumulation of host RNA in the nucleus , the major effect of silencing Rae1 expression was to make the cells more resistant to the inhibition of transcription by VSV . These results lead to a new model for how the interaction of M protein with Rae1 inhibits host gene expression . They also support the idea that Rae1-Nup98 complexes play a previously under-appreciated role in regulation of cellular transcription . M protein does not inhibit host gene expression simply by interfering with Rae1 function , since Rae1 is not essential for host gene expression [17] , [18] . This raises the question of how interaction of M protein with a sub-population of a protein that is not essential for gene expression can have a global effect on host gene expression at multiple levels . To address this paradox , we propose a model where M protein interacts with Rae1-Nup98 complexes that serve as a platform for M protein to interact with other essential host proteins , thereby , interfering with their function . The “platform hypothesis” predicts the opposite effects of silencing Rae1 expression compared to hypotheses based on M protein inhibition of Rae1 function . The latter hypotheses predict that Rae1 siRNA cells should be more sensitive than control cells to the effects of M protein , because of the lower level of Rae1 expression . In contrast the “platform hypothesis” predicts that Rae1 siRNA cells should be less sensitive to the effects of M protein than controls , since there is less Rae1 to mediate the interaction of M protein with other targets . Our data showing that Rae1 siRNA cells are relatively resistant to the inhibitory effects of M protein ( Figures 5 , 6 , and 9 ) provide support for the platform hypothesis and are largely inconsistent with hypotheses based on M protein interference with Rae1 function . The structural features of Rae1-Nup98 complexes are well-suited to mediate the interaction of M protein with other cellular targets . Rae1 is a member of the family of WD repeat proteins [22] , [23] , [24] , which are known to adopt beta propeller folds [39] , [40] , [41] that have large surface areas suitable for multiple protein interactions . Human Rae1 , which has four WD repeats in its sequence [22] , [24] , has been shown to form seven bladed β propellers with extensive surface loops [42] , which provide large surface areas that could serve as interacting regions for M protein to disrupt function of other proteins associated with Rae1 . Nup98 has a small globular region near its C-terminus . However , most of the remaining sequence contains FG-repeats , which are intrinsically disordered in other FG-repeat-containing proteins [43] . The FG-repeat region of Nup98 provides sites of interaction with a wide variety of other cellular proteins [43] . Rae1-Nup98 complexes have a larger apparent Stokes radius in gel filtration and a smaller sedimentation velocity than would be expected of compactly folded proteins . This could be due to an elongated structure , but is most likely due to the presence of disordered regions in the protein sequence . From our gel filtration data and that of Matsuoka et al [44] , the Stokes radius of the Rae1-Nup98 complex is estimated to be 70–75 Å , which combined with an estimated s20 , w of 5S ( Figure 2 ) gives a molecular weight of approximately 150 , 000 . This is a reasonable result for a 1∶1 complex of Rae1 and Nup98 . Our data also support the idea that the interaction of M protein with Rae1-Nup98 complexes inhibits host gene expression by inhibiting host transcription ( Figure 5 ) . Previous data had suggested that Rae1 and Nup98 interact with the transcriptional machinery . Both Rae1 and Nup98 are present in the nucleoplasm , as well as the nuclear envelope and cytoplasm [7] , [18] , [22] , [23] , [24] , [37] , [38] . The localization of Rae1 at the nuclear envelope is affected by inhibitors of RNA polymerase I and II activity [22] . This suggests that the localization of Rae1 is dependent on ongoing transcription . Similarly , the mobility of Nup98 in the nucleus is also dependent on ongoing transcription [37] . Nup98 in the nucleoplasm has been shown to interact with developmentally regulated genes in Drosophila , and altering Nup98 expression alters the expression of these genes , implicating Nup98 in the control of transcription [34] , [35] . Recent evidence suggests that the steps involved in gene transcription , nascent mRNA processing , and transport are coupled [45] , [46] . Rae1 can be cross-linked to poly A-containing mRNA [23] , and Rae1 interacts with other mRNA binding proteins [26] , suggesting that Rae1 and Nup98 may be a part of larger ribonucleoprotein complexes in the nucleus . M protein , by interacting with Rae1 and Nup98 , would target these complexes to inhibit both transcription and transport of nascent mRNA . Although Nup98 is likely to be important for the M protein-mediated inhibition of nuclear-cytoplasmic RNA transport , it may not be important for the inhibition of host transcription , since silencing Nup98 expression did not affect the inhibition of host transcription by VSV ( Figure 5B ) . Alternatively , the level of silencing of Nup98 may not have been sufficient to have an effect on the inhibition of host transcription by VSV . The effect of M protein on nuclear accumulation of cellular RNA depends on the cell type and the mRNA target being analyzed . Nuclear accumulation of RNA resulting from the inhibition of transport is most obvious in cells in which M protein has little if any effect on transcription , such as Xenopus oocytes [6] , [7] , [13] . However , in most mammalian cells , there is relatively little net accumulation of constitutively expressed mRNAs relative to pre-existing mRNAs in the nucleus during VSV infection , because their synthesis as well as their transport is inhibited by M protein . This was originally demonstrated in the pulse-chase experiments of Weck and Wagner [20] , and is confirmed by our analysis of the distribution of actin mRNA ( Figure 7 ) . In contrast to constitutively expressed mRNAs , mRNAs for IL-6 and cJun , which are induced by VSV infection , accumulate in the nucleus , with very little present in the cytoplasm ( Figure 7 ) . Experiments using in situ hybridization with oligo-dT have shown an apparent accumulation of total mRNA in the nucleus of VSV-infected cells . However , this result has not been confirmed by an independent approach and may be subject to artifacts such as masking of poly A-containing mRNAs in the cytoplasm of VSV-infected cells as a result of their accumulation in poorly translating ribonucleoprotein particles [47] , [48] . Further , not all nuclear-cytoplasmic transport is inhibited by M protein . For example , export of tRNA [6] , [7] and RNA bearing constitutive transport element [7] is resistant to the inhibition , as is export of complexes containing hnRNP-A1 and other hnRNPs [49] . Silencing Rae1 expression inhibits export of hnRNP-A1 in VSV-infected cells [49] , but has little if any effect on nuclear accumulation of host mRNAs ( Figure 7 ) . The level of mRNA in the nucleus reflects a balance of transcription , transport , and turnover . Thus it is possible that silencing Rae1 expression may have an effect on mRNA transport in VSV-infected cells that is balanced by changes in transcription or turnover . The inhibition of host translation in VSV-infected cells is not due to depletion of host mRNAs from the cytoplasm as a result of the inhibition of host transcription and nuclear-cytoplasmic transport [16] , [48] , [50] . Instead , the translational apparatus is altered in VSV-infected cells such that translation of pre-existing host mRNAs is inhibited , and only newly appearing mRNAs are translated [16] , namely those produced by the viral RNA-dependent RNA polymerase . This alteration of the translation apparatus is correlated with the dephosphorylation of the cap-binding translation factor eIF4E [5] , [51] . The results presented here indicate that silencing Rae1 expression has little if any effect on this process ( Figure 8 ) , suggesting that other molecular targets are involved . In summary , the data presented here have addressed the role of host Rae1 in the M protein-mediated inhibition of host gene expression at three different levels . The data support a model in which Rae1 serves as a platform for interaction of M protein with other molecular targets . Our findings also lead us to propose a new function for Rae1 in regulating transcription in VSV- infected cells , as well as providing new insights into the mechanism of VSV-mediated inhibition of host gene expression .
To construct a wild type ( wt ) M protein with BamHI and NotI restriction site , the wt M gene in pET21d vector [52] served as a template . A BamHI restriction site was added using the primer 5′GCGGCCGGATCCATGGCTTCCTTAA 3′ , and a NotI restriction site was added using reverse primer 5′ GCCCGCGCGGCCGCCTACTCGAGTTTG 3′ . The resulting PCR fragment was cleaved and ligated into the vector pGEX-6P-1 ( GE Healthcare ) . The resulting M protein had an N- terminal glutathione-S-transferase tag [GST-M] . Mutations within the M gene were made using the Quick change mutagenesis kit ( Stratagene ) . Sequences of all clones were verified through DNA sequencing . The plasmids were transformed into BL21 ( DE3 ) pLysS E . coli cells . Day cultures were grown until the cells reached an optical density of A600 nm∼0 . 7 and induced with 200 µM isopropyl-ß-D-thiogalactopyranoside ( IPTG ) for 3 hours at 37°C . Cells were centrifuged at 4000× g for 20 minutes at 4°C , and pellets were frozen at −20°C until use . Recombinant wt and mutant M proteins with the GST tag were prepared using the protocol described in [13] with a few modifications which are as follows . The cells were lysed in phosphate buffered saline ( PBS ) with 1% TritonX100 with 1 mM phenyl methylsulfonyl fluoride . Following sonication and centrifugation , the protein was immediately loaded onto glutathione-Sepharose beads ( GE Healthcare ) and incubated for 1 hour at 4°C . Beads were washed with PBS and used in experiments . HEK 293 cells were cultured in Dulbecco's modified Eagle's medium with 10% fetal calf serum and 2 mM glutamine . To prepare lysates , the cells were washed with PBS and incubated for 10 minutes on ice in lysis buffer ( 50 mM Tris pH 8 . 0 , 150 mM NaCl , 15 mM MgCl2 , and 0 . 5% NP40 ) with an EDTA-free protease inhibitor mixture ( Roche ) . Lysates were centrifuged at high speed for 15 minutes at 4°C . The resulting supernatant was collected and frozen at −80°C or used immediately in experiments . For transfections , cells were transfected with 9 µg of plasmid encoding hemagglutinin ( HA ) epitope tagged Rae1 [a gift from B . Fontoura used in [14]] using the calcium phosphate method . The plasmid encoding HA epitope tagged Rae1 ( HA-Rae1 ) was modified to encode the entire sequence of the HA epitope tag to enhance antibody binding . Twenty four hours post-transfection , the cells were washed with PBS and lysates were prepared as described above . For infecting cells , recombinant wild type VSV with wild type M protein ( rwt ) or recombinant VSV containing the M51R mutant M protein ( rM51R-M ) virus stocks were prepared in BHK cells as described [30] . Twenty four hours prior to infection , 1×106 HEK 293 cells were seeded in 100 mm dish . Cells were infected with either rwt or rM51R-M virus at a multiplicity of infection ( MOI ) of 10 plaque forming units/cell for 6 hours . Following infection , cells were harvested in lysis buffer as described above . Wt or mutant GST-M proteins on glutathione beads were incubated in binding buffer ( 20 mM HEPES pH 7 . 4 , 110 mM potassium acetate , 2 mM MgCl2 , and 0 . 1% Tween 20 ) for 1 hour at 4°C . Lysates from siRNA transfected or untransfected cells ( 250 µl ) were incubated with 25 µl packed volume of GST-M proteins on glutathione beads ( 500 ng of GST-M protein ) suspended in 250 µl of binding buffer at 4°C . Unless otherwise noted , where the incubation time was varied , the proteins were incubated for 1 hour . Bound and unbound fractions were separated by spinning the samples at 4000× g for 2 minutes at 4°C . The bound fraction was washed several times with the binding buffer and analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis ( SDS-PAGE ) and immunoblotting . Lysates from cells transfected with HA-Rae1 were prepared as described above . The lysates were incubated overnight with 30 µl of HA antibody ( Roche ) . The lysates were incubated with protein A agarose beads ( Sigma ) prepared in 10 mm Tris pH8 . 0 for 2 hours at 4°C . The supernatant and pellet fractions were separated by centrifugation at high speed for 5 minutes . The pellet fractions were washed several times with cell lysis buffer and analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis ( SDS-PAGE ) and immunoblotting . Proteins were resolved by SDS-PAGE using either 10% Bis-Tris NuPAGE gel ( Invitrogen ) or 10% Tris-HCl polyacrylamide gels . Following electrophoresis , proteins were transferred onto polyvinylidene difluoride ( PVDF ) membranes and blocked in Tris buffered saline with 0 . 02% Tween- 20 ( TBS-T ) with 5% milk ( Difco ) or in PBS with 0 . 05% Tween-20 ( PBS-T ) and 3% milk . The membranes were probed using primary antibodies to Nup98 ( Sigma ) or the HA tag ( Sigma ) or TBP protein ( Sigma ) prepared in TBS-T with 2 . 5% milk . Antibody against Rae1 ( R2905: Sigma ) or M protein ( 23H12 ) were prepared in PBS-T with 1% milk . After several washes in either TBS-T or PBS-T , the blots were incubated with respective secondary antibodies linked to horseradish peroxidase ( Amersham ) used at 1∶10000 in TBS-T with 2 . 5% milk or PBS-T with 1% milk . The blots were washed in either TBS-T or PBS-T , and proteins were detected using enhanced chemiluminescence substrate ( Thermo Scientific ) . The intensities of the bands were quantified by scanning and analysis using Quantity One software ( Bio-Rad ) . Lysates from mock-infected cells were concentrated approximately 3-fold to 500 µl using Ultracel −10K ( Millipore ) before chromatography on size exclusion chromatography . Lysates were chromatographed on a Superdex 200 column ( length = 30 cm , diameter = 1 cm ) in cell lysis buffer using an FPLC apparatus ( Bio-Rad ) , and thirty 1 ml fractions were collected . The fractions were collected at a flow rate of 0 . 5 ml per minute at 4°C ( approximately 50 min ) . Equal volumes of fractions were analyzed for the presence of proteins by SDS-PAGE followed by immunoblotting . The standards used to calibrate the column were bovine serum albumin ( BSA ) , ovalbumin , and aldolase prepared in cell lysis buffer without NP40 . Gel filtration fractions obtained were incubated with GST-M protein on glutathione beads for 1 hour to obtain bound fractions as described above . Lysates were overlaid on 5–20% sucrose gradients in cell lysis buffer . Gradients were centrifuged at 35 , 000 rpm for 18 . 3 hours at 4°C in a SW41 . 0 rotor ( Beckman Instruments ) . Twenty fractions of equal volumes were collected from the top of the gradient and analyzed by SDS-PAGE and immunoblotting . The gradient was calibrated with standard proteins of known sedimentation coefficient , BSA ( 4 . 4S ) and phosphorylase b ( 8 . 8S ) . Sucrose gradient fractions were incubated with GST-M protein on glutathione beads for 14 hours at 4°C to obtain bound and unbound fractions as described above . To immunoprecipitate from sucrose gradient fractions , fractions 2–3 , 4–8 and 9–11 were incubated with HA-Rae1 antibody and purified with protein A agarose beads as described above . Rae1 siRNA ( D-011482-02 , Dharmacon ) was used at final concentration of either 5 µM or 10 µM with similar results . Nup98 siRNA ( D013078-01 , Dharmacon ) was used at a final concentration of 5 or 10 µM to achieve similar silencing efficiency . The nontargeting ( NT ) siRNA whose sequence is scrambled and does not match any sequence on the human genome used was as a control ( D-001210-01 , Dharmacon ) . All transient siRNA transfections were carried out in HeLa cells using Hiperfect transfection reagent ( Qiagen Corporation ) according to the manufacturer's instructions and as described previously [49] . For binding experiments , lysates from silenced cells were prepared at 48 hours post transfection as described above . Silencing of each protein was confirmed by immunoblotting . Bound and unbound fractions of cell lysates containing endogenous Rae1 or HA-Rae1 after incubation with GST-M protein on glutathione beads were prepared as described above . The bound fraction was washed and the beads were incubated with fresh lysates twice more to increase the amount of bound protein for analysis . The bound fraction was washed after each incubation . The bound fraction was re-suspended in rehydration buffer [8 M urea , 2% chaps , 50 mM dithiothreitol and 0 . 2% ampholytes ( Bio-Rad ) ] . The unbound fraction was precipitated using 1∶1 ethanol: ether solution and then re-suspended in rehydration buffer . The bound and unbound fractions were incubated for 16 hours at room temperature in an IPG strip pH 3–10 , 11 cm ( Bio-Rad ) . The strips were focused in a Protean IEF cell . Following focusing , the strips were run in the second dimension using an 8–16% Tris–HCl gel ( Bio-Rad ) , transferred onto PVDF and probed for Rae1 . HeLa cells were transfected Rae1 , Nup98 or NT siRNA , and at 48 hours post transfection , cells were re-seeded at a density of approximately 1×106 cells in 35-mm culture dishes . After 24 hours cells were mock-infected or infected with rwt virus at MOI = 30 in the presence or absence of actinomycin D ( 5 µg/ml ) as described previously [19] . At 6 hours postinfection , cells were labeled with [3H]-uridine ( 100 µCi/ml ) for 30 minutes , washed , and harvested in PBS . RNA was precipitated with trichloroacetic acid , and radioactivity was determined by scintillation counting . All solutions used for RNA purification were prepared in diethyl pyrocarbonate-treated water . At 72 hours post transfections with Rae1 siRNA or NT siRNA , cells were mock-infected or infected with rwt virus at MOI = 10 for 6 hours . RNA was isolated from the nucleus and cytoplasm as described in [32] with a few modifications which were as follows . After scraping the cells in cold PBS , the pellet was resuspended in lysis buffer ( 10 mM NaCl , 10 mM Tris-Cl [pH 7 . 4] , 3 mM MgCl2 ) containing 20 mM vanadyl-ribonucleoside complex ( Sigma ) . An equal volume of the same lysis buffer with 10% ( vol/vol ) deoxycholate and 20% Tween-40 was added to the cells on ice with gentle mixing . Nuclei and cytoplasmic fractions were separated by centrifugation over a sucrose cushion . Supernatant ( cytoplasmic ) and pellet ( nuclear ) fractions were analyzed without further manipulation in order to recover equal cell-equivalent amounts of nuclear and cytoplasmic fractions . To normalize the data for RNA recovery , samples were spiked with 3 µg of E . coli total mRNA ( Ambion ) before isolation RNA using TRIzol reagent ( Invitrogen ) . At 72 hours post transfection with Rae1 siRNA or NT siRNA , cells were mock-infected or infected with rwt virus at MOI = 30 . At 6 h postinfection , total RNA was isolated using TRIzol reagent . Each RNA sample was processed according the manufacturer's protocol ( Affymetrix ) and hybridized to the Affymetrix Human Genome U219 Array strip representing 20 , 000 well-characterized human genes . Each chip was scaled to a target intensity of 500 , normalized to control probe sets present on each chip , and then expressed as a ratio to the nonspecific background on a per-gene basis . Analysis of data was carried out using Affymetrix Data Mining Tool software ( Affymetrix ) . The intensity values from all of the probe sets on the arrays were log2-transformed and adjusted by systematic variation normalization [53] . Oligonucleotide primers and probes were designed and purchased from Sigma-Genosys . Primers for uidA gene ( beta-glucuronidase ) in E . coli were ( forward ) 5′-AGGTGCACGGGAATATTTCG-3′ and ( reverse ) 5′- ACGCGTCGGGTCGAGTT-3 . The probe for E . coli uidA was CCACTGGCGGAAGCAACGCG . Primers for IL-6 gene were ( forward ) 5′-CCCCCAGGAGAAGATTCCAA- 3′ and ( reverse ) 5′-TCAATTCGTTCTGAAGAGGTGAGT-3 . The probe for IL-6 was ATGTAGCCGCCCCACACAGACAGC . Primers for c Jun gene were ( forward ) 5′- GCAAAGATGGAAACGACCTTCT- 3′ and ( reverse ) 5′- GCTCTCGGACGGGAGGAA-3 . The probe for c-Jun was TGACGATGCCCTCAACGCCT . The probes for each gene were labeled at the 5′ end with the reporter dye carboxyfluorescein and at the 3′ with the quencher tetramethylrhodamine . The primers and probe sequences for β-actin were as described in [54] . Real time RT-PCR analysis was performed with a TaqMan One-Step RT-PCR Master Mix Reagents kit ( Applied Biosystems ) as described by the manufacturer using a 25-µl sample volume and 0 . 25 ng of sample RNA . For actin , IL-6 and c-Jun , 5 µM concentrations of primers , and 2 . 5 µM concentration of probes were used , and for E . coli uidA , 10 µM concentrations of primers and 5 µM concentration of probe were used . TaqMan PCR assays were performed using an ABI 7700 instrument ( Applied Biosystems , Foster City , CA ) as described [54] . All samples were tested in triplicate . The critical threshold cycle ( CT ) is defined as the cycle at which the fluorescence becomes detectable above background and is inversely proportional to the logarithm of the initial number of template molecules . A standard curve was plotted for each primer-probe set with CT values obtained from amplification of known quantities of plasmid DNA coding for either β-actin or of total E . coli mRNA . The standard curves were used to transform CT values of the experimental samples to the relative number of DNA molecules . At 72 hours post transfection with Rae1 siRNA , Nup98 or NT siRNA , cells were mock-infected or infected with rwt virus at MOI = 30 and then labeled with [35S] methionine for 10 min at varying times after infection , as described [5] . Lysates were assayed for protein content and equal amounts of protein were resolved on SDS-PAGE gel . Gels were stained with Coomassie blue and were analyzed by phosphorescence imaging ( Amersham Biosciences ) . The intensities of corresponding host and viral protein bands were quantified using ImageQuant software ( Molecular Dynamics ) . For viral protein bands , the background was determined from an equivalently sized region of the gel immediately above the viral protein band . For host protein bands , the regions of the gel devoid of viral proteins between viral L and G , G and N , and P and M proteins were quantified , and similarly sized regions of the image without radioactivity were used as background . Templates for in vitro transcription of M mRNA were generated by linearizing plasmid pSD-M [11] , [33] with SalI , followed by phenol chloroform extraction and ethanol precipitation . mRNA was transcribed in vitro using the mMessage Machine SP6 Kit ( Ambion ) according to the manufacturer's instructions , and the RNA was precipitated with lithium chloride . HeLa cells were transfected with Rae1 or NT siRNA , and at 48 hours post-transfection were re-seeded at a density of approximately 1×106 in 35-mm culture dishes . After 24 hours , cells were transfected with varying amounts of M mRNA and yeast tRNA to adjust the total RNA to 750 ng , together with pGL3 plasmid DNA ( 100 ng , Promega ) using the Mirus TransIT mRNA reagent . Luciferase activity was determined using Luciferase Assay System ( Promega ) . The nuclei from HeLa S2 spinner cells were fractionated essentially as described [36] . All solutions had protease inhibitors added immediately before use . Briefly , cells were pelleted and resuspended in ice-cold RSB buffer ( 10 mM Tris-Cl [pH 7 . 4] , 0 . 5 mM MgCl2 , 10 mM KCL ) . Cell membranes were disrupted in a Dounce homogenizer by 35 strokes of Teflon coated pestle . The integrity of the nuclear membranes were generally intact as monitored by light microscopy . The lysates were overlaid on buffer B ( 2 . 3 M sucrose , 50 mM Tris-HCl [pH 7 . 5] , 25 mM KCl , 5 mM MgCl2 , 2 mM DTT ) and spun at 2000 rpm to pellet the nuclei . The pellets were resuspended in 100 µl buffer A ( 0 . 25 sucrose , 50 mM Tris-HCl [pH7 . 5] , 25 mM KCl , 5 mM MgCl2 , 2 mM DTT ) and the nuclei were counted and frozen at −80°C until use . 1×107 nuclei were thawed by placing in 30°C water bath and centrifuged at 2500 rpm for 1 minute . The pellet was resuspended by adding 300 µl of lysis buffer ( 0 . 1 mM MgCl2 , 1 mM DTT , 5 µg/ml of DNaseI and 5 µg/ml of RNaseI ) dropwise , and vortexing . Following resuspension , 1 . 3 ml of extraction buffer ( 10% sucrose , 20 mM triethanolamine [pH 7 . 5] , 0 . 1 mM MgCl2 , 1 mM DTT ) was added dropwise and the pellet was incubated for 15 minutes at room temperature . The resuspended nuclei were underlaid with 500 µl of 30% sucrose cushion ( 30% sucrose , 20 mM triethanolamine [pH 7 . 5] , 0 . 1 mM MgCl2 , 1 mM DTT ) and centrifuged by slowly increasing the speed to 4000 rpm for 10 minutes . The supernatant and pellet fractions were separated and the pellet was resuspended in 300 µl of extraction buffer [pH7 . 5] dropwise followed by 170 µl of extraction buffer [pH7 . 5] containing 0 . 3 mg/ml of heparin . The resuspended nuclei were underlaid on 30% sucrose cushion and centrifuged as before . The process was repeated , with the pellet resuspended in 170 µl of extraction buffer [pH7 . 5] . The isolated fractions were incubated with GST-M protein or GST for 14 hours suspended in cell lysis buffer and analyzed by SDS-PAGE and immunoblotting . The chromatin-associated fractions and nuclear membrane fractions from uninfected cells were cleanly separated . However , when this procedure was applied to VSV-infected cells , the nuclear membranes appeared to be disrupted during the procedure , perhaps due to greater fragility , so that they were not cleanly separated from the chromatin-associated fractions . Microarray data were deposited in the Gene Expression Omnibus [GEO] database ( Accession Number: GSE38866 ) : http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE38866 .
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All viruses have mechanisms to suppress or evade host antiviral responses . These mechanisms are critical for viral pathogenicity . Vesicular stomatitis virus ( VSV ) suppresses antiviral responses by global inhibition of host gene expression mediated by the viral matrix ( M ) protein . M protein interacts with the host protein Rae1 in a complex with the nucleoporin Nup98 . It had been thought that interaction of M protein with Rae1 blocks nuclear-cytoplasmic mRNA transport . However , other data show that Rae1 is not essential for mRNA transport . With this discrepancy in mind , we re-examined the interaction of M protein with Rae1 and Nup98 and the level of host gene expression in which they are involved . A key result was that silencing Rae1 expression did not affect host gene expression , but instead increased cellular resistance to inhibition by M protein . Furthermore , silencing Rae1 expression primarily affected the inhibition of host transcription with no significant effect on nuclear accumulation of mRNA . These results support a model in which Rae1 serves as a “platform” to promote interaction of M protein with cellular targets involved in host transcription . This illustrates a general principle that viral proteins can have multiple cellular effects by interacting with host proteins that are themselves multi-functional .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"medicine",
"infectious",
"diseases",
"viral",
"diseases"
] |
2012
|
Complexes of Vesicular Stomatitis Virus Matrix Protein with Host Rae1 and Nup98 Involved in Inhibition of Host Transcription
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Mitochondrial dysfunction underlies numerous age-related pathologies . In an effort to uncover how the detrimental effects of mitochondrial dysfunction might be alleviated , we examined how the nematode C . elegans not only adapts to disruption of the mitochondrial electron transport chain , but in many instances responds with extended lifespan . Studies have shown various retrograde responses are activated in these animals , including the well-studied ATFS-1-dependent mitochondrial unfolded protein response ( UPRmt ) . Such processes fall under the greater rubric of cellular surveillance mechanisms . Here we identify a novel p38 signaling cascade that is required to extend life when the mitochondrial electron transport chain is disrupted in worms , and which is blocked by disruption of the Mitochondrial-associated Degradation ( MAD ) pathway . This novel cascade is defined by DLK-1 ( MAP3K ) , SEK-3 ( MAP2K ) , PMK-3 ( MAPK ) and the reporter gene Ptbb-6::GFP . Inhibition of known mitochondrial retrograde responses does not alter induction of Ptbb-6::GFP , instead induction of this reporter often occurs in counterpoint to activation of SKN-1 , which we show is under the control of ATFS-1 . In those mitochondrial bioenergetic mutants which activate Ptbb-6::GFP , we find that dlk-1 , sek-3 and pmk-3 are all required for their life extension .
Once considered relatively rare , mitochondrial disorders are now recognized as one of the most common inherited human diseases [1] . Mitochondrial dysfunction is a causative factor in many of the major diseases that limit life-expectancy in humans [2] and is associated with chronic diseases such as type 2 diabetes [3] , metabolic syndrome [4] , Alzheimer’s disease [5 , 6] , Parkinson’s disease [7] , depression [8] , blindness [9] and even aging itself [10–13] . There is hope , however , for coping with , or even overcoming , some forms of mitochondrial dysfunction . In humans , diseases that affect the mitochondrial electron transport chain are pleiotropic and may take years to manifest . Some people remain asymptomatic [14] , and there are even examples of spontaneous recovery [15] . This reflects complex interactions with other genes [16] and the environment [17] , and suggests that cells are able to adapt to some level of mitochondrial impairment . Even more striking are those organisms that adapt to mitochondrial electron transport chain ( ETC ) disruption and actually have a longer lifespan as a result of it . This has been reported across phyla–including mice [18]ȁbut has been most extensively studied in the nematode Caenorhabditis elegans [19] . C . elegans’ response to mitochondrial ETC dysfunction is threshold dependent; low levels produce no phenotype , moderate levels can result in increased lifespan , while severe disruption , as in humans , leads to overt pathology and shortened lifespan [20] . Intriguingly , research suggests that pathology resulting from severe mitochondrial dysfunction develops not as a direct consequence , but from the cell’s maladaptive response to the compromised mitochondria . For example , when the p53 homolog , cep-1 , is knocked out , worms become long-lived when subjected to levels of mitochondrial disruption that would otherwise shorten lifespan [21] . This gives greater hope that we may be able to target and modulate such responses in humans . The central role of mitochondria in the pathogenesis of multiple diseases is in part a consequence of their essential role in various cellular processes , including apoptotic signaling [22] , ATP production [23] , calcium sequestration [24] , Fe-S cluster formation [25] , immunity [26] , nucleotide biosynthesis [27] , oxidative stress signaling [28] , stem cell maturation [29] , steroid biosynthesis and xenobiotic detoxification [30] . The essential nature of mitochondria necessitates their functional status be closely monitored and it is now well established that signaling between the nucleus and mitochondria is bi-directional [31] . So-called retrograde response signaling originates from mitochondria and functions to orchestrate adaptive changes in nuclear gene expression to resolve or reduce mitochondrial stress . A variety of retrograde responses are known and are activated by an assortment of mitochondrial stressors , including depletion or mutation of mtDNA [32] , reduced ETC activity [33] , reduced mtDNA translation [34] , oxidative stress [35] , misfolded protein aggregation [36] , altered mitochondrial turnover dynamics [37] and exposure to bacterial toxins [38] . Part of how organisms recognize a pathogen attack and activate an immune response is by monitoring their own core cellular functions , including cytosolic protein translation and mitochondrial function [38 , 39] . Disruption of such processes is preemptively interpreted as evidence of a pathogen attack . This is a key adaptation for host organisms because the mechanisms of survival and reproduction of pathogens often remain critically dependent upon disrupting core cellular processes , even though pathogens may evolve to evade recognition by other forms of immune surveillance . As one example , many pathogens remain obliged to meet their requirement for iron by stealing it from their host’s mitochondria through use of siderophores [40] . Mitochondrial retrograde responses can be viewed therefore in a much broader sense as signaling elements of the cell surveillance system . The well-studied mitochondrial unfolded protein response ( UPRmt ) is one type of retrograde response and , in C . elegans , it is activated by a number of bacteria native to its habitat . Interestingly , the UPRmt can also be suppressed by alternate branches of the cell surveillance system when other responses are deemed more urgent [41] . The UPRmt in worms has been well characterized by the Ron and Haynes labs [42] and this process is critical for both development in the face of mitochondrial disruption [43] and for resistance to infection [39] . Two studies utilizing RNAi knockdown of ubl-5 –an important factor mediating the UPRmt response [44]–suggested that the UPRmt may be specifically required for life extension in response to mitochondrial dysfunction [18 , 45] . However , ubl-5 may have a constitutive role in mitochondrial homeostasis beyond UPRmt induction , making the UPRmt-specific transcription factor , atfs-1 [43] , a better candidate to test the involvement of UPRmt in longevity [46] . Contrary to expectation , not only does constitutively active ATFS-1 fail to extend lifespan [47] , removal of atfs-1 by RNAi or mutation does not prevent life extension following mitochondrial disruption by isp-1 ( qm150 ) or cco-1 RNAi [46] . These results suggest that activation of the UPRmt may not produce the life extension observed upon mitochondrial dysfunction . Similarly , a recent study on the proteomes of several long-lived mouse models found that longevity correlated with decreased expression of multiple subunits of complexes I , III , IV and V and that this was not accompanied by any activation of the UPRmt [48] . Thus we set out to find other signaling pathways that are triggered independently of atfs-1 in response to mitochondrial dysfunction , and which might instead be required for life extension .
To identify genes in C . elegans that are upregulated independently of ATFS-1 following mitochondrial ETC disruption , we utilized previously published microarray data [43] . We identified 148 genes upregulated more than two-fold in wild-type worms ( N2 Bristol ) treated with RNAi targeting the mitochondrial metalloprotease spg-7 and which remained elevated in mutant atfs-1 ( tm4525 ) worms following the same RNAi treatment ( S1 Table ) . Of these genes , the one showing greatest induction upon mitochondrial disruption was the uncharacterized β-tubulin , tbb-6 . It was upregulated more than fifty-fold in wild-type animals , and nearly seventy-fold in atfs-1 ( tm4525 ) worms . Indeed , tbb-6 was among the ten most highly upregulated of all genes following spg-7 RNAi treatment and , of these ten , the only one that did not require atfs-1 for its induction ( Fig 1A ) . Promoter analysis of the 148 atfs-1 independent genes identified five motifs that were significantly over-represented: Three motifs were restricted to six small heat shock proteins and all were related to the well-characterized heat shock regulatory element [49] . Forty genes ( 27% ) contained one or more EOR-1 binding motifs ( significant at a p-value of 2 . 1e-43 ) ( Fig 1B and S1 Table ) , while forty-two genes ( 28% ) contained one or more CCAAT/enhancer binding protein ( C/EBP ) -like motifs ( significant at a p-value of 3 . 2e-31 ) ( Fig 1C and S1 Table ) . Interestingly , the two groups of genes containing the latter two motifs were largely independent of each other ( Fig 1D and S1 Table ) . DAF-16/FOXO is a transcription factor best known for its role in life extension following inhibition of the insulin/IGF-1-like signaling pathway in worms [50] but has repeatedly been shown to be uninvolved in life extension following mitochondrial disruption ( reviewed in [19] ) . Recent studies have shown that half of all promoters bound by DAF-16 also contain one or more EOR-1 binding motifs [51] , yet of the forty genes that we identified with EOR-1 binding motifs , only seven also contained a DAF-16 binding motif ( Fig 1D and S1 Table ) . DAF-16 binding sites were not significantly over represented in our sample set beyond expectation , even though there were 27 genes containing one or more matches to the DAF-16 binding site consensus ( Fig 1D ) . The promoter of tbb-6 contains two C/EBP motifs , as well as PHA-4 and DAF-16 binding sites ( Fig 1E and S1 Table ) . Collectively , our data hint at the presence of one or more unexplored signaling pathways that are activated independently of the ATFS-1 dependent UPRmt pathway , and which function downstream of mitochondrial disruption to coordinately modulate the expression of multiple genes . Given the extent to which tbb-6 is upregulated upon mitochondrial disruption ( ~70 fold ) , we reasoned that tbb-6 expression would serve as a useful marker for a potentially unexplored mitochondrial retrograde response that controls lifespan . We constructed a Ptbb-6::GFP transcriptional reporter strain and observed background expression in the pharynx , which is consistent with the presence of a PHA-4 binding site in the tbb-6 promoter region ( Fig 1E ) . There was no expression of GFP anywhere else in these worms ( see vector control in Fig 2A ) . We tested whether the Ptbb-6::GFP reporter , like the UPRmt , could be induced upon various RNAi-mediated disruptions to the mitochondrial ETC and related proteins . In all instances where the reporter was activated in adult worms , we observed strongest expression in the intestine ( Fig 2A ) . We also detected faint neuronal expression on some occasions , and during the L4 larval stage Ptbb-6::GFP was often transiently but strongly expressed in the hypodermis . In adult worms , depending upon which respiratory complex was affected , the level of Ptbb-6::GFP expression varied greatly . On average , RNAi knockdown of subunits of complex V led to the highest Ptbb-6::GFP induction . Expression was lower , but still well above background , following knockdown of complex I , III or IV subunits ( Figs 2 , S1 and S4 and S2 Table ) . In contrast , using these same RNAi treatments , Pgst-4::GFP expression was most strongly induced upon disruption of complex I ( Figs 2 and S2 ) . This reporter is controlled by the oxidative stress sensitive SKN-1/NRF2 transcription factor . With few exceptions , the UPRmt-specific reporter Phsp-6::GFP was robustly induced when any subunit of the electron transport chain was disrupted ( Figs 2 and S3 ) . Removing paralogous subunits from our analysis did not change our overall conclusions ( S4 Fig ) . Finally , we also observed induction of Ptbb-6::GFP expression using four additional RNAi clones that disrupt mitochondrial function and can increase lifespan–hsp-6 , mrpl-47 , mrps-5 and F13G3 . 7 ( orthologous to human SLC25A44 ) ( S5 Fig ) . Previous work has suggested that mitochondrial dysfunction resulting from genetic mutations that disrupt subunits of the ETC may invoke retrograde responses that are fundamentally different from those activated following RNAi-knockdown of the same ETC subunits [53] . We crossed our three transcriptional reporters into isp-1 ( qm150 ) [54] and nuo-6 ( qm200 ) [53] worms to see if their mutations ( disrupting complexes III and I , respectively ) , would also lead to tbb-6 induction . In line with our RNAi data , Ptbb-6::GFP was induced in isp-1 ( qm150 ) worms , but markedly less so in nuo-6 ( qm200 ) animals . Interestingly , Pgst-4::GFP exhibited the reciprocal expression phenotype , while both isp-1 ( qm150 ) and nuo-6 ( qm200 ) worms strongly induced the Phsp-6::GFP reporter ( Fig 3A ) . ctb-1 ( qm189 ) is a mitochondrial DNA mutation which alters cytochrome b of complex III . This mutation attenuates the slow development of isp-1 ( qm150 ) worms but not their extended lifespan [54] . By itself , the ctb-1 ( qm189 ) mutation reduces complex III activity by up to 50% compared to wild-type animals [55] . Crossing our three transcriptional reporters into both ctb-1 ( qm189 ) and isp-1 ( qm150 ) ; ctb-1 ( qm189 ) genetic backgrounds , we observed that Ptbb-6::GFP and Phsp-6::GFP were each induced in isp-1 ( qm150 ) ; ctb-1 ( qm189 ) double mutants ( but less so than in isp-1 ( qm150 ) animals ) , while there was no expression at all of the Pgst-4::GFP reporter ( Fig 3A ) . ctb-1 ( qm189 ) mutants , instead , showed the reciprocal pattern of reporter protein induction ( Figs 3B and S6A ) . These findings are intriguing because within isp-1 ( qm150 ) ; ctb-1 ( qm189 ) mutants the ctb-1 ( qm189 ) mutation increases the activity of complex I specifically within supercomplex assemblies [55] . A reciprocal relationship between Ptbb-6::GFP and Pgst-4::GFP reporter expression was further underscored when ctb-1 ( qm189 ) worms were exposed to RNAi targeting different subunits of the ETC ( Figs 3B and S6B ) . Taken together , these data show that Ptbb-6::GFP is broadly induced by mitochondrial disruption and that its expression appears independent of UPRmt activation . Intriguingly , Ptbb-6::GFP induction exhibits a strong complementarity to SKN-1 activation ( Figs 2 and 3 ) . These findings suggest that tbb-6 could indeed reflect activation of a novel retrograde response . It has been shown repeatedly that DAF-16 is unnecessary for the life extension that follows mitochondrial ETC disruption in C . elegans [12 , 13 , 21 , 45 , 54 , 56 , 57] . Since the tbb-6 promoter contains a DAF-16 binding element , we nonetheless tested the role of this transcription factor in tbb-6 promoter activation . Knock-down of daf-16 by RNAi in isp-1 ( qm150 ) ; Ptbb-6::GFP worms failed to block reporter gene induction ( Table 1 ) . In worms , ATFS-1 is the master transcriptional regulator of the UPRmt , while SKN-1 is the key NRF-2 like transcription factor that responds to oxidative- and xenobiotic stresses [58] . The activation of both proteins has been reported in Mit mutants [20 , 43] . As expected from our analysis of the spg-7 microarray data , ATFS-1 is not required for Ptbb-6::GFP activation . In Fig 4A , we show that removal of atfs-1 by RNAi completely blocked both Phsp-6::GFP [43] and Pgst-4::GFP induction in isp-1 ( qm150 ) Mit mutants , while Ptbb-6::GFP was not reduced . The dependency of SKN-1 activation on ATFS-1 following mitochondrial dysfunction has not been previously reported . Intriguingly , our data show that not only does SKN-1 sit downstream of ATFS-1 , but it may also have a role in activation of downstream UPRmt components; treating isp-1 ( qm150 ) and nuo-6 ( qm200 ) worms with skn-1 RNAi completely blocked Pgst-4::GFP expression but also mildly , but significantly , attenuated Phsp-6::GFP induction ( Figs 4A and S7A and S7B ) . In contrast to the other two reporters , Ptbb-6::GFP induction by isp-1 ( qm150 ) was not only undiminished by atfs-1 RNAi , it was markedly further activated ( see Fig A in S7 Fig for quantitation ) . Surprisingly , in nuo-6 ( qm200 ) worms , which minimally induce Ptbb-6::GFP , we also observed hyperactivation of Ptbb-6::GFP following atfs-1 removal ( Fig B in S7 Fig , quantification in Fig C in S7 Fig ) . Furthermore , our data reveal that atfs-1 RNAi specifically induces Ptbb-6::GFP expression in the context of mitochondrial dysfunction , because the reporter remained unchanged when wild type worms were treated with the same atfs-1 RNAi ( Fig 4B ) . This difference in phenotype was unlikely to be due to differences in the efficacy of RNAi knockdown between the strains ( Fig 4C ) . Thus tbb-6 is not only daf-16 , atfs-1 and skn-1 independent , but it is activated complementary to UPRmt and oxidative stress signaling . A number of genes function epistatically to ATFS-1 in response to various forms of mitochondrial disruption and this has been linked to their role in synthesizing mevalonate ( hmgs-1 ) and ceramide ( ran-4 , sptl-1 and F40F12 . 7 ) [26] . Both hmgs-1 and sptl-1 have also been previously reported to be required for other cellular surveillance responses , including induction of Pgst-4::GFP upon treatment with azide [60] . To test whether any of these genes are also required for induction of tbb-6 , we assayed the effect of RNAi knockdown of each on our isp-1 ( qm150 ) transcriptional reporter lines ( Table 1 and S3 Table ) . As reported , RNAi against hmgs-1 , ran-4 , sptl-1 and F40F12 . 7 largely blocked Phsp-6::GFP induction by isp-1 ( qm150 ) . The effect of these same RNAi on Ptbb-6::GFP expression was strikingly different . Like loss of atfs-1 , neither hmgs-1 , ran-4 nor sptl-1 were required for Ptbb-6::GFP induction ( Fig 5A ) and knockdown of hmgs-1 or sptl-1 further upregulated Ptbb-6::GFP ( quantified in S8 Fig ) . Only F40F12 . 7 RNAi completely blocked Ptbb-6::GFP induction in isp-1 ( qm150 ) worms ( Figs 5A and S8 ) . The protein encoded by F40F12 . 7 is predicted to act as a transcriptional coactivator and bears significant orthology with CREB-binding proteins and thus from hereon we will refer to it as CBP-3 . Liu and colleagues reported that loss of Phsp-6::GFP expression in animals treated with cbp-3 ( F40F12 . 7 ) , ran-4 or sptl-1 RNAi could be rescued by exogenous application of C24 ceramide [26] . Using the cbp-3 RNAi , we replicated this effect on Phsp-6::GFP expression in isp-1 ( qm150 ) worms . In contrast , ceramide had no effect on the recovery of Ptbb-6::GFP expression ( Fig 5B ) . Thus , of all the genes reported to be epistatic to atfs-1 and the UPRmt , only cbp-3 is also required for tbb-6 activation , but in a manner independent of ceramide . Many pathogens secrete toxins that interfere with mitochondrial function [26] . Consequently , C . elegans respond to mitochondrial dysfunction as a pathogen attack and indeed the UPRmt activates genes involved in innate immunity [38 , 39] . Numerous other signaling pathways have reported roles in pathogen response . To test whether tbb-6 might be part of an immune response separate from the UPRmt , we assayed Ptbb-6::GFP expression in isp-1 ( qm150 ) worms upon RNAi knockdown of four genes reported to mount cellular defenses against infection: elt-2 [69] , fshr-1 [70] , hsf-1 [71] and zip-2 [72] . None of these treatments diminished Ptbb-6::GFP expression ( Table 1 and S3 Table ) , further suggesting that tbb-6 marks a novel branch of the cell surveillance system . Since several transcription factors have already been implicated in the life extension of isp-1 ( qm150 ) worms [21 , 33 , 67 , 81 , 82] , we tested whether any are required for tbb-6 expression . The genes we tested included: aha-1 , ceh-18 , ceh-23 , cep-1 , hif-1 , hlh-30 , jun-1 , nhr-27 , nhr-49 , and taf-4 . RNAi knock-down of each showed no attenuation of Ptbb-6::GFP expression in isp-1 ( qm150 ) worms ( Table 1 , see also S3 Table ) . Indeed , some of these RNAi treatments resulted in further upregulation of Ptbb-6::GFP; most notably , taf-4 RNAi dramatically upregulated intestinal Ptbb-6::GFP in isp-1 ( qm150 ) but not in otherwise wild-type worms . Durieux and colleagues demonstrated that mitochondrial disruption confined to neurons was sufficient to both increase lifespan and induce a UPRmt response cell non-autonomously in the intestine [45] . Recently , Burkewitz and colleagues showed that mitochondrial morphology in worms is modulated by neurotransmitters; specifically , when neurons perceive a low energy state via AMPK signaling , neuronal octopamine release is switched off , causing mitochondria in distal tissues to assume a more fused and elongated morphology [83] . Similar mitochondrial morphology has been previously reported in Mit mutants [12] . Taken together , these observations suggest that neuronal mitochondrial dysfunction may alter mitochondrial morphology and lifespan of the whole worm through neurotransmitter or neurohormonal signaling . Furthermore , it is possible that tbb-6 upregulation in the gut may not be the result of local mitochondrial disruption but of signaling from neurons with compromised mitochondria . We tested the involvement of octopamine and related neurotransmitters in tbb-6 regulation via complementary approaches . First , we simply increased neurotransmitter availability in isp-1 ( qm150 ) worms through exogenous application of octopamine , dopamine , and L-tyramine . Second , we removed these neurotransmitters/neurohormones by crossing our Ptbb-6::GFP reporter into cat-2 ( e1112 ) and tdc-1 ( ok914 ) mutant backgrounds—genes required for synthesis of dopamine and octopamine , respectively—and asked if there was constitutive reporter activation . In short , neither treatment affected Ptbb-6::GFP expression . Specifically , when isp-1 ( qm150 ) ; Ptbb-6::GFP reporter worms of various larval stages were transferred to plates supplemented with octopamine , dopamine , or L-tyramine , and GFP expression subsequently monitored over several days , under no condition was Ptbb-6::GFP expression altered relative to untreated control animals ( Fig 5C ) . Likewise , absence of tdc-1 or cat-2 did not constitutively induce Ptbb-6::GFP , nor did it enhance Ptbb-6::GFP expression in animals fed isp-1 RNAi relative to control-treated worms ( Fig 5D ) . Finally , unc-13 is required for neurotransmitter release [79] . When we treated isp-1 ( qm150 ) ; Ptbb-6::GFP worms with unc-13 RNAi , we again observed no diminution of Ptbb-6::GFP reporter expression ( Table 1 ) . We conclude that neither octopamine , dopamine nor L-tyramine modulates tbb-6 expression . Segref and colleagues [84] have presented evidence for a novel cell surveillance mechanism that is active in both human cells and worms following mitochondrial respiratory dysfunction . They showed that activity of the ubiquitin/proteosome system ( UPS ) is specifically repressed in the cytosol following insult to various mitochondrial respiratory chain and matrix bioenergetic targets , and that this response is strongly exacerbated by removal of SKN-1 . This reduction in cytosolic UPS activity was not due simply to exhaustion of ATP levels , instead UPS activity could be recovered by increasing the assembly and activity of the 26S proteosome , or by addition of N-acetyl cysteine . These findings indicate that the 26S proteosome becomes limiting under conditions of mitochondrial bioenergetic stress , and the authors speculated that the 26S proteosome was re-directed to the outer mitochondrial membrane ( OMM ) as part of the Mitochondrial-associated Degradation ( MAD ) pathway . The MAD pathway functions analogously to the endoplasmic reticulum-associated degradation ( ERAD ) pathway [85] to retrieve and degrade dysfunctional OMM proteins [86 , 87] . Both pathways utilize overlapping machinery , in particular the conserved AAA-ATPase Ccd48/VCP/p97 , as well as the ubiquitin-binding and Ccd48-binding heterodimeric cofactor UFD1/NPL4 , to dislodge ubiquitinated proteins from each respective organelle and chauffeur them to the 26S proteosome for degradation . Specificity is obtained through additional co-factors that recognize ubiquitinated proteins in each compartment and also bind to the core complex . Wu and colleagues [74] , recently confirmed using yeast that disruption to the mitochondrial respiratory chain , the matrix protein folding environment , or mitochondrial oxidative stress , are all sufficient to strongly activate the MAD pathway . We tested if MAD pathway activity plays a role in controlling the expression of TBB-6::GFP in isp-1 ( qm150 ) worms . ufd-1 encodes the sole UFD1 ortholog in C . elegans . Yeast two-hybrid analyses have shown this protein interacts with both CDC-48 . 1 and CDC-48 . 2 , as well as NPL-4 . 2 [88] . RNAi-mediated inhibition of all four genes reduced Ptbb-6::GFP expression ( Fig 5E and 5F and Table 1 ) . These findings imply that the signal for Ptbb-6::GFP reporter activation is downstream of MAD pathway activation and they raise the intriguing possibility that reduced UPS activity in the cytosol might result in stabilization and activation of a cytosolic signaling pathway that ultimately leads to upregulation of tbb-6 expression . Mitogen activated protein kinase ( MAPK ) cascades are conserved across eukaryotes as cytosolic signaling pathways that respond both to mitogens and to stressful stimuli . The p38 family of MAPKs respond to a variety of stressors and play an integral role in activating the immune response [89] . C . elegans is no exception; the p38 MAPK , PMK-1 , is crucial to immunity [90] and activates both SKN-1 ( Nrf2 ) [91] and DAF-16 ( FOXO ) [92] in response to oxidative stress . The other family of stress-activated protein kinases are the c-Jun N-terminal kinases ( JNKs ) , which perform a vast repertoire of functions [93] and may mediate the mammalian UPRmt [42] . One of the C . elegans JNKs , KGB-1 , is involved in cellular surveillance and pathogen aversion [38] , and acts in a competitive manner with the UPRmt [41] . We tested for a role of MAPK signaling in tbb-6 expression by assaying whether RNAi-mediated knockdown of each of the 14 known C . elegans MAPKs blocked reporter induction in isp-1 ( qm150 ) ; Ptbb-6::GFP worms ( Table 1 ) . Significantly , pmk-3 RNAi alone completely blocked Ptbb-6::GFP expression ( Fig 6A ) . Knockdown of two uncharacterized MAPKs had a weak inhibitory effect ( C05D10 . 2 , F09C12 . 2 ) , while jnk-1 and sma-5 further upregulated Ptbb-6::GFP expression . All other MAPKs were without effect . The requirement for pmk-3 in Ptbb-6::GFP activation was not unique to isp-1 ( qm150 ) mutants; it was also readily apparent in isp-1 ( qm150 ) ; ctb-1 ( qm189 ) worms ( Fig A in S9 Fig ) , and even in nuo-6 ( qm200 ) worms which only show weak Ptbb-6::GFP induction ( Fig B in S9 Fig ) . Moreover , using a reciprocal approach , pmk-3 ( ok169 ) mutants containing the Ptbb-6::GFP reporter failed to induce GFP when cultured on various RNAi targeting subunits of the mitochondrial ETC , including isp-1 ( Fig 6B and Fig C in S9 Fig ) . Notably , while inactivation of pmk-3 completely blocked Ptbb-6::GFP induction outside the pharynx , it had no effect on Phsp-6::GFP expression in either isp-1 ( qm150 ) ( Fig 6A ) or nuo-6 ( qm200 ) mutant animals ( Fig B in S9 Fig ) , and it further upregulated Pgst-4::GFP in isp-1 ( qm150 ) worms that previously only showed moderate induction of this reporter ( Fig 6A ) . We next used RNAi to map additional upstream elements of the pmk-3 MAPK signaling cascade and tested all 10 known MAPK kinases ( MAP2K ) , and 12 MAPK kinase kinases ( MAP3K ) ( Table 1 ) . We found the uncharacterized MAP2K sek-3 , and the well characterized MAP3K dlk-1 , both to be unequivocally required for Ptbb-6::GFP upregulation in isp-1 ( qm150 ) , isp-1 ( qm150 ) ; ctb-1 ( qm189 ) and nuo-6 ( qm200 ) animals ( Figs 6A , S9A and S9B ) . Knockdown of four other MAP2Ks had milder effects on Ptbb-6::GFP induction: knockdown of mkk-4 consistently increased reporter expression while the expression phenotype produced by mek-2 knockdown was highly variable , with some worms very dark and others very bright . Knockdown of either jkk-1 or sek-1 both reduced Ptbb-6::GFP expression , but not to the extent produced by sek-3 knockdown . ( Table 1 ) . Thus , we conclude that a novel MAPK cascade consisting of DLK-1 , SEK-3 and PMK-3 is required in worms for mitochondrial bioenergetic disruption to induce Ptbb-6::GFP . Both DLK-1 and PMK-3 play important roles in axon and synapse development [65 , 94 , 95] as well as efficient axon regeneration [96] . In these capacities , DLK-1 and PMK-3 function with the MAP2K , MKK-4 [65] . While our RNAi-based approach for identifying MAP2Ks essential for Ptbb-6::GFP expression in isp-1 ( qm150 ) mutants did not detect a role for mkk-4 , but instead sek-3 ( Table 1 ) , we independently verified this result using mkk-4 ( ok1545 ) and sek-3 ( ok1276 ) loss-of-function mutants . We crossed our Ptbb-6::GFP reporter into both mutant backgrounds and monitored GFP induction when worms were treated with isp-1 RNAi . Consistent with our earlier observation , only loss of sek-3 , and not mkk-4 , abrogated GFP expression . The mkk-4 ( ok1545 ) mutation , in fact , enhanced Ptbb-6::GFP reporter expression over and above that of control worms ( Fig 6C ) . It has been reported previously that a DLK-1::GFP translational fusion reporter , expressed under the control of the endogenous DLK-1 promoter , localizes specifically to neurons , accumulates in axonal boutons , and is tightly controlled by the E3 ubiquitin ligase , rpm-1 [62] . We have shown that expression of our Ptbb-6::GFP transcriptional reporter in isp-1 ( qm150 ) mutants is strongly activated in intestinal cells , and less so in neurons ( Fig 2 ) . This expression occurs in a dlk-1 , sek-3 and pmk-3 dependent manner ( Fig 6A–6C ) . To determine whether neuronal DLK-1 signaling functions non-cell autonomously to mediate the intestinal expression of Ptbb-6::GFP , we expressed a constitutively-active form of DLK-1 [62] exclusively in the neurons of Ptbb-6::GFP reporter worms . Under these conditions , Ptbb-6::GFP fluorescence was detected only in neuronal cells and not in the intestine ( Fig 6D ) , opening the intriguing possibility that DLK-1 is expressed in cells outside of neurons or is activated differently under conditions of mitochondrial dysfunction ( see Discussion ) . While Mit mutants typically exhibit a collection of co-segregating phenotypes—including delayed development , smaller size , and extended lifespan , these phenotypes can , in fact , be separated [20] . This was first demonstrated by the discovery of the isp-1 ( qm150 ) ; ctb-1 ( qm189 ) double mutant which , as previously mentioned , exhibits an attenuated delay in development but the same extended lifespan as isp-1 ( qm150 ) [54] . We proceeded to test for a role of PMK-3 in development and lifespan . RNAi knockdown of pmk-3 neither accelerated nor delayed the development of either isp-1 ( qm150 ) or nuo-6 ( qm200 ) Mit mutants . To test the effect of further upregulation of PMK-3 , we reasoned that knocking down a negative regulator of MAPKs should result in hyperactivation of PMK-3 . Dual-specificity phosphatases ( DUSPs ) act as negative regulators of MAPKs [97] . We used BLAST to identify potential DUSPs in C . elegans and assayed isp-1 ( qm150 ) development and Ptbb-6::GFP induction upon RNAi knockdown of each ( Table 1 ) . Most treatments had no effect on either phenotype . Of the two that did , the most dramatic was knockdown of VHP-1 , a DUSP known to act preferentially on the stress-activated protein kinases—the JNKs and p38s . Significantly , vhp-1 RNAi dramatically further upregulated Ptbb-6::GFP and arrested both isp-1 ( qm150 ) and nuo-6 ( qm200 ) worms at the L3 larval stage ( Figs 7 and S10A ) . Upregulation of Ptbb-6::GFP by vhp-1 RNAi was also observed in isp-1 ( qm150 ) ; ctb-1 ( qm189 ) mutants ( Fig A in S9 Fig ) . This response was specific to the context of mitochondrial disruption , as wild-type worms cultured on vhp-1 RNAi displayed only minimal hypodermal induction of Ptbb-6::GFP ( S11 Fig ) and , as has been previously reported , did not arrest but matured into smaller adults [98] . To confirm that the arrest of isp-1 ( qm150 ) worms upon vhp-1 knockdown was due to hyperactivation of PMK-3 , we assayed both isp-1 ( qm150 ) and wild-type worm development following simultaneous knockdown of vhp-1 in combination with either of the 14 annotated worm MAPKs ( Figs 7 and S11 ) . No MAPK RNAi had any effect on vhp-1 arrest with the notable exception of pmk-3 , which resulted in a near total rescue of the phenotype; that is , isp-1 ( qm150 ) worms grown on a 1:1 combination of vhp-1 and pmk-3 RNAi by-passed L3 larval arrest and matured into fertile adults ( Fig 7 ) . It is possible that use of a combination RNAi approach differentially reduced the efficacy of vhp-1 RNAi specifically in combination with pmk-3 RNAi; this too would permit worms to continue development . To exclude this possibility , we constructed a nuo-6 ( qm200 ) ; pmk-3 ( ok169 ) double mutant and then examined its ability to proceed through development when cultured on full strength vhp-1 RNAi . Like isp-1 ( qm150 ) mutants , nuo-6 ( qm200 ) single mutants normally arrest under these conditions . Genetic removal of pmk-3 , however , allowed these worms to by-pass larval arrest and produce offspring ( Fig A in S10 Fig ) . We next tested whether PMK-3 is required for Mit mutant longevity , again using independent approaches through use of both genetic and reciprocal RNAi-mediated mitochondrial disruption . We first treated wild-type and pmk-3 ( ok169 ) null worms with RNAi targeting nuo-2 ( complex I ) , isp-1 ( complex III ) , cco-1 ( complex IV ) , or atp-3 ( complex V ) . Life extension of wild type worms on these particular RNAi constructs has been well-characterized by us and others [13 , 20 , 99] . By itself , the pmk-3 ( ok169 ) null mutation had no effect on lifespan , yet on each of the four RNAi treatments , pmk-3 null worms had significantly attenuated life extension relative to wild-type animals ( Fig 8A–8D ) . The effect of the pmk-3 mutation on atp-3 RNAi was especially pronounced , with one replicate showing a complete absence of life extension ( Fig 8A and S4 Table ) . We next used a reciprocal approach to test the effect of pmk-3 RNAi on the lifespan of four genetically-defined Mit mutants: isp-1 ( qm150 ) , nuo-6 ( qm200 ) , clk-1 ( qm30 ) and tpk-1 ( qm162 ) . The latter two mutants indirectly affect the mitochondrial electron transport chain [100]: clk-1 encodes demethoxyubiquinone mono-oxygenase , an enzyme required for ubiquinone biosynthesis , while tpk-1 disrupts the TCA cycle by limiting thiamine , which is essential for α-ketoacid dehydrogenase activity . We found that pmk-3 knockdown significantly ( p-value < 0 . 001 ) attenuated the life extension of isp-1 ( qm150 ) and tpk-1 ( qm162 ) mutants , but had no effect on either clk-1 ( qm30 ) or nuo-6 ( qm200 ) animals ( Fig 8E–8H ) . Intriguingly , the selective requirement for pmk-3 in the life extension of only some Mit mutants correlated both with the specific respiratory complex that was targeted , and induction of Ptbb-6::GFP . For example , pmk-3 knockdown had moderate to no effect on the lifespan of animals with disrupted complex I activity , namely nuo-6 ( qm200 ) mutants and worms with RNAi-induced nuo-2 knockdown , which only moderately or weakly induce Ptbb-6::GFP , respectively , in line with the effect on lifespan following pmk-3 removal . In contrast , pmk-3 knockdown significantly attenuated life extension in the context of complex III , IV or V disruption , as in isp-1 ( qm150 ) mutants and worms with RNAi knockdown of isp-1 , cco-1 or atp-3 , all conditions which strongly induce Ptbb-6::GFP . Finally , we tested the effect of knocking out the upstream components of the MAPK cascade on lifespan following complex III disruption . Similar to pmk-3 ( ok169 ) , both dlk-1 ( ju476 ) and sek-3 ( ok1276 ) mutants have lifespans close to wild-type animals cultured on vector alone , but have dramatically attenuated life extension when exposed to isp-1 RNAi ( Fig 9 ) , emphasizing the specific requirement of this pathway for longevity in the face of mitochondrial disruption . Significantly , while several genes have been found to be required for Mit mutant longevity ( Table 1 ) , this is the first demonstration of a mitochondrial stress response required for life extension in relation to specific forms of mitochondrial dysfunction . We have used Ptbb-6::GFP throughout this study as a marker of activation of a potential mitochondrial retrograde response . Expression of this reporter positively correlates with life extension across multiple ETC disruptants ( compare S1 Fig and Fig 8 ) , and tbb-6 was one of the most highly upregulated of all genes following spg-7 RNAi treatment ( Fig 1A ) . We tested whether tbb-6 itself plays a role in life extension following ETC disruption . When isp-1 ( qm150 ) worms were cultured on tbb-6 RNAi , a mild ( ~7% ) but significant ( p < 0 . 01 ) reduction in lifespan was observed ( Fig 10A ) . We speculate that TBB-6 may have a function in regulating ADP entry into mitochondria ( Fig 10B , and Discussion ) . We identified two C/EBP-like motifs present in the promoter of tbb-6 ( Fig 1E ) . As a first step toward identifying transcription factors that function downstream of PMK-3 , we tested whether either of these motifs was required for Ptbb-6::GFP activation following mitochondrial ETC disruption . We used site-directed mutagenesis to selectively remove each site , as well as both sites together . These mutated promoters were then coupled to GFP , and finally co-injected into worms along with mCherry expressed under control of the wild-type tbb-6 promoter . As expected , removal of both promoter elements completely abolished the ability of isp-1 RNAi to induce GFP ( Fig 10C ) .
In this study we have identified a novel MAPK cascade which is required in worms for life extension following mitochondrial bioenergetic dysfunction . We do not know whether this signaling cascade simply acts during development and is essentially a permissive factor that allows mitochondrial retrograde response signaling to occur , whether the cascade functions as a bona fide retrograde response that controls longevity directly , or whether it forms part of a signaling pathway that is activated in distal cells as a consequence of mitochondrial dysfunction in unrelated tissues ( that is , cell non-autonomous signaling ) . At present we favor the notion that DLK-1 , SEK-3 and PMK-3 function as a true retrograde response based on the following supporting evidence: ( i ) tbb-6 is the most highly upregulated gene among the 148 atfs-1 independent gene set that we initially described . When we coupled GFP to a copy of the tbb-6 promoter and treated worms with various ETC insults , this reporter was most strongly expressed in the gut , the same tissue that the bona fide UPRmt reporter Phsp-6::GFP was activated , suggesting tbb-6 is activated in cells directly experiencing mitochondrial stress ( Fig 2 ) . ( ii ) The novel DLK-1 , SEK-3 and PMK-3 stress cascade , which we show is essential for tbb-6 induction , functions cell autonomously; that is , when we constitutively activated DLK-1 in neurons we observed expression of Ptbb-6::GFP only in neurons ( Fig 6D ) . ( iii ) The Mitochondrial-associated degradation ( MAD ) pathway functions within cells experiencing mitochondrial dysfunction to extract and remove damaged outer mitochondrial membrane proteins . Inhibiting core elements of this pathway should exacerbate mitochondrial dysfunction and enhance any stress signaling to distal tissues . Despite this , RNAi-mediated inhibition of MAD components in isp-1 ( qm150 ) mutants did not enhance Ptbb-6::GFP expression , rather , it suppressed it ( Table 1 ) . This finding argues that tbb-6 is induced cell autonomously following MAD pathway activation in cells directly experiencing mitochondrial damage . Promoter analysis of the 148 atfs-1 independent genes identified in this study revealed significant enrichment of two transcription factor binding sites in essentially non-overlapping gene sets ( Fig 1 ) . One group of 42 genes shared a DNA motif closely related to the DNA binding site of mammalian CCAAT/enhancer binding proteins ( C/EBP transcription factors ) . We showed that this motif is used in signaling mitochondrial ETC stress as its removal from the promoter of the Ptbb-6::GFP reporter blocked induction by isp-1 RNAi . A second group of 40 genes contained an EOR-1 binding element . Future studies will address the role of EOR-1 in Mit mutant longevity , which is a likely proposition given that EOR-1 is an essential component of a recently-described longevity response mediated by EGF in adult worms [102 , 103] . Suffice to say , we have found that RNAi to EOR-1 does not block Ptbb-6::GFP expression , raising the possibility that more than one signaling pathways may function in the longevity control of Mit mutants . In this regard , the genes under EOR-1 control that are essential for the longevity response mediated by EGF in adults worms [103] , are over-represented in our 148 gene set ( 10 out of a total of 503 up- or down-regulated genes , hypergeometric probability <0 . 003 ) . Recently , EOR-1 was also implicated in the genetic response to dietary restriction and the set of genes under its control were enriched in mitochondrial targets [104] . Moreover , while DAF-16 binding elements were not significantly enriched in our 148 gene set , we nonetheless found 27 genes that contained DAF-16 binding sites ( Fig 1D ) . Kumar and colleagues [51] recently described a signature set of 37 genes that directly bound DAF-16 in all DAF-16 chromatin-binding studies to date . It has been repeatedly shown that DAF-16 is not required for the Mit phenotype yet , surprisingly , four of these 37 core DAF-16 binding genes are present in our set of 148 atfs-1 independent genes . Based on our sample size , this is unlikely to have occurred by chance ( hypergeometric probability <0 . 0002 ) . We predict that EOR-1 and the transcription factor ( s ) that binds the CCAAT/enhancer binding protein site , will work in concert to turn on a novel kind of hybrid stress response in Mit mutants . If true , this idea would be in line with the remarkable study of Stroustrup and colleagues [105] that showed Mit mutants in particular ( and to a lesser extent , dietary restriction ) , did not simply temporally scale lifespan , as various other genetic and environmental interventions that also extend life did , but instead fundamentally changed the way worms age . In further support of such a possibility , a search for enriched functional GO terms among the 148 atfs-1 independent genes using DAVID [106] , revealed a significant ( q-value < 0 . 05 ) enrichment of genes encoding FBOX-containing proteins ( 8 genes ) , small heat shock proteins ( sHSPs , 6 genes ) , and gene clusters involved in aging ( 12 genes ) , ER-nuclear signaling and cytochrome P450 activity . FBOX proteins are components of SCF ubiquitin E3 ligase complexes that play important roles in protein turnover [107] , along with sHSPs . The FBOX cluster was enriched in genes containing the CCAAT motif , while the sHSPs and other clusters were enriched in genes containing EOR-1 motifs . Based on the well-established roles of other MAPKs , we speculate that PMK-3 controls the activity of one or more transcription factors . Again , we do not know if DLK-1 , SEK-3 and PMK-3 function prior to , or after , mitochondrial bioenergetic stress , but if it is after then we predict likely targets could be members of the CCAAT/enhancer binding proteins ( C/EBP transcription factors ) , since removal of either of the two C/EBP-like binding motifs in the promoter of tbb-6 blocked Ptbb-6::GFP reporter induction , which we also showed is dependent upon PMK-3 . In C . elegans , there are three transcription factors orthologous to mammalian C/EBPs , namely , CEBP-1 , CEBP-2 , and ZIP-4 . These belong to a broader category of transcription factors known as bZIPs for the basic leucine zipper domain which binds the DNA . Intriguingly , both ATFS-1 and SKN-1 are themselves bZIP transcription factors , suggesting possible mechanisms for the complementary nature with our novel retrograde pathway: ATFS-1 may bind and compete with C/EBP-like proteins for the same promoter elements , or they might share a common protein binding partner . We have already tested the bZIP jun-1 for its known requirement in Mit mutant longevity [33] and cebp-1 for its known role with pmk-3 in neuron morphology [108] . Since neither of these diminished Ptbb-6::GFP activation by isp-1 ( qm150 ) , our efforts will now be focused on the remaining bZIP transcription factors in C . elegans . In mammals , C/EBPδ is known to act in a calcium-activated , mitochondrial retrograde response [109] , raising the possibility that increases in cytoplasmic calcium following mitochondrial depolarization could also be involved in the novel MAPK pathway that we have identified in this study . Interestingly , C/EBP proteins are known to recruit CREB-binding protein ( CBP ) [110] . One possible function for CBP-3 , the CBP ortholog which we found to be essential for Ptbb-6::GFP induction in this study , might be that it is needed to directly interact with transcription factors that bind to C/EBP motifs . If CBP-3 functions downstream of PMK-3 , one prediction is its removal by RNAi should permit isp-1 animals cultured on vhp-1 RNAi to resume larval development , analogous to co-treatment with pmk-3 RNAi . We have found this not to be the case , although it did block Ptbb-6::GFP hyperactivation ( Fig B in S10 Fig ) . It is difficult to interpret the significance of this result , however , since cbp-3 RNAi itself causes isp-1 ( qm150 ) worms to arrest [26] and we found it to result in sterility and early mortality even in wild-type worms . Clearly , cbp-3 has essential roles , including in ceramide biosynthesis [26] , and whether it plays a specific or general role in signaling mitochondrial dysfunction shall require further investigation . The previously described roles for PMK-3 relate to a MAPK cascade required for both neuronal development [65] and axon regeneration [111] . Interestingly , while this MAPK cascade is also initiated by DLK-1 ( MAP3K ) , it utilizes the MAP2K MKK-4 , instead of SEK-3 which we found to be required for Ptbb-6::GFP induction . Whether these differences in MAP2K usage are mediated by different DLK-1 isoforms or reflect different tissues of activation remains a question for future study . Intriguingly , it was recently shown that sensory neurons of Mit mutants have reduced functionality relative to wild-type animals [112] , suggesting there could be competition for DLK-1 by the two MAP2Ks in the same tissue and that increased neuronal response time may be the payoff for long term survival under stress . In our studies , both genetic and RNAi-mediated removal of mkk-4 failed to reduce Ptbb-6::GFP expression . The same RNAi construct was employed previously and shown to block SKN-1 activation induced by oxidative stress [113] . These findings further highlight the complementarity between the PMK-3 and SKN-1 signaling pathways that we have discovered in this work . DLK-1 also been implicated in Wallerian degeneration in mammals and flies [114] , the active process by which severed axons self-destruct . This is especially interesting because DLK-1 is coupled to JNK activation in this pathway , via MKK4/7 and the NAD+ sensor and adaptor protein SARM1 [115] . Presumably other adaptor proteins could act to modulate DLK-1 target proteins in a different setting , and this may be what is behind the novel DLK-1 , SEK-3 , PMK-3 signaling pathway that we have identified in this study [116] . MAPK signaling is highly conserved across phyla , and p38 signaling has been implicated in numerous pathologies . However , most studies have looked at the role of the p38α isoform , to the extent that it is referred to simply as p38 in much of the literature [117] . However , the four mammalian p38 isoforms differ in expression across tissues as well as in their substrate specificity , and inhibition of different isoforms can produce opposite effects [118] , limiting the potential for broad spectrum p38 inhibitors in ameliorating disease . The complexity of p38 MAPK signaling is similar in worms: The three isoforms exhibit differential tissue specificity and methods of activation [119] . In worms , the p38 that behaves most like the well-studied mammalian p38α is PMK-1 , which , as stated previously , is activated by oxidative stress and plays an essential role in immunity . Further study of the other two p38 isoforms in C . elegans is likely to shed light on the roles of the less studied mammalian isoforms as well . Finally , while we used Ptbb-6::GFP as a marker of PMK-3 activity that somehow permitted a functional Mit mutant longevity response following complex III , IV and V disruption , we also showed that tbb-6 itself is required for life extension following mitochondrial disruption . TBB-6 is unusual among β-tubulins in that its C-terminus is notably truncated relative to other β-tubulins ( Fig 9B ) . Rostovtseva and colleagues [101] have reported that the C-termini of β-tubulins which are enriched in glutamate can plug the voltage-dependent anion channel ( VDAC ) and reduce ADP entry into mitochondria [101] . This finding raises the intriguing possibility that TBB-6 may function to enhance ADP entry into mitochondria under stressed conditions . The identification of the precise mechanism by which TBB-6 functions to extend life , along with the mode of action of DLK-1 , SEK-3 and PMK-3 in mitochondrial stress-induced longevity , stands to be an exciting area for future investigation .
Gene Expression Omnibus dataset GSE38196 , first described in [43] , was used to identify genes upregulated independently of atfs-1 following mitochondrial dysfunction ( spg-7 RNAi ) . Full details of our procedure to isolate atfs-1 independent genes from this dataset is provided in S1 Text . The MEME Suite of tools ( v4 . 10 . 1 ) [120] was used to identify enriched DNA elements ( ungapped ) among the promoter regions of the identified gene subset . We limited our search to 400 bp of the most proximal 5’ sequence of each gene . MAST [121] , was used to locate DAF-16 binding sites using a weighted matrix based on the consensus identified by Kumar and colleagues [51] . A complete list of C . elegans strains used in this study is provided in S6 Table . All strains were maintained at 20°C on standard NGM-agar plates [20] . Recombinant array construction , microinjection procedures and choice of strain background are detailed in S1 Text and S6 Table . Feeding RNAi and RNAi dilution studies were performed as previously described [20] . Details regarding either the source or construction of feeding RNAi constructs is provided in Supplemental Experimental Procedures ( S1 Text ) . Images of first day adult worms were captured using an Olympus DP71 CCD camera connected to an Olympus SZX16 fluorescence dissecting microscope . Where relevant , images were quantified using ImageJ software ( NIH ) . A one-way ANOVA , or Student’s t-test with correction applied for multiple testing was employed , as indicated in figure legends . qRT-PCR was used to measure the efficacy of atfs-1 RNAi knockdown in Fig 4C . Details of strain culturing , mRNA extraction , cDNA synthesis , primer design for qRT-PCR analysis , data normalization and statistical testing are provided in S1 Text . Lifespan studies were performed as described previously [20] . Use of FudR was avoided . The first day of adulthood was designated as day one . Data was analyzed using the log rank test and Cox’s proportional hazard model . A full description of all lifespan experiments is provided in S4 Table . Raw lifespan data is provided in S5 Table .
|
In humans , mitochondrial dysfunction contributes to numerous age-related diseases , and indeed even aging itself . Yet organisms also have an amazing capacity to compensate for mitochondrial impairment , paradoxically sometimes even living longer for it . This is exemplified in the roundworm Caenorhabditis elegans . In this study we examine how C . elegans with disrupted mitochondrial electron transport chains respond to such dysfunction and delineate a novel signaling cascade that is required for their life extension . Significantly , the components of this pathway are well-conserved in humans .
|
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2016
|
DLK-1, SEK-3 and PMK-3 Are Required for the Life Extension Induced by Mitochondrial Bioenergetic Disruption in C. elegans
|
Differentiation of one life-cycle stage to the next is critical for survival and transmission of apicomplexan parasites . A number of studies have shown that stage differentiation is a stochastic process and is associated with a point that commits the cell to a change over in the pattern of gene expression . Studies on differentiation to merozoite production ( merogony ) in T . annulata postulated that commitment involves a concentration threshold of DNA binding proteins and an auto-regulatory loop . In this study ApiAP2 DNA binding proteins that show changes in expression level during merogony of T . annulata have been identified . DNA motifs bound by orthologous domains in Plasmodium were found to be enriched in upstream regions of stage-regulated T . annulata genes and validated as targets for the T . annulata AP2 domains by electrophoretic mobility shift assay ( EMSA ) . Two findings were of particular note: the gene in T . annulata encoding the orthologue of the ApiAP2 domain in the AP2-G factor that commits Plasmodium to gametocyte production , has an expression profile indicating involvement in transmission of T . annulata to the tick vector; genes encoding related domains that bind , or are predicted to bind , sequence motifs of the type 5'- ( A ) CACAC ( A ) are implicated in differential regulation of gene expression , with one gene ( TA11145 ) likely to be preferentially up-regulated via auto-regulation as the cell progresses to merogony . We postulate that the Theileria factor possessing the AP2 domain orthologous to that of Plasmodium AP2-G may regulate gametocytogenesis in a similar manner to AP2-G . In addition , paralogous ApiAP2 factors that recognise 5'- ( A ) CACAC ( A ) type motifs could operate in a competitive manner to promote reversible progression towards the point that commits the cell to undergo merogony . Factors possessing AP2 domains that bind ( or are predicted to bind ) this motif are present in the vector-borne genera Theileria , Babesia and Plasmodium , and other Apicomplexa; leading to the proposal that the mechanisms that control stage differentiation will show a degree of conservation .
The process of differentiation from one stage to the next is critical for survival , propagation and transmission of parasites within the phylum Apicomplexa . Differentiation steps can be conserved across genera . For example , generation of merozoites from an intracellular schizont , and the formation of gametocytes via merozoites that are committed for the sexual phase of the life-cycle , are events common to different members of the phylum . Moreover , differentiation steps across the Apicomplexa show a number of similarities indicating that the mechanisms involved are likely to have a degree of conservation . Apicomplexan stage differentiation events can occur in a stochastic manner ( i . e . are asynchronous , with the probability of a differentiation step occurring influenced by culture/growth conditions and cell lineage ) and are induced by multiple distinct stimuli [1 , 2] . In addition , work on Plasmodium and Theileria differentiation systems has provided evidence for an intermediate position , with progression towards or reversal from a point that commits the cell to generate the next life-cycle stage [3 , 4] . Drugs or conditions that alter the probability of a differentiation event occurring are likely to operate by altering the ability of a cell to reach a commitment threshold [5] , and it can be hypothesised that the probability of switching from repeated rounds of asexual proliferation to the next phase of the life-cycle is governed by stage-determining commitment circuits that compete against each other , as identified in higher eukaryotic cell systems [6] . Candidates for Apicomplexan factors that control the switch in gene expression following a commitment to differentiate include members of the ApiAP2 gene family . ApiAP2 proteins were initially identified in the Apicomplexan genera Cryptosporidium , Plasmodium and Theileria [7] , and have been subsequently identified in all Apicomplexan genomes analysed to date . All ApiAP2s possess an Apetala ( AP2 ) domain of approximately 60 amino acids , originally identified as the DNA binding domain of transcription factors ( TFs ) that control developmental and stress-regulated gene expression in plants [8] . Work initially performed in Plasmodium has shown that ApiAP2s can bind to specific nucleotide motifs in the upstream regions of stage-regulated genes and are required to control their differential expression [9 , 10] . In addition , recent studies on Toxoplasma gondii have demonstrated the involvement of ApiAP2 factors in the regulation of the transition from the tachyzoite stage to the bradyzoite encysted stage [11 , 12] and they have also been shown to operate in commitment to gametocytogenesis in Plasmodium [13 , 14] . Identification of AP2 binding sites coupled with enrichment analysis of binding sites in stage-regulated genes has allowed prediction of networks that operate to control expression of ApiAP2 genes and their associated targets during the Intra-erythrocytic Developmental Cycle ( IDC ) of P . falciparum [9] . Moreover , the prediction that ApiAP2s regulate their own expression indicates they could operate in the stochastic model of stage differentiation previously proposed for Theileria [4] . Theileria is a tick-borne Apicomplexan parasite responsible for an economically important disease syndrome that threatens hundreds of millions of ruminants over large areas of the Old World . Currently , drugs are used as part of disease control strategies but emerging resistance against the most commonly used drug , buparvaquone , indicates that novel therapeutics will be required [15] . Based on the observation that the infection and treatment method of vaccination against T . parva operates by delaying differentiation to the intracellular macroschizont stage , targeting stage differentiation can be considered as a control strategy [5] . Previous work on T . annulata established an in vitro system of stage differentiation from the proliferating multi-nucleated macroschizont to production of the uni-nucleated merozoite ( merogony ) . Analysis of this system established that differentiation is stochastic and that the probability of merogony occurring could be increased by inhibition of DNA synthesis , while inhibition of protein synthesis reduced the potential to reach commitment [16] . From these results it was postulated that during differentiation , an increase in the level of key DNA binding factors relative to their nucleic acid template occurs until a quantitative threshold , involving auto-regulation of gene expression , is reached that commits the cell to merozoite production [2] . Support for this model was provided by evidence for an increase in levels of factors in nuclear extracts of differentiating cultures that bind to a motif identified in the promoter region of the major merozoite antigen gene , Tams1 [17] . In this study we have utilised microarray analysis to profile gene expression in T . annulata from the sporozoite stage through merogony to the piroplasm stage . Stage-regulated genes encoding AP2 DNA binding domains with orthologues in ApiAP2 factors of , primarily , related vector-borne genera ( Babesia and Plasmodium ) were then identified . Following this , cohorts of co-expressed genes were analysed to determine enrichment of nucleotide motifs bound by AP2 domains . The results identify ApiAP2 DNA binding domains ( ApiAP2s ) that are conserved across Apicomplexan genera and can be incorporated into a stochastic model of competitive factor binding that promotes reversible progression to the commitment point of stage differentiation .
Three cell lines were used in this study: the T . annulata infected D7 and D7B12 cloned cell lines provide a comparative in vitro system for merogony , as while D7 undergoes efficient differentiation to the merozoite when placed at 41°C , the D7B12 line ( re-cloned from D7 ) is severely limited in its ability to differentiate under identical culture conditions [4]; BL20 is an uninfected bovine lymphosarcoma cell line [18] . Cell lines were cultured , induced to differentiate to the merozoite stage by increasing the temperature from 37°C to 41°C , harvested by centrifugation and total RNA isolated at Day 0 , 4 , 7 and 9 using Tri-reagent , as previously described [4 , 19] . RNA was also isolated using Tri-reagent from sporozoite-infected Hyalomma ticks and purified piroplasms , as described [20] . A whole-genome tiling microarray approach was used to investigate T . annulata gene expression during stage-differentiation . The most recent version of the T . annulata ( Ankara C9 ) reference genome assembly and annotation [21] , which was released in 2009 and is available at GeneDB ( http://www . genedb . org/Homepage/Tannulata ) , was utilised to design a custom parasite microarray . The microarray consisted of abutting 45-mer oligonucleotide probes representing both DNA strands of each of the four nuclear chromosomes and the mitochondrial genome . The BLAST-like alignment tool ( BLAT ) [22] was used to match probe sequences to annotated spliced gene sequences . The sequence of each probe on the array was mapped to coding sequences utilising a flagging system similar to the web-based application , ProbeLynx [23] . A flag value of 1 represents a perfect , full-length alignment between a probe and gene , while a flag value of 5 represents poor alignment . For each individual probe , if a clear best match within the coding sequence was identified , that coding sequence ( i . e . gene ) was designated as the target of that probe and any poorer scoring BLAT-aligned sequences were designated as cross-hybridisation candidates . Only gene-specific probes were used in the present analysis , with flag thresholds based on previous experimental sensitivity and specificity studies of oligonucleotide arrays [24] . The array was designed for use on a 1 , 024 x 768 resolution chip and comprises 392 , 778 probes in total , 95% of which are targeted to the T . annulata genome . The remaining probes comprise bovine gene-targeted probes or control probes , including a set of over 15 , 000 oligonucleotides with random sequence and of mixed GC content . cDNA synthesis , labelling of cDNA and hybridisation to the microarray were performed by Roche NimbleGen . Parasite gene expression levels were determined using log2-transformed median intensity values and the data normalised using the Robust Multi-array Average [25] . The data discussed in this publication has been deposited in NCBI's Gene Expression Omnibus [26] and is accessible through GEO Series accession number GSE71307 ( http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE71307 ) . To determine whether a gene is expressed in a particular sample , the probe values for each gene were compared with background values from non-specific , random probes with equivalent GC content . Background hybridisation never exceeded a log2 intensity value of 10 . Genes with a value of 10 or more were scored as expressed in a given parasite stage . DNASTAR ArrayStar3 software was used to perform hierarchical clustering on log2-transformed gene expression levels . The results were visualised as a heat-map with the data clustered by sample ( horizontally ) and gene ( vertically ) . Rank Product ( RP ) analysis is a non-parametric statistical test that may be used to identify differentially expressed genes between conditions using limited sets of replicates [27] . RP analysis was conducted on the following pair-wise comparisons: sporozoite to macroschizont , macroschizont ( Day 0 ) to merozoite ( Day 9 ) , merozoite to piroplasm , and piroplasm to sporozoite . The obtained RP score was used to rank all the T . annulata genes in the dataset according to statistical confidence levels . Differentially expressed genes were assigned based on a false discovery rate ( FDR ) < 0 . 05 [28] and a fold change ≥ 2 ( absolute ) . The same pipeline was used to generate a list of differentially expressed parasite genes between the D7 and D7B12 cell lines cultured at 37°C . Expression values for all identified T . annulata AP2 domain genes were then extracted from both datasets . Profiles of gene expression values ( log2 ) across stages and during the differentiation time course were generated using DNASTAR ArrayStar3 software . Two-step quantitative Reverse Transcription PCR ( qRT-PCR ) incorporating SYBR Green qRT-PCR methodology was utilised . cDNA synthesis was carried out in a total volume of 20μl using oligo ( dT ) primers and the method provided with the AffinityScript Multi-temperature cDNA Synthesis Kit ( 200436 , Agilent ) . qRT-PCR reactions were performed using 500 ng cDNA template in a final volume of 25μl according to Brilliant SYBR Green QPCR Master Mix protocol ( http://www . chem-agilent . com/ ) for real-time fluorescence detection of PCR product . To normalise qRT-PCR data , the genes encoding the heat shock 70 kDa protein ( TA11610 ) and a heat shock 90 kDa protein ( TA10720 ) were used based on constitutive expression from both microarray , semi-quantitative RT-PCR data and previous analysis by northern blotting [29] . Primers for both control and test genes were as follows: TA13515 F , 5'-CGGGGAAGAGTGTAAAAATGAGTG and R , 5'-GGAGGTGATGGTCGTGATGG; TA11145 F , 5'-CGTTGAGGGATCTTGTGAC and R , 5'-CTTCACACTCCTGTTCCCA; TA15705 F , 5'-TGGAGATGGAGATAGCATGC and R , 5'-CTGGACCTCCAGATGCAC; TA11610 F , 5'-ACGCAAATGGAATCCTCAAC and R , 5'-TATTCGTCGTGCTCTGCTAA; TA10720 F , 5'-ACAATAGCAGAATCAGGAACAG and R , 5'-TATTGGGAAACGGATGAATTCTG; TA07100 F , 5'-GCCACCCAGTAGACCTTCA and R , 5'-GTCGAGCATCAGCAAGTGT . Thermal cycling parameters used were: 1 cycle enzyme activation and initial denaturation , 10 min at 95°C; 40 cycles of PCR amplification ( denaturation , 30 sec at 95°C; annealing , 60 sec at 60°C; elongation , 60 sec at 72°C ) ; 1 cycle dissociation curve ( 60 s at 95°C , 30 s at 55°C and 30 s at 95°C ) . All qRT-PCR data was captured and analysed by MxPro v4 . 10 software with the Mx3005P Real-Time PCR System ( Agilent Technologies ) . Melting curve analysis was carried out to verify product specificity and determine the presence of primer-dimers and other non-target products . Three technical replicates of each experimental time-point and no template controls were included in the PCR reactions for all sample points and primer sets . Expression values of target genes were normalised against Hsp70 ( TA11610 ) and an Hsp90 gene ( TA10720 ) and fold-change calculated relative to a calibrator point/condition , Day 0 –macroschizont stage , using a -2-ΔΔCt equation [30] . Data was plotted as normalised mean values of log2 fold change ± the standard error of the mean ( SEM ) . Statistical analysis was performed using a one-tailed Student’s t-test . Genes in T . annulata encoding orthologues of AP2 domains in related Apicomplexan species and genera were identified using BLASTP ( www . ncbi . nlm . nih . gov/BLAST ) . ApiAP2 domain boundaries were defined as in Balaji et al . [7] and confirmed using the Pfam database ( pfam . sanger . ac . uk ) . A cut-off of > 50% sequence identity was employed . Sequence alignments were generated using ClustalW ( www . ebi . ac . uk/Tools/msa/clustalw2/ ) . Alignment of all TaApiAP2s using T-coffee software ( www . ebi . ac . uk/Tools/msa/tcoffee/ ) was generated to identify general conservation of the domain in T . annulata . To establish whether upstream intergenic regions ( IGR ) of differentially expressed sets of genes were enriched for selected Plasmodium falciparum ApiAP2 domain target motifs , the motif pattern search ( www . piroplasmadb . org/piro ) function in PiroplasmaDB ( version 1 and 2 ) was utilised . PiroplasmaDB was released in 2011 and is based on the pre-existing 2009 GeneDB assembly/annotation for T . annulata . A size restriction of 400 bp upstream of the predicted translation ATG start codon was employed , based on an average IGR length of 400 bp ( with a large variance ) . This size was selected as IGRs are larger in a significant number of genes when flanked by the 5' boundary of predicted protein coding regions [31] . A search was also performed 100 bp upstream of the ATG , based on 5' un-translated region ( UTR ) size of 114 bp for the Tams1 gene ( TA17050 ) of T . annulata [17] . Motif enrichment analysis was performed on the complete dataset of T . annulata predicted genes together with subsets of genes differentially expressed across stages and time points of the macroschizont ( Day 0 ) to merozoite ( Day 9 ) time course . The obtained data was exported to an Excel file and motif distribution data was tabulated . For each subset of genes , a motif enrichment P value was calculated by comparing the proportion of genes within the subset that possess the motif with the proportion of genes in a background list that possess the motif using a Fisher’s Exact Test . Pearson Correlation ( positive or negative ) of the expression pattern of genes which possess an ApiAP2 domain binding motif in their upstream region with the profile displayed by the gene encoding the ApiAP2 domain predicted to bind the motif was performed using Excel . The Multiple Expectation Maximization for Elicitation of Motifs ( MEME; version 4 . 6 . 1 ) software [32] was used to screen for putative motifs in IGRs of stage-regulated genes . Input sequences were prepared by extracting sequences upstream of predicted protein coding sequences ( CDS ) from the T . annulata GeneDB database . Searches were performed using a motif length of between 5 and 8 bp , 8 and 12 bp and 8 and 20 bp , and ZOOPS ( Zero Or One Occurrence Per Sequence ) . The statistical significance of the motif was computed as an E-value based on an estimation of the expected number of motifs with the given log likelihood ratio and with the same width and site count that could be expected in a similarly sized set of random sequences . To investigate the potential of ApiAP2 domains to bind to motifs in upstream of genes encoding the domain ( auto-regulation ) , sequence alignments of upstream regions of selected T . annulata ApiAP2 genes to their T . parva orthologues was performed using ClustalW and visualised using Jalview . Alignments representing TA13515 , TA11145 , TA12015 and TA16485 were then searched for the core DNA binding motifs ( 5'-GTGTAC , 5'-CACACA/ACACAC , G-box/C-box or 5'-TCTACA ) identified for the respective orthologous domain in P . falciparum [9] or C . parvum [33] . Based on previous phylogenetic analysis [7 , 9] , four TaApiAP2 domains ( encoded by TA11145 , TA0710 , TA19920 and TA02615 ) that could be predicted to bind to ( A ) CACAC ( A ) type motifs were selected and aligned to T . parva , T . orientalis and P . falciparum domain orthologues . Domain boundaries were defined using the Pfam database and a Maximum Likelihood tree constructed using RAxML [34] . Reciprocal BLAST analysis of each domain was also performed , as described above . Expression of selected AP2 domains as glutathione S-transferase ( GST ) fusion proteins was performed using the pGEX system . The regions selected for amplification included 10–20 nucleotides on either side of the sequence encoding each domain . Primers designed to create N-terminal GST-fusion constructs contained 5' and 3' extensions to create EcoRI and XhoI restriction sites respectively , for cloning . Primer sequences for each domain were: TA13515 F , 5'-CAGGAATTCGTACAGGGTATGGTTGGATATTCT and R , 5'-GCACTCGAGGCTGAATACGCTCTACTGGAGTGC; TA11145 F , 5'-CAGGAATTCCAAAGAACGAGCGCAAAGATTC and R , 5'-GTTCTCGAGTGTTAAATCTTATCATTATGTCTAAGTGC; TA16485 F , 5'-CAGGAATTCAGAGCAAATTACTACCGAAGATTAG and R , 5'-GCACTCGAGCGGTCAGATTTGTTGGTTGGTTTCTG; TA12015 F , 5'-CAGGAATTCTACCGAAGGAAGCCAATCTCATC and R , 5'-GCACTCGAGAGATGTGGTTCCTCTCGGT . PCR amplification was performed using the proof-reading Polymerase ( Pfu ) and T . annulata DNA ( strain Ankara , clone C9 ) isolated from purified piroplasms . Amplicons were purified using a QiaQuick PCR Purification Kit ( Qiagen , 28104 ) , ligated into pGEX5x-2 vector DNA digested with EcoRI and Xhol , and competent XL-1 Blue cells ( Stratagene , 200249 ) transformed using standard methodology . Recombinant clones were validated by DNA sequencing ( Eurofins MWG Operon , Germany ) . Validated pGEX constructs were then re-transfected into BL21 Codon Plus ( DE3 ) -RIL ( Stratagene ) competent cells and fusion proteins induced by IPTG ( final concentration of 0 . 2 mM ) . Purification of fusion protein was performed using glutathione sepharose affinity beads ( Sigma-Aldrich , GE17-0756-01 ) according to the manufacturer’s methodology . Protein concentrations were generated using the Better Bradford Assay Reagent , ( Pierce Biotechnology , 23238 ) . If required , GST-fusion proteins were concentrated using Amicon Ultra-15 Centrifugal Filter Units , with an Ultracel-3 membrane ( Millipore , UFC900308 ) . Eluted proteins were stored at -80°C in 25–50μl aliquots , at a concentration of 1 mg/ml . Parasite-enriched Nuclear Extracts ( PNE ) were generated based on the method of Shiels et al . [17] but using the NE-PER Nuclear and Cytoplasmic Extraction Reagent kit , following the supplier’s instructions ( Thermo Scientific ) . A differential centrifugation step ( x 500 g to pellet host nuclei , followed by re-centrifugation of the supernatant at x 16 , 000 g ) to enrich for parasite nuclei was incorporated after the initial cell lysis . To investigate protein-nucleic acid interaction , the Thermo Scientific LightShift Chemiluminescent Electrophoretic Mobility Shift Assay was employed . Single-stranded HPLC purified 5'-biotinylated oligonucleotides containing an ApiAP2 target or mutated motif ( synthesised by Eurofins Genomics , Germany ) were re-constituted in water to 100 pmol/μl . Labelled and complementary unlabelled oligonucleotides were annealed using a thermocycler in 20 mM Tris-HCl , pH 7 . 6; 50 mM NaCl , 10 mM NaCl at 50 μmol . Annealed oligonucleotides were diluted to 1 pmol/μl for non-labelled and 20 fmol/μl for biotinylated probes . For EMSA using fusion protein , in addition to the standard components used in the kit protocol , each reaction included 1 μl 50% glycerol , 1 μl 1% NP40 , 2 μl fusion protein ( 0 . 7–1 mg/μl ) , 1 μl biotinylated oligo ( 20 fmol/μl ) . For reactions with PNE , additional components for optimisation were: 1 μl 50% glycerol , 1 μl 100 mM MgCl2 , 1 μl 1% NP40 , 1 μl EDTA , 5 μl of PNE , 2μl biotinylated oligo ( 40 fmol/μl ) . A 4% polyacrylamide gel was run at 100V , at 4°C and free and bound probes transferred to Biodyne Precut Nylon Membrane ( Thermo Scientific , 77015 ) and then cross-linked at 120 mJ/cm2 using UV-light . Detection was performed using the Chemiluminescent Nucleic Acid Detection Module ( Thermo Scientific , 89880 ) . For competition experiments , cold double-stranded oligos were added to the reaction mix at 4–10 pmol and incubated on ice for 20 minutes before addition of the labeled probe . Oligonucleotides used as EMSA probes are listed ( S1 Table ) .
A microarray approach was utilised to profile gene expression of T . annulata . The array was screened with cDNA representing an in vitro stage-differentiation time-course from the macroschizont ( Day 0 ) to cultures undergoing significant production of merozoites ( Day 7 and Day 9 ) , with an intermediate time-point ( Day 4 ) included . The array was also hybridised with RNA representing sporozoites ( the stage transmitted by ticks ) that infect leukocytes and intra-erythrocytic piroplasms ( the stage transmitted to ticks ) . Hierarchical clustering was performed on log2-transformed gene expression data representing each T . annulata coding sequence ( CDS ) . The data was clustered by sample and CDS , and is presented as a heat-map ( Fig 1 ) . This analysis showed that the Day 4 dataset clusters with Day 0 , while the Day 7 data shows greatest similarity to the profile obtained for Day 9 . However , with detailed inspection it can be seen that the day 4 time-point represents a transitional state , with genes that are down-regulated or up-regulated in the later time-points showing intermediate expression at Day 4: a few genes showed peak expression at this time-point . Significantly , clear differences in the expression level of genes were observed across different life-cycle stages and points of the in vitro differentiation time course e . g . Day 4 to Day 7 . In addition , an appreciable number of genes , clustered at the top of the heat-map , show a pattern indicating constitutive expression . It can be concluded that a major change over in the control of gene expression occurs between Day 4 and Day 7 of differentiation to the merozoite in vitro . Further analysis was performed using Rank Products ( RP ) to identify differentially expressed genes between different stages and time-points [27] . The numbers of genes identified for each pair-wise comparison are shown in Table 1 . Datasets of the top 100 differentially expressed genes were generated , with further analysis focusing on the macroschizont ( macro ) to merozoite ( mero ) differentiation step . The up-regulated macro-mero list ( S2 Table ) is mostly comprised of genes encoding hypothetical proteins but also includes genes encoding rhoptry-associated proteins ( TA05870 , TA05760 and TA05705 ) , as predicted from previous studies [4 , 16] . Genes encoding a Map2 kinase ( TA21080 ) , cysteine protease ( TA04105 , TA15660 ) , myosin ( TA20555 ) , a phosphate transporter ( TA13530 ) , a ubiquitin-conjugating enzyme E2 ( TA10690 ) , a cyclin-dependent serine/threonine kinase—related protein ( TA08470 ) and an aspartyl ( acid ) protease ( TA17685 ) were also identified as up-regulated during merogony . Three genes ( TA13515 , TA16485 and TA12015 ) encoding proteins annotated as possessing AP2 DNA binding motifs were identified as significantly ( FDR<0 . 05 ) up-regulated during differentiation to the merozoite . The list of down-regulated macro-mero genes ( S3 Table ) includes members of two gene families encoding proteins predicted to be secreted into the host cell compartment implicated in establishment of the macroschizont infected cell [35–37] . Thus , members of the SVSP family ( e . g . TA11410 , TA09805 , TA09790 and TA09420 ) and TashAT family genes ( TA2009 , TA03125 , TA03120 , TA03145 and TA03165 ) were identified as highly down-regulated during differentiation to the merozoite . In addition , the gene encoding the macroschizont specific T cell antigen , Ta9 ( TA15705 ) [38] , was present in the list , as were members of the SfiI-subtelomeric fragment-related protein family and a gene ( TA10735 ) encoding a putative GATA type transcription factor . Down-regulated expression ( relative to the Day 0 ( macroschizont ) time-point ) was validated for Ta9 by qRT-PCR with reduced expression most marked between the Day 4 and Day 9 time-point ( S1 Fig ) . K means clustering was performed on log2-transformed gene expression data for all 22 ApiAP2 encoding genes in T . annulata . Two groups displayed expression profiles that could be associated with differentiation to the merozoite stage , i . e . showing generally progressive up-regulation and down-regulation respectively . The first of group of genes ( Fig 2A ) included the three AP2 domain genes identified by RP analysis as up-regulated during merogony . These genes were elevated , 7 . 36 fold ( TA13515 ) , 6 . 84 fold ( TA16485 ) and 4 . 01 fold ( TA12015 ) between Day 0 ( macroschizont ) and Day 9 ( merozoite ) , with an additional ApiAP2 gene ( TA11145 ) displaying a 3 . 08 fold increase between these time-points ( FDR = 0 . 07 ) . Notable differences in profile between these genes were , a higher relative level of expression in the macroschizont stage ( Day 0 ) for TA11145 , a delayed elevation in expression for TA16485 ( between Day 4 and Day 7 ) and a sustained , significant elevation in expression of TA13515 through the Day 9 time-point ( merozoite ) to the piroplasm stage . Based on their temporal expression patterns we have denoted the factors encoded by these genes as TaAP2 . me1 ( TA11145 ) , TaAP2 . me2 ( TA12015 ) , TaAP2 . me3 ( TA16485 ) ; the fourth factor ( encoded by TA13515 ) we have denoted as TaAP2 . g based on elevated expression of the encoding gene in the piroplasm stage and high identity of the AP2 domain to the domain of the Plasmodium AP2-G factor ( see below ) . Genes in the second group possess a profile indicating reduced expression from the macroschizont stage ( Day 0 ) through the merozoite stage ( Day 9 ) to the piroplasm stage ( Fig 2B ) . The change in expression level was not as marked but like the up-regulated group of ApiAP2 genes , differences between their profiles were manifest . For example , for TA13395 a decrease in expression was observed between Day 0 and Day 4 , whereas for TA07550 expression increased from sporozoite though to the intermediate Day 4 time-point , followed by a reduction in levels at Day 7 and Day 9 ( merozoite ) . TA07100 did not display a reduction until between Day 9 ( merozoite ) and the piroplasm stage . Of the four macroschizont to merozoite up-regulated AP2 genes , two , TA11145 ( TaAP2 . me1 ) and TA13515 ( TaAP2 . g ) , were selected for validation by qRT-PCR . The qRT-PCR results broadly supported the array data with significant up-regulation ( p<0 . 05 ) relative to the Day 0 time-point at the Day 7 and Day 9 time-points and the piroplasm stage ( Fig 2C and 2D ) . TA11145 ( TaAP2 . me1 ) displayed elevation in expression level during merogony while for TA13515 ( TaAP2 . g ) the most significant increase in expression level was detected later , between the merozoite ( Day 9 ) and piroplasm stage . In general , higher differences in expression levels between time-points were indicated by RT-PCR compared to microarray data , and a significant difference was detected in expression of TA11145 between Day 4 and Day 7 that was not apparent with the array data . These differences are likely to arise from the increased quantitative sensitivity of qRT-PCR over the microarray platform , and inherent variability between differentiation time courses used to generate RNA for the two procedures [2] . Previous work has identified a considerable number of distinct consensus DNA motifs bound by different apicomplexan AP2 domains [9 , 39] . Moreover , it is known that ApiAP2 domain sequences can show conservation across Apicomplexan genera and that orthologous domains can bind closely related DNA motifs [9 , 12 , 39 , 40] , although this is not always the case and domains that bind similar DNA motifs can show sequence diversity [39] . We , therefore , investigated conservation of the AP2 domain of the four T . annulata AP2 encoding genes that are up-regulated during merogony . Across Theileria species there is a high level of conservation in the primary structure of the AP2 domains within each of the four groups of orthologous domains with maintenance of the three anti-parallel beta strands and the alpha helix secondary structure ( Fig 3 ) . However , a degree of divergence between the four paralogous domains is evident ( S2 Fig ) . In addition , for Ta . AP2 . me1 ( TA11145 ) , TaAP2 . me3 ( TA16485 ) and TaAP2 . g ( TA13515 ) , orthologous AP2 domains with strong identity were identified in Babesia and Plasmodium ( Fig 3 ) species supporting previous studies [7] , while for TaAP2 . me2 ( TA12015 ) AP2 domain orthologues were identified in Babesia and Cryptosporidium but not Plasmodium . Thus , it can be predicted that while orthologous groups of these AP2 domains may recognise similar DNA motifs , the four paralogous domains encoded by genes that are up-regulated during merogony in T . annulata are likely to recognise distinct motifs . Based on identity across orthologues , data on the primary DNA motifs bound by Plasmodium AP2 domains [9] was utilised to investigate enrichment of these motifs in the T . annulata genome . Plasmodium orthologues ( PF3D7_1222600 ( previously , PFL1085w ) , PBANKA_143750 ) of TA13515 ( TaAP2 . g ) encode the AP2-G factor critical for commitment to gametocytogenesis [13 , 14] . Plasmodium AP2-G binds the motif GxGTACxC , with GTAC identified as core nucleotides [9]: this motif was found to be significantly enriched ( P < 0 . 0001 ) within a 400 bp region upstream of the ATG start codon on the positive strand of T . annulata genes up-regulated from merozoite to piroplasm ( 29% vs 4% of all other genes ) . No statistical enrichment of this motif was found in any other subset , implying this motif may be important for the up-regulation in expression of these genes from merozoite to piroplasm . The motif was also significantly enriched within 100–85 bp upstream of the ATG in the up-regulated merozoite to piroplasm gene set ( 25% vs 1 . 38% ) . This indicates the motif is either located within the 5' UTR or is just proximal to the transcription start site of genes with a UTR of less than 100 bp . A motif associated with genes enriched near telomeres and those encoding signal peptide proteins has been reported just proximal to the transcription start site in T . parva [31] . To validate that expression of genes enriched for the motif correlates with the expression profile of the gene encoding the AP2 domain predicted to bind the motif , the Pearson correlation coefficient value was computed . A perfect positive correlation ( R = 1 ) was identified for TA13515 ( TaAP2 . g ) and the average profile of merozoite to piroplasm up-regulated genes possessing the motif ( S3 Fig ) . Enrichment for the core TCTAC ( T ) A motif bound by the Plasmodium orthologue ( PF3D7_1239200 ( PFL1900w ) ) of the AP2 domain of TaAP2 . me3 ( encoded by TA16485 ) indicated a possible association within 400 bp upstream of the ATG start codon of genes down-regulated from macroschizont to merozoite; 11 . 5% vs 6 . 7% of all other genes ( P = 0 . 057 ) . There was no significant enrichment indicated within the first 100 bp upstream of the translation start in the down-regulated gene set . A significant negative correlation ( R = -0 . 92 ) was computed for the average profile of down-regulated macroschizont to merozoite genes enriched for the TCTAC motif and the expression profile of the TA16485 ( TaAP2 . me3 ) gene ( S3 Fig ) . No direct orthologue of the AP2 domain encoded by TA12015 ( TaAP2 . me2 ) can be identified in Plasmodium , but the domain orthologue in C . parvum ( cgd8_810 Cpar ) binds a G-box like motif [7 , 33] . A similar G-box like motif , A ( G ) NGGGGC ( A ) showed significant enrichment in the 400 bp upstream of the translation start site on the positive strand in IGRs of genes categorised as up-regulated from merozoite to piroplasm stage , with 45% vs 9% ( P < 0 . 0001 ) of IGRs containing this motif . In addition , a significant depletion ( 1 . 7% vs 9 . 4% ) was computed on the positive strand of upstream IGRs of genes down-regulated from macroschizont to merozoite ( P < 0 . 005 ) . The motif was not detected on the positive strand within 100 bp of the ATG start codon for either the down or up-regulated gene set . The orthologue of the AP2 domain of TaAP2 . me1 ( TA11145 ) in P . falciparum is encoded by PF3D7_0802100 ( previously denoted , MAL8P1 . 153 ) , which has been demonstrated to recognise a core motif rich in AC di-nucleotides [A/G]CACA[C/T][A/T] [9] . Although this motif type was commonly found within non-coding ( intergenic ) regions of the T . annulata genome , enrichment analysis found that there is a depletion of the motif in the 400 bp upstream region of IGRs of genes down-regulated from macroschizont to the merozoite stage , 13% vs 25% ( P < 0 . 005 ) . There was also evidence of enrichment 400 bp upstream of the ATG start codon in IGRs of genes up-regulated in merozoite , 31% vs 24% ( P = 0 . 06 ) and piroplasm stages , 46% vs 24% ( P < 0 . 05 ) . No significant enrichment or depletion was obtained on analysis of the region 100 bp upstream of the translation initiation ATG codon . A positive Pearson Correlation ( R = 0 . 93 ) was observed for expression of the TaAP2-me1 gene ( TA11145 ) and the average profile of macro-mero most up-regulated gene set enriched for ACACAC in their upstream IGRs ( S3 Fig ) . Analysis of 5' IGRs of genes upregulated from macroschizont to merozoite was also performed by MEME . The top motif identified was a 14 bp motif ( AG ) AATGTGTAA ( AG ) ( GT ) ( TAG ) ( AT ) ( E-value = 1 . 3 x 10−9 ) with a conserved core motif of AATGTGTAA . This motif shows similarity with the reverse complement of the ACACAC motif , and identity with the motif previously identified by MEME in 5' IGRs of T . parva and T . annulata [31] . The motif has identity with a P . falciparum conserved TGTGT ( G/A ) ( A/T ) motif , and like its Plasmodium counterpart has a widespread distribution in non-coding regions of the genome . A role as a binding site for regulatory nuclear proteins other than transcription factors was proposed [31] . To test whether T . annulata AP2 domains could bind the nucleotide motifs predicted for their Plasmodium orthologues , GST fusion proteins of the AP2 domain were generated for TaAP2 . g ( TA13515D ) , TaAP2 . me1 ( TA11145D ) , TaAP2 . me2 ( TA12015D ) and TaAP2 . me3 ( TA16485D ) . The fusion proteins were then used in electrophoretic mobility shift assays against biotinylated double-stranded motif probes . As shown ( Fig 4 ) , recombinant AP2 DNA-binding domain of TaAP2 . g ( TA13515D ) strongly bound to the probe representing the consensus core motif , GTGTACAC ( GxGTACxC ) bound by orthologous AP2-G domains of Plasmodium [13 , 14] . The shift complex was competed with unlabelled probe , and no shifts were obtained using a mutated core binding site ( G/C replaced with A in motif ) probe ( Fig 4 , lane 6 ) . Similar results were obtained for the recombinant AP2 domain of TaAP2 . me1 ( TA16485D ) , as a shift was obtained using a probe containing the core motif TCTACA identified for the orthologous P . falciparum domain [9] . The EMSA generated a clear band shift ( S4 Fig ) with binding specificity indicated by a reduction in the detected shift on addition of cold probe . EMSA with the AP2 domain encoded by TA12015 , predicted to bind a G box like motif , did not generate a detectable shift ( S5 Fig ) . The P . falciparum orthologue of the AP2 domain of TaAP2 . me1 ( TA11145 ) has been shown to bind the motif ACACAC [9] . To test that TaAP2 . me1 could also bind this motif , EMSA was performed using the AP2 domain fusion protein and a probe containing a double ACACAC type motif located in the intergenic region upstream of the encoding gene ( TA11145 ) . The TaAP2 . me1 AP2 domain fusion protein ( TA11145D ) generated a strong shift with this probe ( Fig 5A ) . To confirm that binding required the ACACAC motifs , these motifs were mutated . A shift was not observed with the mutated probe . Thus , the TaAP2 . me1 AP2 DBD has the capacity to bind specifically to a double motif in the upstream region of its own encoding gene ( TA11145 ) . To determine if native nuclear factors could bind to the probe representing the double ACACAC type motif , , EMSA was performed using extracts from parasite-enriched nuclear fractions derived from macroschizont-infected cells ( Day 0 ) and infected cells undergoing differentiation to the merozoite ( Day 9 ) . Fig 5B shows that EMSA performed with extracts derived from parasite-enriched nuclear extracts generated a total of 4 shift complexes A-D . Shifts A , C and D were also detected with nuclear extracts derived from uninfected host BL20 cells ( S6 Fig ) and were concluded to be derived from host contamination in PNE . Shift B , however , was only obtained using extracts derived from cultures undergoing merozoite production and was not detected in host-derived nuclear extracts . To confirm that the up-regulated B shift required the ( A ) CACAC ( A ) motifs , EMSA was performed using the mutant probe and Day 9 PNE ( Fig 5C ) : the up-regulated shift B was not obtained with this probe . The results indicate that a nuclear factor ( s ) associated with cultures undergoing differentiation to the merozoite can specifically bind to ( A ) CACAC ( A ) motifs upstream of the TA11145 gene that is up-regulated during merogony . Demonstration that the ACACAC motif in the IGR upstream of the TA11145 gene is recognised by the AP2 binding domain encoded by the gene indicates that its expression may be auto-regulated . This is of interest as the stochastic model of merogony in T . annulata predicted that the commitment to differentiate is reached via the capacity of regulators of differential gene expression to auto-regulate . It was investigated , therefore , whether there is a greater occurrence of the motif in the IGR upstream of the domain encoding TA11145 gene relative to the other 21 AP2 encoding genes . Seven ACACAC type motifs were found in the IGR upstream of TA11145 ( including the double motif separated by five nucleotides ) and six were conserved upstream of the T . parva orthologue ( S7 Fig ) . In contrast , a maximum of three motifs were detected in the IGR upstream of two other AP2 domain genes ( TA05055 and TA08375 ) and an average of 0 . 95 motifs per AP2 gene IGR was obtained . Both ApiAP2 genes with three motifs were classed in the same expression profile as TA11145 ( up from macroschizont ( Day 0 ) to merozoite ( Day 9 ) ) . Auto-regulation has also been predicted for genes encoding the Plasmodium AP2G factor ( PF3D7_1222600 , PBANKA_143750 ) [13 , 14] . Screening for the core motif ( GTAC ) bound by the TaAP2 . g domain detected it’s presence at three positions in the upstream intergenic region of the encoding gene ( TA13515 ) , including a double motif separated by 6 bp ( core A to core G ) . These three motifs were conserved in the upstream region of the T . parva gene encoding the orthologous domain ( TP02_0497 ) [41] . In P . falciparum , multiple AP2 domains have been shown to bind to motifs rich in CA di-nucleotides , two variants being ACACAC and CACACA [9] . We term these ( A ) CACAC ( A ) type motifs , where an A is present either at the 5' , 3' or both ends of the motif . Theileria orthologues of Plasmodium AP2 domains that bind ( A ) CACAC ( A ) can be identified in the phylogenetic analysis performed by Balaji et al . , [7] . Thus domains encoded by TA11145 , TA07100 and TA02615 were found to be orthologues of the domains encoded by PF3D7_0802100 ( MAL8P1 . 153 ) , PF3D7_0420300 ( PFD0985w . D1 ) and PF3D7_1305200 ( PFL13_0026 ) , while the domain encoded by TA19920 was placed in a position in the tree intermediate between TA07100 and TA11145 but without a clear domain orthologue indicated in Plasmodium . To analyse this group of domains in more detail , a maximum likelihood tree was constructed with the four P . falciparum domains and the putative orthologous domains from T . annulata , T . parva and T . orientalis ( Fig 6 ) . The tree generated essentially supports the phylogeny of Balaji et al . [7] with three clear orthologous groups , containing TA07100 , TA11145 or TA02615 domains , indicated . The domains encoded by TA19920 and a fourth Plasmodium ( A ) CACAC ( A ) binding domain , encoded by PF3D7_1456000 ( PF14_0533 ) , did not fit into an orthologous group . This was supported by reciprocal BLAST analysis with no clear orthologue identified for the TA19920 AP2 domain in Plasmodium or the PF3D7_1456000 domain in Theileria . An alignment of AP2 domains in the orthologous groups represented by TA11145 and TA07100 domains , respectively ( Figs 3B and S8 ) indicates that these domains are highly likely to bind related ( A ) CACAC ( A ) motifs in Babesia , Theileria and Plasmodium . Thus , there are , at least , two phylogenetically related AP2 domains conserved in vector-borne Apicomplexa that bind ( A ) CACAC ( A ) type motifs , with orthologous members of a third ApiAP2 domain ( represented by TA02615 ) possibly binding to this , or a closely related , motif . Cell line D7B12 is severely attenuated in its ability to undergo differentiation to the merozoite stage [4] . However , merogony is not totally abrogated and it can be postulated that the attenuated phenotype may be linked to a quantitative alteration in expression of key regulatory molecules . To test whether this might be associated with AP2 domain encoding genes , microarray data was generated for the D7B12 line ( Day 0 ) and compared to data for the differentiation competent D7 line ( Day 0 ) . Three AP2 domain genes were predicted to show significantly higher expression in D7 relative to D7B12 ( S4 Table ) . One of these genes ( TA11145 ) encodes the domain shown to bind ( A ) CACAC ( A ) and is up-regulated during merogony; while the gene ( TA07100 ) encoding the other AP2 domain in T . annulata that is strongly predicted to bind ( A ) CACAC ( A ) did not show a significant difference . To validate the difference in expression qRT-PCR was performed for the TA11145 , and TA01700 genes using RNA derived from D7 and D7B12 cells cultured at 37°C ( Day 0 ) and during progression to merogony at 41°C ( Day 4 and Day 7 ) . The results indicate that RNA levels of TA11145 were significantly higher ( 5 . 4 fold , log2 ) in D7 vs D7B12 cells at the Day 0 time-point and that this difference is exacerbated following culture at 41°C: 8 . 7 fold ( log2 ) at Day 4 and 11 fold ( log2 ) at Day 7 ( Fig 7 ) . In contrast , qRT-PCR performed for TA07100 showed a relative difference of 0 . 2 fold , 0 . 6 fold and 2 . 2 fold ( log2 ) higher in D7 cells at Day 0 , Day 4 and Day 7 , respectively . This validates that the TaAP2 . me1 gene ( TA11145 ) is expressed at a higher level in a cell line competent for differentiation and that up-regulation is independent of a heat shock response . Thus , the expression level of TA11145 relative to TA07100 is clearly altered in favour of TA11145 in the D7 cell line and this bias is increased during progression towards merogony ( Day 4 and Day 7 ) .
Within the life cycles of Apicomplexan parasites , transition from stages that undergo multiple rounds of asexual replication to stages that promote life-cycle progression and parasite transmission are regulated by critical cellular differentiation events . Evidence generated across apicomplexan genera indicates that these transition points operate on a stochastic basis and that stage-differentiation steps can be programmed to occur in a time-dependent manner [1 , 2 , 13 , 14 , 42] . Together , these findings indicate that a basic mechanism may have been conserved . From previous investigation of merogony in T . annulata in vitro it was proposed that the stochastic differentiation mechanism involves the build up of DNA binding protein ( s ) relative to their DNA template to generate a commitment point involving an auto-regulatory loop [2] . The aim of the present study was to identify potential DNA binding factors and nucleotide motifs that could play a role in this differentiation model . To search for motifs and DNA binding factors associated with stage differentiation , expression data representing the sporozoite stage , a macroschizont ( Day 0 ) to merozoite stage ( Day 9 ) differentiation time-course , and piroplasm stage was generated . Comparative analysis produced two sizeable lists of genes up- or down-regulated during differentiation to the merozoite ( 152 and 115 at FDR < 0 . 05 , respectively ) . Both lists contained genes predicted from previous studies . For example , genes encoding rhoptry proteins , Tams1 [4] and cysteine proteinases [43] were defined as up-regulated whereas members of the TashAT and SVSP encoding gene families , implicated in establishment of the proliferating macroschizont-infected cell [36 , 37] , were identified as down-regulated during differentiation to the merozoite . Several general observations could be made from the temporal expression patterns . Firstly , genes expressed at a high level in one stage were often indicated as expressed at a low level in the preceding or subsequent stage . This supports previous studies reporting that merozoite genes are expressed at the macroschizont stage [4] , and that a low level of non-stringently regulated mRNA expression operates in T . parva [44] . Thus , repression of gene expression in a stage-specific manner at the mRNA level is unlikely to be absolute in Theileria . The data also indicated differences in the pattern of expression for distinct genes across the differentiation ( merogony ) time-course , implying regulation of gene expression via multiple factors that operate in a temporal order . Similar results have been reported for related Apicomplexa [9 , 33 , 45] and cascades of transcriptional regulators proposed for these systems are likely to operate for T . annulata . Recent studies on DNA binding proteins have provided strong evidence of their involvement in the regulation of Apicomplexan stage-differentiation events . The T . annulata microarray data was therefore screened for predicted DNA binding proteins that showed differences in expression level between macroschizont and merozoite stage . Genes encoding four putative AP2 domain DNA binding proteins were found to show elevation of mRNA levels between macroschizont and merozoite . Comparison of the four up-regulated T . annulata AP2 domain amino acid sequences with the orthologous domains in Plasmodium or Cryptosporidium ( TA12015 ) showed that there was greater identity for orthologues across genera than between these four paralogous domains within T . annulata . This allowed prediction that each of the four domains bound different target motifs . In addition , consensus motifs bound by the AP2 domains in Plasmodium or Cryptosporidium were predicted for the orthologous domain in T . annulata . EMSA performed with fusion protein domains encoded by TA11145 , TA13515 and TA16485 demonstrated that this prediction was valid . Based on previous studies [9 , 39 , 40] this does not mean that the AP2 factors from different genera operate to control gene expression in the same life-cycle stage or regulate the same genes , because orthologous domains across genera have been shown to target different gene sets . Our results for domains encoded by TA13515 and TA11145 , however , do show parallels with data obtained for their orthologues in Plasmodium . The direct orthologue of the AP2 domain encoded by TA13515 in Plasmodium is the domain of the AP2-G factor that is essential for commitment to gametocyte production [13 , 14] . The AP2 domain of AP2-G shows a high degree of conservation with the domain encoded by TA13515 ( 92% identity ) and binds the motif GxGTACxC . As expected , the Theileria AP2 . g domain specifically bound the GxGTACxC motif . This motif is enriched in the upstream region of genes up-regulated from merozoite to piroplasm stage in T . annulata , with no enrichment in any other subset of stage-regulated genes . Furthermore , in a similar manner to Plasmodium AP2-G , a GTAC core motif is present in three copies ( one double motif ) in the upstream region of the TaAP2 . g gene ( TA13515 ) and T . parva orthologue ( TP02_0497 ) , indicating putative auto-regulation of gene expression . A role in regulating gene expression as the parasite differentiates into the piroplasm stage is highly likely . The piroplasm stage has been postulated to be equivalent to gametocytes and it is known that a sexual phase occurs within the tick [46] . Thus , as recently suggested , orthologues of AP2-G could contribute to sexual stage switching across vector borne Apicomplexa and provide a target for transmission blocking strategies [47] . AP2-G expression and gametocytogenesis has been associated with a stress response in Plasmodium [48] . The expression profile obtained for T . annulata , however , indicates that up-regulation is primarily liked to developmental events . This conclusion is supported by demonstration of significantly elevated expression in the D7 cell line vs D7B12 cell line when both lines were cultured for 7 days at 41°C ( S9 Fig ) . The AP2 domain encoded by TA11145 ( TaAP2 . me1 ) is the orthologue of the PF3D7_0802100 ( MAL8P1 . 153 ) domain in P . falciparum and TGME49_071030 in T . gondii [39] , and domain orthologues with high identity are present in Babesia ( Fig 3 ) . Our findings allow postulation that TA11145 is a key regulator of stochastic commitment to merozoite production in T . annulata . The gene is expressed at the RNA level at the preceding stage of the life-cycle and shows significant elevation during the differentiation time-course . Moreover , expression is significantly reduced in a cell line that has lost the ability to differentiate to the merozoite . Motifs recognised by the AP2 domain encoded by TA11145 are the ( A ) CACAC ( A ) type motifs detected by its orthologous domain in Plasmodium [9] . This motif is common in the non-coding region of the genome , but showed evidence of being enriched in the upstream IGRs of genes up-regulated during merogony , while depleted in upstream regions of down-regulated genes . The motif type is also over-represented in non-coding regions of the Plasmodium and Toxoplasma genomes [31 , 49 , 50] , but was observed to be associated with a large group of genes expressed during the middle to later stages of the Intra-erythrocytic Developmental Cycle ( IDC ) of P . falciparum [50] . In addition , this motif type is recognised by two AP2 factors critical for regulation of tachyzoite to bradyzoite conversion in T . gondii [11 , 12] , one of which possess a AP2 domain that is the orthologue of the domain encoded by TA07100 in T . annulata and PF3D7_0420300 ( PFD0985w . D1 ) in P . falciparum [39] . The motif may have a general role in genome organisation associated with differential gene expression , possibly acting as a site for accessory factors that modulate chromatin structure . In Plasmodium , four AP2 domains have been shown to recognise ( A ) CACAC ( A ) type motifs , three of which are closely related to each other [9] . Expression of the genes encoding these three domains occurs at different points of the IDC , and two ( PF3D7_0802100 and PF3D7145600 ) are predicted to auto-regulate [9] . Based on phylogenetic analysis , a similar situation exits for Theileria , with at least two domains ( encoded by TA11145 and TA07100 ) displaying a level of similarity to their Plasmodium orthologues that indicates binding to the same or similar motif . Auto-regulation is predicted for TA07100 and TA11145 ( and potentially TA02615 ) . However , since there is only one ( A ) CACAC ( A ) motif upstream of TA07100 relative to seven in TA11145 there is a much stronger prediction of auto-regulation for TA11145 . Auto-regulation of this gene was supported by demonstration that the encoded AP2 domain binds specifically to a probe representing a double ( A ) CACAC ( A ) type motif present in the upstream IGR . Multiple auto-regulatory sites were also reported for P . falciparum AP2-G [13] . One possibility is that these sites generate and/or detect a gradient of DNA binding factor that influences when a commitment event will occur . It is known that double motifs allow higher interaction affinities and slower dissociation of DNA binding proteins [51] . Multiple domains that recognise ( A ) CACAC ( A ) type motifs allow speculation that different AP2 factors could bind to the same promoter and potentially compete for binding if co-expressed . Indeed , the TA11145 AP2 domain can bind to the motif predicted for the TA07100 domain ( S10 Fig ) . In addition , the data of Campbell et al . [9] indicate that individual domains bind to variants but show greater affinity to their preferred motif . The expression patterns of genes in T . annulata encoding AP2 domains that are predicted to bind ( A ) CACAC ( A ) motifs overlap during differentiation to the merozoite ( see Fig 2 ) , with TA11145 showing significant up-regulation relative to TA07100 . These findings support the previous stochastic model of differentiation for T . annulata [2] , where a functional overlap between regulatory factors of different life-cycle stages was predicted . In an update of this model , we propose that low-level expression of merozoite genes involves regulation by macroschizont ( AP2 ) factors that bind to ( A ) CACAC ( A ) motifs in the upstream region of TA11145 . Thus expression of TA11145 at the macroschizont stage may be influenced by a stoichiometric relationship between competing factors that bind to ( A ) CACAC ( A ) motifs and promote low ( repressed ) or elevated ( activated ) gene expression . Following placement at 41°C , an elevation in protein levels relative to DNA template occurs and generates a skewed increase in TA11145 expression over time via an auto-regulatory loop . This loop would be promoted by preferential binding of the AP2 domain encoded by TA11145 to multiple ( A ) CACAC ( A ) sites in its own upstream region . One prediction of the model is that the relative level of competing factors would differ between parasite lines attenuated or competent for a stage-differentiation event . This appears to be the case for genes encoding AP2 domains that bind the ( A ) CACAC ( A ) motif , with a significant increase in the level of TA11145 expression , relative to TA07100 , in an infected cell line that is able to undergo differentiation to the merozoite compared to a line which has lost this ability ( Fig 7 ) . Further experimental data are required to validate , refute or modify the above model . Nevertheless , it could account for a number of findings common across stage-differentiation events of different Apicomplexan genera . These include , low level expression of genes in the life-cycle prior to the stage where they are expressed at a high level [4 , 12–14]; a gene expression profile that is intermediate between two stages that may be reversed or progressed , depending on culture conditions [3 , 4 , 16 , 52 , 53]; evidence for multiple DNA-binding proteins that bind to related motifs and show a temporal order of expression linked to stage-differentiation [9 , 11 , 12]; and parasite lines with marked , quantitative differences in their potential to undergo a stage-differentiation event [4 , 11 , 13 , 42 , 54] . It should be noted though that even if a common mechanism operates across genera , it is unlikely that the target genes regulated during stage differentiation steps will be necessarily conserved . Recognition of closely related binding motifs by multiple DNA binding proteins shared across genera operates to regulate developmental gene expression in higher eukaryotes , with auto-regulation and competition for binding sites evident [55] . For example , the double GATA motif upstream of the GATA-1 gene that is required for developmental expression is first bound by GATA-2 to initiate expression of GATA-1 , followed by preferential GATA-1 binding and auto-regulation via the same motif [51 , 56 , 57] . Thus , we propose that competition between related DNA binding proteins can determine whether an Apicomplexan parasite stays at the same life-cycle stage or progresses to the next , and may be a remnant of an ancestral stochastic mechanism of cellular differentiation retained in both lower and higher eukaryotes .
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The ability of vector-borne Apicomplexan parasites ( Babesia , Plasmodium and Theileria ) to change from one life-cycle stage to the next is critical for establishment of infection and transmission to new hosts . Stage differentiation steps of both Plasmodium and Theileria are known to involve stochastic transition through an intermediate form to a point that commits the cell to generate the next stage in the life-cycle . In this study we have identified genes encoding ApiAP2 DNA binding proteins in Theileria annulata that are differentially expressed during differentiation from the macroschizont stage , through merozoite production ( merogony ) to the piroplasm stage . The results provide evidence that the ApiAp2 factor in Theileria that possesses the orthologue of the Plasmodium AP2-G domain may also operate to regulate gametocytogenesis , and that progression to merogony is promoted by the ability of a merozoite DNA binding protein to preferentially up-regulate its own production . In addition , identification of multiple ApiAP2 DNA binding domains that bind related motifs within and across vector-borne Apicomplexan genera lead to the proposal that the mechanisms that promote the transition from asexual to sexual replication will show a degree of conservation .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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ApiAP2 Factors as Candidate Regulators of Stochastic Commitment to Merozoite Production in Theileria annulata
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We investigated genomic diversity of a yeast species that is both an opportunistic pathogen and an important industrial yeast . Under the name Candida krusei , it is responsible for about 2% of yeast infections caused by Candida species in humans . Bloodstream infections with C . krusei are problematic because most isolates are fluconazole-resistant . Under the names Pichia kudriavzevii , Issatchenkia orientalis and Candida glycerinogenes , the same yeast , including genetically modified strains , is used for industrial-scale production of glycerol and succinate . It is also used to make some fermented foods . Here , we sequenced the type strains of C . krusei ( CBS573T ) and P . kudriavzevii ( CBS5147T ) , as well as 30 other clinical and environmental isolates . Our results show conclusively that they are the same species , with collinear genomes 99 . 6% identical in DNA sequence . Phylogenetic analysis of SNPs does not segregate clinical and environmental isolates into separate clades , suggesting that C . krusei infections are frequently acquired from the environment . Reduced resistance of strains to fluconazole correlates with the presence of one gene instead of two at the ABC11-ABC1 tandem locus . Most isolates are diploid , but one-quarter are triploid . Loss of heterozygosity is common , including at the mating-type locus . Our PacBio/Illumina assembly of the 10 . 8 Mb CBS573T genome is resolved into 5 complete chromosomes , and was annotated using RNAseq support . Each of the 5 centromeres is a 35 kb gene desert containing a large inverted repeat . This species is a member of the genus Pichia and family Pichiaceae ( the methylotrophic yeasts clade ) , and so is only distantly related to other pathogenic Candida species .
Pathogenic Candida species are ascomycete yeasts that cause over 46 , 000 invasive infections annually in the US alone , with a 30% mortality rate [1] . C . albicans is the most common and the most extensively studied , but non-albicans candidiasis infections are becoming increasingly common . The top five pathogenic Candida species in order of prevalence in invasive candidiasis worldwide are C . albicans ( 52% of infections ) , C . glabrata ( 21% ) , C . tropicalis ( 14% ) , C . parapsilosis ( 9% ) and C . krusei ( 2% ) ( calculated from data in [2] ) . Among these , C . krusei is the least-well studied . Although uncommon in the normal human flora , C . krusei is sometimes carried intestinally by healthy individuals and in one remote Amerindian community it was found to be present in over 30% of the population , much higher than C . albicans , and was probably acquired from food or the environment [3] . As well as being associated with humans , C . krusei has been detected in feral pigeons and other wild animals [3 , 4] . In 1980 , Kurtzman and colleagues proposed that C . krusei is the asexual form ( anamorph ) of a species whose sexual form ( teleomorph ) is Pichia kudriavzevii , which would make the two names synonymous . This proposal was initially made on the basis of DNA reassociation and mating tests [5] , and later confirmed when the sequences of the D1/D2 regions of the 26S ribosomal DNA of the type strains of C . krusei and P . kudriavzevii were discovered to be identical [6] . When P . kudriavzevii was first formally described in 1960 [7] , it was reported to be able to sporulate , but cultures of the type strain were later described as being unable to conjugate or sporulate [8 , 9] . A third name , Issatchenkia orientalis , is obsolete [6] but continues to be used in the literature by some laboratories [10 , 11] . Strain CBS5147 was deposited as the type strain of I . orientalis [7] , but this species was later renamed P . kudriavzevii [6]; C . krusei has a different type strain , CBS573 . P . kudriavzevii isolates are widely distributed in nature . They are often encountered in spontaneous fermentations and the species is used to produce several traditional fermented foods [9 , 12] . Crucially , this yeast is not regarded as a pathogen . It has been given ‘generally recognized as safe’ status by the US Food and Drug Administration [13] because it has been used for centuries to make food products such as fermented cassava and cacao in Africa , fermented milk in Tibet and Sudan , and maize beverages in Colombia [13] . It is used in starter cultures for sourdough breads [14] , and in starters ( daqu ) for Chinese vinegar production from wheat [15] . It also has potential as a probiotic [16] . P . kudriavzevii is exceptionally stress-tolerant and has a growing role in biotechnology , for production of bioethanol [17 , 18] and succinic acid ( a high-value platform chemical ) [10] . It is also used for the industrial production of glycerol , under the name Candida glycerinogenes ( [19]; see Discussion ) . Publications related to industrial applications generally use the species names P . kudriavzevii , I . orientalis or C . glycerinogenes in preference to C . krusei , possibly because of the negative safety connotations of using a pathogen in a biotechnological or food context . To date , relatively little genetic or genomic investigation has been carried out on isolates of C . krusei and P . kudriavzevii . Genome sequences have been published for four P . kudriavzevii strains ( [10 , 20–22] ) and one C . krusei clinical isolate [23] , but none of these provides a chromosome-level assembly or transcriptome-based annotation . Estimates of the number of genes range from 4949 to 7107 [10 , 23] , and only Cuomo et al . [23] discussed the genome organization and content . Moreover , the type strain of C . krusei has not been sequenced , and the only available sequence for the type strain of P . kudriavzevii is highly fragmented ( Y . Takada et al . , NCBI accession number BBOI01000000 ) . Although an extensive study of genetic diversity in clinical isolates was conducted using multilocus sequence typing ( MLST ) [24] , there has never been an analysis that compares both clinical ( ‘C . krusei’ ) and environmental ( ‘P . kudriavzevii’ ) isolates . As a result we do not know whether the clinical and environmental isolates are genetically distinct . It is important to understand the relatedness of these two types of isolate , because if there is no difference between them it could mean that environmental and industrial strains are capable of causing disease . For instance , Saccharomyces cerevisiae used in food products is capable of causing opportunistic infections [25] , so the same could be true of P . kudriavzevii . There is also uncertainty about the ploidy of the species . The MLST study indicated that isolates are diploid [24] , as did two genome analyses [10 , 23] , but evidence of triploid and aneuploid strains has also been reported [26] . C . krusei is of particular concern as a pathogen because of its intrinsic resistance to fluconazole , a drug commonly used for long-term antifungal prophylactic treatment of immunocompromised individuals [27 , 28] . Fluconazole resistance in C . krusei is not fully understood but appears to have two causes: its ergosterol synthesis enzyme Erg11 has unusually low affinity for fluconazole , and the drug efflux pumps Abc1 and Abc11 are constitutively expressed [26 , 27] . Echinocandins such as micafungin are the current drugs of choice for treatment of C . krusei infections , but echinocandin-resistant strains with point mutations in the FKS1 gene have been reported [29 , 30] . Additionally , it is possible that drug resistance may differ between clinical and environmental strains , but this has not been investigated . The very large evolutionary distance between C . krusei and other pathogenic Candida species is often not appreciated in clinical settings . By phylogenetic analysis of rDNA and other genes , systematists have determined that P . kudriavzevii/C . krusei is a species in the genus Pichia which is in the family Pichiaceae , often called the methylotrophic yeasts [9 , 31] . It uses the universal genetic code ( CUG = Leu ) [32] . C . krusei ( family Pichiaceae ) , C . albicans ( family Debaryomycetaceae ) and C . glabrata ( family Saccharomycetaceae ) are as distantly related to each other as humans are to sea-squirts [33] and it is rather misleading that they are all named Candida ( which simply means that a sexual cycle has not been observed in any of them ) . Apart from C . krusei , the only other known pathogens in family Pichiaceae are the rare species Pichia norvegensis ( also called Candida norvegensis ) and Pichia cactophila ( also called Candida inconspicua ) [34] . To better understand their genetics , phylogeny , and drug resistance , we sequenced the type strains of both C . krusei and P . kudriavzevii , as well as 30 other clinical and environmental isolates . We generated a high-quality reference genome for C . krusei CBS573T , using a combined PacBio/Illumina strategy to assemble complete sequences of its 5 nuclear chromosomes and its mitochondrial genome , and annotated it using RNAseq data to detect introns . We investigated genetic diversity , ploidy , and loss of heterozygosity , as well as centromere and mating-type locus structure . Our results show unequivocally that C . krusei and P . kudriavzevii are the same species , that clinical and environmental strains are not distinct , and that high levels of drug resistance are common in environmental isolates . Our work provides a resource for future molecular biology research on this yeast species that has four names and is both an emerging pathogen and an emerging workhorse for biotechnology .
In this section , we describe the construction of a PacBio/Illumina reference genome sequence for the type strain of C . krusei CBS573 , and PacBio sequencing of the P . kudriavzevii type strain CBS5147 . We then comment on the content of genes and mobile genetic elements , and on several other features: the centromeres , ribosomal DNA , telomeres , mitochondrial genome , introns , ribosomal protein genes , MAT locus and pheromone genes . Previous phylogenetic and phylogenomic analyses have established that P . kudriavzevii is a member of the genus Pichia and family Pichiaceae , often called the methylotrophic yeasts clade [6 , 31] . Within the genus Pichia , one of the closest known relatives of P . kudriavzevii is P . norvegensis , also called Candida norvegensis [6] . Clinical infections with P . norvegensis have been reported [34] . We used Illumina sequencing to sequence the genomes of the type strain of P . norvegensis ( originally isolated from sputum ) , and a strain of P . fermentans ( from pickled cucumber [45] ) that had been misidentified as P . kudriavzevii ( Table 2 ) . We constructed a phylogenetic tree using the Mdn1 protein . MDN1 is the largest gene in budding yeast genomes and codes for a protein of almost 5000 amino acids that functions as a ribosome assembly factor . It is a convenient phylogenetic marker because the protein is large , non-repetitive and has a low rate of insertions/deletions . The tree ( Fig 4 ) confirms that P . norvegensis is close to P . kudriavzevii/C . krusei ( the Mdn1 proteins of CBS573 and CBS5147 are identical ) , with P . fermentans and P . membranifaciens more distantly related . It also confirms that P . kudriavzevii/C . krusei lies in the methylotrophic yeasts clade and is only distantly related to C . albicans . In this section , we describe analysis of genetic diversity in a set of 32 strains . We show that all strains are diploid or triploid , that losses of heterozygosity are common , and we examine the phylogenetic relationships among strains . We assayed the in vitro sensitivity of all the sequenced strains to four antifungal drugs—fluconazole , flucytosine , amphotericin B , and micafungin—using the EUCAST protocol [58] . We also included two P . fermentans strains in the drug assays , one of which ( Pferm-PL1 ) was sequenced and the other ( Pferm-PL2 ) was not . The observed MICs for each strain in each drug are presented in Table 2 . The distribution of MICs for our P . kudriavzevii strains in fluconazole and micafungin were in line with previous distributions reported for C . krusei , while those for amphotericin B were about 2 dilution points higher ( www . eucast . org , Rationale documents for clinical breakpoints ) . No EUCAST ranges exist for flucytosine , but our values were similar to ranges reported in previous studies [59] . We wanted to focus on variation within P . kudriavzevii in its relative levels of drug resistance or sensitivity , so we plotted the distribution of MIC values among strains ( S4 Fig ) , and chose cutoffs that define groups that are ‘relatively resistant’ ( RR ) or ‘relatively sensitive’ ( RS ) to each drug , within the observed distribution . The strains designated as RR and RS for each drug are highlighted in magenta and green , respectively , in Table 2 . The phylogenetic distribution of these RR and RS strains is shown on the tree in Fig 6 .
Our results confirm that P . kudriavzevii and C . krusei are the same species and demonstrate that their genomes are collinear . The discovery that clinical and environmental isolates are interspersed in a phylogenetic tree of strains and do not form distinct clades indicates that there is no justification for continuing to use both names for this species . A third name , I . orientalis , is obsolete , having been formally replaced by the name P . kudriavzevii [6] . Furthermore , we found that the species has a fourth name , Candida glycerinogenes . Since its discovery by Zhuge in 1973 , ‘C . glycerinogenes’ has been used in China for the industrial-scale production of glycerol by fermentation of plant carbohydrates [19] . Extensive research has been carried out into its osmotolerance , and genetic manipulation methods have been developed ( e . g . , [61 , 62] ) . We find that 37 of the 38 C . glycerinogenes gene sequences available in NCBI are virtually identical to P . kudriavzevii sequences , including the 18S rDNA . The existence of multiple names for this species has almost certainly impeded research into it . In keeping with the One Fungus One Name principle [63] , we suggest that P . kudriavzevii should be the only name used in future . One of the most unexpected features of the genome is the structure of its centromeres , which consist of a simple but large IR . The 99% DNA sequence identity of the 8–14 kb units that form the IRs means that centromere organization would have been difficult to deduce without long-read PacBio data . The structure of the centromeres most closely resembles those of Komagataella phaffii , another yeast in the methylotrophs clade . However , the K . phaffii centromeres are much smaller , consisting of just a 2-kb IR on each chromosome with a 1-kb central region [40] . The only other yeasts in this clade whose centromeres have been characterized are Ogataea polymorpha , whose centromeres contain clusters of Ty5-like retrotransposons and do not seem to have an IR structure , and Kuraishia capsulata which has been reported to have point centromeres [40 , 64] . The P . kudriavzevii genome does not contain any Ty5-like elements . Its centromeres do contain pseudogenes of Ty3-like elements , and these are more abundant at the centromeres than elsewhere in the genome , but the only intact Ty3-like elements are not centromeric . Centromeres with similar IR structures also occur outside the family Pichiaceae , in C . tropicalis ( family Debaryomycetaceae ) [41] and Schizosaccharomyces pombe ( subphylum Taphrinomycotina ) [65] . The centromeres of Sch . pombe chromosomes 1 and 2 are similar in size and organization to those of P . kudriavzevii , whereas its third centromere is larger and more complex [40] . An important remaining question concerns the sexual cycle . When P . kudriavzevii was first described , it was reported to be able to sporulate , forming one spore per ascus [7] . Later studies by Kurtzman and colleagues reported that the type strain of P . kudriavzevii does not mate or sporulate [8 , 9] . Our discovery that this strain is triploid provides a possible explanation for its failure to sporulate , or at least its failure to produce viable spores . It will be of interest to re-investigate the question of sporulation using strains that are diploid MATa/α heterozygotes . Of the 32 strains we studied , 20 have this status ( Table 2 ) . It will also be of interest to test if mating can be induced between strains with MATα/α and MATa/a genotypes . The genome of CBS573 appears to contain a complete repertoire of sexual cycle genes , including pheromone genes ( MFa , MFα ) and orthologs of most of the genes in the MAPK kinase pathway that controls mating in S . cerevisiae . It also contains orthologs of many genes involved in meiosis , although IME1 , the master inducer of meiosis , has not been found in P . kudriavzevii nor any other species outside the family Saccharomycetaceae [66] . A possible explanation for the triploid isolates is that , for example , a MATa/α diploid underwent loss of heterozygosity to become MATα/α , and then mated with a MATa haploid spore to form a MATa/α/α triploid . Because clinical isolates were found to be closely related to environmental isolates , either infections are being acquired opportunistically from the environment , or yeast strains from infected humans are colonizing the environment . In view of the range of sources , the former possibility is more likely . The use of P . kudriavzevii in biotechnology therefore presents a potential hazard to the health of immunocompromised workers , and potentially also to consumers [67] . Moreover , high resistance to fluconazole is common in environmental isolates . The resistance to fluconazole is shared with P . fermentans ( Table 2 ) , P . norvegensis and other P . cactophila clade species [28 , 34] and therefore seems to be a trait of the whole genus Pichia . C . krusei and P . kudriavzevii are both categorized as Biosafety Level 1 ( BSL-1 ) , which is the lowest level of precaution . In another case of a pathogen with a major biotechnological role , it was suggested that a harmless closely related species should be used as a replacement [68] . Similarly , it may be advisable to consider non-pathogenic Pichia species as possible alternatives for some industrial applications . It would also be advisable to set limits on the levels of drug resistance permissible in P . kudriavzevii strains that are used in industry , particularly the food industry .
Yeast strains were obtained from the laboratories and culture collections listed in Table 2 . For clinical isolates obtained from hospital laboratories , all isolates came from different patients and where possible we obtained isolates that were taken prior to drug treatment . High molecular weight DNA for PacBio sequencing was purified using Qiagen Puregene Yeast/Bacterial Kit B . DNA for Illumina sequencing was harvested from stationary-phase cultures by homogenization with glass beads followed by phenol-chloroform extraction and ethanol precipitation . Purified DNA was concentrated with the Genomic DNA Clean & Concentrator-10 ( Zymo Research , catalog D4010 ) . Isolation of mRNA for RNAseq was done using the MasterPure Yeast RNA Purification kit ( Epicentre , Madison , WI , USA ) from CBS573 cultures grown to early log phase ( OD600 ~ 1 ) in YPD media at 30°C . PacBio DNA sequencing of strains CBS573 and CBS5147 was done at the Earlham Institute , UK , with 4 SMRT cells per strain . Illumina sequencing of these two strains was also done at the Earlham Institute using Low Input Transposon Enabled ( LITE ) libraries . Illumina sequencing of all other strains was done by the core facility of the University of Missouri , USA , using TruSeq libraries ( coverage details are given in Table 2 ) . Illumina RNA-seq ( 30 million reads ) of CBS573 was done in-house at University College Dublin . Assembly of the CBS573 PacBio data using HGAP3 software initially produced seven nuclear contigs ( 115x coverage ) and the mitochondrial genome . Overlaps between the ends of two pairs of contigs were merged manually to obtain five near-complete chromosome sequences . Illumina sequencing of the same strain ( 35x coverage ) was then used to error-correct the chromosome sequences , in particular to remove insertion/deletion errors in homopolymer tracts . Error correction was done using Pilon [69] and manual comparison to de novo Illumina contigs assembled by SPAdes version 3 . 10 [70] . Assembly of the CBS5147 PacBio data using HGAP3 yielded 13 contigs ( 94x coverage ) . This assembly appeared to have a higher level of indel errors than the CBS573 assembly , so we used CBS573 as the reference genome sequence for annotation and downstream analyses . De novo assemblies of the other 30 strains were made using SPAdes version 3 . 10 [70] . Nucleotide sequence identity of 99 . 6% between the reference chromosome sequences of CBS573 and CBS5147 was calculated from a MUMmer ( v3 . 23 ) alignment of the whole genome [37] . Ploidy was estimated with a modified version of the method of Popolo et al . [71] . Briefly , aliquots of exponentially growing cells in YM medium ( 3 g/L yeast extract , 3 g/L malt extract , 5 g/L peptone and 10g/L dextrose ) , were adjusted to OD600 = 1 in 1 mL sterile ice-cold water , centrifuged ( 5 min , 5000 rpm ) and fixed in 1 mL cold 70% ethanol for 24 hours at 4 °C . Fixed cells were next treated with 100 μL 1 mg/mL RNAse A for 90 min at 37 °C after centrifugation to remove the ethanol . RNase A treated cells were centrifuged and the pellet stained with 100 μL 0 . 05 mg/mL propidium iodide at 4 °C for 24 hours . Fifty μL of stained cells was diluted to 500 μL with ice-cold water , filtered with 50 μm celltrics filters ( Sysmex , UK ) and run on a BD Accuri C6 flow cytometer . Data were analysed using Flowjo software ( Flowjo , LLC ) . BAM alignments of Illumina reads from each strain to the CBS573 reference genome were generated using the Burrows-Wheeler Aligner ( BWA ) with default parameters [46] . Unmapped reads were removed using SAMtools [72] and headers were added using the AddOrReplaceReadGroups program in Picard Tools [http://picard . sourceforge . net] . Variants against the reference were called with the GATK HaplotypeCaller tool in DISCOVERY genotyping mode with the following parameters: “-stand_emit_conf 10 -stand_call_conf 30—emitRefConfidence GVCF” [73] . The resulting set of 32 GVCF files defined an initial set of 169 , 789 SNP sites that were variable among the 32 strains , and this set was used for ploidy analyses ( Fig 5A ) . To analyze patterns of LOH , we divided the genome into consecutive 50-kb windows and calculated the number of heterozygous SNPs in each window ( with allele frequencies between 0 . 15 and 0 . 85 , from the initial set of 169 , 789 sites ) . Windows containing <30 heterozygous sites were categorized as showing LOH ( Fig 5B; S2 Table ) . The threshold of 30 heterozygous sites was chosen because it is a local minimum in the distribution of heterozygous SNP numbers among all windows in all strains . For phylogenetic and STRUCTURE analyses ( Fig 6; S3 Fig ) , we first filtered the 32 GVCF files to remove low allele frequency sites ( allele frequency <0 . 15 ) . The filtered GVCFs were then jointly genotyped with the GenotypeGVCFs function of GATK to produce a single multisample SNP file containing data on every strain . This filtered dataset contained 150 , 306 variable sites . For phylogenetic analysis of SNP data , we used the program RRHS [74] to preserve the impact of heterozygous SNPs . This program generated 100 datasets in which , for each heterozygous site in each strain , one allele was chosen randomly . Each of the 100 datasets was used to build a phylogenetic tree by maximum likelihood using IQ-TREE v1 . 6 . 5 [53] , with option “-m GTR+ASC” to account for ascertainment bias . A single unrooted consensus tree was then constructed from these trees ( Fig 6 ) . STRUCTURE [54] uses SNP data to infer the population structure of the genomes in the dataset , assuming that the individuals are drawn from k populations . It also provides a value of estimated log likelihood ( ln Pr ) for the model used . We ran STRUCTURE ( v2 . 3 . 4 ) for values of k between 2 and 8 , and present the results for the value that gave the highest log likelihood , k = 4 . Minimum Inhibitory Concentrations ( MICs ) of the four antifungal agents were determined using the EUCAST broth dilution method [58] with slight modifications . In brief , stock antifungal agents prepared with EUCAST recommended solvents were diluted to appropriate working concentrations in double strength RPMI-1640 2% G ( RPMI-1640 supplemented with 2% w/v glucose ) . The working concentrations used were 128 mg/L for fluconazole and flucytosine , and 32 mg/L for amphotericin B and micafungin . A ten-series two-fold dilution starting with 200 mL working concentration of each agent was made row-wise in flat-bottomed 96-well plates using double strength RPMI-1640 2% G as diluent . Consequently , the wells of each dilution series yielded 100 mL of twice the recommended series of drug concentrations required for MIC determinations . The last two wells of each row containing an antifungal drug serial dilution were filled with 100 mL of drug-free RPMI-1640 2% G . Yeast inocula were prepared by growing three distinct colonies of each strain overnight on Sabouraud agar at 37°C and suspending them in sterile distilled water . To achieve final cell densities of 0 . 5–2 . 5 x 106 cfu/ml in the microtitre wells as recommended , these suspensions were adjusted to OD600 0 . 1 and then further diluted 1/10 in sterile water . Cell densities were confirmed by plate counting . Wells of each dilution series as well as the 11th well containing drug-free RPMI-1640 2% G were inoculated with 100 mL of the prepared yeast suspensions . The last well was filled with 100 mL of sterile distilled water to serve as contaminant control . Inoculated plates were incubated without shaking at 37°C for 24 hours . Plates were read for OD600 values using a Spectramax 190 microplate reader ( Molecular Devices , Sunnyvale , California , USA ) . As recommended in the EUCAST protocol [58] , we calculated MIC90 for amphotericin B , and MIC50 for the other three drugs . One of the recommended control strains for yeasts in the EUCAST protocol is the type strain of C . krusei ( CBS573T , synonymous with ATCC6258T ) , and we used the type strain of C . parapsilosis ( CLIB214T ) as a second control . MICs for the two control strains were within EUCAST guideline ranges , except for C . krusei CBS573T in amphotericin B , which was 1 dilution point more resistant than the guideline . The sequence data reported in this manuscript has been submitted to the NCBI nucleotide database with the following accession numbers: P . kudriavzevii CBS573 PacBio/Illumina annotated reference genome sequence ( CP028773-CP028778 ) ; P . kudriavzevii CBS573 RNAseq Illumina reads ( SRA accession SRP139056 ) ; P . kudriavzevii CBS573 MATα allele region ( MH260578 ) ; P . kudriavzevii CBS5147 PacBio genome sequence ( CP028531-CP028535 ) ; Illumina genomic sequencing reads from 32 P . kudriavzevii strains ( SRA accession SRP139299 ) ; P . fermentans strain fo/MP/02 ( Pferm-PL1 ) Illumina WGS assembly ( QAWB00000000 ) ; P . norvegensis strain CBS1922 ( Pnorv-NO1 ) Illumina WGS assembly ( QAWC00000000 ) .
|
Infections with yeasts resistant to antifungal drugs are an increasing cause of concern . One species , Candida krusei , has innate resistance to the widely-used drug fluconazole . It is one of the five most prevalent causes of clinical yeast infections , and is responsible for significant levels of morbidity and mortality in immunocompromised patients . In this study , we show that C . krusei is the same species as Pichia kudriavzevii , a yeast that is regarded as non-pathogenic and has important applications in biotechnology and food industries . We examined the genomes of 20 clinical isolates ( ‘C . krusei’ ) and 12 environmental isolates ( ‘P . kudriavzevii’ ) and find that there is no genetic distinction between them . The environmental isolates have similar levels of drug resistance to the clinical isolates . As well as providing a resource for future studies of this yeast , our results indicate that caution may be needed in the use of drug-resistant P . kudriavzevii strains for biotechnology and food applications .
|
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2018
|
Population genomics shows no distinction between pathogenic Candida krusei and environmental Pichia kudriavzevii: One species, four names
|
Differential modulation of NF-κB during meningococcal infection is critical in innate immune response to meningococcal disease . Non-invasive isolates of Neisseria meningitidis provoke a sustained NF-κB activation in epithelial cells . However , the hyperinvasive isolates of the ST-11 clonal complex ( ST-11 ) only induce an early NF-κB activation followed by a sustained activation of JNK and apoptosis . We show that this temporal activation of NF-κB was caused by specific cleavage at the C-terminal region of NF-κB p65/RelA component within the nucleus of infected cells . This cleavage was mediated by the secreted 150 kDa meningococcal ST-11 IgA protease carrying nuclear localisation signals ( NLS ) in its α-peptide moiety that allowed efficient intra-nuclear transport . In a collection of non-ST-11 healthy carriage isolates lacking NLS in the α-peptide , secreted IgA protease was devoid of intra-nuclear transport . This part of iga polymorphism allows non-invasive isolates lacking NLS , unlike hyperinvasive ST-11 isolates of N . meningitides habouring NLS in their α-peptide , to be carried asymptomatically in the human nasopharynx through selective eradication of their ability to induce apoptosis in infected epithelial cells .
Neisseria meningitidis ( Nm ) is a leading cause of severe invasive infections mainly in children , leading to septicaemia and meningitis . The onset of these infections can be extremely rapid , leading to high morbidity and mortality despite appropriate antimicrobial chemotherapy and modern intensive care [1] . However , this pathogen is also frequently carried asymptomatically in about 10% of the general population as part of the commensal flora of the human nasopharynx [2] . A combination of host and bacterial factors may ultimately lead to meningococcal disease [3 , 4 , 5] . Indeed , only few meningococcal genetic lineages , referred to as hyperinvasive clonal complexes and rarely encountered in healthy carriers , are responsible for most cases of meningococcal disease [6 , 7] . Among these lineages , the clonal complex ST-11 ( ST-11 ) , that is most frequently of serogroup C , has been provoking outbreaks worldwide with high mortality rate [8 , 9] which has promoted the use of conjugate vaccine against serogroup C meningococci [10 , 11] . There is increasing evidence that invasive meningococcal infections lead to cytopathic effects that are consistent with the extensive cell injury and tissue damage [12 , 13 , 14 , 15] . We have previously shown a strong association between ST-11 isolates and apoptosis of infected epithelial cells [16 , 17] that required sustained activation of c-Jun N-terminal kinase ( JNK ) as a consequence of alteration of NF-κB activity [17 , 18] . In contrast carriage isolates promote a sustained cytoprotective NF-κB activity with only transient activation of JNK . The NF-κB consists of a heterodimeric complex composed of two subunits , commonly p50/NF-κB1 , a DNA-binding subunit , and p65/RelA subunit which provides the transactivation activity of NF-κB . This heterodimeric complex is sequestered in the cytoplasm of resting cells and is rendered inactive through its association with the inhibitor of NF-κ ( IκB ) [19] . NF-κB-activating stimuli such as bacterial infection , proinflammatory cytokines or LPS , facilitate IκB kinase ( IKK ) -mediated IκB phosphorylation and subsequent degradation of IκB by the proteasome machinery [20] , resulting in the release and subsequent nuclear translocation of the NF-κB complex for regulation of genes that are involved in the immunity process , adhesion molecules and cell survival [21] . We aimed in the present study to determine the mechanism leading to the differential impairment of NF-κB activity between invasive ST-11 isolates ( referred to as ST-11 isolates ) and carriage isolates ( referred to as non-ST-11 isolates ) .
Immunoblotting analysis showed that both ST-11 and non-ST-11 isolates caused IκBα degradation ( Figs 1A and S1A ) . Consistently , nuclear translocation of both p65/RelA and p50/NF-κB1 subunits was detected by immunofluorescence microscopy and immunoblotting ( Fig 1B and 1C ) . While persisting in the nuclear fraction of cells infected with the non-ST-11 isolate LNP21019 , the level of p65/RelA decreased beyond 6 h in the nuclear fraction of cells infected with the non-ST-11 isolate LNP19995 . Intriguingly , the decrease in the nuclear amount of p65/RelA subunit paralleled with a progressive increase of a 40 kDa reactive band ( named p40 ) that was recognized with the same antibody ( Fig 1C , left panel ) . The p40 band could result from the cleavage of p65/RelA subunit . Indeed , enhanced detection of a ~25-kDa reactive band ( named p25 ) with a C terminus-specific antibody to p65/RelA consolidated this hypothesis ( Fig 1D ) . Similar results were obtained with other ST-11 and non-ST-11 isolates ( S1B Fig ) and with A549 airway epithelial cell line ( S1C Fig ) . Cleavage of p65/RelA was restricted to the nuclear fraction as no alteration of p65/RelA was observed in cytosolic fractions ( Fig 1C , right panel ) . It is worth noting that alteration of NF-κB was selective to p65/RelA subunit because expression of the p50/NF-κB1 subunit was not affected by meningococcal infection in either fraction ( Fig 1C , bottom blots ) . Taken together , these results suggest that ST-11 isolates promote nuclear cleavage of p65/RelA subunit during late steps of infection . We next showed that cleavage of p65/RelA was blocked when Hec-1-B cells were infected with LNP19995 ( ST-11 ) in presence of 5μg . ml-1 chloramphenicol antibiotic that inhibits bacterial protein synthesis but not by cycloheximide ( a eukaryotic protein synthesis inhibitor ) , suggesting that cleavage of p65/RelA required de novo synthesized bacterial proteins ( Fig 2A , left panel ) . Moreover , cleavage of p65/RelA was observed upon incubation of the nuclear fraction from LPS-stimulated cells with native ( but not heat-inactivated ) bacterial culture supernatant of LNP19995 suggesting that meningococcal secreted proteins ( MSP ) may be involved ( Fig 2A , right panel ) . The presence of the serine proteases inhibitor PMSF abrogated the cleavage of p65/RelA in both , in vivo and in vitro cleavage assays ( Fig 2A ) further suggesting that the involved secreted meningococcal protein is most likely a serine protease that is able to reach the nuclear compartment of infected cells . We therefore prepared intact cytosolic-free nuclei from infected or uninfected cells ( see Materials and Methods section and S2A Fig ) . Proteins of isolated nuclei were then subjected to 2D-gel electrophoresis and immnublotting with anti-MSP specific mouse serum . Several spots of high molecular weight reacted with the serum from infected but not from non-infected cells ( S2B Fig , upper panel , compare a and c ) . None of these spots reacted with the pre-immune serum ( S2B Fig , lower panel ) . The apparent electrophoretic mobility and isoelectric point of one of these spots is compatible with the neisserial IgA protease , a type V autotransporter secreted serine peptidase ( S2B Fig , upper panel , compare b and d ) [22] . Moreover , examination of the primary structure of p65/RelA revealed the presence of a specific IgA protease cleavage site close to the C terminus of p65/RelA subunit P-P-|-X-P ( shown by the vertical line ) , where X is either S , T or A amino-acid ( Fig 3A ) [23 , 24 , 25] . The meningococcal IgA protease is expressed as a polyprotein precursor molecule having three domains ( Fig 3B ) . These include an N-terminal signal sequence , a C-terminal outer membrane-embedded translocator domain ( Igaβ ) and the central secreted passenger domain ( IgaPα ) that includes the protease sub-domain ( referred to as IgaP ) followed by α-peptide sub-domain ( referred to as Igaα ) [26 , 27 , 28] harbouring eukaryotic nuclear localisation signal ( NLS ) [29] . A cleavage site CS1 upstream Igaα resulted in release of the IgaP 100 kDa fragment . In presence of NalP ( a phase variable meningococcal surface protease ) , an alternative proteolysis at cleavage site CS2 downstream Igaα , allowed the release of a predominant 150 kDa form corresponding to IgaP linked to Igaα ( referred to as IgaPα ) ( Fig 3B ) [28 , 30] . Both of these two proteins ( 100 kDa and 150 kDa ) are detected in MSP of meningococcal isolates with a “phase on” nalP gene ( S3A Fig ) . The same pattern was observed in the cytosolic fraction of infected cells ( S3A Fig , lower left panel ) . Interestingly , the anti-IgaP polyclonal serum detected a progressive accumulation of IgaPα , but not IgaP , in the nuclear fraction of cells infected with ST-11 isolates that coincided with the cleavage of p65/RelA . However , the absence of IgA protease from the nucleoplasm of cells infected with non-ST-11 isolates correlated with the expression of intact p65/RelA ( Figs 3C and S3B ) . Collectively , these results suggest that nuclear cleavage of p65/RelA in cells infected with ST-11 isolates correlated with the nuclear appearance of IgaPα . To establish a direct cause effect relationship between IgA protease expression of ST-11 isolates and the nuclear cleavage of p65/RelA , we generated an iga deletion mutant ( named 19995Δiga ) and the complementing strain ( named 19995Δiga/iga ) . The absence of IgaP and IgaPα expression was confirmed in the MSP fractions prepared from 19995Δiga mutant strain , while the expression of both IgA protease forms was restored in the MSP of the complementing strain as the parental strain ( S4A Fig ) . Furthermore , substitution of iga by the spectinomycin resistance cassette in the mutant 19995Δiga had no polar effect on the expression of trpB gene downstream iga as confirmed by RT-PCR ( S4B Fig ) . Hec-1-B cells were infected with either strain and expression of p65/RelA in the nuclear compartment was followed by immunoblotting . Nuclear cleavage of p65/RelA occurred progressively beyond 6h in LNP19995-infected cells , but not in the 19995Δiga-infected cells ( Fig 4A ) . Consistently , NF-κB transcriptional activity was altered in cells infected with LNP19995 whereas sustained in cells infected with 19995Δiga as the non-ST-11 isolate LNP21019 ( S4C Fig ) . The complemented strain 19995Δiga/iga19995 restored the cleavage of p65/RelA in infected cells resulting in alteration of NF-κB activity comparably to the WT strain ( Figs 4A and S4C ) . van Ulsen et al . , reported that the serine protease autotransporter protein NalP is involved in modulating the processing of other meningococcal autotransporters , including IgA protease . As reported elsewhere , the nalP mutant strain 19995ΔnalP , secreted increased level of IgaP lacking the α peptide and strongly decreased level of IgaPα comparing to the WT parental strain LNP19995 ( S4D Fig and [30] ) . Consistently , 19995ΔnalP strain reproduced similar phenotypes as 19995Δiga mutant regarding cleavage of p65/RelA ( Fig 4A ) . It is worth noting that NalP was not detected in the nuclear fraction of LNP19995-infected cells ( Fig 3C ) , ruling out any direct effect of NalP on the nuclear cleavage of p65/RelA . These results suggest that NalP is involved in down regulation of NF-κB activity by ST-11 isolates , most likely through modulation of IgaPα secretion . To further determine the role of α-peptide in the nuclear translocation of ST-11 IgA protease , Hec-1-B cells were transfected separately with mammalian C-terminus DsRed-tagged constructs harbouring either IgaP19995 , Igaα19995 , or IgaPα19995 . We found that IgaP19995 , as DsRed control empty vector , was located in the cytosol of transfected cells , whereas a substantial amount of DsRed signal was located into the nucleus of cells transfected with Igaα19995 or IgaPα19995 ( Fig 4B , upper panel ) . Accordingly , purified His6-tagged catalytic protease sub-domain ( IgaP19995 ) or full passenger domain ( IgaPα19995 ) ( S5A Fig ) were able to provoke cleavage of p65/RelA when incubated with nuclear fractions prepared from LPS-stimulated Hec-1-B cells ( Fig 4C , upper panel ) . However , purified His6-tagged α-peptide sub-domain ( Igaα19995 ) ( S5 Fig ) was unable to do so ( Fig 4C , upper panel ) . The role of the protease sub-domain in the cleavage of p65/RelA would imply that the active site IgA protease is required for the processing of p65/RelA . To test this possibility , we generated an active-site mutant strain 19995igaS267V . Immunoblot examination was performed to verify the expression of IgaS267V . As expected , disabled active-site resulted in accumulation of full-length IgaS267V in the whole cell lysate ( S4D Fig ) , hence 19995igaS267V-infected cells expressed intact nuclear p65/RelA ( Fig 4A ) comparably to 19995Δiga mutant strain . Furthermore , purified IgaP-S267V ( Fig 5B ) was unable to cleave p65/RelA in vitro in contrast to the WT IgaP ( Fig 4C ) . These results corroborate with the effect of PMSF observed in Fig 2A . Indeed , PMSF treatment strongly decreased the levels of secreted IgA protease and other serine proteases , including NalP in the culture medium of infected cells ( Fig 2A ) . This effect did not result from a defect of protein expression , as immature full length serine proteases were detected in the bacterial lysates recovered from the same culture medium ( Fig 2B ) . Altogether , these set of experiments suggest that active site of IgA protease is required for its role in processing p65/ReA . The cleavage of p65/RelA seems to occur through a direct interaction with IgA protease as suggested by co-immunoprecipitation experiments using MSP prepared from WT , but not 19995Δiga mutant , when pull-down was performed with an anti-IgaP specific serum ( Fig 4D , left panel ) . Both IgaP and IgaPα , co-immunoprecipitated with p65/RelA when pull-down was performed with anti-p65 mAb comparing to irrelevant mouse mAb ( Fig 4D , right panel ) . We next examined the role of IgA protease in inducing apoptosis of epithelial cells upon infection of cells with the parental WT LNP19995 or with the isogenic strains 19995Δiga and 19995Δiga/iga19995 . The activation of JNK and apoptotic levels were analysed over time using immunoblotting and flow cytometry , respectively . The mutant strain 19995Δiga promoted a transient activation of JNK ( Fig 5A ) and a significant decrease in apoptotic level of epithelial cells ( Fig 5B ) comparing to the parental strain . Consistently , the isogenic mutants 19995igaS267V ( disabled in S267 active site ) and 19995ΔnalP ( that was affected in secretion of IgaPα ) reproduced similar phenotypes as 19995Δiga ( Fig 5 ) . The complemented strain 19995Δiga/iga19995 restored all these phenotypes similarly to the WT strain ( Fig 5 ) , suggesting that IgA protease of ST-11 isolates contribute to apoptosis of epithelial cells . Cells exhibited sustained activation of NF-κB when infected by the non-ST-11 strain LNP21019 with a transient activation of JNK and apoptotic level close to uninfected cells ( LNP21019 in Figs 5A , 5B and S4C ) . To understand why non-ST-11 isolates did not alter the nuclear activity of p65/RelA in vivo , we examined the expression and subcellular localisation of IgA protease of these isolates . Unlike ST-11 isolates , only the 100 kDa-IgaP was detected in the MSP fractions prepared from non-ST-11 isolates that could be also found in the cytosolic fractions of infected cells ( S3A Fig , right panel ) , suggesting that non-ST-11 isolates were unable to release IgaP linked to α-peptide , although a priori express NalP ( S3A Fig ) . These findings were also confirmed by immunofluorescence microscopy examination . Indeed , after 12 h of infection , the fluorescent signal specific to IgA protease ( red ) appeared in the cytosolic compartment but a substantial signal colocalized also with the nuclear compartment ( blue ) of cells infected with the ST-11 isolate LNP19995 ( appears as magenta in merged panel ) . In contrast , IgA protease of the non-ST-11 isolate LNP21019 appeared as a punctuate pattern exclusively localized in the cytosolic space ( Fig 6A ) . These results suggest that IgA protease released from non-ST-11 isolates did not present a defect in cell internalisation but rather in nuclear translocation . It is worth noting that purified IgaP sub-domain of the non-ST-11 isolate LNP21019 ( IgaP21019 ) , as MSP prepared from different non-ST-11 isolates , exhibited an in vitro cleavage activity of p65/RelA comparable to ST-11 isolates ( Fig 4C , lower panel ) , ruling out a defect in the protease activity . We then compared α-peptide encoding regions of non-ST-11 isolates to those from ST-11 isolates . From all ST-11 isolates examined , PCR amplification yielded a single PCR band of ~ 1500 bp ( Fig 6B ) . Amino acid-derived sequence analysis revealed the presence of two bipartite NLS sequences flanked by two cleavage sites CS1 and CS2 ( Figs 6C and S6 ) . Of the 20 non-ST-11 isolates examined , all yielded a single α-peptide PCR product with a smaller length than those resulted from ST-11 isolates ( Fig 6B ) . This difference resulted from the deletion of ∼813 bp ( 271 amino-acids ) encompassing the NLS sequences ( S6 Fig ) . Indeed , DsRed fused to α-peptide of the carriage isolate remained in the cytosolic compartment ( Fig 4B , lower panel ) suggesting impaired nuclear transport . Importantly , all isolates shared the cleavage site CS1 separating IgaP and α-peptide ( Igα ) . However , the alternative cleavage site CS2 downstream α-peptide was missing in all non-ST-11 isolates ( S6 Fig ) . These observations were confirmed experimentally by incubating the purified C-terminal His6-tagged passenger domains IgaPα of LNP19995 ( 1500 residues extending from A28 to T1527 ) and LNP21019 ( 1235 residues extending from A28 to T1262 ) with the MSPs of LNP19995 and LNP21019 , respectively ( Fig 6C ) . Cleavage of LNP19995 passenger domain generated two His6-tagged fragments of ~ 60 kDa ( that resulted from cleavage at the site CS1 ) and ~14 kDa ( that resulted from the cleavage at site CS2 ) in presence of increasing amounts of MSPs . These fragments correspond to Igaα ( ~44–45 kDa ) associated to the linker domain ( ~14 kDa ) ; and the linker domain alone , respectively ( Fig 6C , left panel ) . However , only one His6-tagged fragment of ~ 31 kDa ( corresponding to Igaα associated to the linker ) was generated from the cleavage at CS1 of LNP21019 passenger domain ( Fig 6C , right panel ) . These results suggest that proteolytic cleavage of IgA protease may therefore occur at two cleavage sites in ST-11 isolates LNP19995: CS1 autocleavage site ( separating the protease domain from the α peptide ) and CS2 autocleavage site ( separating the α peptide from the translocator domain ) . However , the proteolytic cleavage may occur at the unique CS1 site , leading to release of α-peptide-lacking IgA protease in non-ST-11 isolates . To examine more thoroughly the role of α-peptide , each of the iga knock-out mutant strains 21019Δiga and 19995Δiga were complemented with iga allele of the heterologous isolate LNP19995 and LNP21019 , respectively . The resulting recombinant strains 21019Δiga/iga19995 and 19995Δiga/iga21019 released comparable IgA protease pattern as the non-ST-11 isolate LNP19995 and the non-ST-11 isolate LNP21019 , respectively ( S4A Fig ) . More importantly , the recombinant 21019Δiga/iga19995 altered full length p65/RelA , promoted sustained activation of JNK and promoted substantial apoptotic level , concomitantly to the accumulation of the IgaPα in the nuclear compartment of infected cells comparably to ST-11 isolates ( Figs 5 and 6D ) . In contrast , the recombinant strain 19995Δiga/iga21019 did not promote nuclear localisation of IgaPα , or alteration of the full length p65/RelA in the nuclear compartment of infected cells ( Figs 5B and 6D ) . These results suggest that IgA protease of ST-11 isolates may restore the ability of non-ST-11 isolates to cleave the nuclear p65/RelA and promote apoptosis of epithelial cells . To test for the functional relevance of ST-11 IgA protease-mediated nuclear cleavage of p65/RelA , we asked whether ST-11 IgA protease-mediated cleavage of p65/RelA culminates in alteration of the expression of NF-κB responsive genes . For that purpose , relative mRNA levels of three NF-κB responsive targets; the pro-inflammatory cytokines TNF-α , interleukin ( IL ) -8 and the major anti-apoptotic protein cFLIP [31] were examined by qRT-PCR . As shown in Fig 7A and 7B , expression of both IL-8 and cFLIP increased progressively and reached a peak level at 6h post infection . While persisted longer in cells infected with the carriage isolate LNP21019 and the Δiga mutants , mRNA levels of cFLIP and IL-8 decreased significantly in cells infected with the ST-11 isolate LNP19995 and the complemented strain 19995Δiga/iga comparing to the isogenic mutant strain 19995Δiga , although more pronounced for cFLIP than for IL-8 which remained detectable at substantial level . Interestingly , peak levels of TNF-α transcripts occurred as early as 2h post-infection , after which they rapidly decreased by 6h and remained substantially stable up to 12h . The expression profile of TNF-α was comparable between WT and Δiga mutants in contrast to the former targets ( Fig 7C ) . Taken together , these results suggest that cleavage of p65/RelA mediated by ST-11 IgA protease resulted in alteration of selective NF-κB-responsive targets .
Several pathogens elicit apoptotic cell death by inducing an inflammatory response that may lead to disruption of tissue barriers allowing efficient microbial spread in the host [32 , 33] . In this work , we revealed a mechanism used by ST-11 isolates of Nm ( but not by the non-ST-11 isolates ) to disrupt the epithelial cells by apoptosis induction . The secreted IgA protease from these isolates is transported to the nucleus of infected cells where it cleaves the p65/RelA component of NF-κB complex . NF-κB is tightly controlled by negative feedback loops mediated primarily by IκB , leading to oscillatory responses , in which NF-κB shuttles between the cytoplasm and nucleus with the period of about 100 min [20] . Comparing to other reports [34] , the steady decrease of IκB over the period of 12h of infection was surprising . Meningococcal infection may interact with other components of NF-κB signaling pathway including IKK complex and/or A20/TNFAIP3 to attenuate the negative feedback loop mediated by IκB [35 , 36 , 37 , 38] although cell lines and bacterial strains used in this study may account for these differences . Persistent degradation of IκB has also been reported for other bacterial pathogens , but the mechanism responsible for that decrease remains unknown [39 , 40 , 41 , 42] . Additional research will clearly be needed to elucidate the precise mechanism of this phenomenon . On the other hand , aberrantly prolonged NF-κB activation may have deleterious cellular effects [43 , 44 , 45 , 46 , 47] . However , the persistent NF-κB activation observed in cells infected with non-ST-11 isolates suggest that these isolates drive somehow mechanism ( s ) required to maintain a fine balance of NF-κB activation in infected cells to dampen the inflammatory response at levels that are advantageous for bacteria yet that would allow the maintenance of a healthy ecological niche . The expression of NF-κB-regulated genes was altered as a consequence of ST-11 IgA protease-mediated cleavage of p65/RelA . Interestingly , this alteration targets selectively some NF-κB-regulated genes ( for instance IL-8 and cFLIP ) . In contrast to TNF-α , expression of IL-8 and cFLIP , follows obviously the kinetic of NF-κB activity ( S4C Fig ) . These differential effects of IgA protease could be related to the balance between the level of available intra-nuclear IgA protease and the kinetic of expression for a given NF-κB-regulated target . Indeed , TNF-α is an early up-regulated cytokine that is rapidly down-regulated within 4 to 6h post-infection , a time for which the level of IgA protease may not be good enough to compromise NF-κB activity and hence TNF-α expression . Alternatively , IgA protease may interact with NF-κB in selective manner dependent on the nature of NF-κB-regulated promoter to alter their expression following cleavage of NF-κB p65 subunit . This hypothesis suggests that α peptide-associated IgA protease may have a DNA-binding activity to some NF-κB-responsive promoters . In agreement with this hypothesis , Arenas et al . [48] have recently reported the ability of α peptide subdomain to bind DNA . Alteration of IL-8 and TNF-α expression was not completely compromised , in contrast a substantial levelq of IL-8 and TNF-α mRNAs remained detected over 12 h of infection . This may be related to an alternative mechanism regulating the expression of these targets independently to NF-κB . Indeed , the role of JNK in up-regulation of IL-8 has been demonstrated [49 , 50 , 51] . Alteration of NF-κB activity promoted by ST-11 isolates should have multi-faceted consequences . For instance , activation of JNK was sustained in ST-11-infected cells and this may account for the high level of IL-8 expression despite alteration of NF-κB activity . It has been reported that transient activation of JNK is normally terminated by MAP Kinase phosphatases ( MKPs ) , a mechanism itself controlled by NF-κB survival signaling [52] . Alteration of NF-κB may therefore down regulate the MKPs activity and provoke persistent JNK activation that may account for high levels of IL-8 expression in one hand and make the cells to succumb to apoptosis under infection with ST-11 isolates . Sustained activation of JNK may not be the only reason for induction of apoptosis . Attenuation of NF-κB-regulated anti-apoptotic factors , such as cFLIP , that interacts and specifically inhibits the caspase-8 , may also account for apoptosis promoted by ST-11 isolates . Cleavage of p65/RelA occurs at the C-terminal region which contains the transactivation domain ( TAD ) . Removal of the TAD from the rest of the protein may therefore disable the activation capacity of the native p65/RelA molecule . Alternatively , cleavage may generate a truncated N-terminal p65/RelA that can still bind DNA and thus potentially acts as a dominant-negative inhibitor by competing with intact p65/RelA . Bacterial proteins that target the nuclei of host cells may alter cell biology , which is an emerging pathogenic mechanism of bacteria [53 , 54] . Few bacterial proteins were found to induce host cell pathology through nuclear targeting including the cytolethal distending toxins CdtB of Escherichia coli and Campylobacter jejuni [55 , 56] , the outer membrane protein OmpA and transposase of Acinetobacter baumannii [57 , 58] , OspF of Shigella species [59] and recently two other meningococcal autotransporters App and MspA [60] . Neisseria IgA protease was previously reported to cleave human IgA1 [61] , the lysosome-associated membrane protein 1 ( Lamp1 ) promoting intracellular bacterial survival in epithelial cells in vitro [24 , 62 , 63] , the human chorionic gonadotropin hormone ( hCGH ) and the membrane vesicular protein synaptobrevin II [25 , 64] . The biological significance of these processing remains unclear . Poliovirus protease 3C , the Chlamydial Protease-like Activity Factor ( CPAF ) and recently the type III secretion protease of enteropathogenic and enterohemorrhagic Escherichia coli , compromise NF-κB activation by targeting the cytosolic p65/RelA [65 , 66 , 67] . In contrast to these pathogens , the cleavage of p65/RelA by IgA protease of ST-11 meningococcal isolates occurs exclusively within the nuclear compartment . One possible explanation for this site specific effect could be the intracellular trafficking of this protease that may render it either temporarily inactive or inaccessible to p65/RelA within the cytosol . This issue relates to the mechanism of uptake and the intracellular trafficking of IgA protease . For instance , the IgA protease domain alone ( IgaP ) from non-ST-11 isolates was able to be internalized , as it could be detected intracellularly in the cytosolic fractions . These results suggest that this internalisation was mediated by the conserved protease domain , but cannot exclude a cooperative effective role of α peptide when associated to the protease domain . Upon Nm-epithelial cells contact , the IgA protease is upregulated [68] allowing local production of substantial amounts of IgA protease , its accumulation in the nuclei of infected cells , the cleavage of p65/RelA and the induction of apoptosis . Nevertheless , absence of iga expression did not completely abolish the apoptotic effect promoted by ST-11 isolates . Other bacterial factors such as the outer membrane protein , PorB , that promotes apoptosis in epithelial cells by mitochondrial pathway [17 , 69] and autotransporter protein NhhA that has been demonstrated to trigger apoptosis in macrophages via an undefined mechanism [70] could be involved . The α-peptide is a unique characteristic of pathogenic Neisseriae [29] . Our data and other reports revealed an extensive polymorphism within this region between ST-11 and non-ST-11 isolates [71 , 72 , 73] . Accordingly , José et al . described four different variants of meningococcal α proteins regarding the number of NLS and sequence variability . The majority of the strains analyzed in this report were isolated from nonsymptomatic carriers at different locations in Germany [73] . Our findings extended from previous investigations showed that the high diversity in some genetic lineages such as ST-32 , correlated with heterogeneity in virulence for mice . In contrast , the homogeneous genetic structure of isolates of the clonal complex ST-11 , regardless of their serogroup , correlated positively with a fatal outcome of the infection and increased virulence in mice [16] , and pathogenic effects toward infected cells as determined by apoptotic assays [17] . Therefore , one can assume that apoptotic effect of some meningococcal strains but not others seems to be strain specific , which could be related in part to the capacity of some strains to protect their host cells from apoptosis . This polymorphism may explain the presence of two cleavage sites on IgA protease of ST-11 isolates and the production of two forms: an α-peptide-free smaller form , IgaP ( ~100 kDa ) and a predominant α-peptide-linked peptidase longer form , IgaPα ( ~150-kDa ) . Non-ST-11 isolates release the only IgaP smaller form . Consistently , the nalP gene was in “phase on” status in all the isolates of our study , further suggesting that the absence of released IgaPα in non-ST-11 isolates is related to the lack of the cleavage site downstream α-peptide , leaving the α-peptide domain associated with the outer-membrane-embedded β core instead of being released extracellularly . A previous report suggested that NLS-carrying α-peptide of the gonococcal strain MS11 mediate nuclear targeting of reporter proteins but failed to detect IgA protease in the nuclear compartment of infected cells [29] . Indeed , MS11 gonococcal strain lacks a functional NalP protein that is responsible for release of IgA protease linked to α-peptide . Recently , Roussel-Jazédé et al . [74] reported the lack of NalP expression from the FAM18 strain , a ST-11 invasive isolate that harbor a second autocleavage site separating the α peptide from the translocator domain . FAM18 was unable to express a protease domain associated to α peptide ( IgaPα ) . Consistently , the ratio of IgaPα to IgaP was strongly decreased in our NalP mutant of the ST-11 isolate LNP19995 . Although NalP was not detected in the nuclear fractions of ST-11 infected cells ( Fig 3C ) , our results may suggest a role of NalP in the down regulation of NF-κB activity most likely by modulating the alternative autocleavage site of IgA protease , providing therefore a stable passenger IgaPα able to interact with target cells and hence reach the nuclear compartment . Our DsRed-chimeric fusion proteins and heterologous substitutions of iga alleles between ST-11 and non-ST-11 isolates further suggest that the attentive cleavage site by NalP is requested for NLS-harbouring α-peptide to act as carriers for nuclear transport of IgA protease to target the regulatory function of p65/RelA and probably other eukaryotic proteins . Like many respiratory invasive bacterial pathogens , N . meningitidis colonize the epithelium of the nasopharynx , at the upper respiratory tract . Acquisition of N . meningitidis at this portal of entry may be asymptomatic or result in local inflammation [75] . A study after an epidemic in Burkina Faso reported that coughing , nasal congestion or sore throat during the preceding month were associated with carriage of the W135 associated outbreak strain that belong to the clonal complex ST-11 [76] . Induction of inflammatory response at this site could be beneficial for the invasive strains to induce cell death . Neutralization of infected cells by apoptosis may allow bacteria to persist or disseminate to deeper sterile sites . The modulation of the inflammatory response during meningococcal bacteraemia , may also enhance the death of endothelial cells and the permeability of the blood-brain barrier leading to dissemination of the bacteria to meninges [20] . Sustained NF-κB activity would allow commensal relationship of carriage isolates at their ecological niche through eradication of the alternative cleavage site on the IgA protease . This site present in the hyperinvasive ST-11 isolates may contribute to their ability to invade the host .
RPMI-Glutamax , Fetal calf serum ( FCS ) , trypsin-EDTA and penicillin/streptomycin solution were purchased from Gibco Laboratories ( Saint Aubin , France ) , FITC-Annexin V , and propidium iodide , were purchased from R & D Systems ( Lille , France ) . Lipopolysaccharide of E . coli Serotype O55:B5 , protease inhibitor cocktail tablets , phenylmethylsulfonyl fluoride ( PMSF ) , protein A-agarose beads , cycloheximide and antibiotics were from Sigma ( Saint-Quentin-Fallavier , France ) . Rabbit polyclonal to NF-κB p50 , goat polyclonal antibody to C-terminal ( residues 501–551 ) , mouse monoclonal antibody to N-terminal ( residues 136–224 ) NF-κB p65 , rabbit polyclonal anti-histone H3 and anti-His6 tag mAb were obtained from abcam ( Paris , France ) . Mouse anti-IκBα monoclonal antibody was purchased from Life technologies ( Saint Aubin , France ) . Rabbit anti-GAPDH was from Sigma Aldrich ( Saint-Quentin-Fallavier , France ) . Rabbit antibodies directed against JNK and its phosphorylated form were obtained from Cell signaling ( Leiden , The Netherlands ) . HRP- and Texas red-conjugated secondary antibodies were purchased from Jackson immunoreseach ( Marseille , France ) . Escherichia coli strain DH5α [77] was used for plasmid preparation and E . coli BL21 ( DE3 ) pLysS [78] , was employed for overexpression of His6-tagged proteins . When indicated ampicillin , kanamycin , spectinomycin or chloramphenicol were added at final concentrations of 100 μg . ml-1 , 50 μg . ml-1 , 40 μg . ml-1 and 15 μg . ml-1 , respectively . N . meningitidis clinical isolates in France are sent to the National Reference Centre for Meningococci ( NRCM ) for full typing . N . meningitidis was grown in GCB medium with Kellog supplements [79] . Phenotypes ( serogroup: serotype: serosubtype ) and MLST genotypes were determined as previously described [80] . Sequence types ( ST ) and clonal complexes were assigned using the Neisseria MLST database ( http://pubmlst . org/neisseria ) . Phenotypic and genotypic characteristics of all N . meningitidis strains used in this study are listed in S1 Table . Meningococcal Secreted proteins ( MSPs ) were prepared as previously described [81] . Preparations contained between 375–560 μg ml−1 proteins . Anti-PorA monoclonal antibodies ( NIBSC , UK ) were used to check for contaminating outer membrane proteins . Genomic and plasmid DNA were extracted using Qiamp DNA mini kit ( Qiagen , Courtaboeuf , France ) and PureLink Quick plasmid Miniprep Kit ( Life Technologies , Saint Aubin , France ) , according to manufacturer instructions , respectively . All restriction and modification enzymes were used according to manufacturers’ recommendations . All primers used in this study were purchased from Sigma and are listed in S2 Table . As iga gene from LNP19995 and LNP21019 had not been sequenced , we selected primers based on conserved sequences in other meningococcal and gonococcal iga alleles described previously ( strains MC58 , Z2491 and Ng44/76 with accession numbers AE002424 , AL162754 and X82481 , respectively ) . The iga knockout construct was obtained as follows . Two DNA fragments of 534 bp and 475 bp ( corresponding to positions 24 to 554 and 4950 to 5448 of MC58 iga orf , respectively ) were amplified by PCR from chromosomal DNA of the stain LNP19995 using primer pairs iga5’Fw/iga5’Rev and iga3’FwEcoRI /iga3’RevNcoI , respectively . Both PCR products were purified , digested with appropriate restriction enzymes , when adapter sites were included in the primers , and sequentially cloned into pGEM-T-easy ( Promega , Charbonnieres , France ) , with in between a PCR-generated spectinomycin-resistance cassette ( aadA ) from pHP45Ω-spec [82] that was inserted into the blunt-ended EcoRI site to yield plasmid pGEM-iga::aad . This plasmid was linearised by SalI restriction enzyme and transformed into LNP19995 ( ST-11 ) and LNP21019 ( non-ST-11 ) meningococcal isolates by homologous recombination and allelic replacement . Transformants were selected on 70 μg . ml-1 spectinomycin-supplemented GCB agar plates . The chromosomal configuration of spectinomycin-resistant strains was confirmed by PCR and DNA sequencing . One candidate from each transformation was named 19995Δiga and 21019Δiga , respectively and was selected for further analysis . To generate complemented strains , iga gene was amplified using the primers iga5’Fw and iga3’RevNcoI ( nucleotide 24 to 5448 , according to MC58 nucleotide sequence ) from LNP19995 or LNP21019 strains . The amplified fragments were inserted separately into pGEM-T-easy vector to generate the recombinant plasmids pGEM-iga19995 and pGEM-iga21019 , respectively . Then , a 180 bp fragment corresponding to down-stream iga stop codon was generated by PCR using primers igadownFw-Nco and igadownRev and was inserted into blunt-ended NcoI site of pGEM-iga19995 or pGEM-iga21019 vectors . This insertion led to generate a new NcoI site in between iga and the fragment downstream . Finally , a blunt-ended erythromycin resistance cassette erm generated by PCR from the plasmid pMGC20 [83] using the primers ERAM1 and ERAM3 , was inserted into the blunt-ended NcoI site . The leading recombinant plasmids were named pIga19995-erm and pIga21019-erm . These plasmids were linearised with SalI restriction enzyme and each plasmid was transformed into both strains 19995Δiga and 21019Δiga . Transformants that lost resistance to spectinomycin and acquired resistance to erythromycin were selected and named 19995Δiga/iga19995 , 21019Δiga/iga19995 ( for transformants generated with the plasmid pIga19995-erm ) and 19995Δiga/iga21019 and 21019Δiga/iga21019 , ( for transformants generated with the plasmid pIga21019-erm ) , respectively . Correct replacement of deleted iga with the wild type alleles was verified by PCR and restored expression of IgA protease was confirmed by immunoblotting . Inactivation by replacement of the active-site serine ( 267S ) with a valine residue was accomplished by site-directed mutagenesis using the PCR-based megaprimer method [84] . The mutagenic primers igamutRev coding for replacement of serine with valine at position 267 , was used in combination with the igapFwBsa primer ( S2 Table ) . The 672 bp PCR product generated was gel purified and used as large forward primer ( megaprimer ) in a second PCR together with the reverse primer iga3’RevNcoI ( S2 Table ) to amplify the 5307-bp iga fragment . This product was subcloned into pGEM-T-easy to generate the plasmid pGEM-igaS267V . Then , the 180 bp fragment corresponding to down-stream iga stop codon was generated by PCR using primers igadownFw-Nco and igadownRev and was inserted into blunt-ended NcoI site . This insertion led to generate a new NcoI site in between mutated iga and the fragment downstream that was used to insert blunt-ended erythromycin resistance cassette leading to a recombinant plasmid pGEM-igaS267V . This plasmid was linearised with SalI restriction enzyme and was transformed into strain 19995Δiga . Transformants that lost resistance to spectinomycin and acquired resistance to erythromycin were selected and named 19995igaS267V . Correct replacement of deleted iga with the S267V mutation was confirmed with PCR and DNA sequencing . To generate a 19995ΔnalP mutant strains , 2175 bp nalP fragment extending from nucleiotides 473 to 2647 ( according to MC58 orf ) was amplified by PCR from LNP19995 genomic DNA using the primers nalPKOFw and nalPKORev ( S2 Table ) . The PCR fragment was subcloned into pGEM-T-easy to generate the pasmid pGEM-nalP . The erm cassette conferring resistance to erythromycin was inserted into the blunt-ended restriction site of pGEM-nalP , resulting to the recombinant plasmid pGEM-nalP::erm . This vector was linearised with NcoI and was transformed into LNP19995 . Transformants were then selected on plates containing erythromycin at 2 μg . ml-1 . Correct inactivation of nalP gene was verified by PCR and immunoblotting using specific serum directed against NalP . One transformant was named 19995ΔnalP and was selected for further analysis . PCR-generated fragments encoding the protease domain ( IgaP ) , α-peptide ( Igaα ) or both associated sub-domains IgaPα of IgA protease were generated from strains LNP19995 and LNP21019 using the couple of primers igapFwBsa/igapRevXho , alphaFwBsa/alphaRevXho and igapFwBsa/alphaRevXho , respectively . The PCR fragment encoding the protease domain harbouring the active site mutation S267V was also generated using the primers igapFwBsa/igapRevXho and pGEM-igaS267V as template . The PCR products were digested with BsaI and XhoI restriction enzymes and inserted between NcoI and XhoI restriction sites of the plasmid pET28b ( Addgene , Middlesex , UK ) to generate C-terminal His6-tagged fragments . The resulting recombinant plasmids ( pIgaP19995 , pIgaP21019 , pIgaα19995 , pIgaα21019 , pIgaPα19995 and pIgaPα21019 , respectively ) were used to transform , over-express and purify the different cloned domains from E . coli BL21pLysS strain as described elsewhere [85] . To generate C-terminal DsRed-tagged domains , the same fragments were similarly amplified from each strain using the primers igapFwNhe/ igapRevSma , alphaFwNhe/ alphaRevSma and igapFwNhe/alphaRevSma . The resulting fragments were digested with NheI and SmaI restriction enzymes and inserted into pDsRedN1 ( Clonetech , France ) opened with the same enzymes to yield the recombinant plasmids pIgaP-Red19995 , pIgaP-Red21019 , pIgaα-Red19995 , pIgaα-Red21019 , pIgaPα-Red19995 and pIgaPα-Red21019 Anti-NalP antiserum was a generous gift from Dr . Isabel Delany ( Novartis Vaccines , Research Center , Siena , Italy ) . To produce mouse serum against secreted Meningococcal proteins ( MSPs ) , 6-week-old BALB/c mice were injected subcutaneously on days 1 with 30 μg of MSPs that were emulsified with Freund’s complete adjuvant ( 1:1 , v/v ) in a 500 μl total volume prior to injection . This injection was followed at days 14 and 21 by two MSPs booster injections in sterile PBS . On day 30 , animals were test bled in comparison to pre-immune serum . Mice were sacrificed and sera were collected by cardiac puncture and stored at -20°C . Rabbit polyclonal serum against the protease sub-domain IgaP was prepared using purified His6-tagged IgaP of the strain LNP19995 . Polyclonal serum was produced by immunizing a New Zealand White rabbit once with 30 μg of the purified protein mixed with Freund's complete adjuvant and twice with the same amount of antigen mixed with Freund's incomplete adjuvant at 2 week intervals . The animal was test bled 7 days after the third immunisation . The animal was sacrificed and the serum was stored at −20°C . Pre-immune serum was obtained before immunization . Before use in immunoblots , rabbit serum was pre-adsorbed for 3 h at 37°C with a 10% ( v/v ) suspension of each 19995Δiga and 21019Δiga mutants before being cleared by centrifugation at 14000 g at 4°C . All experiments including immunizations and bleeding of animals were performed according to the European Union Directive 2010/63/EU ( and its revision 86/609/EEC ) on the protection of animals used for scientific purposes . Our laboratory has the administrative authorization for animal experimentation ( Permit Number 75–1554 ) and the protocol was approved by the Institut Pasteur Review Board that is part of the Regional Committee of Ethics of Animal Experiments of the Paris region ( CETEA 2013–0190 ) . Hec-1-B cells ( American Type Culture Collection , Manassas , VA ) were maintained in RPMI containing 10% FCS and 1X penicillin/Streptomycin until a confluence of 80% . A549 alveolar epithelial cells were cultured in DMEM ( Invitrogen , France ) plus 10% FBS , 2mM L-glutamine , 50 U/mL penicillin , and 1X penicillin/Streptomycin until 80–85% of confluence . Depending on experiments , cells were seeded in 24-well plates , 10-cm diameter dish plates or 75cm2 flasks at a density of 5 . 105 cells/cm2 in antibiotic-free medium . Prior to infection , cells were washed and incubated with bacteria at bacteria to cell ratio of 25:1 . When stated , infection was performed in presence of 20μg . ml-1 cycloheximide , 5 mM PMSF or 5 μg . ml-1 chloramphenicol ( a concentration that was sufficient to block bacterial protein synthesis , as judged by growth inhibition , but low enough to allow survival of bacteria as judged by growth resumption , when chloramphenicol was removed ) . All transfections were carried-out in OptiMEM medium ( Life Technologies , France ) in absence of antibiotics using Lipofectamine 2000 ( Life Technologies , France ) according to the manufacturer’s protocol . Plasmid p ( Igκ ) 3conaluc was a generous gift from Pr . Alain Israel’s laboratory . Before transfection , cells were washed extensively and were then transfected with 2 μg/ml of each p ( Igκ ) 3conaluc [86] and pCMVβ ( Addgene , Middlesex , UK ) . Fourty eight hours post-transfection , cells were washed using PBS and then infected as indicated above . At indicated time points , luciferase activity was performed as described previously ( 19 ) . Results are reported as relative luciferase units ( RLU ) after normalizing for β-galactosidase activity and protein concentration . For immunofluorescence microscopy , cells were first grown on 12-mm glass coverslips . Adherent cells were then transfected with 2 μg/ml of DsRed fusion constructs as before and then proceeded for immunofluorescence microscopy . Total RNA was extracted from infected or uninfected Hec-1-B monolayer cells at indicated time points using RNeasy Mini Kit ( 50 ) ( Promega , France ) according to the manufacturer's instructions . Two hundred nanograms of RNA were used as the template in the reverse transcription reaction . The total cDNA was obtained by reverse transcription PCR using the oligo ( dT ) 18 primer and AMV reverse transcriptase ( Biolabs , France ) as described elsewhere [87] . The mRNA sequences for the target genes ( IL-8 , TNF-α , and cFLIP and β-actin of Homo sapiens ) were obtained from the GenBank database ( http://www . ncbi . nlm . nih . gov/ ) . β-Actin was used as an internal control . Specific primers were designed using Primer Premier 5 . 0 ( S2 Table ) and synthesized by Sigma Aldrich ( France ) . The qPCR reaction was performed on an Applied Biosystems model StepOne plus in triplicate using 25 ng of cDNA and SYBR green Universal PCR Master Mix in a total volume of 25 μl . The program consisted of an initial denaturation at 95°C for 10 min , followed by 40 cycles of 95°C for 15 s and 60°C for 1 min . Quantification of the targets was performed relative to uninfected sample using β-actin as internal control and the 2−ΔΔCT method [88] . Intact nuclei were sorted by adapting a previously described flow cytometer sorting-based technique [89] . Briefly , Hec-1-B cells infected with GFP-expressing bacteria ( S1 Table ) or left uninfected were washed carefully with PBS and harvested by centrifugation at 1500 g for 10 min . Unless otherwise indicated , the following steps were carried-out at 4°C . Cells were resuspended in 1 ml phosphate-buffered salin ( PBS ) , pH 7 . 5; supplemented with a cocktail of protease inhibitors and 50 μg . ml-1 RNase A ( Thermo Scientific , France ) . Cells were homogenized by several strokes through a 26 gauge-needle attached to a 1 ml syringe until 80–90% lysis was reached as judged under light microscope . Samples were then centrifuged for 15 min at 1500 rpm . Supernatant containing cytosolic fraction was saved at -80°C until use and the pellet containing a mix of free nuclei , cell debris , unbroken cells and bacteria , was carefully resuspended in 500 μl PBS and stained for 15 min with 5 μg . ml-1 propidium iodide ( PI , red fluorescence ) at 4°C in the dark to label free nuclei or cells that lost membrane integrity . After staining , samples were washed with PBS , pelleted for 15 min at 1500 rpm and resuspended in 1 ml PBS . Samples were analyzed using a FACSCalibur flow cytometer ( BD Biosciences ) equipped with an argon laser emitting at 488nm for the excitation of PI and GFP . Preliminary control experiments included non-labelled bacteria , GFP-expressing bacteria , lysed or intact cells stained or not with PI , confirming location of the fractions in the homogenized sample . Free nuclei were first discriminated from intact cells by SS ( side scatter ) , FS ( forward scatter ) and FL2 ( red fluorescence ) parameters . GFP-positive ( FL-1 ) events characterizing bacteria were then excluded from the sorted gate . Then , free nuclei defined as PI-positive and GFP–negative populations were gated in the region R4 ( See S3 Fig ) and were sorted using single cell sorting mode adjusted to 250–300 events/s , thereby limiting the generation of coincidental events . Sorted population was re-analyzed to confirm purity . Relative intensities of SS , FL1 and FL2 were recorded as log scale , 1024 channels and 4 decades . Relative intensities of FS was recorded as linear scale . To validate the sorted population , nuclei were examined by immunofluorescence microscopy after DAPI staining and immunoblotted for specific nuclear markers . Sorted nuclei were pelleted at 3000 rpm for 15 min at 4°C , resuspended in 150 μl rehydration buffer ( 8 M urea , 2% CHAPS , 2% IPG buffer , 20 mM DTT and 0 . 002% Bromophenol Blue ) and analyzed by two dimensional gel electrophoresis ( 2DGE ) as described elsewhere [90] . Proteins were first separated according to their isoelectric point ( pI ) in the immobilin Dry-Strip pH 3–10 ( Biorad ) using IPGphor isoelectric focusing system ( Amersham Biosciences , Piscataway , NJ ) . After equilibration , proteins separated on the strips were layered on 12% SDS-PAGE gels and subjected to electrophoresis . Gels were then subjected to immunoblotting using mouse serum directed against secreted meningococcal proteins , rabbit serum specific to IgA protease domain or respective pre-immune sera . Hec-1B cells were stimulated for 1h with 10 μg . ml-1 LPS of E . coli 0111:B4 . Nuclear extracts were prepared as described by Philpott et al . [91] and were used as a source of translocated p65/RelA . One microgram of this fraction was incubated with increasing amounts of purified IgA protease domains IgaP , Igaα , or IgaPα in a final volume of 20 μl of reaction buffer ( 10 mM Tris-HCl pH 7 . 4 , 150 mM NaCl , 0 . 5 mM DTT , 2 . 5 mM CaCl2 , and 0 . 5 mM MgCl2 ) . In another set of experiments , 500 ng of purified IgaPα19995 or IgaPα21019 were incubated with 5 or 10 μg of MSPs from LNP19995 or LNP21019 , respectively in a final volume of 20 μl of the same reaction buffer . The reaction mixtures were incubated at 25°C for 3 h . The reaction was stopped with 1 X Laemmeli buffer and separated in 10% SDS-PAGE before immunobloting using appropriate antibody ( anti-p65/RelA antibodies or anti-His tag mAb ) . IgA protease activity was performed as described elsewhere [92] . Adherent cells were washed carefully , harvested by centrifugation at 1500 g for 5 min at 4°C and stained with 10 μl FITC-conjugated annexin V and 5 μg/ml propidium iodide ( PI ) and analyzed using flow cytometer FACSCalibur ( BD Biosciences , Germany ) as indicated elsewhere ( 18 ) . Data were analyzed using Cyflogic software v . 1 . 2 . 1 . Cells were fixed for 20 min in 3 . 7% paraformaldehyde in PBS for 15 min . When indicated , cells were permeabilised with 0 . 5% Triton-X in PBS containing 2% BSA , and subsequently stained for immunofluorescence microscopy as described before ( 18 ) . Slides were then viewed with a conventional immunofluorescence microscope Zeiss Axio Imager D1 coupled to AxioCam MRm vers . 3 ( Carl Zeiss , Germany ) . Digital images were acquired using appropriate filters and combined using the Axiovision Rel . 4 . 6 software ( Carl Zeiss ) . Cell fractions ( cytosolic and nuclear fractions ) were prepared as described elsewhere [91] . LNP19995 and iga deletion mutant 19995Δiga were grown in GC medium base until midlog phase . Then bacteria were centrifuged and the supernatant was concentrated 50 X nd incubated with 500 μg of nuclear extracts prepared from LPS-stimulated Hec-1-B cells ( that served a source of translocated NF-κB ) in presence of 5 mM PMSF as serine protease inhibitor . After 6h of incubation , 5 μg of anti-IgaP rabbit serum ( or rabbit irrelevant antibody ) or 1 μg of anti-N-terminal p65/RelA mAb ( or irrelevant mouse IgG mAb antibody ) were added and immunoprecipitation was performed as described elsewhere [93] . Protein complexes were solubilised in 1× Laemmeli buffer , resolved by SDS-PAGE and transferred to polyvinylidene difluoride ( PVDF ) membrane that was probed with appropriate primary antibodies . The immunoreactive band was visualized using appropriate HRP-conjugated secondary IgG antibody and ECL detection reagents ( Amersham Pharmacia Biotech , France ) . The membranes were visualized using ChemiDoc XRS imager and QuantityOne 4 . 6 software ( Bio-Rad ) . Total RNA was isolated from plate-grown bacteria using a hot-phenol method described by Ducey et al . [94] . cDNA specific to trpB gene ( encoding tryptophane synthase beta chain ) downstream iga gene was generated from 2 μg total RNA with trpBRev primer using SuperScript II RT-PCR kit according to manufacturer instructions ( Invitrogen ) . The PCR step was performed using trpBFw and trpBRev primers ( S2 Table ) . Expression of porA was performed as internal control using primers porA0 and porA101 ( S2 Table ) . The genome databases of strain MC58 was interrogated using the server available at http://microbes . ucsc . edu/lists/neisMeni_MC58_1/refSeq-list . html . PCR products were sequenced by Eurofins-Cochin ( Paris , France ) . DNA and protein sequence analysis was carried out using BioEdit Sequence Alignment Editor Software Version 7 . 2 . 5 available at http://www . mbio . ncsu . edu/bioedit/bioedit . html . Data were analyzed by two-way ANOVA test using the software GraphPad Prism version 4 . 00 for Windows ( Graph-Pad Software , San Diego , California , USA , www . graphpad . com ) . P < 0 . 05 was considered statistically significant .
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Strains of Neisseria meningitidis isolated from patients induce apoptotic cell death , whereas strains isolated from healthy carriage isolates do not . Part of the difference has been shown to arise from differential modulation of NF-κB during meningococcal infection . While non-invasive isolates of Neisseria meningitidis provoke a sustained NF-κB activation in epithelial cells , hyperinvasive isolates only induce an early NF-κB activation followed by a sustained activation of JNK and apoptosis . Here , we elucidate the mechanism conferring this differential modulation , specifically showing that ST-11 hyperinvasive isolates promote specific cleavage of NF-κB p65/RelA component in a manner dependent on the secreted IgA protease . This cleavage occurs within the nuclear compartment . Secreted IgA protease from non-invasive isolates was unable to reach the nuclear compartment of infected cells , resulting in a sustained activation of NF-κB activity and subsequent cytoprotective effect . Modulation of NF-κB-related signaling is likely a double-edged sword to decide the fate of meningococcal infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Hyperinvasive Meningococci Induce Intra-nuclear Cleavage of the NF-κB Protein p65/RelA by Meningococcal IgA Protease
|
Very solid evidence suggests that the core of full length PrPSc is a 4-rung β-solenoid , and that individual PrPSc subunits stack to form amyloid fibers . We recently used limited proteolysis to map the β-strands and connecting loops that make up the PrPSc solenoid . Using high resolution SDS-PAGE followed by epitope analysis , and mass spectrometry , we identified positions ~116/118 , 133–134 , 141 , 152–153 , 162 , 169 and 179 ( murine numbering ) as Proteinase K ( PK ) cleavage sites in PrPSc . Such sites likely define loops and/or borders of β-strands , helping us to predict the threading of the β-solenoid . We have now extended this approach to recombinant PrPSc ( recPrPSc ) . The term recPrPSc refers to bona fide recombinant prions prepared by PMCA , exhibiting infectivity with attack rates of ~100% . Limited proteolysis of mouse and bank vole recPrPSc species yielded N-terminally truncated PK-resistant fragments similar to those seen in brain-derived PrPSc , albeit with varying relative yields . Along with these fragments , doubly N- and C-terminally truncated fragments , in particular ~89/97-152 , were detected in some recPrPSc preparations; similar fragments are characteristic of atypical strains of brain-derived PrPSc . Our results suggest a shared architecture of recPrPSc and brain PrPSc prions . The observed differences , in particular the distinct yields of specific PK-resistant fragments , are likely due to differences in threading which result in the specific biochemical characteristics of recPrPSc . Furthermore , recombinant PrPSc offers exciting opportunities for structural studies unachievable with brain-derived PrPSc .
Prions are infectious proteins [1 , 2] . They propagate by inducing the host’s isosequential normal cellular prion protein ( PrPC ) to adopt the infecting prion’s conformation [2] . Prions can be transmitted from one organism to another by different means , for example by oral route [2 , 3] , hence their infectious nature . Prions pique an extraordinary theoretical and experimental interest because they challenge the notion that only nucleic acids are able to transmit heritable information . But they are also of critical practical importance , since some of them are associated with devastating neurodegenerative diseases . In particular , the mammalian PrPSc ( prion protein , “scrapie” isoform ) is the causal agent of the fatal transmissible spongiform encephalopathies ( TSEs ) [2–4] . TSEs affect both humans and agriculturally important animals , and while PrPSc prions typically remain contained within a given species , transmission of bovine PrPSc to humans occurred in the aftermath of the massive European bovine spongiform encephalopathy epizootic , killing more than 200 people and generating widespread alarm [5 , 6] . Fortunately , through the intervention of regulators , the crisis has largely abated , although transmission of CJD through blood transfusion remains a concern [5] . This leaves only sporadic Creutzfeldt-Jakob disease ( CJD ) , a rare ailment with a yearly incidence of ~1 case per million people , as the main human prion disease [2 , 3] . Elucidating the molecular mechanism that governs the propagation of PrPSc , including the aforementioned transmission barriers has been a central issue and a challenge in prion research since these agents were first discovered [1] . This endeavor has been linked to the quest to elucidate the structure of PrPSc , an obvious pre-requisite to understand how such conformation propagates , i . e , how it is copied . In this respect , it is important to note that most known prions , and in particular , PrPSc , form amyloids [4 , 7–9] . Therefore , the main force driving and modulating prion propagation must be templating of an incoming partially or totally unfolded prion precursor protein molecule by the upper and lower surfaces of the amyloid fiber . These contain “sticky” β-strands ready to form an array of hydrogen bonds and thereby induce the formation of a new β-strand-rich layer , thus promoting growth of the amyloid filament in the direction of its axis . A recent cryo-electron microscopy study has determined the outline of the architecture of GPI-anchorless PrPSc , showing that it is a 4-rung β-solenoid [10] . This agrees with prior fiber X-ray diffraction [11 , 12] , 2D electron crystallography [11 , 13] and SAXS-based [14] studies of other brain-derived wild type ( wt ) PrPSc molecules leading to a similar conclusion . On the other hand , another recent study has shown that shorter PrP sequences , such as PrP23-144 , can adopt a flat , in-register amyloid architecture which is also infectious [15] . During propagation of multi-rung β-solenoidal structure , only the upper and lower rungs participate in inter-molecular hydrogen bonding . Identifying the specific amino acid residues that participate in β-strands , in particular those that make up the templating interfaces is essential to understand the details of PrPSc propagation , and , critically , to understand transmission barriers . In the past , we have used limited proteolysis to probe PrPSc , in an attempt to identify sequential stretches that comprise β-strands vs . those that constitute the random coil loops/turns of PrPSc . It should be noted that , in contrast with early hypotheses , the elegant studies of the Surewicz and Caughey groups [16 , 17] demonstrated that no α-helical secondary structure is likely to exist in PrPSc . Data from deuterium/hydrogen exchange studies , and limited proteolysis experiments are incompatible with the presence of any substantial amount of α-helical structure , and a critical reassessment of FTIR studies strongly suggests that absorbance peaks ascribed to α-helices is likely to have been a mis-assignment [9] . Using two analytical approaches , high resolution SDS-PAGE combined with epitope analysis , and mass spectrometry , we identified positions ~116/118 , 133–134 , 141 , 152–153 , 162 , 169 and 179 ( murine numbering ) as PK cleavage sites in brain-derived PrPSc . These sites likely define loops and/or borders of β-strands , and are helping us to define the hypothetical threading of the β-solenoid [18] . In this context , recPrPSc is a very attractive tool for structural studies , given that it allows the introduction of the sequence variations , labels and isotopically labeled amino acid residues necessary for rigorous NMR studies . A number of recombinant PrP preparations with different degrees of infectivity have been described since the seminal report by Legname et al . [19–22] . Recently , Wang et al . generated recPrPSc exhibiting incubation times similar to those of brain-derived PrPSc of the same sequence and causing the same pathogenic changes as that of wt prion disease [23 , 24] . While incubation times should be considered very cautiously , given that a long incubation time can be the result of low titer but also of a transmission barrier , the study by Wang et al . has led to the definitive acceptance that bona fide , highly infectious recPrPSc can be generated in vitro . As a corollary , the possibility to use the versatile recPrPSc as a convenient model for elucidation of the structure of PrPSc in general was opened . Here , we report studies to probe the structure of infectious recPrPSc using limited proteolysis . Mouse and bank vole ( Myodes glareolus ) recPrPSc prions yield an array of N-terminally truncated PK-resistant fragments very similar to that seen after PK treatment of brain-derived PrPSc . This is strongly supportive of shared key architectural elements between both prion types .
The following reagents were obtained from the indicated commercial sources: PNGase F , from New England Biolabs ( Ipswich , MA , USA ) ; Tris/Tricine electrophoresis buffer and Broad-Range SDS-PAGE Standards from BioRad ( Hercules , CA , USA ) ; Sypro Ruby dye , and Novex Sharp Pre-stained Portein Standard , from Thermo-Fisher ( Whaltman , MA , USA ) ; Immobilon P 0 , 45 μm PVDF membranes , from Millipore ( Billerica , MA , USA ) ; Ultra-low Range Molecular Weight Marker , Pefabloc , PMSF and PK , from Sigma-Aldrich ( St Louis , MO , USA ) . All other reagents were from Sigma-Aldrich unless otherwise indicated . Antibody R1 , which recognizes PrP epitope 225–230 [25] , was a generous gift from Anna Serban , Institute for Neurodegenerative Diseases , UCSF , and was used at a 1:5000 dilution; antibody #51 , which recognizes PrP epitope 92–100 [26] was kindly provided by Lothar Stitz , Fridrich Loeffler Institut , Insel Reims , Germany , and was used undiluted; antibody 3F10 , which recognizes PrP epitope 137–151 [27] was a generous gift from Yong-Sun Kim , Hallym University , Republic of Korea , and was used at a 1:5000 dilution . Antibody SAF-84 , which recognizes PrP epitope 165–172 , was from Thermo Fisher Scientific ( Rockford , IL , USA ) , and as used at a 1:5000 dilution . Secondary antibodies were goat anti-human ( Thermo Fisher ) and goat anti-mouse ( GE Healthcare Life Science , Chicago , IL . USA ) , used to detect R1 , 3F10 and #51 , respectively; both were used at a 1:5000 dilution . Recombinant mouse PrP23-230 ( MoPrP23-230 ) was expressed in E . coli competent cells . Bacteria were harvested by centrifugation at 5 . 000 g . Bacterial pellets were lysed by incubation for 30 minutes at room temperature with shaking in lysis buffer ( 50mM Tris-HCl , 5mM EDTA , 1% Triton X-100 , 1mM PMSF , 100 μg/ ml lysozyme , pH = 8 ) ; MgCl2 and DNase I were then added to 20mM and 5μg/ml final concentrations , respectively , and further incubation at room temperature carried out for 30 minutes . Inclusion bodies thus obtained were collected by centrifugation at 20 . 000 g at 4°C for 20 minutes , and solubilized with inclusion body solubilization solution ( 6M Gn/HCl , 10 mM of Tris-HCl , 100 mM Na2HPO4 and 10 mM β-mercaptoethanol , pH = 8 . 0 ) . The solubilized sample was then filtered through a 0 . 22 μm filter and loaded to a 5 ml FF Crude His-Trap column ( GE Healthcare , Life Sciences ( Chicago , IL . USA ) connected to a 1200 Series HPLC system ( Agilent Technology , Santa Clara , CA , USA ) . The column was washed with inclusion body solubilization solution and refolded in-column by gradually diminishing the concentration of Gn/HCl and β-mercaptoethanol with a gradient of 10 mM of Tris-HCl , 100 mM Na2HPO4 , pH = 8 . 0 over 100 minutes; recMoPrP23-230 was then eluted with 30 ml of 200 mM imidazole in10 mM Tris-HCl , 100 mM Na3PO4 , pH = 8 . 0 ) . The eluate was dialyzed against10mM NaH2PO4 , pH = 5 . 8 , and subsequently against d . i . H2O at 4°C . Dialyzed samples were centrifuged to eliminate any aggregated material present and stored at -80°C until used for conversion to recPrPSc . Bank vole PrP23-231 ( BVPrP23-231 ) was expressed following the same protocol , and similarly applied to a His-Trap column as described above; however , it was eluted from the column by application of a solution consisting of 10 mM Tris-HCl , 2M Gn/HCl , and 100 mM Na2HPO4 , pH = 8 . 0 . Elution fractions containing PrP , as determined by SDS-PAGE with Coomassie staining , were then folded by dialysis against 10 mM sodium acetate , pH = 5 . Precipitated material was removed by centrifugation . Two preparations of recombinant ( rec ) murine PK-resistant ( PK-res ) PrP and one of recombinant bank vole PK-res PrP were analyzed in this study; all of them were prepared using different variants of recombinant PMCA ( recPMCA ) . Recombinant MoPrPSc-17kDa was prepared in Grand Rapids ( USA ) and has been described before [23] . Briefly , it was generated de novo from recMoPrP23-230 by recPMCA in the presence of POPG and RNA and its infectivity has been tested in WT mice resulting a 100% attack rate [23 , 24] . A recMoPrPSc ( vide infra with regard to its infectivity properties ) was generated in Bilbao , Spain , from recMoPrP23-230 expressed , purified and folded as described above , by means of recPMCA seeded with recMoPrPSc-17kDa in the presence of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol ( POPG ) and RNA [23 , 24] . This sample was termed recMoPrPSc-950 . A sample of recBVPrPSc ( vide infra ) was prepared by seeded recPMCA using a protocol that will be detailed elsewhere . Briefly , recBVPrP23-231 ( 109I ) prepared , purified and folded as described above , was used as a substrate in a mixture that contains dextran and detergent and that was subjected to several cycles of PMCA; the initial seed used was a small portion of brain homogenate from a bank vole ( 109I ) infected with deer CWD prions . Transgenic homozygous GPI-anchorless ( GPI- ) PrP mice ( tg44-/- ) , were obtained by crossing of tg44 ( +/- ) heterozygous ( GPI- ) PrP mice [29] , generously provided by Bruce Chesebro , Rocky Mountain Laboratories , NIH , USA [26] . This GPI-anchorless tg mouse model is the same that we have used in the past [26]; additional GPI-anchorless tg mouse models have been developed [30] . Female mice were inoculated ic at six weeks of age with 20 μl of a 2% RML-infected mouse brain homogenate , kindly provided by Juan María Torres , CISA , Madrid , Spain . After 365 days post inoculation , mice were euthanized , their brains surgically removed , rinsed in PBS , and stored at -80 °C until needed . A 10% w/v , brain homogenate was prepared in PBS , 5% sarkosyl , using a dounce homogenizer ( Wheaton Industries Inc , NJ , USA ) , followed by one pulse of sonication to clarify the homogenate , with an ultrasonic homogenizer probe ( Cole Parmer Instrument CO . , Chicago IL , USA ) . The brain homogenate was treated with 25μg/ml of PK for 30 minutes at 37°C , and then deglycosylated with PNGase F following the manufacturer´s recommendations . RecMoPrPSc was treated with 10 μg/ml PK , at 37°C for 30 minutes . The reaction was quenched by adding 2 mM Pefabloc and incubated for 15 minutes on ice . PK-resistant fragments were then pelleted by centrifugation at 18 . 000 g at 4°C for 1 hour using a ( Microfuge 22R centrifuge , Beckman Coulter ) . Under these conditions , all PK-resistant fragments are recovered in the pellet ( S1 Fig ) . Pellets were resuspended in 6M Gn/HCl and stored at -20°C until use . PK-resistant fragments were precipitated with ice-cold 85% MeOH . Pellets were resuspended in MiliQ H2O and Tricine buffer in a ratio 1:2 . Reduction was carried out by adding β-mercatoethanol to 2% ( v/v ) . Samples were boiled for 10 minutes . High resolution electrophoresis was carried as described by Vázquez-Fernández et al . [26] . After electrophoresis , gels were washed with miliQ H2O and incubated with fixing solution ( 10% MeOH , 7% acetic acid ) for 1 hour at room temperature . Sypro Ruby staining was then performed by incubation overnight at room temperature in the darkness . Alternatively , the gels were transferred to Immobilon P 0 . 45 μm PVDF membranes , which were subsequently probed with the antibodies described above . A 1μL sample of the solution of PK-resistant recPrPSc fragments solubilized in 6M Gnd/HCl ( vide supra ) was mixed with 49 μL of sinapinic acid solution ( 10 μg/mL of sinapinic acid dissolved in 30% acetonitrile ( ACN ) with 0 . 3% trifluoroacetic acid ( TFA ) and analyzed by MALDI-TOF . One half μL aliquots were deposited using the dried-droplet method onto a 384 Opti-TOF MALDI plate ( Applied Biosystems , Foster City , CA , USA ) . MALDI analysis was performed in a 4800 MALDI-TOF/TOF analyzer ( Applied Biosystems ) . MS spectra were acquired in linear mode ( 20 kVsource ) with a Nd:YAG , ( 355 nm ) laser , and averaging 500 laser shots . For spectra data analysis of recMoPrPSc samples , an initial external calibration was carried out using insulin ( m/z = 5733 ) , ribonuclease A ( m/z = 13682 ) and lysozyme ( m/z = 14305 ) , ( Sigma-Aldrich ) as standards . A peak with m/z = 9390 . 2 Da , corresponding to fragment N153-S230 , was unambiguously identified with a mass error < 1 Da by ESI-TOF analysis ( vide infra ) of the same sample ( S2 Fig ) . This peak was used as an internal calibrant , and all m/z values in the spectrum corrected accordingly . For recBVPrPSc samples , only external calibration was used . The final resulting m/z values were matched to PrP fragments with the help of GPMAW 6 . 0 software ( Lighthouse , Odense , Denmark ) . Final experimentally calculated mass data are shown in Tables 1 and 2 , and match theoretical values within the experimental error of the MALDI-TOF analysis . As indicated , 10 μl of PK-resistant recPrPSc were subjected to ESI-TOF analysis . The sample was injected to an Agilent 1100 HPLC system equipped with a Vydac 218TP C-18 column ( Vydac , MD , USA ) . A gradient of ACN over 0 . 1% formic acid was applied over 60 minutes , at a flow of 0 . 2 ml/min . The effluent of the column was fed into a Bruker Microtof Focus mass spectrometer ( Bruker Daltonik , Billerica , MA , USA ) and sprayed into the mass detector . The capillary voltage was set at 4500 V , the pressure of the nebulizer was 2 . 5 Bar , the drying gas flow 8 L/minute and the drying temperature , 200 °C . The mass range of the detector was 50–3000 m/z .
Using seeded recPMCA , we generated a recMoPrP auto-propagative species that we termed recMoPrPSc-950 , and was partially resistant to PK ( Fig 1A ) . In order to assess its infectivity , and therefore its prionic nature , we performed animal bioassays . We inoculated this putative recombinant murine prion , into the brains of 18 Tga20 mice . All 18 inoculated Tga20 mice developed standard clinical signs of prion disease ( ataxia , hindlimb paralysis , kyphosis , weight loss ) and were eventually euthanized ( Fig 2A ) . Histopathological and immunohistochemical examination of the brains of animals inoculated with PK-resistant MoPrP , showed characteristic TSE spongiform lesions and PrPSc deposits , typical of prion disease ( Fig 2B ) . Furthermore , immunochemical analysis of brain homogenates revealed the presence of PK-resistant PrP ( Fig 2C ) . All this confirms that the inoculated material was a prion , and therefore it could be appropriately referred to as recMoPrPSc-950 . In this study we also analyzed a preparation of the recombinant murine prion recMoPrPSc-17kDa [23–24] . Although its infectious nature had already been established [23 , 24] , we confirmed it under our experimental conditions . We inoculated a group of 5 Tga20 mice , all of which developed signs of prion disease and were humanely euthanized after 119 ± 20 days . Immunohistochemical and immunochemical analysis of brains confirmed prion disease , in agreement with previous published studies [23 , 24] We subjected recMoPrPSc-950 and recMoPrPSc-17kDa to limited proteolysis using 10 μg/ml of PK for 30 minutes at 37 °C . PK-resistant fragments were detected by Sypro Ruby staining after SDS-PAGE . In recPrPSc-17kDa , a clear , intense ~17 kDa fragment was readily apparent , with two additional somewhat fainter and broader bands , one of ~6 . 5 kDa , and another with a MW between 6 . 5 and 3 . 5 kDa ( Fig 3A , left ) . The ~17 kDa band is obviously equivalent to the classic PrP27-30 PK-resistant fragment seen in brain-derived samples , which migrates between 27–30 kDa [1 , 3 , 16 , 26] . Both PK treated recMoPrPSc-17kDa and PrP27-30 lack amino acids 23–90 , so the difference in migration between the two molecules is due to the lack of a GPI anchor and lack of glycosylation in the PK-treated recMoPrPSc-17kDa . This 17kDa eponymous fragment has been previously reported for recMoPrPSc-17kDa [23] . The lower MW PK-resistant fragments may have been previously overlooked , since they would run near the front in conventional SDS-PAGE systems . In PK treated recMoPrPSc-950 a ~16 kDa band was conspicuous . Additional PK-resistant fragments with smaller apparent MWs between ~15 and ~3 . 5 kDa , several of them with an intensity similar to that of the uppermost ~16 kDa fragment , were also detected ( Fig 3A , right ) . Compared to the pattern obtained from recPrPSc-17kDa , a number of intense bands in the 15–10 kDa range were seen in recMoPrPSc-950 that were extremely faint or altogether absent in recPrPSc-17kDa ( Fig 3A ) . We used a set of monoclonal antibodies with well characterized linear PrP epitopes to perform epitope mapping of the PK-resistant fragments present in our samples . We used antibodies recognizing “N-terminal” ( antibody #51: 92–100 ) , central ( antibody 3F10: 137–151 ) and C-terminal ( antibody R1: 225–230 ) epitopes . The 92–100 epitope is considered here “N-terminal” given the total absence of any PK-resistant species containing the ~23–90 amino-terminal stretch , believed to be flexible in all PrP conformers . Therefore , position ~90 is considered , for simplicity , to be the reference “amino terminus” of PK-treated samples . The amino acid sequences of mouse and bank vole PrP are shown in S3 Fig to facilitate evaluation of the results . The use of a high resolution Tris/Tricine SDS-PAGE system optimized the separation of PK-resistant fragments , particularly the smaller ones , while allowing us to compare their pattern with that of PK-treated GPI-anchorless PrPSc , previously analyzed by our group [26] . These results are shown in Fig 3B–3D , which shows results in the following order: “N-terminal” , central and C-terminal antibodies . The “N-terminal” antibody , #51 ( epitope 92–100 ) , detected the ~17 and ~16 kDa bands stained by Sypro ruby in gels corresponding to recPrPSc-17kDa and recMoPrPSc-950 , respectively ( Fig 3B ) . In agreement with previous studies [26] , antibody #51 recognized the predominant ~17 kDa PK-resistant band in a GPI-anchorless PrPSc-containing sample , which corresponds to ( 81/89-232 ) ( Fig 3B left ) ; it should be mentioned that GPI-anchorless PrP contains two extra C-terminal amino acid residues as a consequence of the way in which the transgene was designed [26] . Considering their apparent sizes , the ~17 and ~16 kDa PK-resistant fragments in the recPrPSc-17kDa and recMoPrPSc-950 samples ( Fig 3B ) must correspond to partially overlapping collections of PK-resistant fragments with “ragged termini” [31 , 32] , with a predominance of cleavages around positions ~86–89 in recPrPSc-17kDa , and 92–98 in recMoPrPSc-950 . This difference is reminiscent of the difference between Drowsy vs . Hyper or CJD type I vs . type II major PK-resistant PrPSc fragments [31 , 32] . The recMoPrPSc-950 sample also contained a broad ~5–7 kDa band , absent in recMoPrPSc-17kDa ( Fig 3B center ) . Considering its apparent MW , it can be concluded that this band necessarily corresponds to doubly N- and C-truncated PK-resistant fragments . Antibody R1 , which recognizes the C-terminal epitope ( 225–230 ) detected , as expected , the ~17 and ~16 kDa PK-resistant fragments also seen using Sypro Ruby and antibody #51 , in GPI-anchorless PrPSc , recPrPSc-17kDa , and in recMoPrPSc-950 , respectively , supporting the notion that these fragments span from ragged ends beginning around position G92 all the way to the C-terminus ( Fig 3C ) . In the GPI-anchorless sample , R1 detected , besides , the 6 additional bands previously described and characterized by Vázquez-Fernández et al . [26] ( Fig 3C left ) . Remarkably , the pattern of bands detected by this antibody was , to a considerable extent , similar in the other two infectious prion samples , i . e . , recMoPrPSc-17kDa and recMoPrPSc-950 . Namely , the ~14 . 6 , ~13 , ~12 , ~10 . 2 , 8 , and ~6 . 7 kDa bands described by Vázquez-Fernández in GPI-anchorless PrPSc [26] were seen in the GPI-anchorless PrPSc , recMoPrPSc-17kDa and recMoPrPSc-950 samples , although the relative intensities of bands varied from sample to sample ( Fig 3C ) . Considering the extreme C-terminal position of the R1 epitope , which leaves virtually no leeway for alternative sequence combinations leading to a given apparent MW , we can tentatively conclude that there might be a very close identity of these bands between the three samples , which in turn means that cleavage sites are approximately the same . On the other hand , there was one evident difference in the PK digestion pattern of recMoPrPSc-950 with respect to the recMoPrPSc-17kDa and GPI-anchorless samples: two bands , with apparent MWs of ~4 . 5 and ~3 . 5 kDa , which are absent in the other samples ( Fig 3C ) . Considering their sizes , they should correspond to novel PK-resistant fragments with N-termini around~G194 and ~E206 , respectively . The central antibody 3F10 ( epitope 137–151 ) should recognize the ~17/16 , ~14 . 6 , ~13 and perhaps the ~12 kDa bands recognized by R1 ( Fig 3C ) , given that they also contain the epitope recognized by 3F10: these bands correspond to fragments ~92/98-230 , ~116–230 , ~134–230 and ~138–230 , respectively [26] . Indeed , the antibody revealed bands of these sizes in the two prion samples , albeit with different relative intensities ( Fig 3D ) . Antibody 3F10 also detected additional fragments of ~10 , ~8 , ~7 and ~6 kDa in the recombinant samples that were not present in GPI-anchorless PrPSc . More specifically , the ~10 kDa band was seen in both samples , while the others were seen in recMoPrPSc-950 ( Fig 3D ) . None of these bands coincides with those recognized by R1 ( compare Fig 3D with Fig 3C ) , whether they have or have not the same size , as there is no possible overlap of epitopes for fragments smaller than 12 kDa . Thus , fragments ~152–230 , ~162–230 and ~169/179-230 , lack the 3F10 epitope . Therefore , the ~10 , ~8 , ~7 , and ~6 kDa fragments recognized by 3F10 must necessarily correspond to doubly N- and C-terminally truncated PK-resistant fragments . Some of these fragments , more specifically some of those seen in the recMoPrPSc-950 sample , also contain the ( 92–100 ) epitope recognized by antibody #51 ( Fig 3A ) , while others do not , and therefore their N-termini must lie beyond the 92–100 sequence . In summary , the combined mapping reveals the existence of a number of PK-resistant fragments with a double truncation at both the N- and C-termini . These fragments are particularly prevalent in recMoPrPSc-950 , with N-termini , in this case , around~G92 . These N- , C-truncated fragments were not seen in PK-treated GPI-anchorless PrPSc ( Fig 3D left ) , in agreement with previous results [26] . We further probed the PK-resistant fragments in PK-treated recMoPrPSc-950 with an additional antibody , SAF-84 ( epitope: 166–172 , located between those recognized by 3F10 and R1 ) . Results were consistent with the patterns revealed by these two antibodies and are described in detail in S4 Fig . We sought to confirm the identity of PK-resistant bands in our recombinant samples , approximately revealed by the sizes and pattern of bands surmised from epitope analysis , by means of mass spectrometry . For logistical reasons , we could only obtain data from recMoPrPSc-950 . As shown in Fig 4 , Table 1 , and S2 Fig , MALDI and ESI-TOF analysis of the same sample identified a number of C-terminal peptides PK-resistant peptides , namely , 89–230 , 97–230 , 116–230 , 134–230 , 138–230 , 141–230 , 152–230 , 153–230 , 162–230 and 179–230 . Such peptides coincide quite well with the apparent MWs of C-terminal peptides detected by antibody R1 ( Table 1 ) . Also , in agreement with results obtained with epitope analysis , these peptides are equivalent to those obtained after PK treatment of GPI-anchorless PrPSc [26] . We also generated a recBVPrP auto-propagative species that was partially resistant to PK ( Fig 1B ) . To confirm its infectious , prionic nature , we inoculated this putative recBVPrPSc into the brains of a group of 10 bank voles expressing homozygous PrP ( 109I ) [33] . Eight of ten bank voles inoculated with putative recBVPrPSc succumbed to prion disease with a mean survival time of 239 ± 49 days post-inoculation , while the other 2 died of inter-current causes at an early age ( 206 days post-inoculation ) , and therefore it cannot be concluded whether they were developing a prion disease or not . Histopathology of brains of these animals confirmed prion disease ( S5 Fig ) . Full details of this prion disease has been reported elsewhere [34] . Therefore , the inoculated material is also a prion and can be appropriately referred to as recBVPrPSc . Treatment of recBVPrPSc with 20 μg/ml of PK resulted in the appearance of a number of PK-resistant fragments , as seen after Coomassie staining ( Fig 5 ) . A doublet of closely migrating ~17 kDa fragments was predominant . We reasoned that it might correspond to the entire PrP sequence minus the extremely flexible ~23–89 tail ( Bank vole numbering ) , with two close but slightly different N-terminal cleavage patterns , i . e . , the equivalent of the ~17 kDa band of GPI-anchorless PrPSc . These two bands were excised and subjected to in-gel tryptic digestion . MALDI analysis of the digest led to the detection of a number of tryptic peptides from amino-terminal ( H111-R136 ) , central ( P137-R148 ) and carboxy-terminal ( E221-R229 ) regions of PrP ( considering the expected loss of the extreme amino-terminal flexible tail , up to ~G90 , in fact confirmed by the complete absence of peptides from that region ) . A characteristic peak with m/z of 1820 Da , corresponding to a “ragged end” tryptic peptide G90-K106 [35]was also seen in both samples ( S6 Fig ) . No obvious differences in the spectra from the two bands were identified . Since an obvious possibility was the slight difference in apparent MW between the two bands might be the result of different ragged termini , a thorough search for peaks corresponding to tryptic peptides with different ragged termini was carried out , but yielded no obvious differences between the two bands . Therefore , the nature of the difference between the two bands cannot be explained at this point . In addition to this doublet , at least three additional PK-resistant fragments were detected in the Coomassie-stained SDS-PAGE gel ( Fig 5 ) . These lower bands were also subjected to in-gel tryptic digestion followed by MALDI-TOF analysis of the resulting tryptic fragments; MALDI spectra ( S6 Fig ) showed signals corresponding to tryptic fragments of different regions of the BVPrP sequence , in different proportions , confirming that these bands are PrP fragments of different sizes . In parallel , direct MALDI analysis of the sample confirmed the presence of fragments with sequences 153–231 , 135–231 , 133–231 , 117–231 , 75/83-231 , and 83/90-231 ( Fig 5 and Table 2 ) . A group of peaks corresponding to peptides with masses between ~7000 and ~8000 Da was also evident ( Fig 5 and Table 2 ) ; these might correspond to doubly N- and C-terminally truncated PK-resistant peptides , similar to those seen in the recMoPrPSc samples , although this cannot be confirmed at this time .
Recombinant PrPSc will become an invaluable tool for prion structural studies . Recombinant PrPSc is produced by converting bacterially derived PrP into recPrPSc , which means that incorporation of stable isotopes or different natural or unnatural amino acids into PrP sequences is greatly simplified . This will allow researchers to prepare custom-made recPrPSc for NMR-based analyses . However , it will be critical for these efforts to use fully infectious recPrPSc samples . To date , reports have described studies of amyloid recombinant PrP preparations exhibiting very limited infectivity [36 , 37] , known to have a structure different to that of PrPSc . On the other hand , very rich structural information is being extracted from highly infectious PrP23-144 amyloid fibers , revealing a flat in-register cross-β stack [15 , 38] that is also different from the 4-rung β-solenoid that characterizes full length PrPSc [10] . Our recPrPSc prions , made in vitro from bacterially derived recombinant PrP , exhibit full infectivity , with attack rates of 100% and incubation periods comparable to wt prions . They share key architectural features with brain-derived PrPSc , when analyzed by a limited proteolysis-based structural analysis [26 , 39 , 40] . Limited proteolysis of these recPrPSc species generated a fragmentation pattern consisting of a number of PK-resistant fragments that were the same as or equivalent to those obtained during limited proteolysis of GPI-anchorless MoPrPSc and wt SHaPrPSc . In particular , mass spectrometry-based analysis revealed nicks at positions 89/90 , 116/18 , 133/134 , 141 , 152/153 , 162 and 179 ( Table 1 ) , in excellent agreement with conclusions derived from epitope analysis ( Fig 3 ) . A group of doubly truncated fragments were much more conspicuous in recMoPrPSc-950 than recMoPrPSc-17kDa . Their exact sequence remains uncertain . However , one of the fragments from recMoPrPSc-950 clearly spans the sequence comprising the epitopes of antibodies #51 and 3F10 . This result is consistent with a fragment from positions ~89–152 . Such a fragment would complement the fragment spanning the sequence 153–231 see in PK treated recMoPrPSc-950 and GPI-anchorless PrPSc . The theoretical MW of such a fragment would be 6 . 7 kDa , in good agreement with the band recognized by antibody #51 ( Fig 3B ) . The existence of three distinct bands recognized by 3F10 indicates additional cleavage sites between ~89 and ~152 . Based on the analysis of other prions , candidates for these N-terminal cleavage sites are ~117/119 and ~134 . Such fragments would be recognized by 3F10 but not #51 . For the previously stated reasons , we are unable to define the precise sequences of these peptides . Furthermore , the different responses of different antibodies complicate interpretation of the data . Thus , the ~6 . 5 kDa fragments detected by 3F10 in recMoPrPSc-17kDa seem not to contain the ( 92–100 ) epitope , but in the absence of additional information , it is difficult to conclude where exactly their termini are located . Doubly truncated fragments have not been associated with the majority of “classical” brain derived prions , such as GPI-anchorless PrPSc [26] , scrapie MoPrPSc , 263K and Dy SHaPrPSc [39] , or CJD PrPSc [41] . In contrast , low MW bands corresponding to doubly truncated PK-resistant fragments are hallmarks of “atypical” PrPSc strains , including Gertsmann-Streussler-Scheinker ( GSS ) -PrPSc , and atypical scrapie-OvPrPSc strains , such as Nor98 PrPSc [40 , 42] . Thus , analysis of brain homogenates from GSSP102L patients showed the presence of two PK-resistant PrP fragments with apparent molecular masses of ~21 and ~8 kDa . The ~21 kDa fragment , similar to the PrP-res type 1 described in CJD ( i . e . , the classic triad of PrP27-30 fragments with variable glycosylation ) , is typically found in some cases , whereas the ~8 kDa fragment is found in all cases , and has been taken to represent a pathognomonic characteristic of GSS [31 , 43] . However , a similar PK-resistant fragment has been also detected in bank vole-adapted CJD PrPSc , blurring to some extent the distinction between classic and atypical strains of PrPSc [41] . Mass spectrometry-based analysis of the GSS ~8 kDa fragment revealed that it consists of a collection of peptides with ragged termini , spanning from 74/78/80/82 to 147/150/151/152/153 [43] . Furthermore , the ~7 kDa PK-resistant fragment of PrPSc detected in A117V GSS cases was seen , using mass spectrometry analysis , to span from Gly88/Gly90 to Arg148/Glu152/Asn153 [44] . As shown by Pirisinu et al . , this pattern is remarkably similar to that of Nor98 atypical PrPSc , treatment of which with PK yields a ~7 kDa resistant fragment whose sequence is 71/79-153 [40] . In contrast , the most resistant part of PrPSc from classical strains is , precisely , the complementary sequence: a 152/153-232 fragment becomes prevalent with increasing treatment time with PK of GPI-anchorless PrPSc [26] , and remains folded upon guanidine-induced partial unfolding [26 , 45] . All of this suggests that the region around 152/153 marks a “hinge” that connects two stable sub-domains within PrPSc . It is noteworthy that this region signals two halves of the putatively folded region of PrPSc of comparable size; since the flexible loop likely spans to P157 ( murine numbering ) , it would connect two sub-domains of~62 and ~72 residues spanning N- and C-terminally with respect to it . , Higher resistance of either the ~152/153-230 half , typical of “classical” PrPSc strains [26 , 39 , 45] ( but vide supra ) or of the ~80/90-152/153 half , characteristic of “atypical strains” [31 , 40 , 43 , 46] might reflect differences in the threading within these specific sub-domains , with differences in the relative content in β-sheet secondary structure ( longer or shorter β strands ) and packing of the loops connecting them . However , the fact that overall similar nicks are detected in all cases suggests that threading differences are not very large , and that overall , the same elements of secondary structure , likely arranged in the same way , are characteristic of the structures of all three classes of PrPSc . It should also be noted that in any given PrPSc prion isolate , including our recombinant ones , there might exist mixtures of more than one structure . In that case , the relative abundance of specific PK-resistant fragments will reflect the relative contributions of such structural variants . Our study also provides preliminary evidence , in recMoPrPSc-950 , of two additional , C-terminally located , PK cleavage sites not previously detected in brain-derived PrPSc . The strongest evidence of the existence of such cleavage sites was provided by a ~4 . 5 kDa band in the Sypro Ruby stained gel of recMoPrPSc ( Fig 3A ) . A band with a similar apparent MW detected by the C-terminal antibody R1 ( epitope 225–230 ) , and since no similar size bands detected by either #51 ( epitope 92–100 ) or 3F10 ( epitope 137–151 ) , it follows that there is a PK-resistant fragment spanning from a position around G194 to the C-terminus . Furthermore , a band detected by R1 ( 225–230 ) , with an apparent MW of ~3 . 5 , suggests the existence of a second C-terminal PK-resistant fragment , starting around position E206 and spanning to the C-terminus . The absence of a clear equivalent band in the Sypro Ruby-stained gel suggests that the relative abundance of this fragment might be small . Recently , we started to elaborate a generic threading model of PrPSc by distributing PK-cleavage sites , proline residues and other known structural constraints into a 4-rung solenoid [18] . A cleavage site at G194 is compatible with the predicted starting point of the lowermost ( C-terminal ) rung . However , definitive proof of the identity of these cleavage points should await confirmation by mass spectrometry . Furthermore , given that these cleavage sites have not been detected in GPI-anchorless PrPSc , it remains to be seen whether they are or not a general feature of the architecture of PrPSc . Ours is not the first structural study of recPrPSc . Recently , Noble et al . probed the structure of an infectious recPrPSc sample by deuterium/hydrogen exchange followed by pepsin digestion and mass spectrometric analysis [47] . They found very substantial protection ( i . e . , resistance to exchange ) in a stretch spanning from position ~89 up to the C-terminus , suggestive of a β-sheet-rich secondary structure . Short stretches exhibiting somewhat lower protection suggest the presence of loops/turns . In particular , the R150-Y154 stretch stands out as the possible location of a loop . The furthermost C-terminal stretch Y224-S230 also shows slightly decreased protection . These results are very similar to those reported by Smirnovas et al . in a similar analysis of GPI-anchorless PrPSc [17] . These authors found substantial protection , indicative of compact , β-sheet-rich structure , from G81 up to the C-terminus , with a lower protection from Y224 to the C-terminus . These results support the notion that the structure of the recPrPSc prepared by Noble et al . is similar to that of GPI-anchorless PrPSc , in agreement with the results reported here . It should be noted that the pattern of exchange of a non-infectious recPrP amyloid sample was very different , with low exchange rates seen only beyond position ~160 [17] . In summary , our studies show that several infectious mouse and bank vole recPrPSc , generated with the concourse of PMCA , exhibit biochemical properties that strongly suggest that they share key architectural elements with brain-derived PrPSc . Furthermore at least in the case of the mouse sample that we have obtained and studied , they seem to feature a mixture of structural properties of “classical” and “atypical” strains of brain PrPSc , although they also show some specific structural nuances . Therefore , we are convinced that such recPrPSc constitute an excellent tool for future additional structural studies . It is noteworthy that cryoEM images of our samples ( S7 Fig ) as expected , showed fibrils that are very similar to those seen in brain-derived GPI-anchorless PrPSc samples . In summary , recPrPSc samples will be very useful in future structural studies based on the use of NMR .
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PrPSc Prions propagate by inducing the refolding of the natively folded normal cellular prion protein ( PrPC ) into the prion conformation in brain and other mammalian tissues ( wild-type ) . Understanding the structure of PrPSc is essential to understanding how PrPSc prions propagate . The secondary structure of PrPC is composed of four α-helical regions , two very small β-sheets and random coil , while PrPSc is composed entirely of β-sheets and random coil . The β-sheets of PrPSc wind four times to form a spring-like 4-rung β-solenoid . The rungs are connected by stretches of random coil . We have used proteinase K ( PK ) , to cleave these random coil connecters , allowing us to identify the location of the more PK-resistant β-strand stretches within wild-type PrPSc . In this work , we use recombinant PrPSc , ( in vitro generated infectious prions ) to show that patterns of PK cleavage for recombinant and wild-type PrPSc are very similar , indicating that they share a common architecture . This also means that recombinant PrPSc is a true surrogate for wild-type PrPSc . Since recombinant PrPSc is derived from recombinant PrP , future structural studies employing specific amino acid or stable-isotope labeled amino acid substitutions are easily achievable . Such substitutions are essential for NMR studies .
|
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"Results",
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2018
|
Recombinant PrPSc shares structural features with brain-derived PrPSc: Insights from limited proteolysis
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It has recently been appreciated that NK cells exhibit many features reminiscent of adaptive immune cells . Considerable heterogeneity exists with respect to the ligand specificity of individual NK cells and as such , a subset of NK cells can respond , expand , and differentiate into memory-like cells in a ligand-specific manner . MHC I-binding inhibitory receptors , including those belonging to the Ly49 and KIR families , are expressed in a variegated manner , which creates ligand-specific diversity within the NK cell pool . However , how NK cells determine which inhibitory receptors to express on their cell surface during a narrow window of development is largely unknown . In this manuscript , we demonstrate that signals from activating receptors are critical for induction of Ly49 and KIR receptors during NK cell development; activating receptor-derived signals increased the probability of the Ly49 bidirectional Pro1 promoter to transcribe in the forward versus the reverse direction , leading to stable expression of Ly49 receptors in mature NK cells . Our data support a model where the balance of activating and inhibitory receptor signaling in NK cells selects for the induction of appropriate inhibitory receptors during development , which NK cells use to create a diverse pool of ligand-specific NK cells .
Natural killer ( NK ) cells are innate lymphocytes that play an important role in defense against viral infections and tumor clearance . NK cells express a wide variety of inhibitory and activating receptors , whose downstream signals integrate to dictate a functional response . For example , the Ly49 family of receptors on murine NK cells plays a key role in NK cell function . Inhibitory Ly49 receptors ( e . g . , Ly49A , Ly49G , Ly49C , and Ly49I ) recognize major histocompatibility complex class I ( MHC I ) and allow NK cells to carry out “missing-self” recognition , a process that eliminates cells with abnormally down-regulated MHC I expression due to certain types of infection or neoplastic transformation [1 , 2] . Also , the activating receptor Ly49H binds to cytomegalovirus ( CMV ) -encoded m157 protein , aiding in the clearance of CMV-infected cells . Ly49 receptors are acquired in a sequential and variegated manner during development , which yields a diverse repertoire of NK cells with various Ly49 receptor expression patterns . Since each Ly49 receptor recognizes a subset of MHC I alleles , the Ly49 receptor expression pattern on an individual NK cell determines its target cell specificity . Thus , unlike T and B cells that create antigen-specific diversity by genetic recombination , NK cells generate ligand-specific diversity by acquiring an assortment of inhibitory and activating receptors; however , the mechanisms that regulate NK cell receptor acquisition during development are not well understood . NK cells commence their acquisition of Ly49 receptors during the immature NK ( CD3ε-CD122+NK1 . 1+DX5- ) bone marrow ( BM ) stage [3 , 4] . Ly49 receptor genes are activated in a specific order , and each receptor possesses a developmental timeframe for the initiation of expression , which is maintained for the lifetime of the NK cell . However , once this window of opportunity passes , the NK cell can never express that Ly49 receptor [5] . Ly49 receptor expression patterns are influenced by polymorphisms in the Ly49 locus and the MHC haplotype expressed in each strain of mouse . Thus , the fraction of NK cells expressing a particular Ly49 receptor is similar within a given mouse strain . For example , ~10% and ~50% of NK cells in C57BL/6 mice express Ly49A and Ly49G2 , respectively . Ly49 receptor gene transcription is controlled by at least two distinct promoters: Pro1 , which is active in immature NK cells , and Pro2 , which is critical in maintaining expression in mature NK cells [6–9] . Each Ly49 receptor possesses a unique Pro1 promoter that acts as a bidirectional switch . Transcription factors bind to Pro1 on either the positive ( forward ) or negative ( reverse ) strand in a probabilistic manner , thus determining forward or reverse transcription from this promoter . Transcription of Pro1 in the forward direction leads to activation of Pro2 [6 , 7] . Pro2 can be regulated through DNA methylation , and forward transcription of Pro1 is thought to remove a repressor complex , allowing for acetylation of histones and/or demethylation of DNA at the Pro2 promoter [9 , 10] . This promotes Ly49 transcription in mature NK cells and the stable expression of the receptor . Pro1-mediated transcription in the reverse direction results in no Pro2 activity and therefore no Ly49 receptor expression . Thus , the proportion of NK cells expressing a given Ly49 receptor is determined by the probability of the specific Pro1 promoter to transcribe in the forward versus reverse direction . Two important factors that shape the NK cell inhibitory Ly49 receptor profile are the MHC haplotype and the MHC-binding specificities of the inhibitory receptors themselves [11] . However , the mechanism by which inhibitory receptor specificity and MHC haplotype regulate NK cell receptor acquisition is unclear , especially since inhibitory receptors block ( through recruitment of phosphatases such as SHP-1 and SHIP ) rather than transmit signals to the NK cell . Mice with NK cells lacking SHP-1 or SHIP display increased proportions of Ly49 receptor-expressing NK cells [12–15] , suggesting that inhibitory receptor-induced phosphatase activity attenuates Ly49 receptor acquisition . To explain how this might work , we hypothesized that activating receptor signals are the driving force behind inhibitory receptor acquisition . We propose that MHC I influences the acquisition of inhibitory receptors by blocking this activating signal , which impedes expression of additional inhibitory receptors . This notion is difficult to test by deleting specific activating receptors , as NK cells express numerous activating receptors that utilize various signaling modules . Instead , we took advantage of mice lacking the adaptor molecule SH2 domain-containing leukocyte protein-76 ( SLP-76 ) . Although initially described as being dispensable for NK cell activation in IL-2-expanded splenocyte cultures [16 , 17] , subsequent studies have shown that SLP-76 is indeed critical for signal transduction downstream of multiple NK cell activating receptors [17–19] . In this study , we report that activating signals downstream of SLP-76 drive the stable expression of a subset of Ly49 receptors by increasing the probability of forward Ly49 transcription from the bidirectional Pro1 promoter . Our data support a model where competing activating and inhibitory receptor signals determine the probability of Ly49 receptor expression , which ultimately shapes an appropriate inhibitory receptor repertoire during NK cell development .
To test whether NK cell effector function following activation is dependent on SLP-76 , wild-type ( WT ) and SLP-76 knockout ( KO ) NK cells were stimulated through three distinct activating receptor families ( ITAM-dependent: NK1 . 1 , Ly49H; costimulatory-like: NKG2D; SAP-dependent: 2B4 ) . We found that the baseline expression level ( MFI ) of all activating receptors on SLP-76 KO NK cells was comparable to controls ( Fig 1A ) . Upon stimulation with antibodies ( Abs ) against the various activating receptors , SLP-76 KO NK cells were significantly defective in degranulation ( as measured by surface CD107a ) compared to WT NK cells ( Fig 1B and 1C ) . Given that SLP-76-mediated signals were critical for NK cell function downstream of multiple activating receptors , we next determined if SLP-76-mediated signals impacted NK cell development . The percentage and absolute number of splenic NK cells in SLP-76 KO mice were higher than WT littermate controls ( Fig 1D and 1E ) . This increase in NK cells was most likely a consequence of the increased availability of homeostatic cytokines due to the lack of competing T cells in SLP-76 KO mice . We also examined expression of SLP-76 in all stages of NK cell development and found that SLP-76 mRNA was highly expressed in both the early and late stages of NK cell development ( Fig 1F ) . Next , WT and SLP-76 KO NK cells were analyzed for expression of activating and inhibitory receptors , including the Ly49 family of receptors . A strikingly significant decrease in Ly49 receptor-expressing splenic and BM NK cells was observed in SLP-76 KO mice . This included both inhibitory ( Ly49A , Ly49G2 , Ly49C , Ly49I ) and activating ( Ly49D and Ly49H ) family members ( Fig 1G and 1H ) . The earliest acquired receptors , Ly49A and Ly49G2 , were most affected by the loss of SLP-76 ( ~90% reduction ) compared to Ly49C and Ly49I ( ~50% reduction ) . Not all MHC I-binding inhibitory receptors were reduced , as the proportion of CD94/NKG2A expressing NK cells was unaltered in SLP-76 KO mice ( Fig 1G ) . Since Ly49 receptor acquisition can also occur at later stages of NK cell development , a maturation defect in SLP-76 KO NK cells could be responsible for the phenotype observed . To test this possibility , we assessed splenic NK cell maturation using the cell surface markers CD27 and CD11b [20] and found that NK cells were more developmentally mature in SLP-76 KO mice ( increased proportion of CD27-CD11b+ NK cells; Fig 1I ) . Moreover , Ly49 receptor expression by SLP-76 KO NK cells was decreased at every stage of splenic maturation compared to WT controls ( S1 Fig ) . These data show that an NK cell maturation defect was not responsible for the reduction in Ly49 receptor expression . Killer immunoglobulin-like ( KIR ) receptors on human NK cells are functional orthologs of Ly49 receptors in mice . To test whether SLP-76-derived signals also contributed to KIR acquisition , we differentiated human NK cells from CD34+ umbilical cord blood cells transduced with SLP-76 or scrambled shRNA in vitro for 21 d . SLP-76 shRNA transduction resulted in a decrease in SLP-76 expression , which correlated with a reduced ability to activate KIR gene expression ( KIR cocktail of KIR2DL1 , KIR2DL2/DL3 , KIR3DL1 ) but not CD56 or NKp46 ( S2 Fig ) . These data along with the Ly49 receptor acquisition defect in SLP-76 KO NK cells suggest that NK cells rely on SLP-76-dependent activation signals for a MHC I-binding inhibitory receptor acquisition . To obtain a more global picture of the Ly49 receptor repertoire of SLP-76 KO NK cells , we examined the coexpression pattern of inhibitory Ly49 receptors . This analysis revealed that SLP-76 KO mice have an expanded population of Ly49 receptor-negative NK cells . Although the proportion of NK cells that express Ly49C or Ly49I was reduced in SLP-76 KO mice ( Fig 1G ) , there was relative preservation of Ly49C and Ly49I single-positive NK cells that did not coexpress other Ly49 inhibitory receptors ( Fig 2A ) . Ly49C and Ly49I bind to MHC I ( H2-Kb ) in C57BL/6 mice , as opposed to Ly49A and Ly49G2 that bind H-2Dd and do not possess ligands in C57BL/6 mice . Since MHC I interactions with Ly49 receptors shape the Ly49 repertoire [12 , 13 , 21 , 22] , we wondered whether the relative preservation of Ly49C and Ly49I expression could be related to their ability to bind MHC I in C57BL/6 mice . To test this , we bred SLP-76 KO mice to the B10 . D2 mouse strain . If ligand binding were responsible for the preservation of Ly49 receptor expression , the proportion of Ly49A+ and Ly49G2+ NK cells would be relatively preserved in SLP-76 KO . B10 . D2 mice , as B10 . D2 mice express H-2Dd . However , we found that SLP-76 KO-B10 . D2 NK cells also displayed a similarly defective Ly49 receptor repertoire as compared to SLP-76 KO NK cells on a H-2b background ( Fig 2B and 2C ) . These data suggest that the Ly49 receptor repertoire defect in SLP-76 KO NK cells is independent of MHC I haplotype . As SLP-76 is expressed in almost all hematopoietic cells , SLP-76 KO mice harbor defects in multiple hematopoietic lineages [23] . Although we predicted that SLP-76-derived signals controlled Ly49 receptor acquisition in an NK cell-intrinsic manner , it was still possible that the defects arose secondary to cell-extrinsic effects . To address this , we generated mixed BM chimeric mice using BM from congenically disparate WT and SLP-76 KO mice mixed at a 2:1 ratio . Ten to twelve weeks after reconstitution , although some variability was seen , the contribution of SLP-76 KO BM to non-T cell/non-NK cells compared to NK cells was similar , suggesting that there was no significant advantage or disadvantage of SLP-76 deficiency in NK cell development ( Fig 3A ) . Consistent with our hypothesis , we found that the proportion of NK cells expressing Ly49A , Ly49G2 , and Ly49I was decreased in SLP-76 KO BM compared to WT BM-derived NK cells ( Fig 3B ) . However , no differences in the proportion of Ly49C , Ly49D , and Ly49H expressing NK cells was observed between SLP-76 KO BM and WT BM-derived NK cells ( Fig 3B ) . Thus , although a subset of Ly49 receptors ( Ly49A , G2 , and I ) was regulated in an NK cell-intrinsic manner , Ly49C , Ly49D , and Ly49H were controlled by a SLP-76-dependent , NK cell-extrinsic mechanism . It has been published that mice deficient in MHC I or inhibitory receptor signaling harbor increased proportions of Ly49-expressing NK cells [12–15] . We hypothesized that the proportion of Ly49 receptor-expressing NK cells is increased in such mice because activation signals are unopposed by MHC-binding inhibitory receptors during NK cell development . The NK cell-intrinsic regulation of some , but not all , Ly49 receptors provided us with an opportunity to test this hypothesis , as we would predict that only NK cells expressing Ly49 receptors regulated by an NK cell-intrinsic mechanism would be increased in MHC I-deficient mice . We examined the Ly49 receptor repertoire of MHC I-deficient β2m KO mice and observed an increase in the proportion of NK cells expressing Ly49 receptors that are regulated in a cell-intrinsic manner ( Ly49A , Ly49G2 , and Ly49I ) . In contrast , the proportion of NK cells expressing Ly49 receptors regulated in an NK cell-extrinsic manner ( Ly49C , Ly49D , and Ly49H ) were the same or reduced in β2m KO mice ( Fig 3D ) . These findings suggest that the lack of inhibitory ligands ( MHC I ) , presumably leading to more NK cell activation , results in an increased chance of NK cells expressing cell-intrinsic Ly49 receptors . In NK cells , SLP-76 can be recruited to the membrane by two independent proximal signaling complexes: one involving LAT family members ( LAT1/LAT2 ) and the other involving ADAP [17 , 24] . As both SLP-76 signaling complexes are important for NK cell function downstream of activating receptors , we predicted that both LAT1/LAT2 and ADAP proteins would contribute to Ly49 receptor acquisition by NK cells . Surprisingly , we found that these SLP-76 signaling complexes differentially contributed to Ly49 receptor acquisition . A significantly decreased proportion of NK cells expressing Ly49A and Ly49I was observed in LAT1/LAT2 DKO but not in ADAP KO mice . Conversely , a significantly smaller proportion of NK cells expressing Ly49G2 was observed in ADAP KO but not LAT1/LAT2 DKO mice ( Fig 4A ) . The LAT1/LAT2/ADAP TKO mice displayed decreased proportions of all three Ly49 receptors similar to the SLP-76 KO NK cells . The upstream ADAP and LAT pathways also differently affected NK cell-extrinsic Ly49 receptors . Ly49C was primarily driven by LAT1/LAT2-dependent signals while Ly49D and Ly49H utilized both pathways for their expression ( Fig 4B ) . These data point to a differential influence of SLP-76 upstream signaling pathways on Ly49 receptor induction during NK cell development . To test whether the reduced frequency of Ly49 receptor-expressing NK cells was due to decreased transcription , we quantified mRNA transcripts of an NK cell-intrinsic Ly49 receptor at early and late stages of NK cell development in WT and SLP-76 KO mice . We found that Ly49G2 mRNA transcripts were reduced in SLP-76 KO immature ( iNK ) and mature ( mNK ) BM subsets compared to WT controls ( Fig 5A ) . Ly49G was chosen as a model gene since this receptor is expressed on half of NK cells . Ly49 receptor gene transcription is driven off the Pro1 promoter region in immature NK cells and the Pro2 region during maturity [6–9] . Transcription factors can bind to Pro1 on either the positive ( forward ) or negative strand ( reverse ) in a probabilistic manner , and this determines the directionality of transcription from this promoter . Forward transcription allows for stable expression of that Ly49 receptor in mature NK cells while reverse transcription leads to no Ly49 expression . To test whether SLP-76-mediated signaling affected transcription from the Pro1 promoter , forward and reverse transcripts from the Ly49G Pro1 promoter were examined . As expected , compared to WT NK cells , DX5− ( BM iNK cells ) and DX5+ ( BM mNK cells ) SLP-76 KO NK cells expressed significantly reduced levels of Ly49G Pro1 forward transcripts ( Fig 5B ) . However , we also surprisingly observed that SLP-76 KO NK cells expressed increased Ly49G Pro1 reverse transcripts in iNK and mNK BM subsets compared to WT NK cells ( Fig 5B ) . These data suggest that SLP-76-mediated signaling affects Ly49 receptor acquisition in developing NK cells by promoting Pro1 forward over reverse transcription , thereby increasing the probability of NK cells to express a given Ly49 receptor . We further investigated the accessibility of chromatin at Ly49G Pro1 and Pro2 in WT and SLP-76 KO NK cells , by performing a chromatin immunoprecipitation for H3K9 acetylation ( H3K9Ac ) , an indicative marker for open/accessible chromatin . The Pro2 loci of Ly49G is CpG poor and has been previously shown to be epigenetically regulated by H3K9Ac [25] . Based on the reduction in Ly49G2 expression in SLP-76 KO NK cells , we predicted there to be less H3K9Ac and less Pro2-mediated transcription . H3K9Ac was observed at Pro2 of Ly49g but not at Ly49e ( silenced in adult NK cells ) in WT NK cells . Surprisingly , however , Ly49G Pro2 H3K9Ac was similar between WT and SLP-76 KO NK cells ( Fig 5C ) , perhaps suggesting that Pro2 chromatin accessibility is not sufficient to drive Ly49G expression in mature NK cells . Although the role of H3K9Ac at Pro1 is unknown , we found SLP-76 KO NK cells showed significantly decreased Ly49G Pro1 H3K9Ac compared to WT controls ( Fig 5C ) . These data suggest that SLP-76-derived signals mainly control transcriptional activity at the Pro1 promoter and that epigenetic alterations at the Ly49 Pro1 loci may control receptor expression in mature splenic NK cells .
Although NK cells are part of the innate immune system , NK cells exhibit many features of adaptive immune cells . Unlike T cells and B cells that create antigen specificity by genetic recombination , NK cells create diversity by expressing a seemingly “random” assortment of inhibitory and activating receptors . The various combinations of expressed receptors generate ligand-specificity , allowing subsets of NK cells to respond , expand , and differentiate into memory-like cells in a ligand-specific manner , as well as create a diverse repertoire within the NK cell pool [26 , 27] . However , how NK cells determine which inhibitory receptors to express on their cell surface during a narrow window of development was largely unknown . The data presented in this manuscript support a model by which NK cell activation during development drives inhibitory receptor acquisition on immature NK cells . Our model proposes that during early NK cell development , NK cells are activated via interactions between activating receptors and their ligands expressed by BM stroma . Activation of NK cells results in a signaling cascade that promotes the transcription of different Ly49/KIR genes . The NK cell acquires these receptors until a self-binding inhibitory receptor is expressed on the cell surface and blocks the activating signal ( Fig 6 ) . Our model potentially explains how MHC I interactions with NK cell inhibitory receptors shape the inhibitory receptor repertoire . The regulation of Ly49/KIR induction by activating receptor-derived signals provides a mechanism whereby developing NK cells can generate a ligand-specific receptor repertoire that appropriately recognizes missing self . Furthermore , the expression of a self-binding inhibitory receptor increases the functional capacity of NK cells , a process known as licensing . Thus , our model suggests that strong activating signals during NK cell development increase the likelihood of developing more functionally active licensed NK cells that can carry out missing self-recognition . SLP-76 KO mice harbored an increased fraction of the most mature subset of NK cells . However , the decreased proportion of Ly49 receptor-expressing NK cells in SLP-76 KO mice could not be explained by differences in maturation , since the proportion of NK cells expressing Ly49 receptors was significantly reduced at each stage of NK cell maturation in SLP-76 KO mice . Our analysis showed that the fraction of Ly49 receptor-expressing NK cells was similar among all maturation stages except for Ly49I , which was overrepresented in the most mature NK cell subset in WT mice . Interestingly , the proportion of Ly49I-expressing NK cells was relatively preserved compared to Ly49A or Ly49G2-expressing NK cells . This could be potentially explained by the increased maturation status of SLP-76 KO NK cells , since almost all Ly49I-positive NK cells in SLP-76 KO mice resided in the most mature NK cell subset . Alternatively , self-binding Ly49 receptors such as Ly49I might drive NK cell maturation , yielding more mature NK cells in SLP-76 KO mice . Further investigation is required to understand how SLP-76-derived signals and self-MHC I binding Ly49 receptors impact NK cell maturation . We were surprised to find that not all Ly49 receptor acquisition was intrinsically driven by SLP-76 signals in NK cells . While Ly49A , Ly49G2 , and Ly49I were acquired in a SLP-76-dependent NK-cell intrinsic manner , Ly49C , Ly49D , and Ly49H were regulated in an NK cell-extrinsic manner . This suggests another cell type is necessary to generate a full Ly49 receptor repertoire . It is possible that myeloid lineage cells such as dendritic cells ( DCs ) may be responsible for NK cell activation that leads to Ly49 receptor expression [28] . NK cells and DCs form stimulatory synapses , resulting in IL-12 secretion and IL-15 transpresentation . IL-12 is critical for optimal NK cell activation by DCs , and IL-15 is required for NK cell survival and Ly49 receptor expression [29] . Since SLP-76 is critical for murine DC migration and cell–cell contact [30] , the interaction of DCs with NK cells may be important for cell-extrinsic Ly49 receptor expression . We previously reported that LAT1/LAT2 and ADAP can independently recruit SLP-76 to NK cell activation synapses [17] . As both signaling pathways are required for optimal NK cell activation , we predicted that they would equally contribute to Ly49 receptor acquisition by developing NK cells . However , LAT1/LAT2 was more important for Ly49A and Ly49I , whereas ADAP contributed to Ly49G2 expression . LAT1/LAT2 signaling pathways primarily contributed to the extrinsically regulated Ly49C and partially impacted Ly49D and Ly49H . ADAP only contributed to Ly49D and Ly49H . The Ly49 receptor phenotype of ADAP KO NK cells is supported from recently published data on SLP-76ace/ace mice that contain a mutation in the SH2 domain of SLP-76 , where ADAP binds [31] . Perhaps , activating receptors that preferentially use either ADAP or LAT1/LAT2 to recruit SLP-76 are engaged at different times during NK cell development , leading to the expression of Ly49 receptors in a specific order . Alternatively , each Ly49 receptor Pro1 promoter may be differentially affected by the assortment of transcription factors induced by the ADAP or LAT1/LAT2 signaling pathways . Alteration of the probabilistic switch function of the Ly49 Pro1 promoter provides a mechanism that explains how SLP-76 signaling could increase Ly49 receptor acquisition . Ly49 receptor expression has been shown to occur in a stochastic manner [32 , 33] , and the probabilistic mechanism has been explained by differential binding of transcription factors to either forward or reverse promoter elements in the Pro1 bidirectional promoter . Transcription factors , such as NFκB , bind this region and are inducible following activating receptor signaling . One study has explored the role of NFκB in NK cell development and Ly49 receptor expression , but the results showed only a small decrease in the proportion of Ly49 receptor-expressing NK cells [34] . Other transcription factors , such as AML and Ets-1 , are expressed in NK cell progenitors prior to Ly49 receptor transcriptional initiation , but it is possible that activation induced signals and other transcription factors contribute to the stabilization of the transcriptional landscape . For example , calcium-dependent NFAT and CREB binding sites in the Pro1 region of Ly49G2 may contribute to forward transcription . Studies examining the contribution of calcium signaling to Ly49 receptor acquisition by NK cells are currently ongoing . Since Pro1 forward transcription is thought to control the accessibility of Pro2 in mature NK cells , we predicted that SLP-76 KO NK cells would exhibit decreased Pro2 chromatin accessibility as measured by H3K9Ac at Ly49G Pro2 . However , we found that SLP-76 KO and WT NK cells exhibited equivalent H3K9Ac at Pro2 , despite decreased Ly49G transcripts in SLP-76 KO NK cells . Instead , we found that H3K9Ac at Pro1 was almost absent in SLP-76 KO NK cells , suggesting that SLP-76-derived signals impacted Pro1 accessibility . This suggests that Pro1 accessibility might be important for Ly49 receptor transcription in mature NK cells and that Pro2 accessibility alone is insufficient to drive Ly49 transcription . This is in line with a recent report proposing that in addition to being a bidirectional switch , Pro1 may act as an enhancer for Ly49 receptor expression in mature NK cells [35] . Further studies will be required to elucidate the exact role of Pro1 H3K9Ac in control of Ly49 receptor expression . SLP-76-silenced human NK cells differentiated in culture were defective in human killer-cell immunoglobulin-like receptor ( KIR ) acquisition . Although the in vitro differentiation system may not precisely recapitulate human NK cell development in vivo , these data suggest that KIR acquisition might be influenced by SLP-76-dependent signals . It has recently been shown that KIR expression may be transcriptionally regulated in a manner similar to Ly49 receptors . There are promoter regions in KIRs similar to the Pro1 and Pro2 elements of Ly49 genes; however , their relative location is inverted . A unidirectional promoter/enhancer is located upstream , and a proximal Pro1-like region near the transcriptional start site is methylated in nonexpressed KIRs [36 , 37] . The bidirectional proximal promoter has putative binding sites for transcription factors such as Sp1 and YY1 [38] . It is thought that the antisense transcripts generated from the proximal switch produce a small RNA that is involved in the transcriptional silencing of KIRs through methylation of the proximal promoter region [39 , 40] . The presence of a bidirectional switch in human KIRs and murine Ly49s suggests a conserved regulatory mechanism of inhibitory receptor acquisition by NK cells . Thus , our studies on activation signals driving Ly49 and KIR expression may also shed light on mechanisms by which KIRs are acquired on human NK cells . Further investigation is needed to determine the exact transcription factors required for inhibitory receptor acquisition , as differences in the proximal signaling pathways suggest differential regulation of the Ly49 receptors . Nevertheless , our work highlights the complexity of Ly49 regulation . The results from this study are likely to be applicable to the regulation of human KIR receptors [41–43] . Our data support a model where competing activating and inhibitory receptor signals determine the probability of inhibitory receptor expression , which ultimately shapes the inhibitory receptor repertoire during NK cell development and creates appropriate ligand-specific diversity within the NK cell pool .
Human NK cell studies: The IRB is the University of Minnesota Institutional Review Board; Study Number: 9709M00134; Principal Investigator: Jeffrey Miller . For mouse studies , mice were euthanized using carbon dioxide according to our IACUC protocol at the University of Pennsylvania ( IACUC protocol#: 804703 , 804245 ) ; Principal investigator: Taku Kambayashi . Mice were housed in pathogen-free conditions and treated in strict compliance with the Institutional Animal Care and Use Committee regulations at the University of Pennsylvania . C57BL/6 ( CD45 . 2+ ) , B6 . SJL ( CD45 . 1+ ) , and β2m KO mice were purchased from The Jackson Laboratory or Charles River Laboratories . LAT1/2 DKO , ADAP KO , and SLP-76 KO mice have been previously described and were bred in our facility [44–46] . SLP-76 KO mice have been ~3 times backcrossed to C57BL/6 mice due to embryonic lethality of fully backcrossed mice and thus , littermate controls were used for all experiments . LAT1/LAT2/ADAP TKO mice were generated by crossing LAT1/2 DKO mice to ADAP KO mice . SLP-76 . B10D2 KO mice were generated by crossing B10 . D2 mice to SLP-76 KO mice and screening for H-2d alleles . All mice were sacrificed and analyzed between 10–12 wk of age . All reagents were purchased from Sigma-Aldrich ( St . Louis , MO ) unless otherwise specified . Cytokines were purchased from Peprotech ( Rocky Hill , NJ ) . Abs for cell stimulation were purchased from BioXcell ( Malaysia ) or Biolegend . Abs for flow cytometry were purchased from Biolegend , eBiosciences , BD Biosciences , and Molecular Probes . The following Ly49 receptor antibodies/clones were used: Anti-Ly49A ( YE1/48 . 10 . 6 ) , anti-Ly49G2 ( 4D11 ) , anti-Ly49I ( YL1-90 ) , anti-Ly49D ( 4E5 ) , anti-Ly49H ( 3D10 ) , and anti-Ly49C/I ( 5E6 ) from BD Pharmigen . Anti-Ly49C ( 4LO3311 ) was purchased from the UCSF Cell Culture Facility ( San Francisco , CA ) . Cells were stained with antibodies against cell-surface antigens and LIVE/DEAD cell stain at 4°C for 20 min . Intracellular staining was performed using the Cytofix/Cytoperm Fixation and Permabilization Kit ( BD Pharmingen ) per manufacturer instructions . Flow cytometry was performed with a FACS Canto flow cytometer ( BD Biosciences ) , and cell sorting was performed using a FACSAria ( BD Biosciences ) . Data were analyzed with FlowJo software ( TreeStar , Ashland , OR ) and Simplified Presentation of Incredibly Complex Evaluations ( SPICE- NIAID , Bethesda , MD ) . Statistical analysis was performed using Prism ( GraphPad , San Diego , CA ) computer software . Splenocytes were plated in 96-well plates in NK-cell media ( MEMα[Invitrogen] with 10% FBS , 1% penicillin/streptomycin , 10 mM HEPES and 1 x 10−5 β-ME ) with human IL-2 ( 1 , 000 U/mL ) on plate-immobilized ( 20 ug/mL ) anti-NK1 . 1 , anti-NKG2D , anti-Ly49H , anti-CD244 or with soluble PMA ( 100 ng/mL ) and ionomycin ( 1 ug/mL ) in the presence of monensin ( eBiosciences ) and anti-CD107a-PE for 6 h at 37°C . Following incubation , IFNγ production and degranulation were analyzed by flow cytometry . SLP-76 KO ( CD45 . 1+ ) BM cells were T/NK cell depleted by CD3 and NK1 . 1 magnetic bead depletion ( Miltenyi Biotec ) . T/NK-cell depleted BM cells from CD45 . 1+CD45 . 2+ WT ( competitor ) mice were mixed at a 2:1 ratio with the SLP-76 KO BM . Cells were injected intravenously into lethally irradiated ( 950 cGy ) CD45 . 2+ recipient mice . Mixed BM chimeric mice were analyzed by flow cytometry 10–12 wk post injection . RNA was purified from equivalent cell numbers of sorted splenic and BM NK cells ( RNeasy kit-Qiagen ) . cDNA synthesis was performed using SuperScript II Reverse Transcriptase ( Invitrogen ) kit and performed using manufacturer’s instructions . Primers for SLP-76 , Ly49G2 , and Ly49I ( Applied Biosystems ) were used . The reaction was performed on the Applied Biosystems StepOnePlus Real Time PCR System ( Carlsbad , CA ) , and ΔΔ-CT method was employed . Results were normalized to the housekeeping gene GAPDH . Total RNA was purified from 100 , 000 sorted cells with the RNeasy Micro Kit ( Qiagen ) , and cDNA synthesis was carried out using Random Hexamer primer , Taqman Reverse Transcription Reagents kit ( Applied Biosystems ) according to the manufacturer’s instructions . The primers used in the Ly49-specific qRT-PCR assay were: Ly49g-Pro1 forward primer ( 5′-CAAGTGATCAGCCTATTCTTGTG-3′ ) ; Ly49g-Pro1 reverse primer ( 5′-CTTGTGTGAGTTTTGTACTTCAG -3′ ) ; Ly49g-Pro1as forward primer ( 5′-CACTGCCTTATATGCCTAAACAC-3′ ) ; Ly49g-Pro1as reverse primer ( 5′-GACTTCATGACTAGTTACTGG-3′ ) ; β-Actin forward primer ( 5′-CCTGGCACCCAGCACAAT-3′ ) ; and β-Actin reverse primer ( 5′-GGGCCGGACTCGTCATACT-3′ ) . Reactions were carried out using the FastStart SYBR Green Master kit ( Roche Diagnostics , Indianapolis , IN , US ) on the 7300 Real-Time PCR System ( Applied Biosystems ) . The qRT-PCR was performed in duplicate and was repeated in at least three separate experiments using the following conditions . Reaction mixtures contained 12 . 5 μL of SYBR Green master mix , 2 pmoles each of forward and reverse primers and 5 ng cDNA . Thermocycler conditions included initial denaturation at 50 and 95°C ( 10 min each ) , followed by 40 cycles at 95°C ( 15 s ) and 60°C ( 1 min ) . Melting curve analyses were performed to verify the amplification specificity . Relative quantification of gene expression was performed according to the ΔΔ-CT method using the StepOne Software 2 . 0 ( Applied Biosystems ) . The results were normalized to the housekeeping gene β-Actin . WT and SLP-76 KO splenic NK cells ( CD3ε −NK1 . 1+NKp46+DX5+ ) were sorted by flow cytometry , cross-linked for 10 min with 1% formaldehyde in cold PBS buffer , and subsequently quenched with 125 mM glycine for 5 min . The cells were pelleted by centrifugation at 470× g for 10 min and washed with PBS containing protease inhibitor cocktail . After centrifugation , the supernatant was discarded , and the cell pellet was stored at −80°C . DNA shearing was performed with a chromatin immunoprecipitation enzymatic shearing kit ( Chromatrap , Ashland , VA ) following the manufacturer’s instructions . Immunoprecipitation was performed with the True MicroChIP kit ( Diagenode , Denville , NJ , USA ) using a CHIP grade antibody against H3K9ac ( Diagenode ) . A nonspecific rabbit IgG was used as a negative control . All ChIP steps were performed in Eppendorf 1 . 5-ml DNA LoBind Tubes ( Eppendorf , Hamburg , Germany ) . The specific primer sequences used in ChIP-qPCR were as follows: Ly49g Pro-1 , forward , 5’- CCCATCAAGGACTATGTGTTTAGG-3’ , reverse , 5’-ATGGTAAACTTCACAGATCTTAGG-3’; Ly49g Pro-2 , forward , 5’-CACAGGAATCACTTCTCAGTAGA-3’ , reverse , 5’-ATCGAGCGCTCACATAACACTAT-3’;Ly49e Pro-2 , forward , 5’-GCAATTTCCTCCTTTTGCTTAGATA-3’ , reverse , 5’-TGGAGGGAAAAGTTGGGTGAAA-3’ . The precipitated DNA fractions were quantified by real-time PCR with the FastStart Universal SYBR Green Master Kit ( Roche Diagnostics , Indianapolis , IN , USA ) using 7300 Real-Time PCR System; ( Applied Biosystems ) . The results were normalized as the percentage of the input ( %input ) from Ct values . The experiments were repeated three times . The use of all human tissue was approved by the Committee on the Use of Human Subjects in research at that University of Minnesota ( Minneapolis , MN ) , and informed consent was obtained in accordance with the Declaration of Helsinki . Lentivirus containing either scramble control or SLP-76 shRNA in pGIPZ vectors was packaged in 293T cells using PAX2 and pMDG . 2 plasmids ( Open Biosystems , Lafayette , CO ) . A pool of four SLP-76 shRNA vectors ( clones V2LHS_62885 , V3LHS_364697 , V2LHS_62886 and V3LHS_364699 ) was used . CD34+ hematopoietic cells were isolated from umbilical cord blood by double-column positive selection using anti-CD34 microbeads ( Miltenyi Biotec ) . Cells were transduced with lentivirus by spin transduction , and CD34+GFP+ cells were sorted . CD34+GFP+ cells were cultured for 21 days on the EL08-1D2 fetal stromal line [47] . The culture media and cytokines used for human NK cell differentiation are published [48] .
|
Natural killer ( NK ) cells are important cells of the immune system , because they kill abnormal cells such as those infected with viruses or have become cancerous . These abnormal cells can lose proteins known as MHC molecules , which are recognized by inhibitory receptors on NK cells . Thus , when an NK cell interacts with a cell with decreased MHC , the NK cell is disinhibited and can kill the target cell . Each NK cell carries a unique assortment of these inhibitory receptors . However , how developing NK cells determine which inhibitory receptors to put on the NK cell’s surface during development is unknown . In this study , we show that signals generated through NK cell activating receptors are important for inducing a subset of inhibitory receptors on NK cells during development . We propose that the NK cell has an increased chance of acquiring an inhibitory receptor until a balance between activating and inhibitory receptor signals is achieved . This process ensures that NK cells can properly detect abnormal cells that have lost MHC .
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2016
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Activating Receptor Signals Drive Receptor Diversity in Developing Natural Killer Cells
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An optimal HIV vaccine should induce broadly neutralizing antibodies ( bnAbs ) that neutralize diverse viral strains and subtypes . However , potent bnAbs develop in only a small fraction of HIV-infected individuals , all contain rare features such as extensive mutation , insertions , deletions , and/or long complementarity-determining regions , and some are polyreactive , casting doubt on whether bnAbs to HIV can be reliably induced by vaccination . We engineered two potent VRC01-class bnAbs that minimized rare features . According to a quantitative features frequency analysis , the set of features for one of these minimally mutated bnAbs compared favorably with all 68 HIV bnAbs analyzed and was similar to antibodies elicited by common vaccines . This same minimally mutated bnAb lacked polyreactivity in four different assays . We then divided the minimal mutations into spatial clusters and dissected the epitope components interacting with those clusters , by mutational and crystallographic analyses coupled with neutralization assays . Finally , by synthesizing available data , we developed a working-concept boosting strategy to select the mutation clusters in a logical order following a germline-targeting prime . We have thus developed potent HIV bnAbs that may be more tractable vaccine goals compared to existing bnAbs , and we have proposed a strategy to elicit them . This reductionist approach to vaccine design , guided by antibody and antigen structure , could be applied to design candidate vaccines for other HIV bnAbs or protective Abs against other pathogens .
Many antibodies capable of neutralizing a large fraction of circulating HIV isolates , broadly neutralizing antibodies ( bnAbs ) , have been isolated from HIV-infected individuals [1–12] . Combinations of bnAbs targeting different epitopes are able to neutralize the great majority of HIV strains , even at low concentrations [4 , 13] . These bnAbs can provide sterilizing immunity against challenge by simian-human immunodeficiency virus ( SHIV ) in macaques [14 , 15] , and can reduce viral load to undetectable levels when administered to chronically infected animals [16 , 17] . For these reasons , it is thought that an optimally protective vaccine will induce sustained titers of potent bnAbs targeting different epitopes . HIV vaccines have not yet induced bnAbs in humans or animal models , except in one case of a knock-in mouse engineered to express the critical , fully mature heavy chain of a potent HIV bnAb [18] . The plausibility of designing a vaccine that can induce bnAbs is under question in part due to the low frequency and complex mechanisms of bnAb induction in natural infection . Potent bnAbs develop in only a few percent of HIV-infected individuals , typically after two or more years [19 , 20] , and recent case studies [8 , 21 , 22] have illustrated how the prolonged and dynamic co-evolution between mutating virus and the adaptive immune system occasionally selects these rare bnAbs from the repertoire [23] . In contrast , a bnAb-based HIV vaccine should induce bnAbs much more reliably—in a majority of vaccine recipients—and should achieve this feat using a small number of immunizations . The plausibility of a bnAb-based vaccine is further challenged by the fact that potent HIV bnAbs typically have one or more unusual features , such as extensive mutation , long ( or short ) complementarity-determining region 3 ( CDR3 ) loops , insertions , deletions , additional disulfides and/or sulfated tyrosines [1 , 2 , 4 , 24–28] . Aside from CDR3 lengths , which are normally set in the naïve B cell , these unusual features are generally produced by somatic hypermutation and induced by the rapidly mutating HIV Envelope ( Env ) during infection . Whether vaccines can be developed to consistently induce highly mutated antibodies with these rare but desirable features is not known . The unusual features of bnAbs to HIV raise the question of whether one can determine which bnAbs are least unusual and therefore potentially less difficult to induce by vaccination . To date , the various features of bnAbs have not been weighed together on a single quantitative scale in order to measure the degree to which HIV bnAbs are unusual compared to other types of antibodies . Considering that such a scale would assist in ranking and prioritization of HIV bnAb epitopes as targets for vaccine design—with the idea that vaccine efforts should focus on the epitopes targeted by the most "normal" or least "unusual" potent bnAbs—here we developed a computational method , termed the Antibody Features Frequency ( AFF ) method , to estimate the "features frequency" of any antibody sequence . The method compares the features in a given sequence with those in a large panel of sequences obtained by next-generation sequencing of paired [29] and unpaired ( this study ) heavy and light chains from human memory B cells from multiple donors . Our AFF analysis of HIV bnAbs not only provides a framework to prioritize epitopes but also motivates the development of minimally mutated bnAbs to serve as potentially more realistic vaccine goals compared to known bnAbs . Aside from which epitopes to prioritize and which bnAbs to use as guides , the critical question is how to design vaccines to elicit bnAbs . One proposed strategy is B-cell-lineage vaccine design , which seeks to use , as immunogens , HIV Env proteins that parallel the evolution of bnAbs in infected individuals [22 , 30] . Such a B-cell-lineage method requires detailed phylogenetic data on both the bnAb lineage and the co-evolving Env lineage from an infected human and may require mapping of multiple bnAb lineages to identify "cooperating" lineages [31] . Thus , its applicability is limited to case studies where such data are available , although the generality of the approach may benefit as more lineages are studied . VRC01-class bnAbs are attractive vaccine leads owing at least to their potency , breadth and protective capacity [17 , 32–36] , and to the fact that their in vitro neutralization curves typically saturate at 100% viral neutralization , in contrast to some other bnAb classes ( V2/Apex , PGT151 , and 10E8 ) that fail to reach complete neutralization for some isolates , likely influenced by glycan heterogeneity [1 , 9 , 37] . However , longitudinal Env and antibody phylogenetic data sufficient to consider a B-cell-lineage approach have only recently become available [38 , 39] , thus alternate vaccine design strategies have been required . To develop candidate immunogens to prime a VRC01-class response , we and others have engineered immunogens with affinity for germline-reverted VRC01-class antibodies [40–43] . We have shown that our most advanced germline-targeting immunogen ( eOD-GT8 60mer ) can prime VRC01-class responses in VRC01-class heavy-chain knock-in mouse models [18 , 44] and can bind VRC01-class human naïve B cell precursors at a frequency of 1 precursor per 400 , 000 to 2 . 4 million naïve B cells , corresponding to 15–90 precursors per resting human lymph node [43] . While germline-targeting immunogens are available as candidates to prime a VRC01-class response , the high degree of mutation and other unusual features in VRC01-class bnAbs have made it very difficult to postulate which or how many different boosting immunogens may be required to induce sufficient favorable ( bnAb-like ) somatic mutations to produce VRC01-class bnAbs via vaccination . Multiple structural and bioinformatic analyses have elegantly defined much of the VRC01-class epitope and paratope [25 , 34 , 40 , 45–49] , and one study engineered VRC01 bnAb variants with reduced framework mutations that improved our understanding of which mutations are required for bnAb activity [50] . However , a picture has persisted that there are important mutations scattered across the CDRs and framework regions of VRC01-class bnAbs , and it remains unclear what types of immunogen structures should be employed as boosts to favor elicitation of the most critical mutations . Here , we developed two minimally mutated VRC01-class bnAbs , one of which had features more common than those in other potent HIV bnAbs analyzed but similar to those in antibodies elicited by common vaccines . We further employed mutational and structural analyses to gain insight into the types of immunogen structures that might be required to induce a minimal set of mutations needed for VRC01-class bnAb activity .
The AFF method computes the antibody features frequency as the product of the frequencies for the following individual sequence features: the combination of VH , DH , and JH genes on the heavy ( H ) chain; the light ( L ) chain VL given the VH; the light chain JL given the VL; the lengths of the complementarity-determining-region 3 regions ( H-CDR3 and L-CDR3 ) ; the percentages of amino-acid mutations on VH and VL; the ratios of framework mutations to total V gene mutations on VH and VL; the number and size of insertions and deletions on the heavy or light chains as a function of the percent mutation on VH or VL , respectively; and the number of cysteines on the heavy or light chains as a function of the percent mutation on VH or VL , respectively ( see Materials and Methods and S1–S3 Figs ) . To test the AFF method , we compared the features frequencies for 388 "normal" memory ( or plasmablast ) antibodies induced by vaccines [51–55] ( and this study ) or found in the human memory B cell repertoire [56] with the features frequencies for 300 , 000 antibody sequences computationally generated by the Monte Carlo method ( mc ) to be consistent with the frequency distributions of the individual features ( S1 Fig ) . The "normal" antibodies , which were not employed in the parameterization of the AFF method , had a mean ( ± standard deviation ) log antibody features frequency ( mean log ( f ) ) of -12 . 0 ± 2 . 1 , while the "mc" antibodies had a mean log ( f ) of -11 . 0 ± 1 . 5 . The similarity of these two distributions supports the validity of the method ( Fig 1A ) . Further support came from agreement between the distributions of features frequencies for germline versions of the "normal" and "mc" antibodies , in which germline antibodies were computationally assigned to have no mutations , insertions , or deletions , and to have only two cysteines ( that form the conserved internal disulfide bond in Ig domains ) in each heavy or light chain variable fragment ( Fv ) region ( Fig 1B ) . The germline "normal" mean log ( f ) was -9 . 6 ± 1 . 1 , while the germline "mc" mean log ( f ) was -9 . 4 ± 1 . 0 . We next evaluated the features frequencies for many HIV bnAbs ( Fig 1 and S4 Fig ) . The set of 49 potent HIV bnAbs ( mean or median IC50 < 0 . 5 μg/mL [27] against >50% of diverse viruses in the TZM-bl assay [57] or a similar assay [58] ) , had a mean log ( f ) of -23 . 0 ± 4 . 1 , significantly lower than -12 . 0 ± 2 . 1 for "normal" Abs or -11 . 0 ± 1 . 5 for "mc" Abs . The set of 19 less potent HIV bnAbs ( 0 . 5 μg/mL < mean or median IC50 < 5 μg/mL ) had a similarly low mean log ( f ) of -20 . 0 ± 4 . 4 . Furthermore , all but one potent HIV bnAb ( PG9 ) had features frequencies of less than 10−17 , whereas only 2 . 8% ( 11 of 388 ) of "normal" antibodies and 0 . 39% ( 1179 of 300 , 000 ) of "mc" antibodies had such frequencies ( Fig 1A ) . Despite those differences , the features frequencies for germline HIV bnAbs ( mean log ( f ) = -11 . 4 ± 1 . 6 ) were similar to those for germline "normal" or "mc" antibodies ( Fig 1B ) . Thus , the significantly lower features frequencies of HIV bnAbs compared to normal human memory antibodies are largely due to higher levels of mutations , insertions and deletions accumulated during affinity maturation , with a smaller contribution from unusual germline features . Among the known potent bnAbs , the least unusual that fall within the tail of normalcy in Fig 1 are the V2/Apex bnAbs PG9 and CAP256 , followed by several PGT151-class bnAbs and the high mannose patch bnAbs PGT130 and 32H3L ( Fig 1 and S4 Fig ) . Overall , this analysis quantifies the large ( several orders of magnitude ) gap in features frequencies between HIV bnAbs and normal human memory antibodies; this gap indicates that the known potent HIV bnAbs generally provide poor direct leads to guide HIV vaccine development , because antibodies with similar features are unlikely to be elicitable in a consistent manner . In contrast , a set of eight anti-influenza bnAbs had a mean log ( f ) of -11 . 9 ± 1 . 6 , with values ranging from -14 . 4 to -10 . 6 , consistent with typical human memory antibodies ( S5 Fig ) . Moreover , the analysis suggests that engineering or discovery of potent HIV bnAbs with higher features frequencies will be needed to focus vaccine efforts toward epitopes targeted by more plausibly inducible potent bnAbs . Our AFF analysis showed VRC01-class bnAbs to be among the most unusual of all HIV bnAbs , with log features frequencies ranging from -21 . 3 to -30 . 9 . Even VRC01-5fH6fL , a VRC01-derived bnAb previously engineered to have reduced framework mutation [50] , retained a low log features frequency of -22 . 3 ( Fig 1A ) , due to substantial mutation levels in VH ( 19 . 8% ) and VL ( 15 . 1% ) , and to an insertion and a deletion on the light chain ( S1B Fig and ref . [50] ) . To establish improved plausibility for a bnAb-based HIV vaccine , we developed two minimally mutated VRC01-class bnAbs . Though VRC01-class bnAbs are among the most mutated of HIV bnAbs [2 , 3 , 59] , crystal structures of VRC01-class bnAbs bound to various core gp120s revealed that many of the somatic mutations are distally located from the core epitope , suggesting that some mutations may not be necessary for potent and broad virus neutralization ( Fig 2A and refs . [25 , 50] ) . We developed a yeast surface display method to assess the importance of all VH or VL mutations for broad gp120 recognition . Libraries based on an inferred germline VRC01 were generated in which positions mutated in VRC01 VH and VL genes sampled only the germline and mutated residues; the libraries also sampled reversion of the insertion and deletion on the VRC01 light chain . These libraries were then sorted for high-affinity binding to a set of recombinant gp120 proteins from diverse HIV strains . Mutations that were heavily enriched ( 67% threshold ) were retained . Using this strategy , we developed two minimally mutated VRC01-class bnAbs , MinVRC01 and Min12A21 , with excellent neutralization breadth and potency only slightly or moderately diminished compared to the original bnAbs VRC01 [2] and 12A21 [3] on a cross-clade 80-virus panel ( Fig 2B to 2D and S1 Table ) . The VH genes of MinVRC01 and Min12A21 are 13% and 17% mutated from the germline VH1-2*02 precursor at the amino-acid level , respectively , whereas those of VRC01 and 12A21 are 42% and 32% mutated , respectively , showing that ~1/2 to 2/3 of the mutations in VRC01 and 12A21 are not strictly required for neutralization . Both MinVRC01 and Min12A21 retain a short L-CDR3 loop of five residues that appears to be structurally required for VRC01-class bnAbs to bind their gp120 epitope [46 , 49] . MinVRC01 , but not Min12A21 , retains a deletion in L-CDR1 and a disulfide between H-CDR1 and H-CDR3 , both of which are present in some VRC01-class bnAbs . MinVRC01 , but not Min12A21 , contains a single mutation that arose from PCR error , G54F , that had previously been shown to improve the potency of VRC01-class antibodies [60] . We retained this F54 in MinVRC01 because it is important for the breadth of MinVRC01 , and similar residues ( F , Y , W ) are found at this position in multiple other VRC01-class bnAbs ( 12A12 , 12A21 , VRC03 , VRC-PG20 ) . Overall , MinVRC01 and Min12A21 have higher features frequencies than any other VRC01-class bnAb , and Min12A21 has the highest features frequency of all HIV bnAbs examined in this study ( Fig 1A ) . The development of these minimally mutated bnAbs , particularly Min12A21 , establishes a more feasible goal for reliable vaccine elicitation of potent anti-HIV bnAbs . Many HIV bnAbs have been identified as poly- or auto-reactive; thus , tolerance mechanisms may serve as a barrier to elicitation of some bnAbs [27] . To assess the polyreactivity of MinVRC01 and Min12A21 , we conducted four assays: cardiolipin binding , HEp-2 cell staining , single autoantigen reactivity , and a polyspecificity reagent ( PSR ) binding assay [61 , 62] measuring binding to preparations of solubilized membrane proteins or cytosolic proteins ( Fig 3 and S6 Fig ) . By all four assays , 12A21 appeared clearly polyreactive whereas Min12A21 did not . In contrast , MinVRC01 was polyreactive in all four assays , whereas VRC01 showed no evidence of polyreactivity . As noted above , MinVRC01 contains one mutation , G54F , that is absent from VRC01 . The point mutant of MinVRC01 containing the VRC01-germline serine at position 54 ( MinVRC01-F54S ) retained polyreactivity ( though reduced compared to MinVRC01 ) , and the Phe54-variant of VRC01 ( VRC01-G54F ) lacked polyreactivity ( S6 Fig ) , therefore Phe54 is not the sole source of polyreactivity in MinVRC01 . Thus , while the reduction of mutation from 12A21 to Min12A21 removed polyreactivity , the removal of mutations from VRC01 to create MinVRC01 gave rise to polyreactivity . Overall , these results further support Min12A21 as a more realistic target for vaccine elicitation . Mutations in MinVRC01 and Min12A21 could be grouped into five spatial patches , three on VH and two on VL ( Fig 2B and 2C , colored patches ) . Alignments of VRC01-class heavy or light chains ( S7 Fig ) revealed similar patches in many of these bnAbs . To assess the relative importance of the mutation patches for antibody function , we generated variants of MinVRC01 with individual patches reverted to germline and tested these patch-revertants for neutralization on a cross-clade 16-pseudovirus panel ( Fig 4A and S2 Table ) . The data revealed a hierarchy of importance for neutralization potency and breadth for the patches , with H-CDR2 > L-CDR1/2 ≈ L-FW3 > H-CDR1 > H-FW3 . Notably , while the H-ΔFW3 revertant retained high breadth ( 94% ) and modest potency ( 1 . 8 μg/mL ) and the H-ΔCDR1 revertant showed modest breadth ( 38% ) and potency ( 1 . 3 μg/mL ) , the H-ΔCDR2 revertant failed to neutralize any viruses and the L-ΔCDR1/2 and L-ΔFW3 revertants each neutralized only 2/16 viruses in the panel . We generated the same patch reversions on VRC01 and observed similar effects but diminished in magnitude , suggesting the parent bnAb may contain some redundancy ( S2 Table ) . Previous structural analyses of VRC01 , 12A21 and other VRC01-class bnAbs interacting with Env subunits provide considerable information on the structural roles of the residues within the patches . The H-CDR2 patch makes direct contacts with four gp120 elements ( loop D , β15/α3 , β20/21 and β23/V5 ) in all VRC01-class bnAbs [25] . The H-CDR1 patch makes little direct gp120 contact [25 , 49 , 60] , but owing to its importance for neutralization we hypothesize that it may stabilize the adjacent H-CDR2 . H-FW3 contacts residues from β3 and β20/21 on the V1/V2 truncated gp120 core [25 , 49 , 60] and has been proposed to contact V3 residues on a neighboring protomer in the trimer [48] , but the precise role of H-FW3 has remained unclear . L-CDR1 in all VRC01-class bnAbs includes either deletions or mutations to glycine , which has been interpreted as a requirement to avoid a clash with Loop D on gp120 [25 , 49] . Comparative analysis of light chains in VRC01 and NIH45-46 , a VRC01-class bnAb with 89% VH sequence identity to VRC01 [33] , and structural analysis of 45-46m2 , an engineered variant of NIH45-46 with improved breadth and potency , have indicated an important but not obligatory role of Tyr28 in VRC01 L-CDR1 for contacting the N276 glycan , and have also shown that 45-46m2 L-CDR2 and L-FW3 residues can contact a short Man4GlcNAc2 glycan at position 276 [45 , 47] . To further dissect the role of light chain patches in interacting with the N276 glycan , we determined the crystal structure at 3 . 25 Å resolution of Fab VRC01 bound to an engineered gp120 outer domain ( eOD ) that contains a Man9GlcNAc2 glycan at position 276 ( eOD-N276Kif ) ( Fig 5A ) . The VRC01 interactions with the N276 glycan contribute an additional 550Å2 of buried surface area to the previously defined epitope [25] , and an additional 229 Å2 of buried surface area compared to the 45-46m2+gp120 structure with a shorter Man4GlcNAc2 glycan at position 276 [47] , due to a significantly different glycan conformation , several new H-bonds , and increased stacking interactions with TyrL28 ( Fig 5B ) . All three L-FW3 affinity-matured residues ( ArgL66 , TrpL67 and ProL69 ) and two of the L-CDR1 affinity-matured residues ( TyrL28 and GlyL29 ) directly contact the N276 glycan ( Fig 5B and S8 Fig ) . Together , the Man9GlcNAc2 N276 glycan interactions constitute a third of the antibody paratope surface area . The two-residue deletion in L-CDR1 eliminates a steric clash between the germline-VRC01 L-CDR1 and the GlcNAc2 base of the N276 glycan ( S9A Fig ) . Steric clashes between germline VRC01 L-FW3 and the N276 Man9GlcNAc2 D2 arm are alleviated by mutations in mature VRC01 ( S9B Fig ) . Structural comparisons with other VRC01-class bnAbs co-crystallized with core gp120 suggest that all VRC01-class antibodies have evolved similar mutations to avoid and/or utilize the N276 glycan ( S9C and S9D Fig ) . The glycoforms present at N276 on infectious particles remain to be identified , information that may be important for VRC01-class vaccine development . Fully-solvated molecular dynamics simulations of eOD with a complex biantennary glycan at N276 suggest that mammalian glycoforms other than oligomannose species could also be accommodated by VRC01-class bnAbs ( S10 Fig ) . This structure and these analyses thus improve our understanding of VRC01-class interactions with the N276 glycan . To further delineate the full extent of the VRC01-class epitope and paratope , we determined the crystal structure ( at 4 . 4 Å ) of a partially deglycosylated BG505 SOSIP trimer in complex with PGT122 Fab and the single-chain variable fragment ( scFv ) of NIH45-46 . The trimer backbone conformation was very similar to the same trimer crystallized either with PGT122 alone [63] ( Cα RMSD 0 . 97 Å for gp120 ) or in the unliganded state [64] ( Cα RMSD 0 . 74 Å for gp120 ) , illustrating that NIH45-46 binds to the "ground-state" conformation of Env [65] and does not induce Env conformational changes . The VRC01-class epitope is densely surrounded by N-linked glycans ( Fig 5C ) , as suggested in the cryo-EM structure of the BG505 trimer with VRC01-class bnAb PGV04 [48] . Glycans account for at least 30% of the surface area buried by NIH45-46 on the trimer; the antibody interacts with N197 , N234 , N276 and N462 glycans on one gp120 protomer and with the N262 glycan on the adjacent gp120 protomer ( S3 Table ) . The N276 glycan appears to be truncated in the trimer structure , as there is no density for glycan moieties beyond the first NAG , which would be consistent with trimming by EndoH that was employed for deglycosylation of the protein used for structural study . This considerably reduces the buried surface area on the 276 glycan compared to the eOD-VRC01 structure . In the absence of the N276 glycan , the N234 glycan appears to have avoided trimming and makes extensive contacts to the NIH45-46 L-FW3 patch , effectively replacing the N276 glycan interactions with L-FW3 seen in the eOD+VRC01 complex . This indicates promiscuity in the ability of the L-FW3 to interact with glycans , and also a level of redundancy in antibody recognition of the HIV Env glycan shield [66] . Neutralization of pseudoviruses with glycan knock-out mutations demonstrated that VRC01 and 12A12 potency improved when the N197 , N234 , N262 , N276 or N462 glycans were absent ( Fig 5C and S4 Table ) . We therefore conclude that N-linked glycans surrounding the CD4bs on the trimer restrict antibody angles of approach and reduce binding and neutralization by VRC01-class bnAbs . The MinVRC01 mutations that enable N276 glycan interactions are required for neutralization of viruses bearing that glycan ( see below ) . Thus , while the HIV Env trimer has evolved a glycan fence around the CD4 binding site that imposes steric and entropic penalties to antibody binding [67 , 68] , VRC01-class bnAbs appear to have evolved solutions that avoid glycan clashes and partially offset the entropic penalties . Based on our trimer structure , we estimate that NIH45-46 buries ~25% more area on the Env trimer than on core gp120 , nearly half of which is due to additional protein contacts ( S3 Table ) . Approximately 75% of the area buried by NIH45-46 on the trimer is contained within elements present on eOD , ~20% is within the bridging sheet or inner domain of the same protomer , and ~5% comes from an adjacent protomer ( Fig 5E and S3 Table ) . Importantly , NIH45-46 recognizes the bridging sheet in its pre-fusion conformation on the BG505 SOSIP trimer , positioning the H-FW3 patch to interact with gp120 elements β21 , β3 and the base of the V2 loop ( Fig 5D and 5E and S3 Table ) . In contrast , when NIH45-46 and other VRC01-class bnAbs bind core gp120 , the bridging sheet adopts the CD4-bound conformation , resulting in a considerably different interaction surface for H-FW3 . Moreover , the N197 glycan , at the V2 base on the trimer , is in H-bonding distance to two affinity-matured NIH45-46 residues , namely ArgH19 ( H-FW1 ) and ArgH82A ( H-FW3 ) . Arg or Lys is present in most VRC01-class bnAbs at these positions , suggesting that these residues may make important contributions to neutralization potency and/or breadth . The trimer structure also indicates that the NIH45-46 H-FW3 patch is probably too distant from the adjacent V3 region to make extensive interactions , although other bnAbs with H-FW3 insertions , such as 3BNC60 , likely have evolved to do so more effectively [26] . Overall , the trimer structure reveals the importance of employing native-like trimer immunogens in regimens to induce VRC01-class bnAbs—only native-like trimers provide the pre-fusion conformation of the bridging sheet , the full VRC01-class epitope including both protein and glycan contacts , and the restrictions on angle of approach due to quaternary packing and the glycan fence around the CD4bs that are also present on the virus . We next evaluated how the different gp120 glycoforms modulated neutralization by MinVRC01 light chain revertants ( Fig 4B ) . Neutralization was tested against a 6-pseudovirus panel produced in four conditions: ( i ) in 293T cells , resulting in viruses having diverse biologically relevant glycoforms , including complex , hybrid and oligomannose glycans , ( ii ) in 293T cells grown with kifunensine ( 293kif ) , producing viruses with uniform Man9GlcNAc2 glycans , ( iii ) in 293 GnTI-/- cells , yielding viruses with oligomannose glycans , ( Man5GlcNAc2 to Man9GlcNAc2 ) [69] , and ( iv ) in 293T cells with an Env point mutation to eliminate the 276 glycosylation site ( N276A ) . While both L-CDR1/2 and L-FW3 mutations are required to achieve maximum breadth and potency against wild-type viruses , the L-CDR1/2 mutations alone are necessary and sufficient for modest neutralization of GnTI-/- viruses , consistent with the proximity of the L-CDR1/2 mutations to the base of the N276 glycan ( Fig 5 and S9 Fig ) . Furthermore , the light-chain germline revertant broadly neutralizes a panel of N276A viruses , which suggests that the primary function of the light-chain somatic mutations of MinVRC01 is to accommodate the N276 glycan . This conclusion holds for VRC01-class bnAbs in general , based on our neutralization assays for mature-H/germline-L chimeras of 10 different VRC01-class bnAbs against a panel of 13 pseudoviruses with and without N276A . All 10 chimeras are potent and broad neutralizers against the N276A panel , with breadth >50% and median IC50 <0 . 3 μ/mL , but only 2 of 10 show similar activity against the panel with N276 intact ( Fig 4C and S5 Table ) , consistent with our structural analysis ( Fig 5 ) . Following on from the finding that MinVRC01-HC/GL-VRC01-LC and other VRC01-class mature-H/germline-L chimeras broadly neutralize N276A viruses , and with the concomitant realization that neutralization of N276A viruses could be an important readout on the pathway to induction of VRC01-class bnAbs , we sought to determine more precisely the minimal heavy-chain mutations required for broad neutralization of sensitive N276A viruses . We generated variants of GL-VRC01 and GL-VRC01-HC/MinVRC01-LC in which we restored only the H-CDR1 , H-CDR2 or H-FW3 patches , and we tested these Abs against a panel of 23 N276A-sensitive viruses . These experiments showed that , for many viruses , only the six H-CDR2 mutations were necessary for weak neutralization ( Fig 4D ) . The GL-VRC01+H-CDR2 HC paired with the GL-VRC01 LC variant had 17% breadth across diverse viruses , while the same heavy chain paired with the MinVRC01 LC had 43% breadth against the same panel . Both Abs neutralized at least one virus each from clade A , B and C .
In summary , we have developed two minimally mutated VRC01-class bnAbs and demonstrated that their features frequencies are more concordant with vaccine-induced Abs in general as compared to VRC01-class bnAbs isolated from individuals following many years of HIV infection . Min12A21 , with the highest features frequency of any of the 68 bnAbs tested , was also free of polyreactivity . Taking advantage of their reduced mutation , we dissected the structural requirements for broad and potent neutralization by the minimally mutated Abs and then used the resulting knowledge to develop a stepwise vaccination strategy as a working concept that is intended to elicit the necessary antibody features for potent and broad neutralization of HIV viruses . We recognize that any immunogen may induce some level of non-critical mutations . The immunization strategy poses specific objectives for affinity maturation at each step and , as such , is amenable to experimental testing and stepwise optimization in a way that vaccine strategies normally are not . Taken as a whole , this work advances the concept of "reductionist" vaccine design guided by structural analysis of minimally mutated bnAbs and their interaction with HIV Env .
Peripheral blood mononuclear cells ( PBMCs ) were isolated from the whole blood of eight healthy donors by gradient centrifugation ( Histopaque-1077; Sigma-Aldrich ) . From each donor , IgG+ memory B cells were separated from 10 million PBMCs by selective depletion ( Switched memory B cell isolation kit; Miltenyi Biotec ) and total RNA was extracted ( RNeasy; Qiagen ) . Approximately 10% of each total RNA sample was subjected to reverse transcription ( Superscript III; Life Technologies ) using cDNA barcoding primers that contain 20 nucleotide long unique antibody identifiers ( UAIDs ) . The resulting cDNA was purified ( Qiaquick; Qiagen ) and eluted into 50uL of water . 10uL of cDNA was used to amplify antibody heavy chains ( HotStarTaq Plus; Qiagen ) in a 50uL total reaction volume using the following thermal cycling program: 94°C for 5 min; 30 cycles of 94°C for 30 s , 55°C for 30 s , 72°C for 2 min; 72°C for 7 min . Following initial amplification , PCR products were purified using 45 μL of SPRIselect beads ( Beckman-Coulter Genomics ) per 50 μL PCR reaction and eluted in 50 μL of water . Illumina sequencing adapters and sample-specific indexes were added during a second round of PCR using 1 μL of purified PCR product in 100 μL of total PCR reaction volume and using the following thermal cycling program: 94°C for 5 min; 10 cycles of 94°C for 30 s , 55°C for 30 s , 72°C for 2 min; 72°C for 7 min . Indexed PCR products were purified using 75 μL of SPRIselect beads and eluted in 50 μL of water . Samples were quantified using fluorometry ( Qubit; Life Technologies ) , pooled at approximately equimolar concentrations and the sample pool was re-quantified . Samples were loaded onto an Illumina MiSeq sequencer with a target loading concentration of 40 pM and 10% PhiX and sequenced ( MiSeq 600-base v3 reagent kit; Illumina ) . Paired-end MiSeq reads were merged with PANDAseq using default settings [72] . Sequences were annotated with AbStar , an antibody analysis software package based on BLASTn , using human germline V ( D ) J databases from IMGT [73] . Following annotation , sequences were loaded into a MongoDB database for querying and additional analysis . To correct sequencing and amplification errors , antibody sequences were binned by the cDNA barcode , and all bins containing only a single sequence were discarded . For each bin containing two or more sequences , the appropriate germline variable gene region was added to the bin to serve as a consensus tiebreaker . The bins were then separately aligned with Muscle , and consensus sequences were generated using Biopython . Consensus sequences were re-processed with AbStar and stored in a separate MongoDB database . Following error correction , sequences were screened with two additional quality filters: 1 ) the sequence must be at least 200 bp ( light chains ) or 250 bp ( heavy chains ) in length; and 2 ) the junction must begin with a conserved cysteine and end with either a phenylalanine ( light chains ) or tryptophan ( heavy chains ) and contain no ambiguous codons . Raw sequence data from DeKosky et al . [29] were downloaded from the Short Read Archive ( SRA ) and , because SRA files are generated by concatenating paired Illumina reads into a single file , each SRA file was split into two ‘read’ files corresponding to the paired sequencing reads . In each pair of read files , paired reads were assigned the same sequence ID to enable reconstitution of native heavy/light pairs . Quality and length trimming was performed on each read file using Sickle [74] ( with options -q 25 and -l 200 ) such that the 3' end of each read was trimmed until a 25-base sliding window contained an average sequence quality of 25 and trimmed reads of less than 200 bases were discarded . Germline V ( D ) J gene assignment and junction identification was performed with AbStar and resulting assignments were stored in a MongoDB database . Heavy-chain junctions were clustered at 96% sequence identity to collapse duplicate sequencing reads and centroid sequences were calculated for each cluster with at least 2 heavy chain junctions . For each centroid heavy chain sequence , the sequence ID was used to retrieve the appropriate paired light chain sequence . Length distributions for heavy , kappa light , and lambda light chains were measured using IMGT [75] conventions . MAbs were cloned from single HPV 16-specific , CD27+IgD- memory B cells as previously described [54] . In brief , PBMC samples were enriched for B cells , separated into two parts , and stained with a multicolor flow cytometry panel and either Alexa Fluor 488 ( AF488 ) -conjugated HPV 16 pseudovirus ( psV ) or AF488-conjugated bovine papillomavirus psV ( negative control ) . AF488-HPV 16 psV+ memory B cells were then single cell sorted by FACS into PCR plates containing lysis buffer . cDNA was generated from the bulk RNA of these sorted cells using RT-PCR with random primers . Full-length heavy and light chain variable regions were then separately amplified from the cDNA by conducting multiple PCRs in parallel with pools of newly designed primers against the leader and constant regions . For this study , we utilized the following PBMC samples: 1 . De-identified PBMC collected one month post-final vaccine dose from women aged 9–13 and 16–26 years of age who received two or three doses of the quadrivalent HPV vaccine as part of a clinical trial [76] ( clinicaltrials . gov Identifier: NCT00501137 ) ; 2 . PBMC collected one month post-final vaccine dose from women aged 18–26 years of age who received the full quadrivalent HPV vaccine series and were HPV 16 seronegative at the start of the study; 3 . PBMC collected from women aged 27–45 years of age who were HPV 16 seropositive and had never been vaccinated against HPV . Monoclonal antibodies were generated as previously described [77] from day 7 plasmablasts from individuals who had received anthrax vaccination . The antibodies were tested for reactivity against PA by ELISA . For next generation sequencing of IgG+ memory B cells , peripheral blood was obtained from healthy adult donors following written informed consent , under a protocol ( IRB# 12–5951 ) approved by the Scripps Institutional Review Board . For analysis of HPV vaccine-induced antibodies , sample group 1 , as outlined above , was collected from de-identified participants in a clinical trial [76] ( clinicaltrials . gov Identifier: NCT00501137 ) ; sample groups 2 and 3 were collected with written informed consent from women enrolled in a study that was approved by the Institutional Review Boards of the University of Washington and the Fred Hutchinson Cancer Research Center ( file numbers 42337 and 7740 , respectively ) . For analysis of anthrax vaccine-induced antibodies , samples were collected from individuals who were recruited and consented in writing in accordance with the University of Chicago institutional review board ( IRB #09-440-A ) . Frequency distributions were measured for multiple antibody features ( see below ) from two sets of human memory antibody sequences: one set of heavy-light paired sequences from three donors from DeKosky et al . [29] and another set of unpaired heavy and light chain sequences from eight donors from this study . Because each antibody chain was sequenced using only a single MiSeq read , the DeKosky et al . sequences were incomplete , generally spanning only from CDR2 through the J-chain on both the heavy and light chains . This meant that the DeKosky et al . sequences could not be used to measure distributions for several of the features . However , the DeKosky et al . paired sequences were essential for measuring the frequency distribution for VL given VH . In total , after we filtered the DeKosky et al . sequencing data as described above , we were left with 127 , 701 paired sequences . From the unpaired sequences from eight donors determined for this study , we used 99 , 678 heavy-chain sequences and 52 , 560 light-chain sequences . Frequency distributions for the following 15 features were measured , with the distributions shown in S1 Fig: ( 1 ) Heavy chain VDJ; ( 2 ) VL given VH , or "VL|VH"; ( 3 ) JL given VL , or "JL|VL"; ( 4 ) H-CDR3 length; ( 5 ) L-CDR3 length , computed separately for kappa or lambda light chains; ( 6 ) Percent amino-acid mutation on VH , or "VHmut"; ( 7 ) Percent amino-acid mutation on VL , or "VLmut"; ( 8 ) Ratio of framework % amino acid mutation to VH gene % amino-acid mutation for heavy chains with different % VH mutation levels , or "FRHmut/VHmut given VHmut" or most compactly written as "[FRHmut/VHmut]|VHmut"; ( 9 ) Ratio of framework % amino-acid mutation to VL gene % amino-acid mutation for light chains with different % VL mutation levels , or "FRLmut/VLmut given VLmut" or "[FRLmut/VLmut]|VLmut"; ( 10 ) sizes of insertions in human heavy chains with different % VH gene mutation levels , or "InsSizesH|VHmut"; ( 11 ) sizes of deletions in human heavy chains with different % VH gene mutation levels , or "DelSizesH|VHmut"; ( 12 ) sizes of insertions in human light chains with different % VL gene mutation levels , or "InsSizesL|VLmut"; ( 13 ) sizes of deletions in human light chains with different % VL gene mutation levels , or "DelSizesL|VLmut"; ( 14 ) number of cysteines in the Fv domain of human heavy chains with different % VH gene mutation levels , or "CysCountH|VHmut"; ( 15 ) number of cysteines in the Fv domain of human light chains with different % VL gene mutation levels , or "CysCountL|VLmut" . ( n . b . Most heavy or light chain Fv domains have two cysteines that form highly conserved disulfide bonds; therefore , counting the number of cysteines was used to track the potential formation of additional disulfide bonds . ) The features frequency ( f ) was computed as the product of the 15 individual frequencies: f = f ( VDJ ) × f ( VL|VH ) × f ( JL|VL ) × f ( VHmut ) × f ( VLmut ) × f ( [FRHmut/VHmut]|VHmut ) × f ( [FRLmut/VLmut]|VLmut ) × f ( InsSizesH|VHmut ) × f ( DelSizesH|VHmut ) × f ( InsSizesL|VLmut ) × f ( DelSizesL|VLmut ) × f ( CysCountH|VHmut ) × f ( CysCountL|VLmut ) , where each term in the equation represents a single frequency with a value greater than 0 and less than or equal to 1 , except for the InsSizes and DelSizes terms which represent the product of the frequencies for each insertion or deletion , respectively , detected in a sequence . Bin sizes and mutation ranges used to compute the various frequency distributions were selected with an attempt to reveal variations in the data above random noise and to minimize the number of bins with zero counts in the data ranges needed to assess HIV bnAb sequences . In the cases of bins with zero counts , the AFF method assigns a frequency of 1/N , where N is the number of sequences used to measure the distribution in question . For example , if the AFF method is asked to evaluate the features frequency of an antibody sequence that has a VHDHJH not observed in the 227 , 379 memory antibody heavy-chain sequences used to construct the VDJ frequency distribution , the value of f ( VDJ ) will be assigned as 1/227 , 379 . For Monte Carlo generation of antibody sequences consistent with the AFF method , features were randomly selected from each feature distribution , using a pseudo-random number generator in awk . We found that the default output of the rand ( ) function in awk , with six significant figures , contained repeats even in 10 , 000 trials . We combined rand ( ) and sprintf ( ) to generate numbers with ten significant figures [as random_number = sprintf ( "% . 10g" , 1-rand ( ) ) ] , and this method generated sequences of numbers with no repeats in 300 , 000 trials that were sufficiently evenly distributed over the interval from 0 to 1 , with less than 1% variation in the frequency of numbers generated among all 20 intervals of size 0 . 05 ( 0<x≤0 . 05; 0 . 05 <x≤0 . 1; etc . ) . By computing the overall features frequency as a product of individual features frequencies , the AFF model makes the approximation that the 15 features frequencies are independent . As described above , we have attempted to construct the features in a manner that makes them independent , by accounting for expected dependencies or correlations ( e . g . f ( VDJ ) accounts for correlations in usage of VH , DH and JH genes , f ( VL|VH ) accounts for VL and VH pairing preferences , f ( JL|VL ) accounts for JL and VL pairing preferences , and multiple features explicitly account for their dependence on % mutation albeit in a rather coarse manner dictated by limited available data ) . There are two notable exceptions , where we were unable to account for an expected dependence . The first is that VHmut and VLmut are treated as independent . In reality , as an antibody undergoes somatic hypermutation , both heavy and light chains are likely to gain mutations; hence , the % mutations on the heavy and light chains are likely to be correlated . The Pearson linear correlation coefficient for VHmut and VLmut computed over the 388 "normal" Abs is 0 . 49 , and the Spearman rank correlation coefficient is 0 . 51 , both indicating a modest but not strong linear correlation ( S2A Fig ) . Therefore , treating VHmut and VLmut as independent modestly overestimates the frequency penalty due to mutation . At present , there are insufficient data available to allow parametrization of the dependence of VLmut on VHmut or vice versa . We noted above that the DeKosky et al . [29] heavy-light paired sequences were incomplete , generally spanning only from CDR2 through the J-chain on both the heavy and light chains; this meant that the DeKosky et al . data could not be used to compute VHmut or VLmut or their correlations . If similar NGS data on heavy-light paired sequences becomes available with complete sequences of heavy and light , then the AFF model could be improved by accounting for the correlation between VHmut and VLmut . We did test the effect of ignoring the VLmut term , which would correspond to underestimating the frequency penalty due to mutation; while the computed frequency for each antibody sequence increased because a penalty term was eliminated , the overall findings of AFF were qualitatively the same . The second expected dependence that we could not explicitly account for in the AFF model is the dependence of H-CDR3 length on the VH , DH and JH genes . It has been shown that , in human peripheral blood antibodies , "long" H-CDR3 loops of length 24 aa or more , and "very long" H-CDR3 loops of length 28 aa or more , are more commonly found in antibodies utilizing JH genes of the J6 family or DH genes of the D2 or D3 families , and less commonly found in antibodies utilizing JH genes of the J4 family [78] . We confirmed these trends in the 227 , 379 memory antibody heavy chain sequences obtained by NGS in this study and in DeKosky et al . , finding that antibodies using DH2 or DH3 with JH6 had an H-CDR3 length distribution most shifted to longer lengths while antibodies using JH4 with neither DH2 nor DH3 had a distribution most shifted to shorter lengths ( S2B Fig ) . Briney et al . [78] further showed that only a small subset of the DH2 or DH3 genes were favored for long H-CDR3s , and they also provided evidence that certain VH gene families were favored or disfavored for long H-CDR3s . We lack sufficient sequencing data to quantify these effects and incorporate them into AFF at this time: even the coarse treatment shown in S2B Fig has too little data to accurately specify distributions at lengths above ~25 amino acids . Therefore , we are not accounting for these effects in AFF , even at this coarse level , at this time . We note that the magnitude of the frequency corrections that would be obtained by accounting for these dependencies is modest: in S2B Fig , over the range of H-CDR3 lengths of 20 to 25 , the average frequency correction for Abs using DH2 or DH3 with JH6 would be to increase the frequency by a factor of 3 . 4 compared to using the distribution for all Abs , while the average correction for Abs using JH4 with neither DH2 nor DH3 would be to reduce the frequency by a factor of 7 . 1 . Frequency corrections of these magnitudes would shift the log ( f ) values in Fig 1 by less than one unit . Thus , while the AFF model currently assigns a frequency based on the H-CDR3 length without incorporating any dependence on VH , DH and JH genes , incorporating these dependencies would improve the accuracy of the model . To evaluate the degree to which the features frequencies might be linearly correlated , we computed the Pearson linear correlation coefficient "r" for each of the pairs of frequencies ( frequencies 1 to 15 above , a total of 105 pairs ) , among the 388 "normal" Abs . The r-values ranged from -0 . 41 to +0 . 39 , indicating that none of the pairs of frequencies were strongly linearly correlated . Indeed , six of the seven r values with absolute value greater than 0 . 2 each involved frequencies ( of insertions or deletions ) with very small data range ( of standard deviation less than 0 . 1 ) indicating no meaningful correlation . Inspection of plots of frequency pairs for the seven largest absolute values of r failed to identify visually compelling correlations . To assess the degree to which the 15 individual terms in the AFF model contribute to the output , we conducted a global sensitivity analysis using as input the 300 , 000 mc antibody sequences . We measured the proportion of the total variance of log ( f_HL ) contributed by the variance in each individual log ( f ) term . The results are shown in S3 Fig . All of the terms contribute to varying degrees , with eight terms each contributing between 7 and 12% of the variance and seven terms each contributing between 2 . 5 and 5% of the variance . Full-length gp120 proteins were produced in FreeStyleTM 293F ( Invitrogen ) suspension cultures or lab-adapted 293S ( GnTI-/- ) suspension cultures by transient transfection using 293Fectin ( Invitrogen ) of a pHLSec plasmid containing gp120 with a C-terminal His6x affinity tag . Protein was harvested from the supernatant after 96 h and purified by affinity chromatography with a HisTrap column ( GE ) followed by Superdex 200 size exclusion chromatography ( GE Healthcare ) using an AKTA Express system ( GE Healthcare ) . eOD-N276Kif was produced in FreeStyleTM 293F ( Invitrogen ) suspension cultures by transient transfection using 293Fectin ( Invitrogen ) of a pHLSec plasmid containing gp120 with a C-terminal His6 affinity tag in the presence of 25 μM kifunensine . Protein was harvested from the supernatant after 96 h and purified by affinity chromatography with a HisTrap column ( GE ) followed by Superdex 75 size exclusion chromatography ( GE Healthcare ) using an AKTA Express system ( GE Healthcare ) . IgG and Fabs were produced using the pFUSEss expression vectors or pHLsec , respectively , and purified as described previously [40] . VRC01 is extensively mutated from its putative germline precursor and we sought to identify all mutations from germline that contributed significantly to the function of the antibody . This was accomplished by generating yeast surface display libraries in which VRC01 variants were expressed on the surface of yeast as scFvs . In these libraries , positions containing somatic mutations in the VH and VL gene segments of VRC01 were allowed to sample either the germline or affinity-matured residues . VRC01 contains 41 mutations in the variable heavy ( VH ) and 23 mutations in the variable light ( VL ) gene segments . Due to limitations on the size of library generation for yeast surface display ( the largest library that can be easily sampled is ~1x107 ) , it was not possible to generate a library that simultaneously sampled all possible combinations on the heavy chain and light chain ( 2 ( 41+23 ) = 1 . 8x1019 ) ; therefore , the library size had to be reduced by ~12 orders of magnitude . The library size was reduced in two ways . First , the heavy chain and light chain were separated into two libraries , in which the heavy chain ( HC ) library was paired with the fully mature light chain ( LC ) , and vice versa . Second , to further reduce the diversity on the HC , only positions that had mutated from the germline precursor in both VRC01 and PGV04 ( the only VRC01-class bnAbs available to us when this study began ) were considered for the library . Libraries were generated using PCR assembly of oligos containing degenerate codons , as described previously [40] . Both the HC_library/LC_Mat and HC_Mat/LC_library were sorted for binding to biotinylated YU2 gp120 . Initially , a LC library was generated in which the two amino-acid deletion in L-CDR1 was removed . However , as high affinity clones failed to enrich , a second library containing the deletion was created and sorted . Sequences were recovered and any mutations that enriched above 60% were retained . At this point , the library was small enough that the heavy and light chains could be combined together and all possible combinations sorted at the same time . Initially this library was sorted for binding to recombinantly produced YU2 gp120 . Position 54 in the library was designed to encode Gly or Ser , but a number of recovered sequences contained a phenylalanine at that position; the phenylalanine presumably arose during PCR . A revised library was created , allowing position H54 to sample Gly , Ser and now Phe . This library was generated , split into 5 separate groups and independently sorted for binding to recombinant gp120 derived from UG037 ( clade A ) , JR-FL ( clade B ) , YU-2 ( clade B ) , CN54 ( recombinant clade BC ) and DU179 ( clade C ) strains of HIV . Any position that enriched for the mature amino acid >67% of the time was included in MinVRC01 . Libraries displaying MinVRC01 scFvs were induced overnight , removed from the induction media , washed and labeled with monomeric gp120 for 1 hour . The cells were pelleted and washed once in PBS + 0 . 2% BSA , then labeled with an anti-c-Myc-FITC conjugated secondary to assess the amount of scFv on the surface and streptavidin PE to detect bound gp120 . The top 10% binding population ( indicated by the FITC:PE ratio ) were sorted into selectable media and regrown to induce and sort again . This process was repeated 4–5 times at decreasing concentrations of gp120 to select the highest affinity clones . The initial library was sorted at a gp120 concentration of160 nM to generate a pool of clones that had properly assembled and displayed the scFv . In subsequent sorts , the concentration of gp120 was decreased such that higher affinity clones could be easily sorted from the majority of the binding population . This process was repeated until reducing the concentration of gp120 resulted in a global decrease in PE signal of all clones in the sort , indicating that all present variants had comparable affinity . The final sorts were typically done at a gp120 concentration of 10–40 nM . The initial GH/ML and MH/GL library was sorted against only YU2 gp120 , and subsequent libraries were sorted against YU2 , UG037 , DU179 CN54 or JRFL gp120 . After 5 sorts , cells were plated out onto selectable media and 48 sequences were recovered from each library . To determine the generalizability of the MinVRC01 mutations , we set out to develop a second minimally mutated VRC01-class antibody . We selected 12A21 [33] as a good candidate because the mature 12A21 bnAb contains no insertions or deletions and has an aromatic residue at position 54 on the heavy chain . The sequence of 12A21 was aligned to MinVRC01 and the somatic hypermutations on 12A21 that appeared equivalent to those in MinVRC01 were preserved . We then generated a directed library for which the remaining positions were allowed to sample either the germline residue or the 12A21 mutation . This library was then sorted for binding to a single gp120 . Two additional mutations , ArgH19 and TrpH37 , were identified in the sorting and were therefore included in Min12A21 . The HEp-2 cell-staining assay was performed using kits purchased from Aesku Diagnostics ( Oakland , CA ) . These Aesku slides use optimally fixed human epithelial ( HEp-2 ) cells ( ATCC ) as substrate and affinity purified , FITC-conjugated goat anti-human IgG for the detection . The procedure followed the manufacturer's instructions . Briefly , 2 . 5 μg or 25 μl of 100 μg/ml mAb and controls were added to wells and incubated on HEp-2 slides in a moist chamber at room temperature for 30 min . Slides were then rinsed and submerged in PBS . Excess PBS was shaken off and 25 μl of FITC-conjugated goat anti-human IgG was immediately applied to each well . Slides were allowed to incubate at room temperature in a moist chamber for another 30 min . Slides were next washed in the same manner as above and then mounted on coverslips using the provided mounting medium . Slides were viewed at 20x magnification and photographed on an EVOS f1 fluorescence microscope at a 250 ms exposure with 100% intensity . Sera of positive and negative controls were provided by the vendor . Samples showing fluorescence greater than the negative control were considered positive for HEp-2 staining . Monoclonal antibodies were screened for reactivity with preparations of solubilized membrane proteins ( SMP ) and cytosolic proteins ( SCP ) as described previously [61 , 62] with a small modification . Briefly , SMP and SCP were extracted from CHO cells ( ATCC ) . The protein concentration was determined using the Dc-protein assay kit ( BioRad ) . SMP and SCP were then immobilized on ELISA plates for mAb screening . The results were established by reading the absorbance at 450 nm of the examined samples . An Anti-Cardiolipin ELISA kit ( Diamedix Corp , Miami Lakes , FL ) was applied to test mAbs for cardiolipin reactivity according to the manufacturer’s instructions . Antibodies were used at concentrations starting at 50 μg/ml and titrated in two fold serial dilutions . 4E10 was the positive control and Humira was the negative control . Single antigen ELISA assays for SSA/Ro , SS-B/La , Sm , ribonucleoprotein ( RNP ) , Jo-1 , double-stranded DNA , centromere B , and histones were purchased from Aesku Diagnostics ( Oakland , CA ) . The 96 wells were separately coated with these eight cellular and nuclear antigens for the qualitative detection of mAbs reactivity . A cut-off calibrator was provided by the manufacturer . The negative control was diluted human serum . Pseudoviruses were generated by transfection of 293T cells ( ATCC ) with an HIV-1 Env expressing plasmid and an Env-deficient genomic backbone plasmid ( pSG3ΔEnv ) , as described previously [57] . Pseudoviruses were harvested 72 h post-transfection for use in neutralization assays . Neutralizing activity was assessed using a single round of replication in a pseudovirus assay with TZM-bl target cells . Briefly , TZM-bl cells were seeded in a 96-well flat bottom plate . To this plate was added pseudovirus , which was preincubated with serial dilutions of antibody for 1 h at 37°C . Luciferase reporter gene expression was quantified 72 h after infection upon lysis and addition of Bright-Glo Luciferase substrate ( Promega ) . To determine IC50 values , dose response curves were fitted using nonlinear regression . VRC01 Fab was produced and purified as previously described [40] . eOD-N276Kif , a minimal glycan , alanine-resurfaced construct possessing only three glycosylation sites ( N18 , N65 and N79 , eOD numbering as in PDB IDs 4JPJ and 4JPK ) was designed and subsequently transfected in HEK 293F ( Invitrogen ) suspension cells in the presence of the mannosidase I inhibitor kifunensine , to yield homogeneous Man9GlcNAc2 carbohydrates . The secreted protein was purified via its C-terminus His6-tag by affinity chromatography using HisTrap nickel columns ( GE Healthcare ) , and subsequently purified to size homogeneity by Superdex 200 gel filtration chromatography ( GE Healthcare ) . After incubation of VRC01 Fab in molar excess of eOD-N276Kif , the complex was purified by Superdex 200 size exclusion chromatography ( GE Healthcare ) and concentrated to ~5 mg/ml for crystallization trials using the automated JCSG/IAVI/TSRI CrystalMation robotic system ( Rigaku ) at the Joint Center for Structural Genomics ( www . jcsg . org ) at TSRI . Crystals used for data collection were obtained with 0 . 16 M ammonium sulfate , 20% ( w/v ) PEG4000 , 20% ( v/v ) glycerol , 0 . 08 M sodium acetate , pH 4 . 6 , as the mother liquor . Prior to data collection , crystals were cryoprotected in the mother liquor supplemented with 40% glycerol and subsequently fast-plunged into liquid nitrogen . The BG505 SOSIP . 664 Env construct was expressed in HEK 293S GnTI-/- cells , together with co-transfection with the furin protease , and purified as previously described [63] . The HEK 293S cells lack N-acetylglucosaminyltransferase I and , therefore , only produce glycoproteins bearing mannose-rich ( Man5-9 ) glycans . Purified SOSIP . 664 gp140 trimers were mixed in molar excess of the PGT122 Fab , and subsequently treated with EndoH ( New England BioLabs ) , resulting in a partially deglycosylated glycoprotein , as previously described [63 , 79] . Following partial deglycosylation , the complex was incubated with a molar excess of NIH45-46 scFv and purified to size homogeneity using a Superose 6 10/30 gel filtration column ( GE Healthcare ) . Partial deglycosylation prior to addition of NIH45-46 scFv was critical to ensure complete saturation of the trimer , as previously described [48] . The purified complex was concentrated to ~5 mg/ml and screened in crystallization trials using the Oryx8 crystallization robot ( Douglas Instruments ) . Crystals were readily obtained from a crystallization condition containing 2 . 4 M ammonium sulfate , 0 . 1 M Tris , pH 8 . 0 . After dehydration and flash freezing , three crystals diffracted particularly well and the x-ray data collected were merged to obtain a high-redundancy complete data set to 4 . 4 Å ( S7 Table ) . The resolution limit was determined based on I/σ > 2 . 0 , the XSCALE-determined CC1/2 significant threshold [80] , and overall quality of the electron density maps calculated to slightly varying resolutions . Data processing was performed using XDS [80] . Statistics for data collection and processing are reported in S7 Table . The VRC01-eOD-N276Kif crystal structure was solved using the coordinates from PDB ID 4JPK as a search model for molecular replacement in PHASER [81] . To solve the partially deglycosylated BG505 SOSIP-NIH45-46 scFv–PGT122 Fab crystal structure , coordinates from PDB IDs 4NCO and 3U7Y were used as search models for molecular replacement using PHASER [81] . Refinement proceeded with non-crystallographic symmetry ( NCS ) and secondary structure restraints . For both structures , refinement was performed using a combination of PHENIX [82] and COOT [83] . Refinement statistics are reported in S7 Table . The crystal structure of mature VRC01 in complex with eOD containing a Man9GlcNAc2 glycan ( Fig 5A and 5B and PDB ID 5KZC ) was used as the template to prepare starting structures for molecular dynamics simulations . The core-fucosylated biantennary complex glycan [Gal β1–4 GlcNAc β1–2 Man α1–6 ( Gal β1–4 GlcNAc β1–2 Manα1–3 ) Man β1–4GlcNAc β1–4 ( Fuc α1–6 ) GlcNAcβ1] was obtained from the BiOligo database ( http://glyco3d . cermav . cnrs . fr ) [84] and edited to match the GLYCAM06h [85] force-field parameters for glycans and ff99SB [86] for protein as per AMBER12 [87] to generate the coordinate and topology files for the starting structures . The TIP3P explicit water model [88] was employed for solvation using periodic boundary conditions and chloride ions were added to neutralize the system using LEAP following standard protocols [89] . Starting with the prepared mature VRC01-eOD complex containing the core-fucosylated biantennary N-glycan system , energy minimization was performed in two steps; first , to remove the initial unfavorable contacts made by the solvent , and , second , to minimize the entire system as a whole , prior to the molecular dynamics ( MD ) simulations . A stepwise protocol was employed for equilibration , beginning with a simulation under constant volume ( NVT ) conditions for 300 ps switching to constant pressure ( NPT ) conditions at 1 atm for a further 500 ps . All simulations were performed at 300 K . MD simulations were then performed on the prepared systems in explicit solvent for 30 ns with a time step of 2 fs . The co-crystal structure of mature VRC01-eOD with the Man9GlcNAc2 glycan on N276 was used as a control for the MD simulations , which , when compared to the simulated structure , did not reveal significant deviation , hence validating the protocol used . Ten simulations each , for the complexes between the mature VRC01 and the eOD containing a Man9GlcNAc2 or the core-fucosylated biantennary N-glycan at N276 , were initiated and these uncorrelated simulations were used to demonstrate data reproducibility . Further , simulations of the unliganded eOD containing a Man9GlcNAc2 or the core-fucosylated biantennary N-glycan were performed to study the range of conformational sampling of glycan species that could be present at N276 of the antigen and the restrictions that antibody binding imposes upon its conformational space .
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Many HIV vaccine design efforts aim to elicit so-called broadly neutralizing antibodies that bind and neutralize diverse strains and subtypes of the virus . However , these efforts are guided by very unusual antibodies isolated from HIV-infected individuals . These antibodies have rare features that limit their use as direct vaccine templates , because it is unlikely that any vaccine could consistently elicit similar antibodies . We engineered HIV broadly neutralizing antibodies that minimized these rare features and may therefore serve as better leads for HIV vaccine design . Antibodies generally gain affinity for their target epitope by accumulating mutations in a natural process of maturation . Figuring out how to use vaccines to elicit particular kinds of antibodies , with particular kinds of helpful mutations , is a major unsolved challenge for vaccine design . We were able to determine which mutations in our new antibodies are most important and which epitope structures are needed to induce those mutations . This analysis allowed us to deduce a logical strategy , which remains to be tested , for how to guide the maturation of these types of antibodies by vaccination . We propose that this reductionist approach to vaccine design , guided by molecular structure and engineering-oriented to allow for optimization , has promise for designing vaccines against HIV and many other pathogens .
|
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2016
|
Minimally Mutated HIV-1 Broadly Neutralizing Antibodies to Guide Reductionist Vaccine Design
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Bacterial communities are taxonomically highly diverse , yet the mechanisms that maintain this diversity remain poorly understood . We hypothesized that an obligate and mutual exchange of metabolites , as is very common among bacterial cells , could stabilize different genotypes within microbial communities . To test this , we developed a cellular automaton to model interactions among six empirically characterized genotypes that differ in their ability and propensity to produce amino acids . By systematically varying intrinsic ( i . e . benefit-to-cost ratio ) and extrinsic parameters ( i . e . metabolite diffusion level , environmental amino acid availability ) , we show that obligate cross-feeding of essential metabolites is selected for under a broad range of conditions . In spatially structured environments , positive assortment among cross-feeders resulted in the formation of cooperative clusters , which limited exploitation by non-producing auxotrophs , yet allowed them to persist at the clusters’ periphery . Strikingly , cross-feeding helped to maintain genotypic diversity within populations , while amino acid supplementation to the environment decoupled obligate interactions and favored auxotrophic cells that saved amino acid production costs over metabolically autonomous prototrophs . Together , our results suggest that spatially structured environments and limited nutrient availabilities should facilitate the evolution of metabolic interactions , which can help to maintain genotypic diversity within natural microbial populations .
Bacteria are ubiquitous and play a fundamental role in sustaining life , for example by driving global bio-geochemical cycles [1 , 2] . Natural microbial communities are phylogenetically highly diverse assemblages and , in many cases , consist of several thousand interacting species [3] . Recent advances in next generation sequencing demonstrated that even seemingly identical bacterial species from the same microbial community show an enormous variability on the genomic , epigenetic , metabolic , or phosphoproteome levels [4–7] . However , the enormous diversity that is frequently observed within bacterial communities is difficult to reconcile with natural selection , which predicts competition for local resources should reduce genotypic diversity witin bacterial species . Moreover , also when different bacterial species compete for the same resources only those should be able to survive that are best adapted to utilizing these resources ( i . e . competitive exclusion principle ) [8 , 9] . A variety of mechanistic explanations have been proposed to explain the unexpectedly high diversity within microbial communities . For example , the partitioning of resources [10] or their utilization at differential rates [11] can allow different organisms to coexist in the same environment . Alternatively , the competitive monopoly of particularly dominant species can be prevented by disturbance [12] , demographic trade-offs [13] , predation [14] , or non-transitivity of competitive interactions [15] . Ecological niches are not only generated by the abiotic environment , but also by biotic interactions ( e . g . competition and mutualism ) . Moreover , multiple bacterial strains of the same or different species can coexist when they engage in metabolic interactions such as the cross-feeding of metabolic by-products [16 , 17] or the exchange of essential nutrients [18] . In both cases , frequency-dependent selection has been suggested to benefit both partners when rare , thus stabilizing these types of interactions in the long-run [13 , 18] . While the release of metabolic by-products is most likely incidental and not selected for , an active investment into the production of costly metabolites such as co-factors or amino acids to benefit other bacterial cells ( hereafter cooperative cross-feeding ) requires explanations concerning the formation and evolutionary stability of such interactions . In particular , it is not clear how these kinds of interactions can be stable against the invasion of types that reap benefits without contributing to the production of the released metabolite . Despite this seeming paradox , cooperative cross-feeding is very common in the microbial world [19–22] and has been shown to readily evolve under laboratory conditions [23 , 24] . Several plausible explanations could account for the frequent occurrence of cooperative metabolic interactions among microorganisms . First , the preference of microorganisms to exist in spatially-structured biofilm communities could enhance local feedbacks among producing cells and thus increase reciprocity [25–28] . As a consequence , metabolite-producing genotypes may form clusters , which could help to exclude non-producing genotypes from cooperative benefits [29 , 30] . Second , the costs of producing certain metabolites may be off-set by receiving others , for which production costs are saved [31 , 32] . This ‘division-of-labor’ effect could tip the benefit-to-cost ratio in favor of metabolic cross-feeding . Third , the availability of certain metabolites ( e . g . amino acids ) in the environment may fluctuate over time . While metabolite-replete conditions may strongly select for the loss of biosynthetic genes and , therefore , favor an uptake from the environment [33] , subsequent metabolite depletion could promote cross-feeding among newly-evolved auxotrophic genotypes [34] . Until now , it remains unclear how much these factors can—singly or in combination—promote the emergence of cooperative cross-feeding of essential metabolites within genetically diverse bacterial populations . Here we address these issues in a cellular automaton modeling approach called CELL-ABC ( Cellular Automaton of Bacterial Cross-feeding ) to simulate the release of metabolites by bacteria into the surrounding environment as well as their subsequent uptake by other bacterial cells . In this way , the cellular automaton allows us to explicitly analyze spatial effects and emergent population structures . The basis of the simulated bacterial phenotypes is an empirical set of Escherichia coli genotypes that differ in their metabolic abilities [18] . These genotypes include: ( 1 ) prototrophic wild type , ( 2 ) a strain producing increased amounts of two amino acids ( hereafter ‘overproducer’ ) , ( 3 ) two genotypes that essentially require one of two amino acids to grow ( hereafter ‘auxotrophs’ ) , and ( 4 ) two genotypes that are auxotrophic for one amino acid , yet produce and release increased amounts of the respective other amino acid into the cell-external environment ( hereafter’cross-feeders’ ) ( Fig 1 ) . In this work , we employ CELL-ABC to identify the range of parameters under which cooperative cross-feeding of essential metabolites can persist within bacterial populations and to determine the population-level consequences that arise in terms of genotypic composition and spatial interaction structure . To address these issues , we monitored the dynamics of populations , in which the cost-to-benefit ratio of metabolite cross-feeding , the environmental availability of focal metabolites , and the diffusion of the released metabolites were systematically varied . In particular , the following hypotheses were tested:
The fitness of the empirically characterized genotypes was determined in the presence of different amino acid concentrations in the environment ( Fig 1B and 1C ) . While the growth of prototrophic cells ( i . e . wild type and the amino acid overproducer ) was insensitive to varying amino acid concentrations in the environment , the two cross-feeding types and the two auxotrophs each showed a unique growth response that differed significantly from the one of prototrophic types as well as from each other ( ANOVA , P < 0 . 05 , n = 8 , Fig 1B and 1C and S3 Fig ) . This empirically determined growth response of each of the focal genotypes was defined as a benefit-to-cost ratios ( BCRs ) of 1 . To determine how changes in metabolite production costs would affect the stability of amino acid cross-feeding interactions , the BCR of the simulated genotypes was computationally in- or decreased . Increasing the costs of amino acid overproduction over the experimentally determined values ( i . e . BCR < 0 . 8 ) always led to a stable state , in which wild type cells occupied all available grid-cells . For a BCR between 0 . 8 and 1 . 0 , mixed populations of wild type , cross-feeding- , and auxotrophic genotypes coexisted , while further decreasing the costs of amino acid production ( > 1 . 0 ) resulted in a competitive exclusion of prototrophic wild type cells . Finally , when benefits strongly outweighed metabolite production costs ( > 1 . 05 ) , non-cooperating auxotrophs were outcompeted by cross-feeding genotypes ( Fig 2A ) . Characteristic clusters of cross-feeding mutants formed at BCRs ranging between 0 . 8 and 1 . 0 , which were virtually always flanked by a belt of non-cooperating auxotrophs ( Fig 2A ) . With increasing metabolite production costs , the size of these clusters increased and the thickness of the fringing belt of non-cooperating types decreased . Decreasing the costs of metabolite production generally altered the qualitative distribution of cross-feeding interactions within populations: reciprocal cross-feeding was favored over a unilateral exchange of metabolites ( Fig 3A and 3B ) . Taken together , these results demonstrate that the costs of amino acid overproduction significantly impacted both the prevalence of cross-feeding genotypes within populations and their spatial distribution . Nevertheless , both unilateral and bilateral cross-feeding was common under a broad range of parameter conditions . To determine how the degree of spatial structuring affects metabolic interactions within the resident populations , the number of iterated diffusion steps within a given environment was varied . In this way it was possible to manipulate the spatial distribution of the released metabolites . The results of these analyses showed that a reduced diffusion of amino acids facilitated the formation of clusters consisting of both cross-feeding genotypes ( Fig 2A ) . Although auxotrophic genotypes benefited from the public goods that were released from clusters of cross-feeding genotypes , they occurred exclusively at the periphery of these clusters . This striking pattern was most likely caused by a limited diffusion of amino acids outside of these clusters , which led to a spatial exclusion of non-cooperating auxotrophs from these public goods . In contrast , when interactions were less localized due to an increased diffusion of metabolites , the benefit auxotrophic mutants gained increased as indicated by the fact that they increasingly accumulated around cross-feeding clusters ( BCR = 0 . 85 , Mann–Whitney U test: P < 0 . 05 , n = 200 and Fig 2A ) . This characteristic pattern was lost in spatially unstructured environments ( mimicking a perfectly mixed environment ) , in which both auxotrophic- and cross-feeding mutants showed a random spatial distribution ( Fig 2A ) with no sign of direct metabolic cross-feeding ( Fig 3A and 3B ) . Taken together , the degree of spatial structuring and thus the access to essential metabolites significantly shaped the composition and spatial distribution of genotypes within the modeled populations . A low diffusion of public goods resulted in the formation of cross-feeding clusters , which were surrounded by non-cooperating auxotrophs that reaped benefits without reciprocating . To investigate the community-structuring effect of obligate cross-feeding , the requirement for uni- and bilateral cross-feeding was relieved by additionally supplying both essential amino acids to the simulated environments . The added amount of amino acids per grid cell were in the same order of magnitude as the amount of amino acids secreted by overproducing genotypes . Auxotrophic genotypes generally benefited from environmentally available amino acids , as reflected by their increased abundance ( Figs 2 and 3 ) . High amino acid concentrations in the environment readily resulted in a total numerical dominance of these genotypes as expected from the growth performance experiments ( Fig 1 ) . The observation that also the connectivity of unilateral cross-feeding increased significantly when amino acids were environmentally available ( Mantel test: P<0 . 05 , n = 9999 ) corroborated the interpretation that auxotrophic genotypes were nutritionally independent under amino acid replete conditions , which resulted in an increased degree of intermixing between different genotypes . Interestingly , an additional supply of amino acids significantly reduced the abundance of cross-feeding genotypes at low BCRs ( < 1 ) . Moreover , due to the relief from obligate amino acid exchange under these conditions , the spatial distibution of cross-feeding genotypes was altered ( Mantel test: P < 0 . 05 , n = 9999 ) with almost no tendency to form clusters ( Fig 3 ) . In sum , externally providing amino acids to the environment decoupled the obligate interactions and thus eliminated the requirements for reciprocal cross-feeding . As a consequence , auxotrophic genotypes that saved amino acid production costs were generally favored over all other genotypes . Finally , the set of simulations conducted was used to systematically investigate the effect of amino acid cross-feeding on the genotypic diversity within the population under a given set of conditions . Starting each simulation run with six different genotypes , which were present in equal numbers and randomly distributed over the grid , the maximal diversity achievable ( Shannon-Weaver diversity index H ) in the simulated population is 1 . 792 . Investigating the genotypic diversity for scenarios , in which the fitness cost of amino acid overproduction was computationally in- or decreased ( i . e . BCR 0 . 8 − 1 . 1 ) relative to experimentally determined genotypes , revealed a bell-shaped diversity distribution in response to increasing BCRs in low diffusion conditions ( Fig 4A ) . The highest diversity ( here 1 . 31 , which corresponds to 73% of the maximally achievable diversity ) emerged at a BCR of 0 . 85 ( i . e . 15% costs of amino acid overproduction relative to experimentally determined values ) . Strikingly , an external supply of amino acids to the growth environment significantly lowered diversity levels populations achieved within spatially structured environments ( Fig 4A ) , while in unstructured environments amino acid supplementation had the opposite effect , particularly at very low ( i . e . < 0 . 9 BCR values ( Fig 4B ) ) . In the absence of environmentally available amino acids , levels of genotypic diversity showed a strong positive correlation with the prevalence of two-way cross-feeding in the corresponding communities ( Spearman’s rank correlation r = 0 . 79 , n = 14 ) when levels of metabolite diffusion were reduced . In contrast , amino acid supplementation to unstructured environments benefited auxotrophs and—to a lesser extent—also cross-feeding genotypes that otherwise ( in the absence of amino acids ) were largely dominated by monocultures of wild type cells ( BCR < 0 . 85 ) . Altogether , these results revealed strong interactive effects between the degree of environmental structure and an increased availability of the required metabolites in the environment on the genotypic diversity of the focal populations . The simulations were frequently characterized by a non-linear development from the random initial distribution of genotypes to the final steady state . This steady state was qualitatively independent of initial community compositions over a broad range of parameter combinations ( S2 Fig ) . While the abundance of overproducing genotypes always converged immediately to zero , the fraction of the remaining strategies commonly followed a complex pattern ( Fig 5 ) . Surprisingly , the abundance of cross-feeders often initially dropped—even for parameter settings that promoted reciprocal cross-feeding in the long run . Here , prototrophic wild type cells and auxotrophic genotypes underwent a short-term increase in their frequency shortly after the simulation started . High abundances of auxotrophic genotypes reduced the overall concentration of amino acids and thus diminished the frequency of cross-feeding genotypes providing the public good . This feedback mechanism damped the increase in the frequency of auxotrophic genotypes . However , random co-localization of complementary cross-feeders in spatially structured environments ( i . e . low metabolite diffusion ) resulted in fitness values that exceeded wild type levels and rapidly developed into fast-growing clusters of cross-feeders . Their spreading across the grid was often flanked by non-producing and hitch-hiking auxotrophic genotypes . Simultaneously , the fraction of grid cells occupied by wild type declined and usually strategies flew into an oscillating steady state with fluctuating , yet stable patterns ( Fig 5 ) . When additional amino acids were available , wild type and auxotrophic mutants were the most dominant genotypes . Their frequencies showed a damped oscillating pattern ( S5 Fig ) . Under these conditions , cross-feeders generally occurred at very low frequencies , except for BCR > 1 . Taken together , cross-feeding interactions drove the dynamic turnover of strategies within metabolically diverse population and promoted spatio-temporal oscillations of genotype frequencies .
Obligate cross-feeding of essential metabolites is very common in the microbial world [19 , 21] . The conditions that favor such synergistic interactions and the consequences that result for the structure and composition of the resident microbial community , however , remain poorly understood . Here we address these issues by identifying the range of conditions that maintain metabolic cross-feeding and , thus , genotypic diversity within bacterial populations . Using genetically engineered loss-of-function mutants as empirical basis , we explore how changes of intrinsic ( i . e . benefit-to-cost-ratio of metabolic cross-feeding ) and extrinsic factors ( i . e . environmental amino acids availability , diffusion rate ) affect the ecological dynamics within genotypically diverse populations ( i . e . six genotypes ) . Our study revealed that unilateral and bilateral cross-feeding of essential metabolites that are based on the release of these metabolites into the cell-external environment is stably maintained over a broad range of conditions including increased costs of metabolite production and increased diffusion rates . Only when the costs of metabolite production exceeded a certain threshold ( i . e . > 20% relative to the experimentally determined values ) or environments were perfectly mixed , prototrophic genotypes outcompete all other types present . An environmental availability of amino acids selected for auxotrophic- and against cross-feeding genotypes . Obligate metabolic cross-feeding helped to maintain genotypic diversity in spatially structured environments , while nutrient supplementation to the environment counteracted this effect . Our analysis of environments that did not contain the limiting resource ( i . e . amino acids ) identified two conditions under which obligate metabolic cross-feeding maintained genotypic diversity within a bacterial population: First , a high degree of spatial structuring , and second , low production costs of the traded metabolites ( Fig 4 ) . These predictions are corroborated by empirical data . For example , Salmonella enterica rapidly evolved increased amino acid production rates to support the growth of auxotrophic E . coli cells , which in turn produced metabolic waste products Salmonella needed to grow [23] . Also in this case , spatial structure was essential for the costly amino acid overproduction mutation to increase in frequency once it had evolved . In contrast , unilateral cross-feeding , in which a receiving genotype is an adaptive mutant that consumes metabolic by-products released by the ancestral donor , does not require spatial structure to allow for coexistence between both partners . A well-documented example of such a cross-feeding polymorphism that emerged and was maintained even in a shaken , liquid environment is the case of acetate-cross-feeders that evolved from glucose-utilizing Escherichia coli cells [16 , 35] . Since this interaction is likely non-obligatory and does not incur a fitness cost to the producing cell , its maintenance in spatially unstructured environments is also predicted by our model ( Fig 2A ) . However , what is the ecological mechanism that favored consortia of cross-feeding genotypes in amino acid-deficient , structured environments ? Under these conditions , groups of cross-feeding cells that coincidentally co-localized formed cell clusters that enjoyed the benefits of cooperative cross-feeding , which more than compensated for the costs of metabolite overproduction . In the long-run , these cooperative clusters could persist despite the presence of non-producing genotypes , most likely because cross-feeders within these clusters enjoyed the benefits of a cooperative metabolite exchange , which were less available to non-cooperating auxotrophs outside these clusters [36] . These conditions resemble the situation experienced by cells growing in a biofilm , in which principles of spatial self-organization facilitate positive assortment among cross-feeding genotypes [37 , 38] . Indeed , both theoretical [39 , 40] and experimental studies [30 , 41] have previously identified spatial structure as a factor favoring the evolution of cooperative interactions . Oliveira and coworkers [42] , however , concluded based on theoretical grounds that problems to find the right complementary genotype in spatially structured environments can also inhibit the evolution of metabolic cross-feeding interactions between genotypes . In contrast to these predictions , our results with six bacterial genotypes that were parametrized using empirical data show that low levels of metabolite diffusion can in fact promote cooperation between complementary cross-feeding genotypes . Experiments using different E . coli mutants to test these predictions are currently being performed and will be presented elsewhere . Simulations with benefit-to-cost ratios between 0 . 8 and 1 . 0 ( i . e . up to 20% costs to the experimentally determined values ) and a low degree of metabolite diffusion revealed specific temporal dynamics . These were characterized by a characteristic alternation of abundances , especially of wild type- , auxotrophic- , and cross-feeding genotypes . First , an increase in the frequency of auxotrophic- and a decline of cross-feeding genotypes was observed to a point , at which the community was not able to sustain more non-cooperating auxotrophic mutants and almost collapsed . Prototrophic wild type genotypes benefited from this situation and thus increased in frequency . This was accompanied by a dramatic decline of genotypic richness in the community and a harmonization of local genotype assemblages . At this point , coincidentally co-localized cross-feeders formed founder populations that subsequently re-populated the grid . Expanding cross-feeding clusters were virtually always flanked by a belt of auxotrophic genotypes . Patches in which auxotrophs persist may thus function as a genetic reservoir , from which cooperative cross-feeding can arise by mutation and spread throughout the population when environmental conditions change . The local turnover of wild type cells , cross-feeding clusters , and auxotrophic mutants in spatially structured environments combined with the observation that global genotype abundances remained relatively stable , is strikingly reminiscent of a spatial zero-sum game ( e . g . the ‘rock-scissor-paper game’ ) . Biological examples include non-transitive competitive networks as displayed by bacteriocin- producing , -resistant , and -sensitive E . coli cells ( see [43] for a review and [44] for a theoretical study ) or the reproductive strategies of small lizards ( Uta stansburiana ) that are associated with color polymorphisms [45] . Our results reveal that environments , in which the essentially required metabolites were not limiting , strongly selected for auxotrophic genotypes ( Fig 2 ) . This pattern was independent of the production costs and the diffusion rate of the focal metabolite . This finding is in line with theoretical work showing that cooperation is favored under resource limited conditions [46] and experimental studies demonstrating that auxotrophic mutants of different bacterial species ( i . e . E . coli , Acinetobacter baylyi , and Bacillus subtilis ) that lack the ability to biosynthesize a certain metabolite gain a selective advantage in environments that contain the corresponding metabolite in sufficient amounts [33 , 47] . Also cross-feeding genotypes benefited from increased metabolite availabilities in the environment—albeit this advantage only manifested at higher benefit-to-cost ratios ( Fig 3 ) . This was likely due to the fact that even though cross-feeders saved the costs to produce one amino acid , they were still burdened with the investment to produce increased amounts of other amino acids . Only when these production cost were very low , cross-feeders increasingly benefited from environmentally supplemented amino acids as well as the metabolite released by the corresponding other cross-feeder . Interestingly , our results demonstrate that obligate cross-feeding of essential metabolites can stabilize genotypic richness in microbial communities even above the limits that are predicted by the competitive exclusion principle [8 , 9] . According to this theory , the number of different species that can coexist is limited by the number of resources that are available in the same environment . In the case analyzed in this study , all genotypes utilize the same carbon source , yet some of them provide new resources that are essentially required by others to grow . Thus , when amino acids are lacking in the environment , both overproducers and cross-feeders construct the niche that allows other community members ( i . e . auxotrophs and cross-feeders ) to grow [48 , 49] . Conversely , externally providing the required metabolites to genotypically diverse communities uncoupled the obligate metabolic interactions and significantly reduced the genotypic diversity in spatially structured environments . This effect is analogous to the so-called ‘paradox of enrichment’ [50]: supplementation of limiting nutrients to an ecosystem does not relax competitive interactions , but intensifies them , by favoring the most competitive species . Originally proposed for interactions between two trophic levels ( i . e . predator-prey interactions ) , nutrient addition has also been shown to destabilize steady states of competitive ecosystems [50] . Thus , our study extends this list by obligate metabolic cross-feeding interactions that are ecologically uncoupled by an environmental nutrient availability . As a consequence , more competitive genotypes will take over , which ultimately leads to a loss of genotypic diversity in the population . Strikingly , experimental nutrient supplementation to soil also resulted in a significantly reduced bacterial diversity [51] . However , future work is necessary to determine whether and to which extend this result was due to the uncoupling of obligate cross-feeding interactions . A main conclusion that follows from the results of our study is that spatially structured environments that show fluctuating nutrient availabilities should select for a loss of biosynthetic genes when the corresponding metabolites are sufficiently available in the environment , yet favor cooperative cross-feeding when metabolite levels drop below a certain level . Indeed , bacteria usually exist in highly structured environments [52] , in which they experience frequent changes in the availability of ( essential ) nutrients [53 , 54] and both uni- and bilateral cross-feeding is common in these bacterial communities [19–22] . Moreover , less than 1% of all bacterial species known are amenable to laboratory cultivation in monoculture [55 , 56] , yet this fraction can be increased by growing seemingly unculturable bacteria in the presence of other community members [57] . These findings suggest that obligate cross-feeding of essential metabolites could explain the frequently observed difficulties to cultivate natural bacteria isolates under laboratory conditions . The fact that simply the deletion of three different metabolic genes was sufficient to generate the complex patterns of metabolic interdependencies [18] analyzed in this work suggests gene loss is a powerful source of synergistic ecological interactions . Once established , obligate metabolic interactions may intensify in a ‘black-queen’-type race [58] , in which locally interacting partners loose additional metabolic functions that are compensated by other community members . Over time , this process should lead to increasingly intertwined metabolic interactions within microbial communities , whose dynamics will most likely be also determined by the key parameters identified in this study: i ) degree of spatial structuring , ii ) benefit-to-cost ratio , and iii ) environmental availability of exchanged nutrients . Given the enormous fitness advantages that result from the different metabolic interactions a question arises: What maintains prototrophic genotypes in the long-run ? By losing the ability to produce certain metabolites , auxotrophic genotypes as well as the type of cross-feeders analyzed here and in [18] trade their metabolic autonomy against an immediate fitness advantage . As a consequence , the reproduction of these types becomes contingent on an environmental supply of the required nutrient , reflecting the dilemma of specialization versus flexibility . Assuming the environmental conditions to which bacterial metapopulations are exposed change frequently , prototrophic bacteria should be globally maintained , because some local patches feature conditions under which they are selectively favored . In this case , prototrophic genotypes would serve as generalist dispersal unit that can found new populations , in which newly-emerged adaptive loss of function mutants can thrive . This scenario is consistent with prototrophic bacterial pathogens such as Pseudomonas fluorescens that opportunistically infect the lung of cystic fibrosis patients and—due to increased metabolite concentrations in the sputum—rapidly evolve amino acid auxotrophies [59 , 60] . Our results indicate that obligate metabolic interactions represent a strong ecological force to stabilize a range of different genotypes , which can help to maintain genotypic diversity within microbial populations and communities . Especially spatial structure with limited metabolite diffusion favored cooperative cross-feeding via local feedbacks that excluded less efficient cooperators or , non-cooperating auxotrophic genotypes . Our model predicts that biofilms ( i . e . highly structured environments with very limited metabolite diffusion ) and environments that frequently fluctuate in their nutrient availability should generally select for cooperative cross-feeding . Taken together , by implementing biologically realistic parameter values , our model suggests that mutualistic cross-feeding interactions between different genotypes should readily evolve in microbial communities .
|
Natural bacterial communities are usually very species-rich and bacterial cells within these communities often exchange metabolites with each other . Whether and to which extent obligate metabolic interactions can contribute to maintaining the observed bacterial diversity , however , is not known . In this study , we address this question computationally , by simulating populations of six different bacterial strains that differ in their requirement to obtain amino acids from the environment as well as their propensity to release other amino acids . By systematically varying key variables such as the cost of metabolite production , the speed with which metabolites diffuse in the environment , as well as the amino acid availability in the environment , we show that a cooperative exchange of essential amino acids is evolutionary stable over a broad range of biologically realistic conditions . In particular spatially structured environments , such as bacterial biofilms , and moderate costs of metabolite production favored metabolic interactions . Finally , our work identifies obligate metabolic interactions as a powerful ecological mechanism to maintain different bacterial genotypes with microbial communities .
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2016
|
Pervasive Selection for Cooperative Cross-Feeding in Bacterial Communities
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Dengue is endemic in more than 100 countries , mainly in tropical and subtropical regions , and the incidence has increased 30-fold in the past 50 years . The situation of dengue in China has become more and more severe , with an unprecedented dengue outbreak hitting south China in 2014 . Building a dengue early warning system is therefore urgent and necessary for timely and effective response . In the study we developed a time series Poisson multivariate regression model using imported dengue cases , local minimum temperature and accumulative precipitation to predict the dengue occurrence in four districts of Guangzhou , China . The time series data were decomposed into seasonal , trend and remainder components using a seasonal-trend decomposition procedure based on loess ( STL ) . The time lag of climatic factors included in the model was chosen based on Spearman correlation analysis . Autocorrelation , seasonality and long-term trend were controlled in the model . A best model was selected and validated using Generalized Cross Validation ( GCV ) score and residual test . The data from March 2006 to December 2012 were used to develop the model while the data from January 2013 to September 2014 were employed to validate the model . Time series Poisson model showed that imported cases in the previous month , minimum temperature in the previous month and accumulative precipitation with three month lags could project the dengue outbreaks occurred in 2013 and 2014 after controlling the autocorrelation , seasonality and long-term trend . Together with the sole transmission vector Aedes albopictus , imported cases , monthly minimum temperature and monthly accumulative precipitation may be used to develop a low-cost effective early warning system .
Dengue is an arthropod-borne disease caused by dengue virus ( DENV 1–4 ) belonging to the Flaviviridae family , with the transmission vectors being Aedes aegypti and Aedes albopictus [1] . Dengue is endemic in more than 100 countries worldwide , mainly in tropical and subtropical regions [2] . Recent global estimates indicate that 390 million people have dengue virus infections with 96 million cases annually [3] . Its incidence has increased 30-fold in the past 50 years [4] . Because of unprecedented population growth , globalisation with increased population movement , uncontrolled urbanisation , climate change , breakdown in public health infrastructure and vector control programs , dengue is the most prevalent and rapidly spreading mosquito-borne viral disease affecting human beings [1] . WHO has defined a global strategy for dengue prevention and control , aimed to reduce mortality and morbidity from dengue at least 50% and 25% by 2020 respectively ( using 2010 as the baseline ) [4] . Evidence-based decisions are essential to prevent and control dengue transmission . A dengue early warning system will be helpful to provide evidence for decision-makers . Human movement has been identified as one of key factors in determining the transmission dynamics of dengue disease [5] . Movements into high-risk areas lead to individual infection , and also contribute to local transmission when infected individuals return to their homes where local transmission vectors establish . Madeira , Portugal reported the first major outbreak of dengue in 2012 , which was probably caused by the virus imported from Venezuela [6] . Yunnan Province of China , bordering Cambodia , Thailand and Vietnam reported the first dengue outbreak in 2013 [7] and in the same year the first dengue outbreak occurred in Henan Province located in the central China [8] . Because of population movement and establishment of Aedes albopictus , local dengue transmission occurred in France twice in 2010 and 2013 , respectively [9 , 10] . Many researches have studied the association between climatic factors and dengue incidence . Among the climatic factors , temperature and precipitation contributed the most in statistical models [11] . Temperature and precipitation can influence dengue transmission via their impact on the vector population , directly and indirectly [12] . Temperature can impact vector population development and reproductive rates [13] . It is also critical to vector capacity: increased temperature decreases the extrinsic incubation period ( EIP ) , the time taken for mosquitoes from imbibing an infectious blood meal to becoming infectious [14] . It may also affect human behaviour [12] . Precipitation can provide breeding sites and stimulate egg hatching , which leads to an increase in the number of mosquitoes [15] . Based on the relationship between these climatic factors and dengue occurrence , temperature and precipitation were often used to predict or project dengue transmission [16 , 17] . Since the first dengue outbreak occurred in 1978 , dengue has been detected in China for nearly 40 years . Local dengue transmission has been identified in Guangdong , Guangxi , Hainan , Yunnan , Fujian , Zhejiang , and Henan Provinces [8 , 18] . Two consecutive large outbreaks occurred in Southern China in 2013 and 2014 , of which Guangdong Province has had an unprecedented dengue outbreak including 21 , 511 notifiable cases and six fatalities ( up to September 2014 , the cases from China Notifiable Reporting System ) in 2014 . Guangdong Province is located in South-eastern China , and has a subtropical monsoonal climate . The population exchange between Guangdong Province and Southeast Asia is very frequent [19] . Several dengue outbreak occurrences in Guangdong Province were caused by imported cases from Southeast Asia [19 , 20 , 21] . Several studies have been conducted to identify the relationship between climatic factors and dengue transmission in Guangdong , yet no real predicting model has been developed [22 , 23 , 24] . Given there is no medication which could effectively treat dengue patients [25] and no multivalent dengue vaccines available , preventative measures are crucial in the disease control . An early warning system , based on existing variables , is the backbone of prevention of local cases and possible outbreaks occurring . In this study , we use imported cases and climatic factors to build a low-cost early warning system , capable of predicting dengue outbreak to enhance decision-making capacity .
Ethical approval for this project was obtained from the Chinese Center for Disease Control and Prevention Ethical Review Committee ( No . 201214 ) and patient data used in the study were de-identified . Guangzhou city is the capital of Guangdong Province , with the highest population density in southern China . Guangzhou is the centre for transportation , industry , finance and trade in southern China and has a large demographic exchange in business , tourism and labour service within Southeast Asia , Africa and the Indian subcontinent . Guangzhou city consists of 12 districts/counties . Given most dengue cases located in Baiyun district , Yuexiu district , Liwan district and Haizhu district , accounted for 74 . 4% of all cases reported in the 12 districts , we chose the four districts as our study areas , with an area of 979 . 09 km2 and population of 5 . 81 million in 2013 ( Fig 1 ) . Records of dengue cases between 2006 and 2014 were obtained from the China Notifiable Disease Surveillance System . All dengue cases were diagnosed according to the China National Diagnostic Criteria for dengue ( WS216-2008 ) [26] . Information of dengue cases included age , gender , occupation , date of onset , whether the diagnosis was clinical or confirmed by laboratory test , local case or not . The criteria of imported or local cases used in [12] was cited . Monthly weather data between March 2006 and September 2014 were obtained from the China Meteorological Data Sharing Service System ( http://cdc . nmic . cn/home . do ) , including monthly minimum temperature , monthly accumulative precipitation . There are two meteorological stations in Guangzhou city ( Fig 1 ) , and the climate dataset used was monitored by meteorological station A which is able to represent the weather situation in the study areas . The population data over the study period for every district were retrieved from the Guangdong Statistical Yearbook .
China Notifiable Disease Surveillance System was notified of 15 , 221 cases , including 15 , 118 local cases and 103 imported cases between March 2006 and September 2014 in the study areas , with the accumulative local dengue incidence 259 per 100 , 000 . Three large outbreaks occurred in 2006 , 2013 and 2014 , with the local dengue incidence 9 . 94 , 18 . 00 , and 203 . 82 per 100 , 000 respectively . The incidence in 2014 was 3 . 7 fold than the accumulative incidence from 2006 to 2013 . Local dengue occurrence had a seasonal pattern and the epidemic months were from August to November . The decomposition result showed that dengue incidence had an increased trend , especially from 2009 to 2014 . Cases imported to Guangzhou also had a seasonal pattern with June , August and October having more imported cases . The result also showed that the number of imported cases had an increased trend pattern . Accumulative precipitation and minimum temperature had seasonal distribution , which were prone to have more precipitation and higher temperature in April-September and May-October , respectively . The accumulative precipitation had an increased trend after 2011 , but the minimum temperature had a decreased trend ( Fig 2 ) ( S2 Table ) . The climatic factors finally included in the model were minimum temperature in the previous month and accumulative precipitation with three month lags ( S3 Table ) ( S4 Table ) . The time-series Poisson model showed that dengue incidence was positively associated with local dengue incidence in the previous month , imported cases in the previous month , minimum temperature in the previous month , positively associated with accumulative precipitation with three month lags . While the estimated effect of minimum temperature had a linear relationship with the dengue occurrence , the estimated effect of accumulative precipitation was non-linear , more precipitation with three month lags associated with more possibility of dengue occurrence . The estimated effect of imported cases in the previous month was also non-linear for dengue occurrence , the effect of imported cases in number 3 and 4 was larger than imported cases in number 1 and 2 ( Fig 3 ) . The R2 of our model was 0 . 98 , with deviance explained 95 . 4% . The fitted result shown in Fig 4 exhibited a good fit of the model . The residual test by autocorrelation function ( ACF ) and partial autocorrelation function ( PACF ) showed residuals were not correlated ( S1 Fig ) . The forecast result showed that the optimal model could predict the large dengue outbreaks which occurred in 2013 and 2014 ( Fig 5 ) .
This study showed that imported cases , minimum temperature and accumulative precipitation could be used to build a low-cost effective dengue early warning model in Guangzhou . Based on these predictors , we may be able to predict large dengue outbreaks one month ahead in Guangzhou and other regions with similar climatic and demographic characteristics , after controlling the autocorrelation , seasonality and long-term trend . Several studies have been conducted to develop dengue early warning system based on weather factors [16 , 31 , 32 , 33] , but these studies were mainly conducted in endemic regions and the transmission vector was Ae . aegypti . There are two major characteristics of dengue in China: 1 ) dengue is an imported disease [34]; and 2 ) the main transmission vector is Ae . albopictus ( the sole transmission vector in Guangzhou ) . Many travellers to Guangzhou come from Southeast Asia including Indonesia , Philippines , Malaysia , Thailand , and Vietnam . Southeast Asia is an epicentre of dengue and our previous study showed the imported cases in Guangzhou were mainly from Southeast Asia [12] . Furthermore , there is an argument that dengue originated from Africa [35 , 36] , and evidence shows that dengue outbreaks are increasing in size and frequency in Africa [4] . The number of Africans travelling to Guangzhou has been significantly increasing in recent years , which may increase the risk of dengue virus imported to Guangzhou . In fact , a report suggested that the dengue outbreak occurred in Guangzhou was caused by an imported case from Tanzania in 2010 [37] . The imported cases in our study had an increased trend corresponding to dengue occurrence . A study conducted in Taiwan , China demonstrated that imported cases served as initial facilitators for possible dengue transmission and the effect of imported cases could last 14 weeks [38] . The population density increased linearly reaching 6425 . 4/km2 in our study area in 2013 . Densely populated conditions provide more susceptible population and suitable Aedes mosquito larval habitats [39] , which makes the imported virus dispersed more possible . Endemicity has not been established in some areas for climates that may not support year-round viral transmission . Therefore , local climate also plays a crucial role in dengue transmission besides imported cases in China . Ae . albopictus is considered to be one of the world’s fastest spreading invasive animal species and has colonized every continent except Antarctica [40] , of which temperature plays a crucial role in the population establishment . Temperature also plays an important role in dengue transmission mediated by Ae . albopictus . Dengue transmission is only achieved when the longevity of the Ae . albopictus exceeds the EIP . The EIP decreased when temperature increased from 18°C to 31°C , and dengue virus might not be transmitted by Ae . albopictus at temperatures below 18°C [41] . Furthermore , temperature can also influence the mosquito dynamics by determining their first gonotrophic cycle ( FGC ) , the time between taking a blood meal and first oviposition . Study showed that the length of FGC decreased non-linearly when temperature increased [42] . A greater of proportion of mosquitoes survive the EIP and FGC , thus they are more likely to deliver virus or oviposit a greater number of eggs . Temperature not only impacts the FGC of Ae . albopictus , but also influences the immature development . Ae . albopictus developed more quickly at higher temperature within the range of 20–30°C [13 , 43] . Our results showed that the effects of temperature linearly increased when temperature increased . The decomposition result of minimum temperature showed that the minimum temperature had a decreased trend over the study period , but the minimum temperature was above 18°C from March to October , which fulfilled the possibility of dengue transmission . Ae . albopictus can breed in both domestic and peri-domestic containers . The Ae . albopictus breeding sites in Guangzhou included flower plot trays , bamboo tubes , metal containers , terrariums , stone holes , ceramic vessels , plastic containers , gutters , used tyre dumps , surface accumulated water , and disposable containers [44] . The residents living in the study areas are familiar with raising flowers named evergreen and lucky bamboo cultured with pure water , and they are reluctant to refresh the water for fear of suppressing flower growth . In addition , many residents in these areas enjoy decorating roofs with hanging gardens directly exposed to the outside . The hanging gardens , flowers indoors and garden breeding sites , create the characteristics of spatial distribution of breeding sites . Heavy rain can flushes away the egg , larvae and pupae of Aedes mosquitoes in the short term , but rainfall can create huge breeding habitats for mosquito in the long run . Therefore , it is reasonable that more precipitation with three month lags had increased the effect of dengue transmission in current month . A study conducted in Taiwan , China showed that extreme precipitation influenced the dengue occurrence with 70 day lagged effects [45] . Real estate developments and urbanisation increased over these years in Guangzhou , and construction sites created ideal conditions for mosquito breeding . It is reported that dengue outbreaks occasionally occurred at the construction sites in the study areas . In recent years , dengue became more and more serious in Guangzhou , China and the record of dengue cases in 2014 is unprecedented in nearly 40 years . China has had to face the unprecedented challenges for dengue control and prevention , both currently and into the future . Given there is no effective medication and vaccination , mosquito control is still the only effective way to prevent and control dengue occurrence and outbreak . Although some novel interventions , for example , wolbachia [46 , 47] and genetic modification [48] have made rapid progress in the control of Ae . aegypti , no achievement has been made in Ae . albopictus . Therefore , routine interventions on mosquito control , for example breeding sites eradication and eliminating adult mosquito are still the main approaches being used . At population level , it is very important to establish an effective platform to get different stakeholders working together for the disease control and prevention , including government organisations , CDCs and local communities . To establish a dengue early warning system will be an important step in this regard , as it will play a crucial role in dengue control . A further step , we will develop a user-friendly platform integrating data including dengue cases from China Notifiable Disease Surveillance System , meteorological data from China Meteorological Data Sharing Service System and analysis model . The platform will be configured in Guangzhou CDC and automatically predict the dengue cases occurrences in an upcoming month . The predicted outbreak message will be sent to district CDCs and public health decision-makers for further response . The district CDCs will validate the predicted outbreak and intensify the entomological surveillance . A proposal will then be submitted to local government departments such as Health , Community Service , Emergency management , to advocate and mobilise the community promptly to eradicate mosquito breeding sites and eliminate adult mosquito . The designated organisations will be responsible for public places to manage mosquito density . The platform will be piloted for one or two years . Based on the sensitivity and specification of outbreak predicting , the parameters will be revised and then put into practice on a large scale .
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Dengue has emerged as the most important mosquito-borne viral disease globally . With increasing global trade and population movement , the disease is transferred to regions which were previously dengue free . When dengue vector exists and weather factors are suitable , there is the possibility for dengue transmission and even outbreaks happening . Dengue is still believed to be a non-endemic disease in China , with imported cases playing a vital role in local dengue transmission . The situation of dengue is becoming more and more severe with two successive large outbreaks hitting southern China in 2013 and 2014 , and the dengue outbreak in 2014 was unprecedented . In this study , we aim to develop a dengue forecasting model that would provide an early warning of dengue outbreak to allow local health authorities and communities to implement timely effective control measures . Our model showed that imported cases in the previous month , monthly minimum temperature in the previous month and monthly accumulative precipitation with three month lags could predict dengue outbreak ahead by one month . We concluded that these variables could be used to develop an early dengue warning model to provide evidence-based decisions for disease control and prevention and including the utilization of limited resources .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
Predicting Unprecedented Dengue Outbreak Using Imported Cases and Climatic Factors in Guangzhou, 2014
|
The essential and distinct functions of Protein Phosphatase type 1 ( PP1 ) catalytic subunit in eukaryotes are exclusively achieved through its interaction with a myriad of regulatory partners . In this work , we report the molecular and functional characterization of Gametocyte EXported Protein 15 ( GEXP15 ) , a Plasmodium specific protein , as a regulator of PP1 . In vitro interaction studies demonstrated that GEXP15 physically interacts with PP1 through the RVxF binding motif in P . berghei . Functional assays showed that GEXP15 was able to increase PP1 activity and the mutation of the RVxF motif completely abolished this regulation . Immunoprecipitation assays of tagged GEXP15 or PP1 in P . berghei followed by immunoblot or mass spectrometry analyses confirmed their interaction and showed that they are present both in schizont and gametocyte stages in shared protein complexes involved in the spliceosome and proteasome pathways and known to play essential role in parasite development . Phenotypic analysis of viable GEXP15 deficient P . berghei blood parasites showed that they were unable to develop lethal infection in BALB/c mice or to establish experimental cerebral malaria in C57BL/6 mice . Further , although deficient parasites produced gametocytes they did not produce any oocysts/sporozoites indicating a high fitness cost in the mosquito . Global proteomic and phosphoproteomic analyses of GEXP15 deficient schizonts revealed a profound defect with a significant decrease in the abundance and an impact on phosphorylation status of proteins involved in regulation of gene expression or invasion . Moreover , depletion of GEXP15 seemed to impact mainly the abundance of some specific proteins of female gametocytes . Our study provides the first insight into the contribution of a PP1 regulator to Plasmodium virulence and suggests that GEXP15 affects both the asexual and sexual life cycle .
Convergent findings from several studies indicate that protein dephosphorylation by phosphatases governs key fundamental processes in the biology of eukaryotic cells including Plasmodium falciparum [1] . Among these phosphatases , the Protein Phosphatase type 1 catalytic subunit ( PP1c ) seems to play a pivotal role in the development and growth of Plasmodium blood stage parasites [2 , 3] . In addition , it has been reported in eukaryotes that several conserved PP1c interacting proteins ( PIPs ) endowed with phosphatase regulatory functions are as essential as PP1c itself [4–7] . In mammalian cells , hundreds of PIPs have been identified and classified as regulators and substrates , capable of targeting PP1c to particular cellular organelles [8 , 9] . The combination of PP1c with an extensive range of PIPs contributes to the constitution of specific PP1 network , playing an effective role as a hub in diverse cellular functions . Our earlier studies on P . falciparum revealed the expression of four conserved putative regulators ( PfLRR1 , Pf Inhibitor 2 , Pf Inhibitor 3 and Pfeif2β ) which have been extensively explored to define their functions [10–15] . In this context , biochemical and structure-activity relationship studies demonstrated that these regulators bind to recombinant PfPP1 and three of them regulate its activity in vitro . Several binding sites have also been defined by structure-interaction studies using mutated recombinant proteins and derived peptides , showing the involvement of LRR/LRR cap motifs for PfLRR1 and the consensus RVxF motif for PfI2 , PfI3 and Pfeif2β . In addition , knock-out approaches suggested their essentiality in the life cycle of blood stage parasites . Finally , these interactions seem to be indispensable since disrupting the interaction between PP1c and PfI2 , PfI3 or PfLRR1 by the use of interfering peptides that inhibit complex formation led to parasite growth inhibition in vitro [12–14] . This proof of concept offers a robust basis to consider PP1c interactions as valuable therapeutic targets . Based on the above data and on the atypical life cycle of Plasmodium with ~60% of unknown genes in its genome [16] , including specific proteins submitted to reversible phosphorylation , our working hypothesis was that Plasmodium must express specific partners , regulators and/or transporters which direct PP1 activity . In order to identify PfPP1 interactors , extensive screens for PfPP1 binding proteins were carried out , using the yeast two-hybrid ( Y2H ) system combined with direct interactions studies using recombinant proteins [17] . A total of 31 proteins in the correct translational reading frame with the Gal4 activating domain were identified . Upon close inspection of the amino acid sequences of binding regions of these proteins , six clones were identified exhibiting a potential RVxF binding motif with a more restrictive and specific consensus sequence of PP1 interactors [17 , 18] . Indeed , we have used the PfPP1 interactome to reevaluate the features of flanking residues of the RVxF motif . We observed enrichment for basic amino acids ( R and K ) at the N-terminal side of this binding motif . We prioritized candidate genes that were Plasmodium-specific with a robust interaction with PfPP1 . One of these genes , formerly described as P . falciparum Gametocyte EXported Protein 15 ( PfGEXP15 ) ( PF3D7_1031600 ) , was repeatedly detectable under stringent conditions of binding to PfPP1 throughout the Y2H screens . In addition , the presence of a potential restrictive binding motif was identified in the interacting region of PfGEXP15 [17] . PfGEXP15 has been classified in the GEXP cluster , grouping different proteins predicted to be exported and detected only in the proteome of early gametocytes or being overexpressed at this stage [19] . However , interestingly , PfGEXP15 was also detected in the proteomes of asexual stages and sporozoites suggesting its involvement at different steps of the parasite life cycle [20] . In this work , we confirm that GEXP15 interacts with PP1 and showed its capacity to regulate the dephosphorylation activity of PP1 via a major contribution of RVxF binding motif in P . berghei . Interatomic analysis revealed that the GEXP15-PP1 are part of two protein complexes involved in mRNA splicing and proteasome pathways , known to play key roles in parasite development . Further , for the first time , we demonstrate that the complete disruption of GEXP15 generates attenuated parasites both for asexual and sexual growth in mice and mosquitoes respectively , suggesting specific and essential functions . Finally , we provide evidence that proteome and phosphoproteome of deficient schizont and gametocyte parasite stages are impacted at different levels arguing for an involvement of GEXP15 in these processes .
In order to extend and to further characterize the GEXP15 that we previously reported as a partner of PP1 in P . falciparum [17] , its ortholog in P . berghei ( PBANKA_0515400 ) was investigated . The predicted PbGEXP15 protein ( 656 aa ) shares an overall identity of 41% with PfGEXP15 and both contain two putative consensus RVxF binding motifs to PP1 ( S1 Fig ) . The construct of PbGEXP15 4–590 , spanning almost the full-length sequence was tested in the Y2H system in which PfPP1c was used as bait as it exhibits 99% identity with PbPP1 . We observed that only the diploids expressing PbGEXP15 and PfPP1c were able to grow on selective and stringent media indicating their ability to specifically interact with each other ( S2A Fig ) . Control constructs ( empty vector , vector expressing unrelated gene ) did not show any growth . To better define the interacting regions , constructs with PbGEXP15 4–178 containing the first RVxF binding motif to PP1 or PbGEXP15 446–596 comprising the second one were used . PbGEXP15 4–178 revealed the same specific interaction with PfPP1c , confirming the data described above ( S2B Fig ) . In the case of PbGEXP15 446–596 with the second RVxF motif no yeast growth was observed , suggesting that it is a random sequence and a non-canonical binding site ( S2B Fig ) . To validate the involvement of the first RVxF binding motif present in PbGEXP15 , site directed mutagenesis was carried out to obtain V34A and F36A ( PbGEXP15 4–178 KKKKKAQA ) . Interaction with PfPP1c was not observed with this mutant , confirming that the native sequence represents a genuine RVxF binding motif ( S2B Fig ) . The main contribution of this RVxF motif was reinforced by the lack of growth on high stringency selection in the presence of PfPP1c mutated at its docking site by replacing F255 and F256 by two alanine residues ( S2C Fig ) [18 , 21–23] . To further support the PbGEXP15-PP1 interaction , GST-PfPP1c pull-down experiments with wild-type and mutated His-PbGEXP15 recombinant proteins were carried out . Western blot analyses showed that PbGEXP15 4–590 ( Fig 1A ) , and PbGEXP15 4–178 ( Fig 1B ) bound to GST-PfPP1c but not to GST alone , while the mutated PbGEXP15 4–178 KKKKKAQA revealed no binding to GST-PfPP1c ( Fig 1C ) . In addition , the interaction of PbGEXP15 4–178 with PfPP1c was tested under stringent conditions ( 500 mM NaCl ) and remained detectable . These data showed that GEXP15 physically and strongly binds to PP1c via the RVxF motif . Based on the ability of recombinant GEXP15 to interact directly with PP1c , its effect on the phosphatase activity was assessed . As depicted in Fig 1D and 1E , using a quantity of PfPP1c generating a linear release of phosphate from pNPP substrate , the addition of either PbGEXP15 4–590 or a shorter PbGEXP15 4–178 protein strongly increased the dephosphorylation activity of PfPP1c in a concentration-dependent manner . A two-fold increase was observed at 100 pmol/well with both versions of PbGEXP15 proteins , suggesting that the main activating region of PfPP1c is carried by the N-terminal moiety of GEXP15 . The use of the PbGEXP15 4–178 KKKKKAQA mutant abolished the regulatory effect on PP1 activity ( Fig 1F ) . These data exclude any non-specific activation of PfPP1c and support the major role of RVxF in the function of GEXP15 . To follow up the localization of PbGEXP15 in blood stages , we generated in GFP-P . berghei lines [24] , parasites expressing PbGEXP15-mCherry or PbPP1-mCherry ( S3A and S3B Fig ) . The expression of these tagged proteins was checked by immunoblots using anti-mCherry antibody ( S3C and S3D Fig ) . Examination of PbGEXP15-mCherry by immunofluorescence assays showed a distribution in the cytoplasm of all parasite stages examined along with clear punctate localization , suggesting potential cytoplasmic organelle structures ( Fig 2A ) . Further , the PbGEXP15 signal clearly exhibited a pattern adjacent to and in the nucleus of trophozoite and gametocyte stages . With respect to PbPP1 , the signal was observed throughout the cytoplasm with fluorescence partially overlapping DNA ( Fig 2B ) . Earlier works reported similar distributions for GEXP15 and PP1 in P . falciparum [10 , 25] , suggesting that the two proteins localize to the same compartments and could interact in vivo with each other . To confirm this , an anti-PbGEXP15 antibody raised against the recombinant protein and recognizing the native protein ( ~100kDa ) ( S3E Fig ) was tested on eluates immunoprecipitated from PbPP1-mCherry parasite extracts with anti-mCherry antibody . As shown in Fig 2C , immunoblot analysis revealed the presence of PbGEXP15 . These data , together with the results reported above , strongly support a physical interaction within the parasite . In order to provide new information about the functional pathways involving GEXP15 , it was important to better define the supramolecular architecture of PbGEXP15 complexes . To this end and to characterize a potential dynamic interactome of GEXP15 , we performed global immunoprecipitation of PbGEXP15-mCherry obtained from schizont and gametocyte soluble extracts using anti-mCherry antibody followed by mass spectrometry analysis ( IP/MS ) . With respect to the schizont stages , bait recovery from the IP/MS of 3 biological replicates yielded between 72 and 232 spectral counts with an average of 47% coverage , supporting the selectivity of this approach ( S1 Table ) . Results were validated and filtered if proteins were detected in at least two biological replicates out of three with ≥ 2 peptides and with peptides and spectra ≥ 2 fold compared with the control parental strain . In total , 18 proteins were identified including PbPP1 ( S1 Table ) . This supports the western blot analysis , confirms the endogenous interaction between the two proteins and demonstrates the reliability of the IP/MS approach . According to their GO annotations , the majority of the partners ( 12/18 ) are linked to mRNA splicing ( 6 proteins ) or proteasome core complex ( 6 proteins ) indicating at least two networks around PbGEXP15 . In the case of the IP/MS in gametocytes , results from two biological replicates have been filtered as described above and we identified 37 proteins ( S2 Table ) . We noticed an overlap of 6 partners already detected in the schizont stage and being mainly involved in splicing and the proteasome . In addition to these proteins , 8 novel members of the proteasome core were identified as well as DDX6 and SmD3 in the mRNA splicing complex confirming the link of PbGEXP15 with these pathways . Regarding PbPP1 , it was clearly detected in one replicate and at the limit of cut-off criteria in the second replicate ( S2 Table , sheet 2 ) . To further identify potential shared pathways in the PP1-GEXP15 complexes , we took advantage of a P . berghei strain expressing PbPP1-HA and completed the PP1 interactome in schizont stages obtained by IP/MS [23] . In this initial work , we confirmed that PbPP1-HA binds with the two most conserved regulators LRR1 and inhibitor 2 , interactions previously reported in P . falciparum [10 , 12] , and a novel regulator designated as RCC-PIP [23] . In this study , further analysis of the PbPP1 interactome was performed . As could be expected given the high number of biological processes implicating PP1 , a total of 178 proteins , including PbGEXP15 , were identified in this IP/MS based on the cut-off criteria used above ( S3 Table ) . These data revealed that the most important network corresponds to the 60S and 40S ribosomal proteins with the detection of 21 and 18 partners respectively and is consistent with outcomes obtained in different organisms [26–31] . When these data were compared with those obtained with the PfPP1 interactome [17] , we observed 18 overlapping proteins . However , other partners can be added since they share similar functions such as HSP/chaperones , 60/40S ribosomal proteins , histones and transcription factors . Most interestingly , comparative analysis of GEXP15 and PP1 interacting proteins revealed that both proteins are part of common protein complexes ( Fig 2D ) . Indeed , 5 and 10 proteins identified in the PbPP1 interactome are known to be part of the mRNA splicing and the proteasome complexes respectively , suggesting that the GEXP15/PP1 complex is a component of two different networks . Of note , previous studies have highlighted the importance of PP1 in these processes in various organisms , including P . falciparum [17 , 26 , 32–35] . To investigate the function of GEXP15 , a complete disruption of gexp15 in P . berghei by double homologous recombination was attempted . A construct comprising 5’ and 3’ UTRs of pbgexp15 flanking the pyrimethamine-resistance cassette was used for selection after parasite transfection ( S4A Fig ) . Among the pyrimethamine-resistant blood parasites , two clones were selected ( Δgexp15cl1 and Δgexp15cl2 ) and the presence of the double crossover was confirmed along with the absence of the wild locus ( S4A Fig ) . We also performed immunoblot experiments using anti-GEXP15 antisera on schizont parasites . PbGEXP15 protein was only detected in parental , but not in the Δgexp15 parasites , demonstrating a lack of PbGEXP15 protein expression in these clones ( S4B Fig ) . To explore the phenotype ( s ) of these parasites in more detail , we used two different mouse malaria models , C57BL/6 for experimental cerebral malaria ( ECM ) and BALB/c for malaria-linked pathologies ( severe anemia , hyperparasitemia ) . The survival was based on euthanizing mice according to criteria described in the Materials and Methods section . When C57BL/6 mice were infected with the parental strain ( 106 parasites ) , about 80% succumbed within 6–8 days post-infection from ECM ( Fig 3A , Table 1 ) due to blood-brain barrier disruption as evidenced by Evans blue staining ( S4C Fig ) . In contrast , none of C57BL/6 mice infected with the Δgexp15 parasites exhibited any ECM symptoms and 61% succumbed exclusively to hyperparasitemia between days 20–25 post-infection . In the case of BALB/c mice , as expected , all mice succumbed from hyperparasitemia before day 15 after infection with 106 parental parasites ( Fig 3B ) . Importantly , all BALB/c mice infected with Δgexp15 survived infection with a rapid clearance of all blood parasites after a peak of between days 10 to 12 ( Fig 3B and 3C ) . Given these data , we further tested whether Δgexp15cl1 infected BALB/c mice that survived the infection could be protected from a secondary infection with parental parasites . As depicted in Fig 3D and Table 1 , mice challenged with 107 infected red blood cells ( iRBC ) showed either low parasitemia ( <1% ) that was quickly cleared or no detectable infection up to 40 days post reinfection , while mice in the control group succumbed to the infection . A similar result was observed with Δgexp15cl2 ( Table 1 ) . These results suggest that the infection of BALB/c with Δgexp15 induces a potent protective response against parental parasites . To assess the effects of deficiency of PbGEXP15 expression on parasite growth , we investigated their intraerythrocytic development . First , the number of merozoites per schizont observed in vitro did not significantly differ between parental and Δgexp15 parasites ( Fig 3E ) . Thereafter , the growth rate was followed in mice infected intravenously with purified schizonts obtained from overnight cultures of parental and Δgexp15 parasites . At 1h post-infection , as shown in Fig 3F , both parental and Δgexp15 parasites exhibited ~80% rings suggesting a similar ability to invade . After 22h , a slight delay in the maturation of Δgexp15 parasites was observed with 64% of trophozoites and 30% of schizonts versus 41% and 50% respectively in parental parasites . At 25h , the examination of parental parasites showed 63% rings while the Δgexp15 parasites presented 15% rings ( p<0 . 0001 ) . The follow up at 29 h post-infection underscored the delay in transition ( 85% trophozoites in parental versus 32% in Δgexp15 , p<0 . 0001 ) . These data clearly indicate that the depletion of PbGEXP15 protein delays the intraerythrocytic growth of P . berghei . Consistent with the first proteomic analysis [19] and this study showing the expression of GEXP15 in gametocytes , we examined whether PbGEXP15 is essential at this stage . Unexpectedly , we noticed that the gametocytemia of Δgexp15 parasites did not differ significantly when compared to parental parasites ( Fig 4A ) and the deletion seemed to have no effect on the number of exflagellation centers of male gametocytes ( Fig 4B ) . These results indicate that PbGEXP15 did not affect the early male gametocyte development . In order to examine the role of PbGEXP15 during the mosquito stages and due to the difficulties to obtain reproducible and reliable data from in vitro ookinete conversion assays with the pG230 line that showed a very low conversion efficiency to ookinetes [36] , we used parental or Δgexp15 infected mice to feed Anopheles stephensi mosquitoes . Two independent experiments were performed and the dissection of the mosquito midguts at day 9 confirmed that 80% of blood meals were positive with parental parasites ( Fig 4C ) . Interestingly , in contrast to parental parasites , Δgexp15 parasites failed to initiate the formation of oocysts . This result was confirmed by the lack of Δgexp15 sporozoites in the salivary glands observed at day 18 whereas 22 , 000 sporozoites , on average , were detected with parental parasites ( Fig 4D ) . We conclude that PbGEXP15 is essential for parasite development in the mosquito . Previous studies showed that phosphatase inhibitors , comprising those acting on PP1 , are toxic to cells and that the uncontrolled activity of the catalytic phosphatase subunits could cause apoptotic cell death [37] . Given the capacity of PbGEXP15 to interact with and regulate the dephosphorylation activity of PP1 , we explored whether PbGEXP15 depletion could change the global phospho-proteomic patterns of Δgexp15 parasites . To investigate this , parental and Δgexp15cl1 schizonts were compared to assess proteomic and phosphoproteomic profiles . The quantitative experiments were performed on four biological replicates and three technical replicates . First , for the whole proteome analysis , we identified 2188 Plasmodium proteins across samples corresponding to 43% of the predicted proteome of P . berghei . We retained 1484 Plasmodium proteins that were reliably quantified in four biological replicates in at least one group ( S4 Table ) . In this global proteome , PbPP1 was detected and no difference was observed between levels in parental and Δgexp15 parasites . We next focused on proteins with significant changes in parental and Δgexp15 proteomes ( FDR<0 . 05 ) . The results indicate a total of 106 proteins ( accounting for ~ 7% of the total proteins identified ) whose abundance is significantly altered , of which 27 and 79 showed a significant increase and decrease respectively in comparison to parental parasites ( Fig 5A and 5B and S4 Table ) . An enrichment analysis of the biological processes was then performed for these proteins versus the global proteome ( Fig 5C ) . Interestingly , 16 proteins playing a role in the pathogenicity , such as RONs and MSPs , were detected with a significant decrease in the Δgexp15 parasites and correspond to the highest significant enrichment ( 5 . 6-fold , p<0 . 001 ) ( Fig 5B and 5C ) . We also noticed an under-representation of proteins involved in translation ( 0 . 13-fold , p<0 . 01 ) while 3 AP2 transcription factors were enriched among the up-regulated proteins ( 5 . 25-fold , p<0 . 05 ) ( Fig 5B and 5C and S4 Table ) . Of note , many proteins involved in these three biological processes have already been described to interact with PP1 ( this study and [17 , 32 , 38] ) . In total , 12% ( 13/106 ) of the altered proteins , such as AMA1 , RON-2 , -4 and -5 , are detected in the Plasmodium interactomes of PP1 ( S5A Fig and S4 Table ) . Collectively , these data indicate that the knock-out of pbgexp15 impacted the expression of several PP1 partners and would tend to confirm the commonality of signaling pathway ( s ) between GEXP15 and PP1 . Next , we explored the phosphoproteome of parental and Δgexp15 parasites . In total 2460 different phosphorylation sites of P . berghei were identified and quantified belonging to 780 Plasmodium proteins ( Fig 6A and S5 Table ) . We observed significant changes for 166 phosphopeptides corresponding to 118 proteins ( FDR<0 . 01 ) ( Fig 6B and S5 Table ) . Levels of phosphorylation of most of the phosphosites ( 143 phosphosites ) were lower in Δgexp15 when compared to the phosphoproteome of the parental parasites . The analysis showed a significant enrichment in proteins acting on RNA metabolism ( 1 . 9-fold , p<0 . 01 ) with 11 out of 12 phosphosites hypophosphorylated in Δgexp15 parasites ( Fig 6C ) . We also noticed the hypophosphorylation of 8 proteins engaged in transcriptional regulation ( including AP2 transcription factors ) , 5 proteins playing a role in post-translational modifications/chaperones and 4 proteins involved in trafficking ( S5 Table ) . A smaller set of 19 proteins was found to be hyperphosphorylated in the Δgexp15 parasites but most of these proteins have an unknown function . We also observed that overall 18% ( 21/118 ) of the phosphoproteins showing significant changes in phosphorylation were previously reported in the Plasmodium interactomes of PP1 suggesting that the phenotypes observed above could be due to a deregulation of the PbPP1 activity ( S5A Fig ) . To explore more deeply the role and the essentiality of GEXP15 in sexual and mosquito stages , we purified parental and Δgexp15cl1 gametocytes for proteomic and phosphoproteomic studies . The quantitative experiments were performed on three biological replicates and three technical replicates . Firstly , we determined the gametocyte proteome and identified 587 Plasmodium proteins that were reliably quantified in three biological replicates in at least one group ( S6 Table ) . As depicted in Fig 7A , 64% of these proteins are also detected in the schizont proteome , a percentage similar to previous overlaps in P . berghei ( 50% ) and P . falciparum ( 59% ) [39 , 40] . Significant changes in parental and Δgexp15 proteomes ( FDR<0 . 05 ) were observed for 11 proteins , with a significant decrease in abundance for 10 proteins in mutant parasites ( Fig 7B and S6 Table ) . One of these proteins , PbGSK3 ( PBANKA_0410400 ) that decreased significantly in Δgexp15 gametocytes and for which commercial antisera were available was tested by western blot experiments in two independent biological samples . Results indicated a drastic decrease of this protein in Δgexp15 gametocytes when compared to the parental strain , validating the proteomic analysis ( S5B and S5C Fig ) . Interestingly , 8 proteins out of the 11 have been described being enriched in female gametocytes and the others 3 in male gametocytes [39–42] . Among these proteins , we detected G377 ( PBANKA_1463000 ) which is localized in the osmiophilic bodies of female gametocytes and plays a role in the formation of these organelles and in the induction of gametogenesis with a delay in female gamete egress [43 , 44] . Furthermore , diverse studies have demonstrated that P25 ( PBANKA_0515000 ) and Lap2 ( PBANKA_1300700 ) play important roles in parasite transmission by mosquitoes and more precisely in the ookinete and oocyst stages [45–48] . Altogether , these data confirmed the phenotypic analyses observed and suggested that the deletion of pbgexp15 impacted key proteins in mosquito transmission . Concerning the phosphoproteome of parental and Δgexp15 parasites , we identified 444 different phosphorylation sites of P . berghei belonging to 278 proteins and we observed significant changes for only 9 phosphopeptides corresponding to 8 proteins ( FDR<0 . 01 ) ( Fig 7C and 7D and S7 Table ) . Unlike the proteome , these proteins did not seem to exhibit features linked to sexual differentiation similar to those shown above . Only two proteins are clearly described to be enriched in male and one in female gametocytes ( S7 Table ) .
The functional diversity of the PP1 catalytic subunit , an essential phosphatase enzyme , is now clearly attributable to more than 200 regulators that have been described in diverse eukaryotic organisms [8 , 9] . To date , only four conserved regulators of PP1 have been identified and characterized in P . falciparum [10–12 , 15] . A more recent study , using an Y2H screening to examine the global PP1 interactome in P . falciparum , identified GEXP15 as a potent regulatory partner of PP1 [17] . Here we confirmed the direct interaction of PbGEXP15 with PP1 and demonstrated its capacity to control the phosphatase activity . These results extend our previous data showing the capacity of conserved regulators to affect PP1 activity to a specific protein expressed by Plasmodium . Structure-activity studies indicate a major contribution of the well-known RVxF consensus binding motif to the function of GEXP15 . Moreover , a short N-terminal region of GEXP15 was able to bind PP1 and to increase its phosphatase activity in a similar manner to that observed with the full length protein . The mutation of the RVxF motif , present in this N-terminal region , completely abolished this regulation . These data suggest that this region seems to carry the regulatory function of GEXP15 on PP1 activity . To further explore the functional role of GEXP15 , we examined the impact of its deletion in the rodent malaria parasite P . berghei . Phenotypic analyses of these deficient parasites revealed a drastic effect on their development both in mice and mosquitoes . Indeed , while BALB/c mice infected with parental parasites succumbed to infection from hyperparasitemia , they were able to efficiently clear Δgexp15 parasites . This could be linked at least in part to the retarded multiplication that we observed . Further , surviving mice exhibited a protection against a secondary challenge by parental parasites , suggestive of a role of these deficient parasites in inducing protective responses . When C57BL/6 mice susceptible to ECM were tested , Δgexp15 parasites were found to be unable to induce ECM . Investigations on ECM in the mouse model indicated that it is a complex process involving both the parasite and the host molecules including proinflammatory cytokines [49–52] . However , when the outcomes of infections by Δgexp15 parasites of C57BL/6 and BALB/c mice ( prototypical Th1 and Th2-type strains respectively ) were compared , we observed a higher rate of mortality in C57BL/6 ( ECM model ) due to hyperparasitemia than in BALB/c ( hyperparasitemia model ) , suggesting a difference in the immune responses raised by these hosts towards the infection with Δgexp15 parasites . Earlier studies mainly focused on phenotypic analyses have shown similar data obtained with targeted disruption of hmgb2 described as a pro-inflammatory protein [53] , MSP7 involved in invasion of erythrocytes [54] or plasmepsin-4 contributing to hemoglobin digestion [55] . Although , the parasite derived molecules triggering host responses are still largely unknown , the use of Δgexp15 parasites might contribute for a better understanding of the protective mechanisms against ECM . Of note , the essentiality of GEXP15 in the blood stages was further supported by a recent study using a piggyBac transposon inserted randomly in P . falciparum genome [56] in which they did not obtain viable parasites with a disrupted pfgexp15 gene despite the presence of 35 potential insertion sites . For an in-depth dissection of the biological functions of GEXP15 , we performed quantitative proteomic and phosphoproteomic analyses . To the best of our knowledge , our proteomic study is the first in which a PP1 partner has been suppressed in Plasmodium . Of particular interest are low abundance proteins in schizonts that are members of the AP2 transcription factor family , which play a role in the regulation of gene expression , and invasion proteins including RONs and AMA1 . The low abundance of three AP2 transcription factors , that have been suggested to be essential [57 , 58] , could explain the general down-regulation observed for the proteins whose expression varies in Δgexp15 parasites . These results highlight the role played by GEXP15 and could explain the attenuated virulence of Δgexp15 parasites in blood stages . In our global phosphoproteomic analysis in schizonts , the data indicate the hyperphosphorylation of 19 proteins in Δgexp15 when compared to parental parasites . This could be expected as the lack of GEXP15 , an activator of PP1 in vitro , may lead to a decrease in PP1 activity and consequently an increase of phosphorylation of target proteins . Should this be the case , these hyperphosphorylated proteins could be considered as potential substrates of the complex PP1-GEXP15 . Interestingly , the RON2 protein , present in lower abundance in Δgexp15 parasites , was found to be hyperphosphorylated , possibly attenuating its known function in invasion [59–63] . However , synchronized Δgexp15 parasites did not show any delay in the first invasive cycles , suggesting a functional overlap and/or compensation between proteins involved in invasion [64] or that the induced defect did not attain a sufficient threshold to interrupt the invasion at least during the first cycles . On the other hand , the data suggest an unanticipated role of GEXP15 in the phosphorylation process . Indeed , we observed a drop in the phosphorylation levels of 100 proteins when compared to controls . These data could be explained either by free and uncontrolled PP1 capable of non-specifically dephosphorylating many and diverse substrates in the absence of GEXP15 and/or by an inhibitory role of GEXP15 on PP1 activity in Plasmodium . This latter possibility cannot be excluded as in vitro experiments , which showed a positive effect of GEXP15 on PP1 activity , were performed with the non-natural pNPP substrate . In addition , any post-translational modifications of GEXP15 in vivo could affect its function , which may be different from that observed with the recombinant protein . In this context , it has been shown that the phosphorylation status of Inhibitor-1 , a well-known regulator of human PP1 , differentially alters its function [65–67] . Concerning the proteome in gametocyte stages , we detected 11 proteins whose expression varies in Δgexp15 parasites . Among these proteins , eight , described to be overexpressed in female gametocytes , are present at lower levels in these deficient parasites . These data along with the above observations indicate that the lack of GEXP15 impacts neither the number of gametocytes nor the exflagellation of male gametocytes and strongly suggest that GEXP15 could function downstream in female gamete formation/egress/fertility or zygote-to-ookinete development . Supporting this is the under-abundance of the G377 protein in Δgexp15 that has been reported as a key actor in female egress/emergence ( 43 , 44 ) . Additional proteins could also contribute to the observed phenotype include Lap2 , demonstrated as being important in the mosquito transmission [47 , 48] or AP2-O2 that was hypophosphorylated on 2 serines in Δgexp15 schizonts compared to the parental parasites . This latter transcription factor is described as being crucial in the development of ookinetes and oocysts in P . berghei [58] while in P . yoelii , a knock-out of AP2-O2 did not seem to affect the gametocytes and ookinetes but only the number of oocysts and sporozoites [68] . In this study , unfortunately , the pG230 line used to generate Δgexp15 parasites exhibits very low conversion efficiency in vitro , hampering these studies . Of note , transfections of two other P . berghei strains did not allow the generation of viable knock-out or stable inducible knock-down parasites . Whatever the explanation , it is clear that the depletion of GEXP15 led to a complete abolition of oocyte/sporozoite formation in vivo . Taken together , our observations suggest that while the lack of GEXP15 expression could be transiently compensated in intraerythrocytic growth in the blood , this compensation seems to be insufficient with a high fitness cost in the mosquito . Interestingly , an earlier study suggested that GEXP15 was a potential orthologue of human CD2BP2 ( CD2 Cytoplasmic Tail Binding Protein 2 ) [69] . CD2BP2 has been described to interact with splicing factors and PP1 through a GYF domain [34] and an RVxF motif respectively [35] . The sequence analysis of PbGEXP15 reveals only 14% identity with HsCD2BP2 , but it presents a GYF like-domain , even if this does not match perfectly the consensus sequence [70] . However , although the IP/MS of PbGEXP15-mCherry demonstrated that several splicing factors are potential partners of GEXP15 , its contribution in the splicing function in Plasmodium requires further investigation in the future . In conclusion , the results shown here indicate that the viability of parasites in the absence of GEXP15 expression is accompanied by major alterations that could contribute to the avirulent phenotype of these parasites and their incapacity to produce oocysts . These alterations could affect spliceosome and proteasome pathways along with extensive changes to the phosphorylation patterns of Δgexp15 parasites that may be linked to an uncontrolled PP1 , capable of dephosphorylating inappropriate substrates . Additional studies are required to examine each novel aspect of the phenotypes of these Δgexp15 parasites and the potential alteration of the RNA splicing pathway .
Plasmids pGADT7/pGBKT7 , pETDuet-1 and pGEX4T3 were purchased from Clontech , Novagen and GE Healthcare Life Sciences . The plasmids pBS-DHFR and pL1886 were kindly provided by Drs R . Tewari and B . Franke-Fayard respectively . The primers used are described in S8 Table . Mice were housed in an Animal Biosafety Level 2 facility at the Institut Pasteur de Lille and maintained in accordance with the French National Guidelines for Use of Animals for Scientific Purposes which is also in line with EU Directive 2010/63/EU . Experimental protocols performed in this study were reviewed and approved by the Comité d’Ethique C2EA-75 en Expérimentation Animale Nord-Pas de Calais-France ( project number: 00527 . 04 ) . Infections and antiserum production were performed in CD1 male mice ( 30g ) ( Charles River ) . BALB/c ( 10 weeks ) and C57BL/6 ( 4-5weeks ) male mice ( Janvier Labs ) were sorted randomly into groups of 5–6 animals and used for hyperparasitemia and ECM comparison between parental and Δgexp15 parasites . The duration of experiments was strictly limited and constant monitoring of infected mice was carried out . When parasitemia was about 60% accompanied with weight body loss , mice were euthanized by CO2 inhalation . Mice susceptible to ECM were euthanized by CO2 inhalation if they displayed paralysis , convulsions/fits or coma . For the disruption of blood brain barrier , 100μl of 2% Evans blue dye in PBS were injected intravenously in C57BL/6 infected mice at day 6 p . i . Mice were then euthanized by CO2 inhalation 1h post-injection and brains were recovered . PbGEXP15 4–590 , PbGEXP15 4–178 , PbGEXP15 446–596 were amplified by PCR on P . berghei gDNA with primers p1-p2 , p1-p3 , p4-p5 respectively ( S8 Table ) and cloned into the pGADT7 vector ( Clontech ) using the In-Fusion HD Cloning system ( Clontech ) according to the manufacturer’s instructions . Gal4-DBD-PfPP1c and PfPP1c F255A/F256A were previously cloned [12 , 23] . PbGEXP15 4–178 KKKKKAQA was obtained by PCR-based site directed mutagenesis with Isis DNA polymerase ( MP Biomedicals ) and pGADT7-PbGEXP15 4–178 as template and primers p6-p7 . pGADT7 and pGBKT7 constructs were transformed into Y2H Gold and Y187 yeast strains ( Clontech ) respectively , and the yeasts were spread on Synthetic Defined agar medium lacking leucine ( SD-L ) or lacking tryptophane ( SD-W ) respectively and grown at 30°C for 3–5 days . Different mating experiments were performed and spread on selective media SD-LW . They were restreaked on more stringent media SD-LWH and SD-LWHA ( L: Leucine , W: Tryptophan , H: Histidine , A: Adenine ) after dilutions at 1:1 , 1:25 , 1:50 . Diploids were incubated for 4–6 days at 30°C . Empty vectors pGADT7 or pGBKT7 and pGBKT7-Laminin were used as negative controls . In order to check Plasmodium gene expression in yeast , RT-PCRs were performed . Total RNA was isolated from cultured yeasts ( OD = 0 . 5 ) after flash freezing and using TRIzol Reagent ( Thermo Fisher Scientific ) with glass beads for 45 min at 65°C with occasional vortexing . RNA ( 5 μg ) was treated with DNAse I ( Thermo Fisher Scientific ) and DNA contamination was checked using an Agilent 2100 Bioanalyzer and by RT-PCR on intronic gene of yeast tub1 . cDNA was synthesized using SuperScript III First-Strand Synthesis SuperMix ( Thermo Fisher Scientific ) according to the manufacturer’s instructions . Amplification of transcripts was carried out by PCR using the Advantage 2 Polymerase Mix ( Clontech ) and the following primers ( S8 Table ) : p13-p14 for TUB1 , p11-p12 for Gal4-DBD-PfPP1c and Gal4-DBD-PfPP1c F255A F256A , p8-p9 for Gal4-AD-PbGEXP15 4–590 , Gal4-AD-PbGEXP15 4–178 and Gal4-AD-PbGEXP15 4–178 KKKKKAQA , and p8-p10 for Gal4-AD-PbGEXP15 446–596 . The coding regions of PbGEXP15 4–590 and PbGEXP15 4–178 were obtained by PCR with the primers p15-p16 and p15-p17 respectively ( S8 Table ) and cloned into pETDuet-1 ( Novagen ) using the In-Fusion HD Cloning system ( Clontech ) . PbGEXP15 4–178 KKKKKAQA was obtained by PCR-based site directed mutagenesis with Isis DNA polymerase ( MP Biomedicals ) , pETDuet-1-PbGEXP15 4–178 as template and primers p6-p7 . GST , GST-PfPP1c and PfPP1c were produced as previously described [11 , 15] . All recombinant GEXP15 expressions were carried out in One Shot® BL21 Star™ ( DE3 ) Chemically Competent E . coli cells ( Life Technologies ) in the presence of 0 . 5 mM IPTG at 16°C overnight . Cells were harvested in non-denaturing buffer ( 20 mM Tris , 500 mM NaCl , 20 mM imidazole and protease inhibitor cocktail ( Roche ) , pH 7 . 5 ) followed by sonication and ultracentrifugation . Pellets were resuspended and centrifuged in denaturing buffer ( 20 mM Tris , 500 mM NaCl , 6 M guanidine , 20 mM imidazole and protease inhibitor cocktail ( Roche ) , pH 7 . 5 ) . Ni2+-NTA agarose beads ( Macherey Nagel ) were used to purify the recombinant proteins as previously described [12] . SDS-polyacrylamide gels were blotted onto nitrocellulose and probed with anti-His antibody ( 1:2000 dilution ) ( Qiagen ) followed by HRP-labeled anti-mouse IgG ( 1:50000 dilution ) . Chemiluminescence detection with SuperSignal™ West Dura Extended Duration Substrate ( Life Technologies ) was carried out . Recombinant proteins were quantified with Pierce™ BCA Protein Assay Kit ( Life Technologies ) . The purified PbGEXP15 4–178 was used to produce antisera as previously described [12] in CD1 mice . Glutathione-Sepharose beads ( Sigma-Aldrich ) coupled with GST-PfPP1c were incubated overnight at 4°C with 2 μg of PbGEXP15 4–590 , PbGEXP15 4–178 or PbGEXP15 4–178 KKKKKAQA in 20 mM Tris , 150 or 500 mM NaCl , 0 . 2 mM EDTA , 20 mM HEPES , 1 mM MnCl2 , 1 mM DTT , 0 . 1% Triton X-100 , 10% glycerol , protease inhibitor cocktail ( Roche ) and pH 7 . 5 . After 5 washes of the beads with the same buffer , proteins bound to the beads were analyzed by 4–20% SDS–PAGE followed by immunoblotting with anti-His ( 1:2000 ) or anti-GST mAb ( 1:2000 ) ( Invitrogen ) as described above . The role of GEXP15 on the activity of PfPP1c was investigated using the p-nitrophenyl phosphate ( pNPP ) assay . Different amounts of PbGEXP15 4–590 , PbGEXP15 4–178 and PbGEXP15 4–178 KKKKKAQA were preincubated with 40 pmol of PfPP1c for 30 min at 37°C . The enzymatic reaction was initiated by the addition of pNPP substrat ( Sigma-Aldrich ) to the reaction medium and the absorbance was measured at 405 nm ( Thermo Scientifc Multiskan FC ) . The lack of phosphatase activity of recombinant GEXP15 alone was checked according to the described procedure in the absence of PP1 . Two independent experiments were carried out in duplicate . In order to tag PbPP1c with mCherry , pbpp1c was amplified with primers p18-p19 ( 1324 bp ) ( S8 Table ) . The insert was subcloned into pL1886 plasmid . The construct was linearized by Tth111I before transfection . The same plasmid was used for PbGEXP15-mCherry . The 3’ region of pbgexp15 was amplified with primers p22-p25 and p24-p23 ( 1332 bp ) and a silent mutation was introduced by PCR-based mutagenesis in order to obtain a BsmI site , used to linearize the plasmid . For the knock-out of pbgexp15 , PCR amplifications were generated with the 5’ and 3’ UTR regions with primers p26-p27 ( 847 bp ) , p28-p29 ( 695 bp ) and P . berghei gDNA as template . The inserts were subcloned into pBS-DHFR plasmid [71] and the construct was linearized by XbaI-ApaI before transfection . Linearized pL1886 plasmids and pBS-DHFR plasmid were transfected by electroporation as previously described [72] in P . berghei ANKA GFP line [24] and pG230 line [36] respectively , kindly provided by Drs O . Silvie and N . Philip . Transfected parasites were inoculated in CD1 mice and positively selected by pyrimethamine in the drinking water , 30h after transfection [72] . Parasitized erythrocytes were lysed with Red blood cell Lysing buffer ( Sigma-Aldrich ) followed by the use of KAPA Express Extract kit ( KAPA BioSystems ) to extract DNA ( manufacturer’s instructions ) . Primers p20-p21 and p15-p21 were used to genotype pbpp1c-mCherry and pbgexp15-mCherry respectively ( S8 Table ) . Deletion of pbgexp15 was verified by diagnostic PCR using primers p30-p31 and p32-p33 and positive pbgexp15 knock-out parasites were cloned via intraperitoneal injection in CD1 mice . Blood from mice infected with PbPP1-mCherry or PbGEXP15-mCherry parasites was fixed with 4% paraformaldehyde and 0 . 0075% glutaraldehyde for 10 min at 4°C . After PBS washing , cells were sedimented on Poly-L-lysine coated coverslips overnight then permeabilized and saturated with PBS , 0 . 5% Triton X-100 and 1% BSA for 30min . Anti-RFP pAb ( MBL , PM005 ) was diluted 1:500 in PBS BSA 1% and applied for 1h at 37°C . Coverslips were washed with PBS and incubated with Goat anti-Rabbit IgG ( H+L ) Cross-Adsorbed , Alexa Fluor 594 ( Invitrogen , A11012 ) in PBS BSA 1% at 1:1000 in addition to DAPI ( 1μg/ml ) for 1h at 37°C . The coverslips were mounted in Mowiol and confocal imaging was performed with an LSM880 microscope ( Zeiss ) . Images were treated with ImageJ . To obtain schizonts , blood from infected mice was incubated 20h at 37°C in RPMI1640 culture medium supplemented with 0 . 4% AlbuMAX™ II Lipid-Rich BSA ( Life technologies ) , then schizonts were purified on a 55% Nycodenz gradient . Gametocytes purification was performed as previously described [73] . Briefly , CD1 mice were treated with phenylhydrazine by the intraperitoneal route ( 200μl , 6mg/ml , Sigma-Aldrich ) 2 days pre-infection then treated with sulfadiazine ( 20mg/ml in drinking water , Sigma-Aldrich ) 3 days post-infection . At day 5 post-infection , blood was collected by cardiac puncture and gametocytes purified on a 48% Nycodenz column in coelenterazine buffer . Purifications were higher than 95% for schizonts and gametocytes . Purified schizonts or gametocytes of PbPP1-HA , PbPP1-mCherry , PbGEXP15-mCherry and parental wild-type parasites used as control , were suspended in 50 mM Tris , 0 . 5% Triton X-100 and protease inhibitor cocktail ( Roche ) , pH 8 . After 10 freeze-thaw cycles and sonication , soluble fractions were obtained after repeated centrifugations at 13000 rpm at 4°C . Anti-HA agarose beads ( Life Technologies ) or RFP-Trap®_A beads ( Chromotek ) were mixed overnight at 4°C with parasite soluble extracts in 20 mM Tris , 150 mM NaCl , 0 . 5% Triton X-100 and protease inhibitor cocktail ( Roche ) , pH 7 . 5 . Beads were washed and elution was performed in Laemmli buffer . Then after 3 min at 95°C , samples were loaded on a 4–20% SDS-PAGE for western blot or mass spectrometry analyses . Western blots were carried out as described above and probed with anti-RFP pAb ( 1:1000 , MBL ) followed by goat anti-rabbit IgG-HRP ( 1:20000 , Sigma-Aldrich ) . Then , the membrane was stripped and probed with mouse sera anti-GEXP15 ( 1:100 ) followed by Mouse TrueBlot® Ultra: Anti-Mouse Ig HRP ( 1:2000 , eBioscience ) . For the Mass-spectrometry analysis , electrophoretic migration , tryptic digestion and nanoLC-MSMS analysis were performed as previously described [74] . Raw data collected during nanoLC-MS/MS analyses were processed and converted into * . mgf peak list format with Proteome Discoverer 1 . 4 ( Thermo Fisher Scientific ) . MS/MS data were interpreted using the search engine Mascot ( version 2 . 4 . 0 , Matrix Science , London , UK ) installed on a local server . Searches were performed with a tolerance on mass measurement of 0 . 2 Da for precursor and 0 . 2 Da for fragment ions , against a composite target decoy database ( 2*22 , 202 total entries ) built with Mus musculus Uniprot database ( 10090–17 , 008 entries ) , Plasmodium berghei PlasmoDB database ( Release 41 . 0–5 December 2018–5 , 076 entries ) fused with the sequences of PbPP1-HA or PbGEXP15-mCherry , recombinant trypsin and a list of classical contaminants ( 118 entries ) . Cysteine carbamidomethylation , methionine oxidation , protein N-terminal acetylation , and cysteine propionamidation were searched as variable modifications . Up to one trypsin missed cleavage was allowed . For each sample , peptides were filtered out according to the cut-off set for proteins hits with one or more peptides longer than nine residues . Ion and identity score were fixed to obtain a 1% false positive rate . In order to evaluate the number of merozoites per schizont , purified schizonts from P . berghei cultures were fixed in 4% paraformaldehyde and 0 . 0075% glutaraldehyde for 10 min at 4°C then incubated 30 min with DAPI . The nuclei were counted with Leica Leitz DMRB fluorescence microscope . To measure growth rate , purified mature schizonts were intravenously injected in CD1 mice . Smears were performed at 1h , 22h , 25h and 29h post-infection and rings , trophozoites and schizonts were counted under the microscope after Giemsa staining . For sexual development , the gametocytemia was determined by microscopy . Exflagellation was assessed after 10–12 min of incubation at 21°C in RPMI 1640 with 25 mM HEPES and 10% fetal calf serum , pH 8 [75] . The exflagellation centers were counted under slide-coverslip by microscopy using a 40x objective . Anopheles stephensi mosquitoes were maintained at the insectarium of the Institut Pasteur de Lille . They are reared at 19°C and 75–80% humidity under 12/12 hour light/dark cycle . Female mosquitoes ( 4 to 6 days ) were fed on anaesthetized infected CD1 mice once gametocytes had been observed . The presence of oocysts in the midgut was checked at day 9 post blood meal and dissection of salivary glands was assessed at day 18 . Fifteen salivary glands were pooled and homogenized per technical replicate . Sporozoite counts were determined with a Kova slide . The experiments were performed twice independently . P . berghei schizonts or gametocytes were purified as described above and treated with 0 . 15% saponin to avoid host contamination . Soluble proteins were extracted in RIPA buffer ( Thermo Fisher Scientific ) , Halt™ Protease and Phosphatase Inhibitor Cocktail ( Thermo Fisher Scientific ) and DNase I ( Thermo Fisher Scientific ) . Proteins were quantified with the Pierce™ BCA Protein Assay Kit ( Life Technologies ) . 82 μg of proteins for the schizonts and 100 μg of proteins for the gametocytes were first reduced with 0 . 1 M DTT final concentration at 60°C for 1h . MS sample preparation was performed using a FASP method ( filter aided sample preparation ) according to Lipecka et al [76] . We set aside around 10 μg of the digested proteins for the analysis of total proteomes , while the remaining samples were used for phosphopeptide enrichments . The expression of PbGSK3 was examined by western blot on purified gametocyte extracts and probed with anti-PfGSK3 ( 1:1000 dilution , Covalab , pab0250 ) and anti-Actin1 ( 1:2000 dilution ) followed by HRP-labeled anti-rabbit ( 1:20000 dilution ) and HRP-labeled anti-mouse ( 1:20000 dilution ) respectively . Relative quantification of PbGSK3 in parental and Δgexp15 gametocytes was normalized using PbActin-1 . Phosphopeptide enrichments were carried out using Titansphere TiO2 Spin tips ( 3 mg/200 μL , Titansphere PHOS-TiO , GL Sciences Inc ) on the digested proteins for each biological replicate . Briefly , the TiO2 Spin tips were conditioned with 20 μL of solution A ( 80% acetonitrile , 0 , 4% TFA ) , centrifuged at 3 , 000 g for 2 min and equilibrated with 20 μL of solution B ( 75% acetonitrile , 0 , 3% TFA , 25% lactic acid ) followed by centrifugation at 3 , 000 g for 2 min . Peptides were dissolved in 20 μL of solution A , mixed with 100 μL of solution B and centrifuged at 1 , 000 g for 10 min . Sample was applied back to the TiO2 Spin tips twice more in order to increase the adsorption of the phosphopeptides to the TiO2 . Spin tips were washed sequentially with 20μL of solution B and twice with 20μL of solution A . Phosphopeptides were eluted by the sequential addition of 50 μL of 5% NH4OH and 50 μL of 5% pyrrolidine . Centrifugation was carried out at 1 , 000 g for 5 min . Phosphopeptides were purified using GC Spin tips ( GL-Tip , Titansphere , GL Sciences Inc ) . Briefly , the GC Spin tips were conditioned according to manufacturer’s instructions , then eluted phosphopeptides from the TiO2 Spin tips were added to the GC Spin tips and centrifuged at 1 , 000 g for 5 min . GC Spin tips were washed with 20 μL of 0 . 1% TFA in HPLC-grade water . Phosphopeptides were eluted with 70 μL of 80% acetonitrile , 0 . 1% TFA ( 1 , 000 g for 5 min ) and vacuum dried . Peptides for the analysis of total proteomes were resuspended in 0 . 1% TFA in HPLC-grade water , 10% acetonitrile and 500 ng of each sample was injected in a nanoRSLC-Q Exactive PLUS ( RSLC Ultimate 3000 , Thermo Scientific ) . Phosphopeptides were resuspended in 42 μL of 0 . 1% TFA in HPLC-grade water and 5 μL of each sample was injected into the mass spectrometer . Samples were loaded onto a μ-precolumn ( Acclaim PepMap 100 C18 , cartridge , 300 μm i . d . ×5 mm , 5 μm , Thermo Scientific ) , and were separated on a 50 cm reversed-phase liquid chromatographic column ( 0 . 075 mm ID , Acclaim PepMap 100 , C18 , 2 μm , Thermo Scientific ) . Chromatography solvents were ( A ) 0 . 1% formic acid in water , and ( B ) 80% acetonitrile , 0 . 08% formic acid . Samples were eluted from the column with the following gradient: 5% to 40% B ( 120 min ) , 40% to 80% ( 6 min ) . At 127 min , the gradient returned to 5% to re-equilibrate the column for 20 min before the next injection . One blank was run between biological replicates to prevent sample carryover . Samples eluting from the column were analyzed by data dependent MS/MS , using the top-10 acquisition method . Peptides and phosphopeptides were fragmented using higher-energy collisional dissociation ( HCD ) . Briefly , the instrument settings were as follows: resolution was set to 70 , 000 for MS scans and 17 , 500 for the data dependent MS/MS scans in order to increase speed . The MS AGC target was set to 3 . 106 counts with maximum injection time set to 200 ms , while MS/MS AGC target was set to 1 . 105 with maximum injection time set to 120 ms . The MS scan range was from 400 to 2000 m/z . Dynamic exclusion was set to 30 sec duration . The MS files were processed with the MaxQuant software version 1 . 5 . 8 . 3 and searched with Andromeda search engine against the database of Mus musculus from swissprot 07/2017 and Plasmodium berghei ANKA from PlasmoDB ( v37 ) [20] . To search parent mass and fragment ions , we set a mass deviation of 4 . 5 ppm and 20 ppm respectively . Strict specificity for trypsin/P cleavage was required , allowing up to two missed cleavage sites . Carbamidomethylation ( Cys ) was set as a fixed modification , whereas oxidation ( Met ) and N-term acetylation were set as variable modifications . For the analysis of MS files issuing from of TiO2 enrichment , the variable modification of phosphorylation on S , T and Y were also added . The false discovery rates ( FDRs ) at the protein and peptide level were set to 1% . Scores were calculated in MaxQuant as described previously [77] . Match between runs was allowed . The reverse hits were removed from MaxQuant output . Proteins were quantified according to the MaxQuant label-free algorithm [77 , 78] using LFQ intensities and phosphopeptides according to intensity . Protein quantification was obtained using at least 2 peptides per protein . Statistical and bioinformatic analysis , including volcano plots and clustering , were performed with Perseus software ( version 1 . 6 . 0 . 7 ) freely available at Perseus [79] . For statistical comparison we set two groups: P . berghei parental and Δgexp15 . Each group contained four and three biological replicates for schizonts and gametocytes respectively and each sample was run in technical triplicates . For the total proteomes , we analyzed the proteingroups . txt file and the Phospho ( STY ) . txt fil for the phosphoproteomes . Protein LFQ and phosphopeptides intensities were transformed in log2 and the site table was expanded to analyze all phosphosites separately . Proteins derived from mouse were filtered out from the analysis and the P . berghei protein and phosphosite distributions were normalized using width adjustment . We further filtered the data to keep only proteins with at least 4 valid values in the parental and/or the Δgexp15 schizonts and 3 valid values for gametocytes . Data were imputed to fill missing data points by creating a Gaussian distribution of random numbers with a standard deviation of 33% relative to the standard deviation of the measured values and 2 . 5 standard deviation downshift of the mean to simulate the distribution of low signal values . We performed a t-test , FDR<0 . 05 ( 250 randomizations ) , S0 = 0 . 1 for the proteomes and FDR<0 . 01 ( 250 randomizations ) , S0 = 0 . 1 for the phosphoproteomes . Hierarchical clustering of proteins and phosphosites that survived the tests was performed with Heatmapper [80] on logarithmized LFQ intensities after z-score normalization of the data , using Pearson distances . The fold enrichments were based on GO annotations and their significance has been calculated by using hypergeometric probability test provided by Graeber lab: http://systems . crump . ucla . edu/hypergeometric/index . php An unpaired two-tailed non-parametric Mann–Whitney U test was used for the pNPP tests , comparison of the number of merozoites per schizont , gametocytes , exflagellation centers , oocysts and sporozoites . Parasitemia and survival curves were analyzed using a Wilcoxon and a log-rank ( Mantel-Cox ) test respectively . For growth rate , a two-way ANOVA followed by Tukey post hoc test was performed . Functional enrichments were analyzed by hypergeometric test . The criterion for a significant difference: * for p< 0 . 05; ** for p< 0 . 01 , *** for p<0 . 001 and **** for p<0 . 0001 . Our statistical analyses were detailed in the figure legends of each experiment . Statistical analyses were performed in GraphPad Prism 6 . For the statistical analysis of the proteomes and phosphoproteomes , the details are mentioned above .
|
In the absence of an effective vaccine and the emerging resistance to artemisinin combination therapy , malaria is still a significant threat to human health . Increasing our understanding of the specific mechanisms of the biology of Plasmodium is essential to propose new strategies to control this infection . Here , we demonstrated that GEXP15 , a specific protein in Plasmodium , was able to interact with the Protein Phosphatase 1 and regulate its activity . We showed that both proteins are implicated in common protein complexes involved in the mRNA splicing and proteasome pathways . We reported that the deletion of GEXP15 leads to a loss of parasite virulence during asexual stages and a total abolishment of the capacity of deficient parasites to develop in the mosquito . We also found that this deletion affects both protein phosphorylation status and significantly decreases the expression of essential proteins in schizont and gametocyte stages . This study characterizes for the first time a novel molecular pathway through the control of PP1 by an essential and specific Plasmodium regulator , which may contribute to the discovery of new therapeutic targets to control malaria .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"phosphorylation",
"parasite",
"groups",
"medicine",
"and",
"health",
"sciences",
"plasmodium",
"gene",
"regulation",
"enzymes",
"gametocytes",
"regulatory",
"proteins",
"dna-binding",
"proteins",
"enzymology",
"parasitic",
"diseases",
"parasitology",
"phosphatases",
"germ",
"cells",
"apicomplexa",
"transcription",
"factors",
"sequence",
"motif",
"analysis",
"research",
"and",
"analysis",
"methods",
"sequence",
"analysis",
"animal",
"cells",
"proteins",
"bioinformatics",
"gene",
"expression",
"biochemistry",
"cell",
"biology",
"post-translational",
"modification",
"proteomes",
"database",
"and",
"informatics",
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"genetics",
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"cellular",
"types"
] |
2019
|
Essential role of GEXP15, a specific Protein Phosphatase type 1 partner, in Plasmodium berghei in asexual erythrocytic proliferation and transmission
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The relative female and male contributions to demography are of great importance to better understand the history and dynamics of populations . While earlier studies relied on uniparental markers to investigate sex-specific questions , the increasing amount of sequence data now enables us to take advantage of tens to hundreds of thousands of independent loci from autosomes and the X chromosome . Here , we develop a novel method to estimate effective sex ratios or ESR ( defined as the female proportion of the effective population ) from allele count data for each branch of a rooted tree topology that summarizes the history of the populations of interest . Our method relies on Kimura’s time-dependent diffusion approximation for genetic drift , and is based on a hierarchical Bayesian model to integrate over the allele frequencies along the branches . We show via simulations that parameters are inferred robustly , even under scenarios that violate some of the model assumptions . Analyzing bovine SNP data , we infer a strongly female-biased ESR in both dairy and beef cattle , as expected from the underlying breeding scheme . Conversely , we observe a strongly male-biased ESR in early domestication times , consistent with an easier taming and management of cows , and/or introgression from wild auroch males , that would both cause a relative increase in male effective population size . In humans , analyzing a subsample of non-African populations , we find a male-biased ESR in Oceanians that may reflect complex marriage patterns in Aboriginal Australians . Because our approach relies on allele count data , it may be applied on a wide range of species .
In dioecious species , contrasting patterns of genetic differentiation between males and females provide important information on social organization [1] , dispersal and mating patterns [2 , 3] , and demographic history [4] . Some correlation may exist between the adult sex ratio and behavior [5]: in bird species with female-biased adult sex ratio , for instance , males have multiple mates and females care for their offspring , while the opposite has been observed in species with male-biased sex ratio [6] . The proportion of females can also provide information about the reproductive potential of a population , which is essential for wildlife management of endangered species [7] . To date , the characterization of sex-specific genetic variation has mainly been based on uniparentally inherited markers: mitochondrial DNA ( mtDNA ) , which is transmitted by females to their offspring , and the non-recombining portion of the Y chromosome ( NRY ) , which is inherited through the male line only [8–14] . However , due to the lack of recombination in both mtDNA and NRY , the potential influence of other evolutionary forces , in particular selection , challenge the interpretation of the observed patterns of genetic diversity [15–17] . To circumvent this problem , an alternative approach has been proposed , which consists in comparing the amount of genetic variation at both autosomal and X-linked markers [18] . Because they recombine , autosomes and X chromosomes harbor markers that may only be locally affected by selection . Such markers are therefore highly informative about demographic differences between males and females [15] , as was shown from the inference of sex-specific processes from the analysis of microsatellite markers [1 , 3 , 18] , single nucleotide polymorphisms ( SNPs ) [19–21] and sequence data [22 , 23] . In an isolated , random mating population with constant size and separate sexes , the effective population size for X-linked genes is expected to be three-quarters of that for autosomal genes , when the numbers of females and males are equal [24–26] . If the numbers of females and males are not equal , however , the ratio of X-to-autosome effective size is expected to deviate from three-quarters . This suggests that an effective sex ratio ( ESR ) , defined as the female proportion of the effective population , can be inferred from the X-to-autosome ratio of genetic diversity [24 , 27] . Accordingly , Hammer et al . [22] estimated the ratio of X-to-autosome effective size from observed levels of diversity , and found an excess of X-linked diversity in six geographically diverse human populations . They interpreted their findings as reflecting the widespread effect of larger female than male effective population sizes in humans . Labuda et al . [23] proposed to estimate the female-to-male breeding ratio from patterns of linkage disequilibrium ( LD ) on the X chromosome and the autosomes in humans . Although the original approach was undermined by errors in their mathematical derivations [28 , 29] , a reanalysis based on corrected equations [28] supported Hammer et al . ’s [22] claim of an excess of breeding females in human history . This LD-based method is not affected by the choice of DNA segments as entire chromosomes are considered . However , the method is only applicable to species for which detailed and reliable linkage maps are available . In yet another approach , Keinan et al . [19] derived an estimator of the ratio of X-to-autosome effective size across pairs of populations , based on measures of differentiation ( FST ) . Contrary to Hammer et al . [22] , they found indirect evidence of a male-biased ESR in the lineage ancestral to the split between European and Asian populations , coinciding with the Out-of-Africa expansion . This apparent paradox [26] was reconciled by Emery et al . [30] , who showed that FST-based approaches are more sensitive to recent events , whereas approaches measuring nucleotide diversity likely respond to older signals in the data . Finally , all aforementioned methods infer contemporary , population-specific ESR and hence provide only indirect information about historical ESR . Altogether , these arguments point to the difficulty of estimating past changes in the ESR . Here , we present a hierarchical Bayesian model to estimate contemporary and ancestral ESR in multiple populations , and therefore , to identify historical changes in sex-specific demography . More precisely , the demographic history of populations is represented as a multifurcating tree , and the ESR is inferred for each branch of that tree . Our approach makes full use of the information contained in genome-wide SNP data and can be applied to a wide range of model and non-model species , i . e . it does not require a detailed and reliable linkage map . Instead of relying on summary statistics ( as in [19 , 21 , 22 , 30] ) , we explicitly model the change in allele frequencies along each branch of the population tree , using Kimura’s time-dependent diffusion approximation [31] . Our method is an extension to the model by Gautier and Vitalis [32] , taking advantage of the joint analysis of autosomal and X-linked allele frequency data . The motivation behind our study is threefold: ( i ) to improve the original model to yield unbiased estimates of the branch lengths , particularly for internal branches; ( ii ) to extend the model and provide estimates of branch lengths for both autosomal and X-linked data , and therefore to infer the ESR; and ( iii ) to evaluate our method through simulations and provide real data application examples from cattle and human . In the following , we show that parameters are inferred robustly even under scenarios that violate some of the model assumptions . In cattle , as expected from the breeding scheme , our method detects a strongly female-biased ESR in both dairy and beef commercial cattle breeds , and a moderately female-biased ESR in African cattle . Conversely , we observed a strongly male-biased ESR during early domestication times , consistent with an easier taming and management of cows , and/or introgression from wild auroch males , that would both cause a relative increase in male effective population size . In humans , the analysis of a subset of whole-genome sequence data recently published by Pagani et al . [33] , provides evidence for a male-biased ESR in Oceanian human populations , that may result from complex marriage patterns among Aboriginal Australian groups .
The starting point for our model is detailed in Gautier and Vitalis [32] , and implemented in the software package KimTree . In short , KimTree is a hierarchical Bayesian model , where the allele frequencies are modeled along each branch of a population tree that needs to be specified a priori , using Kimura’s time-dependent diffusion approximation for genetic drift [31] . Consider a sample of I populations sharing a common history , represented as a tree . Each population has a label , i , which varies from 1 to I for the sampled populations , and from I + 1 to r for the internal nodes of the tree , where r represents the population at the root of the tree ( i . e . , the most ancestral population in the tree ) . In the following , we denote a ( i ) as the ancestral population of population i . The data consist of J bi-allelic SNPs . Let nij be the total number of genes sampled at the jth locus in the ith population . Let yij be the corresponding observed count of the reference allele , which is arbitrarily defined . Assuming Hardy-Weinberg Equilibrium ( HWE ) , the conditional distribution P ( y i j ∣ n i j , x i j ) of yij given nij and the ( unknown ) allele frequency xij is binomial . In the absence of mutation , assuming that population i with effective size Ne , i diverged from a ( i ) for ti discrete non-overlapping generations , the distribution πK ( xij ∣ xa ( i ) j , τi ) of xij , conditional upon the allele frequency xa ( i ) j in the parental population , and upon the branch length τi ≡ ti/ ( 2Ne , i ) is given by Kimura’s time-dependent diffusion approximation ( see Eqs 4 . 9 and 4 . 16 in Kimura [31] ) . In Gautier and Vitalis [32] , the prior distribution π ( xrj ) of the frequency xrj of the reference allele for the jth SNP in the root population follows a beta distribution Beta ( 1 . 0 , 1 . 0 ) , and the branch lengths τi’s are assumed to be sampled from a uniform distribution with support from 10−4 to 10 . Assuming that genetic drift occurs independently in each branch of the tree ( i . e . , there is no migration between branches ) , we may characterize the gene frequency hierarchically along the tree from the most ancestral population toward the leaves . The full model then takes the form: π ( X , τ ∣ Y , N ) ∝ [ ∏ i = 1 I ∏ j = 1 J P ( y i j ∣ n i j , x i j ) ] × [ ∏ i = 1 r - 1 π ( τ i ) ∏ j = 1 J π K ( x i j ∣ x a ( i ) j , τ i ) ] ∏ j = 1 J π ( x r j ) , ( 1 ) where X ≡ ( xij ) is a matrix of allele frequencies for all populations and loci , Y ≡ ( yij ) is a matrix of observed allele counts for all sampled populations and loci , N ≡ ( nij ) is the corresponding matrix of total allele counts , and τ ≡ ( τi ) is a vector of branch lengths . In the present study , the model has been improved in several directions . First , we extended KimTree to estimate the hyper-parameters of the Beta ( α , β ) prior for allele frequencies in the root population . Estimating the hyper-parameters of the beta distribution allows for a more flexible allele frequency distribution at the root , potentially shifting the total age of the tree . Following Gautier [34] , we re-parameterized the beta distribution using hyper parameters μ ≡ α/ ( α + β ) and ν ≡ ( α + β ) . We assumed a uniform prior for μ with support from 0 to 1 and an exponential prior for ν , i . e . μ ∼ U ( 0 , 1 ) and ν ∼ exp ( 1 . 0 ) , respectively . Second , we extended the model to account for the fact that the dataset consists , by construction , of polymorphic sites only . In SNP datasets , indeed , sites that are fixed across the entire sample have been filtered out . This is a non-trivial issue , since the fraction of sites that are monomorphic in the sample , but were polymorphic in the root population , contains information on the branch lengths . Ignoring this information may therefore result in biased estimates of the branch lengths . A solution to this problem is to condition the likelihood on SNP polymorphism , which is achieved by defining an indicator variable λj , which equals 1 if the jth position is polymorphic in the full sample ( 0 < ∑i yij < ∑i nij ) . Using this formalism , we can then compute the probability for a given SNP to be polymorphic across the sampled populations , conditionally on the topology , the branch lengths , and the allele frequencies in the root population . Here , we use a coalescent argument to compute this probability , as detailed in the Materials and methods section . Last , the model was extended to jointly analyze allele frequencies from both autosomal and X-linked markers . In a single , isolated population ( here , along each branch in the tree ) , the effective size for autosomal markers and X-linked markers ( here expressed as numbers of diploid individuals ) may be computed from the relative genetic contribution of both sexes ( males and females ) to the future of the population: N e ( A ) = 4 N e f N e m / ( N e f + N e m ) , and N e ( X ) = 9 N e f N e m / ( 2 N e f + 4 N e m ) ( see Eq 8 . 10 and 8 . 12 in Wright [24] ) . Defining the ESR as: ξ ≡ N e f / ( N e f + N e m ) , these equations can be recast as: N e ( A ) = 4 ξ ( 1 - ξ ) ( N e f + N e m ) and N e ( X ) = 9 ξ ( 1 - ξ ) ( N e f + N e m ) / ( 4 - 2 ξ ) . Since the branch lengths are measured on a diffusion time scale , they must be defined independently for each genetic system ( X or A ) , and therefore read: τ ( A ) ≡ t / ( 2 N e ( A ) ) and τ ( X ) ≡ t / ( 2 N e ( X ) ) . Rearranging the above expressions , it follows that the ESR can be written as: ξ = 2 - 9 8 τ ( X ) τ ( A ) ( 2 ) In principle , it would be possible to analyze the data from both genetic systems independently , and compute the ESR in each branch of the tree from the posterior distributions of the branch lengths for autosomal and X-linked markers . However , this would ignore the constraints that tie the effective sizes ( and hence the branch lengths ) of both genetic systems , since 0 < ξ < 1 ( see S1 Fig ) . Therefore , we defined a new model that allows to borrow information from the prior constraints ( see Fig 1 ) , where all the parameters are specific to one or the other genetic system . In the following , we use the index Ω for the genetic system ( Ω ∈ {A , X} ) . In this new model , as in Eq ( 1 ) , the reference allele counts y i j ( Ω ) follow a binomial distribution P ( y i j ( Ω ) ∣ n i j ( Ω ) ; x i j ( Ω ) ) , given the ( unknown ) allele frequencies x i j ( Ω ) at the leaf nodes and the total number n i j ( Ω ) of genes sampled at the jth locus ( j = 1 , … , J ( Ω ) ) in the ith population . The reference allele frequency for any given SNP j along the branches of the tree is assumed to follow Kimura’s time-dependent diffusion approximation π K ( x i j ( Ω ) ∣ x a ( i ) j ( Ω ) , τ i ( Ω ) ) , conditional upon the ancestral reference allele frequency xa ( i ) j in the parental population and upon the branch length τ i ( Ω ) ≡ t i / ( 2 N e , i ( Ω ) ) ( see Eqs 4 . 9 and 4 . 16 in Kimura [31] ) . At the highest hierarchical level of the model ( see S1 Fig ) , the reference allele frequency at the root node is assumed to follow a beta distribution π ( x r j ( Ω ) ∣ α ( Ω ) , β ( Ω ) ) with hyper-parameters α ( Ω ) and β ( Ω ) . The full joint posterior distribution of the model parameters Θ ≡ {X ( A ) , X ( X ) , τ ( A ) , τ ( X ) , α ( A ) , α ( X ) , β ( A ) , β ( X ) } , given the data D ≡ { Y ( A ) , Y ( X ) , N ( A ) , N ( X ) } , therefore reads: π ( Θ , λ = 1 ∣ D ) ∝ [ ∏ Ω ∈ { A , X } ( ∏ i = 1 I ∏ j = 1 J ( Ω ) P ( y i j ( Ω ) ∣ n i j ( Ω ) , x i j ( Ω ) ) ) × ( ∏ i = 1 r − 1 ∏ j = 1 J ( Ω ) π K ( x i j ( Ω ) ∣ x a ( i ) j ( Ω ) , τ i ( Ω ) ) ) × ( ∏ j = 1 J ( Ω ) π ( x r j ( Ω ) ∣ α ( Ω ) , β ( Ω ) ) ) π ( α ( Ω ) ) π ( β ( Ω ) ) ] ( ∏ i = 1 r − 1 π ( τ i ( A ) , τ i ( X ) ) ) × ( ∏ j = 1 J ( Ω ) P ( λ j ( Ω ) = 1 ∣ α ( Ω ) , β ( Ω ) , τ ( Ω ) , n j ( Ω ) ) ) − 1 ( 3 ) Since all markers are polymorphic , by definition , we assume that λ ≡ { λ j ( A ) , λ j ( X ) } = 1 ( unit vector of length J ( A ) + J ( X ) ) . This model follows from Eq ( 1 ) , except that the square brackets integrate over the two genetic systems . One can also note that the parameters of the beta distribution of allele frequencies at the root node are estimated ( see the first terms in the third line of the above equation ) . Furthermore , the prior distribution of the branch lengths lies outside the square brackets , since π ( τ i ( A ) , τ i ( X ) ) represents the joint prior distribution for the branch lengths ( see the Materials and methods section ) . Last , P ( λ j ( Ω ) = 1 ∣ α ( Ω ) , β ( Ω ) , τ ( Ω ) , n j ( Ω ) ) gives the probability that site j is polymorphic , conditionally on the population tree and the model parameters ( see the Materials and methods section ) . The details of the component-wise Markov chain Monte Carlo ( MCMC ) algorithm , implemented in KimTree to sample from the joint posterior distribution specified by Eq ( 3 ) , are provided in the Materials and Methods section . The posterior distribution of the ESR for the ith branch is then computed from the branch lengths at each MCMC iteration , as: ξ i = 2 - ( 9 τ i ( X ) ) / ( 8 τ i ( A ) ) . Last , for each branch , we compute the support for the hypothesis ξi ≠ 0 . 5 as follows: S i = 1 - 2 ∣ p i - 0 . 5 ∣ ( 4 ) where pi is the proportion of the posterior MCMC draws with ξi > 0 . 5 in the ith branch . Large values of Si ( Si → 1 ) are interpreted as evidence of an absence of departure from ξi = 0 . 5; Si = 0 . 05 ( resp . Si = 0 . 01 ) indicates that 97 . 5% ( resp . 99 . 5% ) of the posterior MCMC draws of ξi are all larger than 0 . 5 , or all smaller than 0 . 5 . In a preliminary evaluation , we confirmed that the improved KimTree model resulted in accurate estimates of external and internal branch lengths ( see S1 Text , and S2–S5 Figs ) . Since the true population history is generally unknown , we investigated the power of the deviance information criterion ( DIC ) [35] to choose between alternative histories . To that end , we simulated 50 datasets using ms [36] for a three-population history with topology ( ( 1 , 2 ) , 3 ) . We then analyzed each of these datasets , conditionally on four alternative topologies . As in Gautier and Vitalis [32] , we found that the DIC provides a clear support in favor of the true ( simulated ) population history ( S6 Fig ) . We further found that , whatever the topology , the DIC supports the model where the likelihood is conditioned on SNP polymorphism ( S6 Fig ) . Then , we evaluated the performance of our model to infer the branch-specific ESR in a population tree , using simulated datasets . First , we simulated scenarios complying to the model assumptions , with constant population sizes along each branch and no migration between branches . Since the KimTree model assumes that all polymorphisms are ancestral ( an assumption which is not made in the simulations ) , we defined a large population size for the root population ( made of 50 , 000 males and 50 , 000 females ) . Fig 2 shows the distributions of posterior means of branch-specific ESR , in a population tree with topology ( ( 1 , 2 ) , 3 ) , where some branches have been simulated with ξ ≠ 0 . 5 . Note that an evaluation of these datasets based on wrong topologies provided consistent results for the terminal branches ( see S7 Fig ) . Fig 3 shows a population history with topology ( ( 1 , 2 ) , ( 3 , 4 ) ) , where the four external branches have biased ESR . We found that the ESR was estimated accurately for all considered cases . Then , by altering a control case ( see Fig 4A ) , we evaluated the robustness of our method to violations of the model assumptions . Our simulations demonstrate that several thousand SNPs are generally sufficient to obtain accurate estimates of the model parameters . We therefore advocate for a subsampling strategy that consists in analyzing pseudo-replicated subsets of the data instead of the full data ( see the Discussion section ) .
In this study , we introduced an improved and extended KimTree model that can be used to infer branch lengths and branch-specific ESR for a given tree topology , taking advantage of a joint analysis of X-linked and autosomal allele frequency data . The inference of branch-specific ESR throughout a population tree requires accurate estimates of branch lengths from autosomes and X chromosome . Model-based methods that reconstruct population histories can be broadly divided into two categories: coalescent-based models ( e . g . , [43] ) and models that use diffusion approximations of genetic drift ( e . g . , [44] ) . However , despite considerable computational advances , coalescent-based likelihood inferences remain in practice intractable when the size of the considered data is large [43 , 45] . Recently , Tataru et al . [46] evaluated the accuracy of Kimura’s time-dependent diffusion approximation for genetic drift , relatively to alternative models like the Gaussian ( used in , e . g . , TreeMix [39] ) , the beta distribution ( used in , e . g . , NB [47] ) or the beta with spikes approximation ( used in SpikeyTree [48] ) . As expected , they found that Kimura’s time-dependent diffusion provides the most accurate approximation to the drift process . Yet , for branch length inference , Tataru et al . [48] showed that SpikeyTree could outperform KimTree [32] , which is based on Kimura’s time-dependent diffusion . We have shown that this discrepancy originated from the fact that in its original implementation , KimTree did not account for the exclusive presence of polymorphic markers in SNP datasets . By construction , these datasets lack the information contained in the fraction of sites that are polymorphic in the root population , but fixed in the sample ( see S2 and S3 Figs ) . Following Tataru et al . [48] , we therefore extended our model to condition on polymorphism at all sites . When compared to the full likelihood model , this conditional likelihood model is strongly supported , based on the DIC criterion ( S6 Fig ) . We have shown that branch length estimates were improved , particularly for internal branches . In a direct comparison , the improved KimTree model outperformed the beta-with-spikes model [48] ( see S4 and S5 Figs ) . We demonstrated through extensive simulations that our method is able to accurately infer the ESR for different scenarios , if the model assumptions are met ( Figs 2 and 3 ) . However , as the ESR is known to be affected by different processes such as selection [49–51] , sex-biased migration [52] , population size changes [53] or SNP ascertainment bias , it is necessary to interpret the results with care . Furthermore , it should be noted that our model cannot distinguish between possible sources of variation for the ESR . For example , social organization ( polygamy ) , sex-specific migration , or differential mortality rates may lead to a similarly unbalanced ESR . Thus , any of such mutually non-exclusive alternatives must be considered when interpreting the results . Independent analyses might therefore be helpful . For instance , computing f-statistics [54 , 55] may serve as a sanity check to rule out substantial migration among populations . However , we have shown that our parameter estimates are robust to different model violations ( Fig 4 and S8 Fig ) . In general , estimates of the ESR for external branches seem to be more robust than estimates for internal branches . This might be due to a higher power in characterizing recent ESR as compared to ancestral ones . In addition , recent ( non-ancestral ) polymorphism seems to more strongly affect internal branches , possibly contributing to a higher uncertainty in the ESR for those branches ( S9 Fig ) . Population size changes may alter the X-to-autosome pattern of diversity [53] , which can then lead to biased estimates of the ESR . The reason for this is the smaller effective population size of the X chromosome compared to the autosomes , allowing X-linked variation to converge faster to its new equilibrium after a population size change . With our approach , we found no evidence for a bias in estimating the ESR due to population size changes: each branch length estimate is very close to that predicted using the harmonic mean of the effective size along that branch , such that the corresponding ESR appears unbiased ( Fig 4B and S8 Fig ) . Although the assumption of conditional independence of SNPs is violated in KimTree , and although the expected extent of LD differs between autosomes and the X chromosome , we found that our model is robust to LD under realistic conditions ( S10 Fig ) . Based on our simulation results , we therefore recommend to subsample SNPs randomly , or to thin the data by taking one SNP out of every n SNPs from the ordered map . Such a strategy is more relevant than LD pruning , because it does not alter the allele frequency spectrum , on which inference is based . Random subsampling of genome-wide data can further be used to provide pseudo-replicated estimates from a handful of reduced datasets . This allows in turn to provide higher support to our conclusions through pseudo-independent estimates of the parameters of interest . From a more technical point of view , another advantage of this approach is that we may reduce the asymmetry in the number of markers for autosomes and the X chromosome . This asymmetry in the amount of information available for each genetic system may indeed cause specific issues for the joint update of branch lengths , with poor acceptance rates . We found that 5 , 000 markers per dataset and per genetic system provided accurate parameter estimates , while limiting the computational burden . Estimation of the ESR might also be affected by SNP ascertainment bias , which notably depends on the ascertainment scheme . Although conditioning the likelihood on the presence of polymorphic sites only does improve the accuracy of branch length estimates ( see above ) , it does not address the specific problem of ascertainment bias in genotyping assays . We found that ascertainment bias may result in biased estimates of branch lengths , in particular when only a subset of populations belongs to the discovery panel ( see S11A , S11B , S11D , S11E , S11G and S11H Fig ) . However , estimates of the ESR were unbiased in the simulated conditions , where the ascertainment scheme was identical for both autosomal and X-linked markers ( see S11C , S11F and S11I Fig ) . Nevertheless , we recommend to be cautious when interpreting the results from ascertained datasets and , if possible , to use whole-genome sequence data . For illustration purposes , we analyzed both cattle and human SNP genotyping data , providing new insights into the sex-specific demographic history of these two species . We chose three cattle breeds ( HOL , ANG and NDA ) with contrasting breeding schemes ( from a widespread use of artificial insemination in the HOL dairy cattle to mostly uncontrolled mating in the NDA cattle from West-Africa ) . These breeds are also representative of the post-domestication history , with HOL , ANG and NDA presumably originating from the same domestication center in the Middle East , ca . 10 , 000 YBP [56] . As expected , we found a strongly female-biased ESR in the commercial breeds ( HOL and ANG ) , with less than two effective males for 100 effective females in both breeds . These ESR estimates integrate over the time of divergence between ANG and HOL , which has occurred ca . 2 , 000 YBP [57] . Since modern genetic improvement programs have been generalized only recently ( in the past 70 years ) , the impact of increased selective pressure for beef ( in ANG ) or milk ( in HOL ) production on the ESR might thus be even higher than our estimate suggests . Before that , indeed , the ESR for commercial cattle breeds might have been only moderately female-biased , as we observe for the traditionally raised NDA with about 36 effective males for 100 effective females . More interestingly , we found a strongly male-biased ESR ( four effective females for 100 effective males ) in the internal branch of the tree , which is ancestral to the ANG and HOL breeds . This result supports the hypothesis that around the period of cattle domestication , females were plausibly more easily managed than males . Keeping and rearing preferentially female offspring would indeed tend to decrease the effective size for females . At the same time , preventing tamed females from breeding randomly with wild males would be a difficult task , which would result in turn in an increased effective size for males ( see [58] , p . 2218 ) , and therefore in a male-biased ESR . Alternatively , introgression of wild auroch males into domesticated cattle [59 , 60] may have increased the male effective population size . Deciphering between these two non-mutually exclusive hypotheses would require further investigations . Finally , we re-analyzed recently published sequence data from Pagani et al . [33] combined with sequences from Drmanac et al . [61] and from the Personal Genomes Project . We found a strong and significant male-biased ESR in the Oceanian sample ( Fig 7 ) , that could not be explained by the small sample size in that branch ( S14 Fig ) . It should be pointed out , however , that because this Oceanian sample consists of only six males , it may not be representative for the whole region . Nevertheless , our results are consistent with Malaspinas et al . [4] , who recently studied high-coverage genomes in a large dataset from Aboriginal Australians and Papuans and provided important insight into the social structure of Aboriginal Australian societies . They inferred greater between-group variation for mtDNA compared to the Y chromosome , suggesting higher levels of male-biased dispersal . The lack of recombination in these markers , however , may complicate the interpretation of their observed patterns of genetic diversity [15 , 16] . With our new approach , we provide additonal evidence of a male-biased ESR in Oceanians , here on the basis of autosomal and X-linked data , which take advantage of thousands of independent loci . Combining these results strengthens the picture of complex marriage and post marital residence patterns among Pama-Nyungan Australian groups , where tribes are divided into exogamous “sections” that are either patrilineal or matrilineal [62] . Matrilineal organization should increase relatedness among women , and therefore reduce the effective number of women as compared to men , which may result in a male-biased effective sex ratio , as we observed . Our method takes advantage of genome-wide SNP data and can in principle be applied to a wide range of species . Its generic character allows it to be also applicable to Pool-seq data , which in contrast to individual sequencing , is based on sequencing individuals in pools , resulting in read count data instead of individual genotypes . Pool-seq allows for cost efficient production of large datasets , and recently became a popular source of data due to its high accuracy-to-cost ratio [63] . For Pool-seq data , one shall assume that the ( observed ) read counts are binomially distributed , given the ( unknown ) allele frequencies and the sample size of each pool [64] , which is straightforward to implement in our hierarchical Bayesian framework [34] . It should be noted however that conditioning the likelihood on the exclusive presence of polymorphic sites in the sample has to be further adjusted for Pool-seq data . Although sites that are fixed among all sampled individuals are also fixed in the Pool-seq data ( baring mutation ) , it may happen that polymorphic sites among sampled individuals appear fixed in the Pool-seq data ( if , by chance , only one allele is sequenced in the Pool-seq experiment ) . This latter possibility must therefore be accounted for when calculating the probability of a polymorphic site in the case of Pool-seq data . Moreover , our method can in principle also be used to detect selection by identifying outliers on either autosomes or X chromosome . This can be achieved by computing ( locus-specific ) posterior predictive p-values , to test if the observed data are plausible under the posterior predictive distribution [65 , 66] . With our model , we can take advantage of the relationship between autosomes and X chromosomes via the ESR and , for example , test for signatures of selection on the X chromosome , while accounting for the demographic information contained in autosomal data . Such an approach was suggested by Dutheil et al . [67] , who analyzed whole-genome data of humans and great apes . They used autosomal data to predict the expected incomplete lineage sorting for the X chromosome , assuming a balanced sex ratio , and found evidence for recurrent selective sweeps on the X chromosome . Using KimTree , we may similarly infer demographic parameters ( branch lengths and branch-specific ESR ) from the joint analysis of autosomal and X-linked markers , and test for locus-specific departures of that demographic history , which might result from selection acting on either genetic system .
Because SNP data from different populations contain , by definition , only polymorphic sites , we condition the likelihood to account for those sites that are polymorphic in the root population but end up as fixed positions in the full sample and are , as such , absent from the dataset ( see Tataru et al . [48] ) . In the following , for the sake of clarity , we develop the computation of the conditional likelihood in the context of the simpler model defined by Eq ( 1 ) . This computation extends naturally to the full model defined by Eq ( 3 ) , for both autosomal and X-linked data . Conditioning the likelihood amounts to defining an indicator variable λj , which equals 1 if the jth position is polymorphic in the full sample ( i . e . , if 0 < ∑i yij < ∑i nij ) . As detailed below , we assume that the prior on λj depends on the sample size nj , the branch lengths τ and the allele frequencies in the root population xrj: P ( λ j = 1 ∣ n j , x r j , τ ) = 1 - P ( ∑ i y i j = 0 ∣ n j , x r j , τ ) - P ( ∑ i y i j = ∑ i n i j ∣ n j , x r j , τ ) ( 5 ) where P ( ∑ i y i j = 0 ∣ n j , x r j , τ ) is the probability that the reference allele is absent in all sampled populations and likewise P ( ∑ i y i j = ∑ i n i j ∣ n j , x r j , τ ) is the probability that the reference allele is fixed in the entire sample . Altogether , the conditional probability of the data ( likelihood ) therefore reads: π ( Y ∣ N , X , τ , α , β , λ = 1 ) ∝ π ( Y , λ = 1 ∣ N , X , τ , α , β ) ∏ j = 1 J P ( λ j = 1 ∣ n j , x r j , τ ) ∝ π ( Y ∣ N , X ) π ( X ∣ τ , α , β ) ∏ j = 1 J P ( λ j = 1 ∣ n j , x r j , τ ) ( 6 ) In order to develop Eq ( 5 ) , we suggest an approach based on coalescent theory , similar in spirit to that described in Beaumont [68] . In a single population ( or a branch in a population tree ) , the number of ancestral lineages of a sample of genes decreases over time ( looking backward ) due to coalescent events . Therefore , in the absence of newly arising mutations , the jth site will be fixed in the sampled populations , if all the ancestral lineages of the sample in the root node carry the same allelic state , i . e . P ( ∑ i y i j = 0 ) = P ( y r j = 0 ) and P ( ∑ i y i j = ∑ i n i j ) = P ( y r j = n r j ) . The probabilities P ( y r j = 0 ) and P ( y r j = n r j ) may be obtained by integrating over the probability distribution of the number of ancestral lineages in the root node , weighted by the probability that all the ancestral lineages are of the same allelic type ( see below ) . The number of ancestral lineages in the root node , which is a random variable , depends upon the number of coalescences that occur in the intervals between the nodes of the tree . For each interval ( i . e . , for each branch ) , we therefore need to compute the number of ancestral lineages , looking backward in time , given the current number of lineages and the branch length . Tavaré [69] derived the distribution of the number k of ancestral lineages P ( k ∣ i , τ ) for one population , given the current number of lineages i , and the time interval τ ( in a diffusion time-scale ) . Because computation of Tavaré’s [69] distribution was shown to be unstable [70 , 71] , we use instead a normal distribution approximation to P ( k ∣ i , τ ) ( see Eqs 4 and 5 in Griffiths [70] ) . To integrate over the full population tree , we start the computation at the leaf nodes , where the number of lineages equals the corresponding sample size nij ( measured in numbers of genes ) , i . e . we compute P ( n ˜ a ( i ) j ∣ n i j , τ i ) for i = 1 , … , I using Eqs ( 4 ) and ( 5 ) in Griffiths [70] . Here , n ˜ a ( i ) j is the ( random ) number of lineages in the ancestral node a ( i ) of i . We then proceed towards the root of the tree by computing P ( n ˜ a ( i ) j ∣ n ˜ i j , τ i ) for all internal nodes , i . e . for i = I + 1 , … , r . For each internal node , we first need to compute the probability distributions of the number of lineages P c ( n ˜ a ( i ) j ) , which is a combination of the probability distributions of the number of lineages for all the daughter nodes of a ( i ) . For example , in the case of two nodes i and i′ that share the same ancestor , i . e . a ( i ) = a ( i′ ) , we get the following probability distribution: P c ( n ˜ a ( i ) j = k ) = ∑ l = 1 n i j ∑ m = 1 n i ′ j P ( l ∣ n i j , τ i ) P ( m ∣ n i ′ j , τ i ′ ) δ k l + m ( 7 ) where δ k l + m is the Kronecker delta: δ k l + m = { 1 if k = l + m 0 otherwise . ( 8 ) Note that , in general , different combinations of l and m contribute to the probability of a single number of lineages k = l + m . Also , note that the probability distribution P c ( n ˜ a ( i ) j ) for the number of ancestral lineages in that node is defined for k = 2 , … , ( nij + ni′j ) lineages ( k = 2 because the node a ( i ) has two daughter nodes in that example ) . The case of more than two populations sharing the same ancestral node follows analogously . The full probability distribution of ancestral lineages for the node a ( i ) after time τa ( i ) is then be given by: P ( n ˜ a ( i ) j = k ′ ∣ τ a ( i ) ) = ∑ k P ( k ′ ∣ k , τ a ( i ) ) P c ( n ˜ a ( i ) j = k ) ( 9 ) Combining all branches , recursively , in the population tree , we get the probability distribution of the number of ancestral lineages in the root node r at site j , P ( n ˜ r j ∣ τ ) . Given that the allele frequency in the root population at site j is xrj , we get: P ( y r j = 0 ∣ x r j , n j , τ ) = ∑ k P ( n ˜ r j = k ∣ n j , τ ) ( 1 - x r j ) k ( 10 ) and: P ( y r j = n r j ∣ x r j , n j , τ ) = ∑ k P ( n ˜ r j = k ∣ n j , τ ) x r j k ( 11 ) Therefore , combining Eqs ( 5 ) , ( 10 ) and ( 11 ) , the probability that all the ancestral lineages in the root node are not of the same allelic type ( and therefore that the full sample is polymorphic ) is given by: P ( λ j = 1 ∣ x r j , n j , τ ) = 1 - [ ∑ k P ( n ˜ r j = k ∣ n j , τ ) [ ( 1 - x r j ) k + x r j k ] ] ( 12 ) For ease of computation , we assume the same sample size n across all sites , which we set to the maximum sample size observed in the dataset . Then the number of ancestral lineages in the root node , P ( n ˜ r j = k ∣ n , τ ) , is independent of site j and is therefore equal across loci . Since the probability of a site to be polymorphic is conditioned on the allele frequency in the root population ( xrj ) , the beta distribution for the allele frequencies in the root population must be interpreted as the distribution of allele frequencies only for sites that are polymorphic in the entire sample . This is different from the model by Tataru et al . [48] , who instead computed the probability of a site to be polymorphic by integrating over the beta distribution of allele frequencies in the root population ( with shape parameters α and β ) . In their case , the beta distribution therefore corresponds to the distribution of allele frequencies in the root population , i . e . , not only for polymorphic sites but also for sites that were polymorphic in the root population and became fixed in the entire sample . In practice , we found both implementations ( and therefore both interpretations of the beta distribution ) to result in similar estimates for the branch lengths . However , integrating over the beta distribution , as in Tataru et al . [48] , sometimes resulted in numerical issues related to the computation of the hyper-parameters α and β , which convinced us that this approach was less robust . Consequently , all the results presented here are based on computing the probability of a site to be polymorphic conditionally on the allele frequencies ( xrj ) in the root population . We implemented a component-wise Markov chain Monte Carlo ( MCMC ) , or Metropolis within Gibbs , algorithm ( see , e . g . , [72] ) to sample from the joint posterior distribution of π ( Θ , λ = 1 ∣ D ) , which is specified by Eq ( 3 ) . For all parameters but τ i ( A ) and τ i ( X ) , this amounts to updating one parameter at each step , iteratively , as detailed in Gautier and Vitalis [32] . For the branch lengths , however , we perform a joint update for τ i ( A ) and τ i ( X ) , assuming a bivariate uniform prior distribution over the support that satisfies 9 τ i ( X ) / 16 < τ i ( A ) < 9 τ i ( X ) / 8 and 8 τ i ( A ) / 9 < τ i ( X ) < 16 τ i ( A ) / 9 ( see S1 Fig ) . At each step of the Markov chain , and for each branch , a new value of τ i ( A ) is drawn from a uniform distribution centered around the current value; if the proposed value lies outside the support defined above , then the excess is reflected back into the support . The same procedure is executed for τ i ( X ) , and the update is accepted or rejected for both parameters altogether , using appropriate Metropolis-Hastings ratios . The proposal distributions for each of the X ( Ω ) , τ ( Ω ) , α ( Ω ) and β ( Ω ) parameters are adjusted by means of short pilot runs ( typically 20 runs with 500 iterations ) , executed before the MCMC , to obtain acceptance rates between 0 . 25 and 0 . 40 ( see , e . g . , [73] ) . Under default conditions , each MCMC was run for 20 , 000 iterations after a burnin-in period of 10 , 000 runs . Samples from the posterior distribution were taken every 20 iterations ( thinning ) to reduce autocorrelation . Because the tree topology is generally unknown , we implemented a model choice procedure to characterize , for any given dataset , the strength of evidence for alternative population histories . Following Gautier and Vitalis [32] , we used the deviance information criterion ( DIC ) , which is a standard criterion for model selection [35] . Up to a constant that does not depend on the model , the DIC is equal to ( 2 D ¯ - D ( Θ ¯ ) ) , where D ¯ is the posterior mean deviance , which can be interpreted as a Bayesian measure of fit , and D ( Θ ¯ ) is the Bayesian deviance evaluated at the posterior mean of the parameters Θ . Extending Eq ( 8 ) from Gautier and Vitalis [32] to our model gives ( dropping the index Ω for the sake of clarity ) : D ¯ = - 2 T ∑ t = 1 T [ ∑ i = 1 I ∑ j = 1 J log [ ( n i j y i j ) x i j ( t ) y i j ( 1 - x i j ( t ) ) n i j - y i j ] - ∑ j = 1 J log P ( λ j = 1 ∣ n j ( t ) , x r j ( t ) , τ ( t ) ) ] ( 13 ) and: D ( θ ¯ ) = - 2 [ ∑ i = 1 I ∑ j = 1 J log [ ( n i j y i j ) x ¯ i j y i j ( 1 - x ¯ i j ) n i j - y i j ] - ∑ j = 1 J log P ( λ j = 1 ∣ n j , x ¯ r j , τ ¯ ) ] ( 14 ) In Eq ( 13 ) , xij ( t ) is the tth sampled value of the parameter xij along the MCMC , out of T total draws . In Eq ( 14 ) , x ¯ i j = 1 T ∑ t = 1 T x i j ( t ) is the posterior mean of xij , and τ ¯ is the vector of the posterior means of the branch lengths . To evaluate the performance of our model to estimate the ESR from autosomal and X-linked data , we used a generation-by-generation coalescent based simulator [74] . In brief , the simulator is based on an algorithm in which coalescence and migration events are considered generation-by-generation until the common ancestor of the whole sample is reached ( see , e . g . , [75] ) . This simulator allows us to specify male and female effective population sizes , and sex-specific migration rates , for each branch in a population tree for any defined demography . The algorithm also accounts for the specificities of autosomal and X chromosomal patterns of inheritance . All loci are simulated strictly independently ( no pedigree is constructed during the simulations , and coalescent trees are therefore independent across loci ) . Each locus is constrained to be strictly bi-allelic ( i . e . , all coalescent trees with more than a single mutation are discarded ) . The mutation rate was set to μ = 1 . 5 × 10−7 with an ancestral ( root ) population made of 50 , 000 males and 50 , 000 females . In general , we simulated 5 , 000 autosomal markers and 5 , 000 bi-allelic X-linked markers . We sampled 50 diploid females from each population ( such that the number of sampled genes is 100 for both autosomal and X-linked markers ) . Typically , 50 independent datasets were simulated for each scenario . The analysis of SNP data is intricate due to the discovery protocols used to ascertain polymorphisms . Typically , SNPs are called using genotypes from a reduced sample of individuals , which is referred to as the discovery panel . Only then , the ascertained SNPs are genotyped in the full sample of interest . As a consequence , the data contain less low-frequency alleles than expected in the absence of ascertainment [76] . To analyze the consequences of SNP ascertainment bias on the inference of the ESR , we simulated SNP datasets mimicking different ascertainment schemes . For all schemes , we considered a population history with balanced topology ( ( 1 , 2 ) , ( 3 , 4 ) ) . We called SNPs using two “ghost” individuals ( out of 50 simulated diploid females ) in a panel of populations . These individuals were used exclusively for SNP calling and discarded from further analyses . Only those sites that were polymorphic in the discovery panel were therefore considered for the KimTree analyses , using allele counts from the remaining 48 individuals of each sample . We considered three schemes differing by the populations contributing to the panel . In the first scheme , all populations ( 1–4 ) were represented in the discovery panel . In the second scheme , only populations 1 and 3 ( that belong to both sides of the balanced tree ) were represented in the panel . In the third scheme , only populations 1 and 2 ( that belong to a single side of the balanced tree ) were represented in the panel . To evaluate the robustness of the model to LD , we simulated additional datasets using msprime [77] , because our generation-by-generation simulator is not designed to generate linked markers . Considering a population history with balanced topology ( ( 1 , 2 ) , ( 3 , 4 ) ) , we generated 100 haplotypes of 100 Mb ( 1 Morgan in our parameterization ) for each population and each genetic system . Assuming a balanced ESR , we considered Ne = 1 , 000 and τi = 0 . 1 in all branches for autosomal data , and Ne = 750 and τi = 0 . 133 for X-linked data . We also reduced the recombination rate for the X chromosome by a 2/3 factor , because of the absence of recombination in males . We then analyzed 50 replicated datasets consisting of 5 , 000 SNPs sampled from a single autosome and 5 , 000 SNPs sampled from a single X chromosome . To vary the extent of LD , we sampled SNPs from the whole chromosomes , or from the first 50 Mb , 20 Mb , or 10 Mb . To mimic more realistic datasets , we considered a “whole-genome” sampling scheme , where 5 , 000 autosomal SNPs were sampled from 20 distinct autosomes and 5 , 000 X-linked SNPs were sampled from a single X chromosome . As a matter of comparison , we also analyzed 50 datasets simulated with msprime , but assuming strictly independent SNPs .
The software package containing the C source code and a detailed documentation is freely available for download at http://www1 . montpellier . inra . fr/CBGP/software/kimtree/ . The code of our generation-by-generation coalescent based simulator , together with all input files that were used to generate the simulated datasets , are available from the Zenodo database [74] .
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The history of populations and their social organization is often intricate due to breeding structures , migration patterns or population bottlenecks . Estimation of the female proportion of the effective population ( sex ratio ) is therefore important to better understand this underlying social structure and dynamics . This question has been mainly investigated so far by comparing genetic variation of mitochondrial DNA and the Y chromosome , two uniparentally inherited markers that reflect the demographic history of females and males , respectively . To overcome the intrinsic limitations of these genetic markers , and to take advantage of the increasing amount of sequence data , we propose a new approach that uses large numbers of independent polymorphisms from autosomes and the X chromosome to estimate sex ratios , throughout the history of populations . This method allows us to confirm a strongly female-biased sex ratio in modern dairy and beef cattle breeds . Yet , we find a strongly male-biased sex ratio during domestication times , consistent with an easier taming and management of cows , and/or introgression from wild auroch males . Analyzing human data from a sample of non-African populations , we find a male bias in Oceanians , possibly indicating complex marriage patterns among Aboriginal Australian groups .
|
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"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods",
"Program",
"availability"
] |
[
"taxonomy",
"medicine",
"and",
"health",
"sciences",
"ruminants",
"vertebrates",
"animals",
"mammals",
"alleles",
"phylogenetics",
"data",
"management",
"x-linked",
"traits",
"phylogenetic",
"analysis",
"amniotes",
"molecular",
"genetics",
"population",
"biology",
"computer",
"and",
"information",
"sciences",
"sex",
"chromosomes",
"chromosome",
"biology",
"x",
"chromosomes",
"autosomes",
"evolutionary",
"systematics",
"molecular",
"biology",
"genetic",
"loci",
"clinical",
"genetics",
"population",
"metrics",
"eukaryota",
"cell",
"biology",
"heredity",
"sex",
"linkage",
"sex",
"ratio",
"genetics",
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"cattle",
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"biology",
"genetic",
"linkage",
"bovines",
"organisms",
"chromosomes"
] |
2018
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Inferring sex-specific demographic history from SNP data
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Protein contacts contain key information for the understanding of protein structure and function and thus , contact prediction from sequence is an important problem . Recently exciting progress has been made on this problem , but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction . This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling ( EC ) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks . The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network , EC information and pairwise potential . By using very deep residual networks , we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus , obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question . Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding . Tested on 105 CASP11 targets , 76 past CAMEO hard targets , and 398 membrane proteins , the average top L long-range prediction accuracy obtained by our method , one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0 . 47 , 0 . 21 and 0 . 30 , respectively; the average top L/10 long-range accuracy of our method , CCMpred and MetaPSICOV is 0 . 77 , 0 . 47 and 0 . 59 , respectively . Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds ( i . e . , TMscore>0 . 6 ) for 203 of the 579 test proteins , while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them , respectively . Our contact-assisted models also have much better quality than template-based models especially for membrane proteins . The 3D models built from our contact prediction have TMscore>0 . 5 for 208 of the 398 membrane proteins , while those from homology modeling have TMscore>0 . 5 for only 10 of them . Further , even if trained mostly by soluble proteins , our deep learning method works very well on membrane proteins . In the recent blind CAMEO benchmark , our fully-automated web server implementing this method successfully folded 6 targets with a new fold and only 0 . 3L-2 . 3L effective sequence homologs , including one β protein of 182 residues , one α+β protein of 125 residues , one α protein of 140 residues , one α protein of 217 residues , one α/β of 260 residues and one α protein of 462 residues . Our method also achieved the highest F1 score on free-modeling targets in the latest CASP ( Critical Assessment of Structure Prediction ) , although it was not fully implemented back then . http://raptorx . uchicago . edu/ContactMap/
De novo protein structure prediction from sequence alone is one of most challenging problems in computational biology . Recent progress has indicated that some correctly-predicted long-range contacts may allow accurate topology-level structure modeling [1] and that direct evolutionary coupling analysis ( DCA ) of multiple sequence alignment ( MSA ) may reveal some long-range native contacts for proteins and protein-protein interactions with a large number of sequence homologs [2 , 3] . Therefore , contact prediction and contact-assisted protein folding has recently gained much attention in the community . However , for many proteins especially those without many sequence homologs , the predicted contacts by the state-of-the-art predictors such as CCMpred [4] , PSICOV [5] , Evfold [6] , plmDCA[7] , Gremlin[8] , MetaPSICOV [9] and CoinDCA [10] are still of low quality and insufficient for accurate contact-assisted protein folding [11 , 12] . This motivates us to develop a better contact prediction method , especially for proteins without a large number of sequence homologs . In this paper we define that two residues form a contact if they are spatially proximal in the native structure , i . e . , the Euclidean distance of their Cβ atoms less than 8Å [13] . Existing contact prediction methods roughly belong to two categories: evolutionary coupling analysis ( ECA ) and supervised machine learning . ECA predicts contacts by identifying co-evolved residues in a protein , such as EVfold [6] , PSICOV [5] , CCMpred [4] , Gremlin [8] , plmDCA and others [14–16] . However , DCA usually needs a large number of sequence homologs to be effective [10 , 17] . Supervised machine learning predicts contacts from a variety of information , e . g . , SVMSEQ [18] , CMAPpro [13] , PconsC2 [17] , MetaPSICOV [9] , PhyCMAP [19] and CoinDCA-NN [10] . Meanwhile , PconsC2 uses a 5-layer supervised learning architecture [17]; CoinDCA-NN and MetaPSICOV employ a 2-layer neural network [9] . CMAPpro uses a neural network with more layers , but its performance saturates at about 10 layers . Some supervised methods such as MetaPSICOV and CoinDCA-NN outperform ECA on proteins without many sequence homologs , but their performance is still limited by their shallow architectures . To further improve supervised learning methods for contact prediction , we borrow ideas from very recent breakthrough in computer vision . In particular , we have greatly improved contact prediction by developing a brand-new deep learning model called residual neural network [20] for contact prediction . Deep learning is a powerful machine learning technique that has revolutionized image classification [21 , 22] and speech recognition [23] . In 2015 , ultra-deep residual neural networks [24] demonstrated superior performance in several computer vision challenges ( similar to CASP ) such as image classification and object recognition [25] . If we treat a protein contact map as an image , then protein contact prediction is kind of similar to ( but not exactly same as ) pixel-level image labeling , so some techniques effective for image labeling may also work for contact prediction . However , there are some important differences between image labeling and contact prediction . First , in computer vision community , image-level labeling ( i . e . , classification of a single image ) has been extensively studied , but there are much fewer studies on pixel-level image labeling ( i . e . , classification of an individual pixel ) . Second , in many image classification scenarios , image size is resized to a fixed value , but we cannot resize a contact map since we need to do prediction for every residue pair ( equivalent to an image pixel ) . Third , contact prediction has much more complex input features ( including both sequential and pairwise features ) than image labeling . Fourth , the ratio of contacts in a protein is very small ( <2% ) . That is , the number of positive and negative labels in contact prediction is extremely unbalanced . In this paper we present a very deep residual neural network for contact prediction . Such a network can capture very complex sequence-contact relationship and high-order contact correlation . We train this deep neural network using a subset of proteins with solved structures and then test it on public data including the CASP [26 , 27] and CAMEO [28] targets as well as many membrane proteins . Our experimental results show that our method yields much better accuracy than existing methods and also result in much more accurate contact-assisted folding . The deep learning method described here will also be useful for the prediction of protein-protein and protein-RNA interfacial contacts .
Fig 1 illustrates our deep neural network model for contact prediction [29] . Different from previous supervised learning approaches[9 , 13] for contact prediction that employ only a small number of hidden layers ( i . e . , a shallow architecture ) , our deep neural network employs dozens of hidden layers . By using a very deep architecture , our model can automatically learn the complex relationship between sequence information and contacts and also model the interdependency among contacts and thus , improve contact prediction [17] . Our model consists of two major modules , each being a residual neural network . The first module conducts a series of 1-dimensional ( 1D ) convolutional transformations of sequential features ( sequence profile , predicted secondary structure and solvent accessibility ) . The output of this 1D convolutional network is converted to a 2-dimensional ( 2D ) matrix by outer concatenation ( an operation similar to outer product ) and then fed into the 2nd module together with pairwise features ( i . e . , co-evolution information , pairwise contact and distance potential ) . The 2nd module is a 2D residual network that conducts a series of 2D convolutional transformations of its input . Finally , the output of the 2D convolutional network is fed into a logistic regression , which predicts the probability of any two residues form a contact . In addition , each convolutional layer is also preceded by a simple nonlinear transformation called rectified linear unit [30] . Mathematically , the output of 1D residual network is just a 2D matrix with dimension L×m where m is the number of new features ( or hidden neurons ) generated by the last convolutional layer of the network . Biologically , this 1D residual network learns the sequential context of a residue . By stacking multiple convolution layers , the network can learn information in a very large sequential context . The output of a 2D convolutional layer has dimension L×L×n where n is the number of new features ( or hidden neurons ) generated by this layer for one residue pair . The 2D residual network mainly learns contact occurrence patterns or high-order residue correlation ( i . e . , 2D context of a residue pair ) . The number of hidden neurons may vary at each layer . Our test data includes the 150 Pfam families described in [5] , 105 CASP11 test proteins [31] , 398 membrane proteins ( S1 Table ) and 76 CAMEO hard targets released from 10/17/2015 to 04/09/2016 ( S2 Table ) . The tested methods include PSICOV [5] , Evfold [6] , CCMpred [4] , plmDCA[7] , Gremlin[8] , and MetaPSICOV [9] . The former 5 methods employs pure DCA while MetaPSICOV [9] is a supervised learning method that performed the best in CASP11 [31] . All the programs are run with parameters set according to their respective papers . We cannot evaluate PconsC2 [17] since we failed to obtain any results from its web server . PconsC2 did not outperform MetaPSICOV in CASP11 [31] , so it may suffice to just compare our method with MetaPSICOV . We evaluate the accuracy of the top L/k ( k = 10 , 5 , 2 , 1 ) predicted contacts where L is protein sequence length [10] . We define that a contact is short- , medium- and long-range when the sequence distance of the two residues in a contact falls into [6 , 11] , [12 , 23] , and ≥24 , respectively . The prediction accuracy is defined as the percentage of native contacts among the top L/k predicted contacts . When there are no L/k native ( short- or medium-range ) contacts , we replace the denominator by L/k in calculating accuracy . This may make the short- and medium-range accuracy look small although it is easier to predict short- and medium-range contacts than long-range ones . As shown in Tables 1–4 , our method outperforms all tested DCA methods and MetaPSICOV by a very large margin on the 4 test sets regardless of how many top predicted contacts are evaluated and no matter whether the contacts are short- , medium- or long-range . These results also show that two supervised learning methods greatly outperform the pure DCA methods and that the three pseudo-likelihood DCA methods plmDCA , Gremlin and CCMpred perform similarly , but outperform PSICOV ( Gaussian model ) and Evfold ( maximum-entropy method ) . The advantage of our method is the smallest on the 150 Pfam families because many of them have a pretty large number of sequence homologs . In terms of top L long-range contact accuracy on the CASP11 set , our method exceeds CCMpred and MetaPSICOV by 0 . 32 and 0 . 20 , respectively . On the 76 CAMEO hard targets , our method exceeds CCMpred and MetaPSICOV by 0 . 27 and 0 . 17 , respectively . On the 398 membrane protein set , our method exceeds CCMpred and MetaPSICOV by 0 . 26 and 0 . 17 , respectively . Our method uses a subset of protein features used by MetaPSICOV , but performs much better than MetaPSICOV due to our deep architecture and that we predict contacts of a protein simultaneously . Since the Pfam set is relatively easy , we will not analyze it any more in the following sections . To examine the performance of our method with respect to the amount of homologous information available for a protein under prediction , we measure the effective number of sequence homologs in multiple sequence alignment ( MSA ) by Meff [19] , which can be roughly interpreted as the number of non-redundant sequence homologs when 70% sequence identity is used as cutoff to remove redundancy ( see Method for its formula ) . A protein with a smaller Meff has less homologous information . We divide all the test proteins into 10 bins according to ln ( Meff ) and then calculate the average accuracy of proteins in each bin . We merge the first 3 bins for the membrane protein set since they have a small number of proteins . Fig 2 shows that the top L/5 contact prediction accuracy increases with respect to Meff , i . e . , the number of effective sequence homologs , and that our method outperforms both MetaPSICOV and CCMpred regardless of Meff . Our long-range prediction accuracy is even better when ln ( Meff ) ≤7 ( equivalently Meff<1100 ) , i . e . , when the protein under prediction does not have a very large number of non-redundant sequence homologs . Our method has a large advantage over the other methods even when Meff is very big ( >8000 ) . This indicates that our method indeed benefits from some extra information such as inter-contact correlation or high-order residue correlation , which is orthogonal to pairwise co-evolution information . One of the important goals of contact prediction is to perform contact-assisted protein folding [11] . To test if our contact prediction can lead to better 3D structure modeling than the others , we build structure models for all the test proteins using the top predicted contacts as restraints of ab initio folding . For each test protein , we feed the top predicted contacts as restraints into the CNS suite [32] to generate 3D models . We measure the quality of a 3D model by a superposition-dependent score TMscore [33] , which ranges from 0 to 1 , with 0 indicating the worst and 1 the best , respectively . According to Xu and Zhang [34] , a model with TMscore>0 . 5 ( TMscore>0 . 6 ) is likely ( highly likely ) to have a correct fold . We also measure the quality of a 3D model by a superposition-independent score lDDT , which ranges from 0 to 100 , with 0 indicating the worst and 100 the best , respectively . Fig 3 shows that our predicted contacts can generate much better 3D models than CCMpred and MetaPSICOV . On average , our 3D models are better than MetaPSICOV and CCMpred by ~0 . 12 TMscore unit and ~0 . 15 unit , respectively . When the top 1 models are evaluated , the average TMscore obtained by CCMpred , MetaPSICOV , and our method is 0 . 333 , 0 . 377 , and 0 . 518 , respectively on the CASP dataset . The average lDDT of CCMpred , MetaPSICOV and our method is 31 . 7 , 34 . 1 and 41 . 8 , respectively . On the 76 CAMEO targets , the average TMsore of CCMpred , MetaPSICOV and our method is 0 . 256 , 0 . 305 and 0 . 407 , respectively . The average lDDT of CCMpred , MetaPSICOV and our method is 31 . 8 , 35 . 4 and 40 . 2 , respectively . On the membrane protein set , the average TMscore of CCMpred , MetaPSICOV and our method is 0 . 354 , 0 . 387 , and 0 . 493 , respectively . The average lDDT of CCMpred , MetaPSICOV and our method is 38 . 1 , 40 . 5 and 47 . 8 , respectively . Same trend is observed when the best of top 5 models are evaluated ( S1 Fig ) . On the CASP set , the average TMscore of the models generated by CCMpred , MetaPSICOV , and our method is 0 . 352 , 0 . 399 , and 0 . 543 , respectively . The average lDDT of CCMpred , MetaPSICOV and our method is 32 . 3 , 34 . 9 and 42 . 4 , respectively . On the 76 CAMEO proteins , the average TMscore of CCMpred , MetaPSICOV , and our method is 0 . 271 , 0 . 334 , and 0 . 431 , respectively . The average lDDT of CCMpred , MetaPSICOV and our method is 32 . 4 , 36 . 1 and 40 . 9 , respectively . On the membrane protein set , the average TMscore of CCMpred , MetaPSICOV , and our method is 0 . 385 , 0 . 417 , and 0 . 516 , respectively . The average lDDT of CCMpred , MetaPSICOV and our method is 38 . 9 , 41 . 2 and 48 . 5 , respectively . In particular , when the best of top 5 models are considered , our predicted contacts can result in correct folds ( i . e . , TMscore>0 . 6 ) for 203 of the 579 test proteins , while MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them , respectively . Our method also generates much better contact-assisted models for the test proteins without many non-redundant sequence homologs . When the 219 of 579 test proteins with Meff≤500 are evaluated , the average TMscore of the top 1 models generated by our predicted contacts for the CASP11 , CAMEO and membrane sets is 0 . 426 , 0 . 365 , and 0 . 397 , respectively . By contrast , the average TMscore of the top 1 models generated by CCMpred-predicted contacts for the CASP11 , CAMEO and membrane sets is 0 . 236 , 0 . 214 , and 0 . 241 , respectively . The average TMscore of the top 1 models generated by MetaPSICOV-predicted contacts for the CASP11 , CAMEO and membrane sets is 0 . 292 , 0 . 272 , and 0 . 274 , respectively . To compare the quality of our contact-assisted models and template-based models ( TBMs ) , we built TBMs for all the test proteins using our training proteins as candidate templates . To generate TBMs for a test protein , we first run HHblits ( with the UniProt20_2016 library ) to generate an HMM file for the test protein , then run HHsearch with this HMM file to search for the best templates among the 6767 training proteins , and finally run MODELLER to build a TBM from each of the top 5 templates . Fig 4 shows the head-to-head comparison between our top 1 contact-assisted models and the top 1 TBMs on these three test sets in terms of both TMscore and lDDT . The average lDDT of our top 1 contact-assisted models is 45 . 7 while that of top 1 TBMs is only 20 . 7 . When only the first models are evaluated , our contact-assisted models for the 76 CAMEO test proteins have an average TMscore 0 . 407 while the TBMs have an average TMscore 0 . 317 . On the 105 CASP11 test proteins , the average TMscore of our contact-assisted models is 0 . 518 while that of the TBMs is only 0 . 393 . On the 398 membrane proteins , the average TMscore of our contact-assisted models is 0 . 493 while that of the TBMs is only 0 . 149 . Same trend is observed when top 5 models are compared ( S2 Fig ) . The average lDDT of our top 5 contact-assisted models is 46 . 4 while that of top 5 TBMs is only 24 . 0 . On the 76 CAMEO test proteins , the average TMscore of our contact-assisted models is 0 . 431 while that of the TBMs is only 0 . 366 . On the 105 CASP11 test proteins , the average TMscore of our contact-assisted models is 0 . 543 while that of the TBMs is only 0 . 441 . On the 398 membrane proteins , the average TMscore of our contact-assisted models is 0 . 516 while that of the TBMs is only 0 . 187 . The low quality of TBMs further confirms that there is little redundancy between our training and test proteins ( especially membrane proteins ) . This also indicates that our deep model does not predict contacts by simply copying from training proteins . That is , our method can predict contacts for a protein with a new fold . Further , when the best of top 5 models are considered for all the methods , our contact-assisted models have TMscore>0 . 5 for 24 of the 76 CAMEO targets while TBMs have TMscore>0 . 5 for only 18 of them . Our contact-assisted models have TMscore >0 . 5 for 67 of the 105 CASP11 targets while TBMs have TMscore>0 . 5 for only 44 of them . Our contact-assisted models have TMscore>0 . 5 for 208 of the 398 membrane proteins while TBMs have TMscore >0 . 5 for only 10 of them . Our contact-assisted models for membrane proteins are much better than their TBMs because there is little similarity between the 6767 training proteins and the 398 test membrane proteins . When the 219 test proteins with ≤500 non-redundant sequence homologs are evaluated , the average TMscore of the TBMs is 0 . 254 while that of our contact-assisted models is 0 . 421 . Among these 219 proteins , our contact-assisted models have TMscore>0 . 5 for 72 of them while TBMs have TMscore>0 . 5 for only 17 of them . The above results imply that 1 ) when a query protein has no close templates , our contact-assisted modeling may work better than template-based modeling; 2 ) contact-assisted modeling shall be particularly useful for membrane proteins; and 3 ) our deep learning model does not predict contacts by simply copying contacts from the training proteins since our predicted contacts may result in much better 3D models than homology modeling . We have implemented our algorithm as a fully-automated contact prediction web server ( http://raptorx . uchicago . edu/ContactMap/ ) and in September 2016 started to blindly test it through the weekly live benchmark CAMEO ( http://www . cameo3d . org/ ) . CAMEO is operated by the Schwede group , with whom we have never collaborated . CAMEO can be interpreted as a fully-automated CASP , but has a smaller number ( ~30 ) of participating servers since many CASP-participating servers are not fully automated and thus , cannot handle the large number of test targets used by CAMEO . Nevertheless , the CAMEO participants include some well-known servers such as Robetta[35] , Phyre[36] , RaptorX[37] , Swiss-Model[38] and HHpred[39] . Meanwhile Robetta employs both ab initio folding and template-based modeling while the latter four employ mainly template-based modeling . Every weekend CAMEO sends test sequences to participating servers for prediction and then evaluates 3D models collected from servers . The test proteins used by CAMEO have no publicly available native structures until CAMEO finishes collecting models from participating servers . From 9/3/2016 to 10/31/2016 , CAMEO in total released 41 hard targets ( S3 Table ) . Although classified as hard by CAMEO , some of them may have distantly-related templates . Table 5 lists the contact prediction accuracy of our server in the blind CAMEO test as compared to the other methods . Again , our method outperforms the others by a very large margin no matter how many contacts are evaluated . The CAMEO evaluation of our contact-assisted 3D models is available at the CAMEO web site . You will need to register CAMEO in order to see all the detailed results of our contact server ( ID: server60 ) . Although our server currently build 3D models using only top predicted contacts without any force fields and fragment assembly procedures , our server predicts 3D models with TMscore>0 . 5 for 28 of the 41 targets and TMscore>0 . 6 for 16 of them . The average TMscore of the best of top 5 models built from the contacts predicted by our server , CCMpred and MetaPSICOV is 0 . 535 , 0 . 316 and 0 . 392 , respectively . See Fig 5 for the detailed comparison of the 3D models generated by our server , CCMpred and MetaPSICOV . Our server has also successfully folded 4 targets with a new fold plus one released in November 2016 ( 5flgB ) . See Table 6 for a summary of our prediction results of these targets and the below subsections for a detailed analysis . Among these targets , 5f5pH is particularly interesting since it has a sequence homolog in PDB but adopting a different conformation . That is , a template-based technique cannot obtain a good prediction for this target . Among these 41 hard targets , there are five multi-domain proteins: 5idoA , 5hmqF , 5b86B , 5b2gG and 5cylH . Table 7 shows that the average contact prediction accuracy of our method on these 5 multi-domain proteins is much better than the others . For multi-domain proteins , we use a superposition-independent score lDDT instead of TMscore to measure the quality of a 3D model . As shown in Table 8 , the 3D models built by our server from predicted contacts have much better lDDT score than those built from CCMpred and MetaPSICOV . On September 10 , 2016 , CAMEO released two hard test targets for structure prediction . Our contact server successfully folded the hardest one ( PDB ID: 2nc8 ) , a mainly β protein of 182 residues . Table 9 shows that our server produced a much better contact prediction than CCMpred and MetaPSICOV . CCMpred has very low accuracy since HHblits detected only ~250 non-redundant sequence homologs for this protein , i . e . , its Meff = 250 . Fig 6 shows the predicted contact maps and their overlap with the native . MetaPSICOV fails to predict many long-range contacts while CCMpred introduces too many false positives . The 3D model submitted by our contact server has TMscore 0 . 570 ( As of September 16 , 2016 , our server submits only one 3D model for each test protein ) and the best of our top 5 models has TMscore 0 . 612 and RMSD 6 . 5Å . Fig 7 shows that the beta strands of our predicted model ( red ) matches well with the native ( blue ) . To examine the superimposition of our model with its native structure from various angles , please see http://raptorx . uchicago . edu/DeepAlign/75097011/ . By contrast , the best of top 5 models built by CNS from CCMpred- and MetaPSICOV-predicted contacts have TMscore 0 . 206 and 0 . 307 , respectively , and RMSD 15 . 8Å and 14 . 2Å , respectively . The best TMscore obtained by the other CAMEO-participating servers is only 0 . 47 ( Fig 8 ) . Three top-notch servers HHpred , RaptorX and Robetta only submitted models with TMscore≤0 . 30 . According to Xu and Zhang [34] , a 3D model with TMscore<0 . 5 is unlikely to have a correct fold while a model with TMscore≥0 . 6 surely has a correct fold . That is , our contact server predicted a correct fold for this test protein while the others failed to . This test protein represents almost a novel fold . Our in-house structural homolog search tool DeepSearch[40] cannot identify structurally very similar proteins in PDB70 ( created right before September 10 , 2016 ) for this target . PDB70 is a set of representative structures in PDB , in which any two share less than 70% sequence identity . DeepSearch returned two weakly similar proteins 4kx7A and 4g2aA , which have TMscore 0 . 521 and 0 . 535 with the native structure of the target , respectively , and TMscore 0 . 465 and 0 . 466 with our best model , respectively . This is consistent with the fact that none of the template-based servers in CAMEO submitted a model with TMscore>0 . 5 . We cannot find structurally similar proteins in PDB70 for our best model either; the best TMscore between PDB70 and our best model is only 0 . 480 . That is , the models predicted by our method are not simply copied from the solved structures in PDB , and our method can indeed fold a relatively large β protein with a novel fold .
This paper has presented a new deep ( supervised ) learning method that can greatly improve protein contact prediction . Our method distinguishes itself from previous supervised learning methods in that we employ a concatenation of two deep residual neural networks to model sequence-contact relationship , one for modeling of sequential features ( i . e . , sequence profile , predicted secondary structure and solvent accessibility ) and the other for modeling of pairwise features ( e . g . , coevolution information ) . Ultra-deep residual network is the latest breakthrough in computer vision and has demonstrated the best performance in the computer vision challenge tasks ( similar to CASP ) in 2015 . Our method is unique in that we predict all contacts of a protein simultaneously , which allows us to easily model high-order residue correlation . By contrast , existing supervised learning methods predict if two residues form a contact or not independent of the other residue pairs . Our ( blind ) test results show that our method dramatically improves contact prediction , exceeding currently the best methods ( e . g . , CCMpred , Evfold , PSICOV and MetaPSICOV ) by a very large margin . Even without using any force fields and fragment assembly , ab initio folding using our predicted contacts as restraints can yield 3D structural models of correct fold for many more test proteins . Further , our experimental results also show that our contact-assisted models are much better than template-based models built from the training proteins of our deep model . We expect that our contact prediction methods can help reveal much more biological insights for those protein families without solved structures and close structural homologs . Our method outperforms ECA due to a couple of reasons . First , ECA predicts contacts using information only in a single protein family , while our method learns sequence-structure relationship from thousands of protein families . Second , ECA considers only pairwise residue correlation , while our deep network architecture can capture high-order residue correlation ( or contact occurrence patterns ) very well . Our method uses a subset of protein features used by MetaPSICOV , but outperforms MetaPSICOV mainly because we explicitly model contact patterns ( or high-order correlation ) , which is enabled by predicting contacts of a single protein simultaneously . MetaPSICOV employs a 2-stage approach . The 1st stage predicts if there is a contact between a pair of residues independent of the other residues . The 2nd stage considers the correlation between one residue pair and its neighboring pairs , but not in a very good way . In particular , the prediction errors in the 1st stage of MetaPSICOV cannot be corrected by the 2nd stage since two stages are trained separately . By contrast , we train all 2D convolution layers simultaneously ( each layer is equivalent to one stage ) so that later stages can correct prediction errors in early stages . In addition , a deep network can model much higher-order correlation and thus , capture information in a much larger context . Our deep model does not predict contact maps by simply recognizing them from PDB , as evidenced by our experimental settings and results . First , we employ a strict criterion to remove redundancy so that there are no training proteins with sequence identity >25% or BLAST E-value <0 . 1 with any test proteins . Second , our contact-assisted models also have better quality than homology models , so it is unlikely that our predicted contact maps are simply copied from the training proteins . Third , our deep model trained by only soluble proteins works very well on membrane proteins . By contrast , the homology models built from soluble proteins for the membrane proteins have very low quality . Their average TMscore is no more than 0 . 17 , which is the expected TMscore of any two randomly-chosen proteins . Finally , the blind CAMEO test indicates that our method successfully folded several targets with a new fold . Our contact prediction method also performed the best in CASP12 in terms of the F1 score calculated on top L/2 long- and medium-range contacts of 38 free-modeling targets , although back then ( May-July 2016 ) our method was not fully implemented . F1 score is a well-established and robust metric in evaluating the performance of a prediction method . Our method outperformed the 2nd best server iFold_1 by about 7 . 6% in terms of the total F1 score and the 3rd best server ( i . e . , an improved MetaPSICOV ) by about 10 . 0% . Our advantage is even bigger when only top L/5 long- and medium-range contacts are evaluated . iFold_1 also used a deep neural network while the new MetaPSICOV used a deeper and wider network and more input features than the old version . This CASP result further confirms that deep learning can indeed improve protein contact prediction . We have studied the impact of different input features . First of all , the co-evolution strength produced by CCMpred is very important . Without it , the top L/10 long-range prediction accuracy may drop by 0 . 15 for soluble proteins and more for membrane proteins . The larger performance degradation for membrane proteins is mainly because information learned from sequential features of soluble proteins is not very useful for membrane proteins . The depth of our deep model is as important as CCMpred , as evidenced by the fact that our deep method has much better accuracy than MetaPSICOV although we use a subset of protein features used by MetaPSICOV . Our test shows that a deep model with 9 and 30 layers have top L/10 accuracy ~0 . 1 and ~0 . 03 worse than a 60-layer model , respectively . This suggests that it is very important to model contact occurrence patterns ( i . e . , high-order residue correlation ) by a deep architecture . The pairwise contact potential and mutual information may impact the accuracy by 0 . 02–0 . 03 . The secondary structure and solvent accessibility may impact the accuracy by 0 . 01–0 . 02 . An interesting finding is that although our training set contains only ~100 membrane proteins , our model works well for membrane proteins , much better than CCMpred and MetaPSICOV . Even without using any membrane proteins in our training set , our deep models have almost the same accuracy on membrane proteins as those trained with membrane proteins . This implies that the sequence-structure relationship learned by our model from non-membrane proteins can generalize well to membrane protein contact prediction . This may be because that both soluble and membrane proteins share similar contact occurrence patterns in their contact maps and our deep method improves over previous methods by making a good use of contact occurrence patterns . We are going to study if we can further improve contact prediction accuracy of membrane proteins by including many more membrane proteins in the training set . We may further improve contact prediction accuracy by enlarging the training set . First , the latest PDB25 has more than 10 , 000 proteins , which can provide many more training proteins than what we are using now . Second , when removing redundancy between training and test proteins , we may relax the BLAST E-value cutoff to 0 . 001 or simply drop it . This will improve the top L/k ( k = 1 , 2 , 5 , 10 ) contact prediction accuracy by 1–3% and accordingly the quality of the resultant 3D models by 0 . 01–0 . 02 in terms of TMscore . We may also improve the 3D model quality by combining our predicted contacts with energy function and fragment assembly . For example , we may feed our predicted contacts to Rosetta to build 3D models . Compared to CNS , Rosetta makes use of energy function and more local structural restraints through fragment assembly and thus , shall result in much better 3D models . Finally , instead of predicting contacts , our deep learning model actually can predict inter-residue distance distribution ( i . e . , distance matrix ) , which provides finer-grained information than contact maps and thus , shall benefit 3D structure modeling more than predicted contacts . Our model achieves pretty good performance when using around 60–70 convolutional layers . A natural question to ask is can we further improve prediction accuracy by using many more convolutional layers ? In computer vision , it has been shown that a 1001-layer residual neural network can yield better accuracy for image-level classification than a 100-layer network ( but no result on pixel-level labeling is reported ) . Currently we cannot apply more than 100 layers to our model due to insufficient memory of a GPU card ( 12G ) . We plan to overcome the memory limitation by extending our training algorithm to run on multiple GPU cards . Then we will train a model with hundreds of layers to see if we can further improve prediction accuracy or not .
Our test data includes the 150 Pfam families [5] , 105 CASP11 test proteins , 76 hard CAMEO test proteins released in 2015 ( S1 Table ) and 398 membrane proteins ( S2 Table ) . All test membrane proteins have length no more than 400 residues and any two membrane proteins share less than 40% sequence identity . For the CASP test proteins , we use the official domain definitions , but we do not parse a CAMEO or membrane protein into domains . Our training set is a subset of PDB25 created in February 2015 , in which any two proteins share less than 25% sequence identity . We exclude a protein from the training set if it satisfies one of the following conditions: ( i ) sequence length smaller than 26 or larger than 700 , ( ii ) resolution worse than 2 . 5Å , ( iii ) has domains made up of multiple protein chains , ( iv ) no DSSP information , and ( v ) there is inconsistency between its PDB , DSSP and ASTRAL sequences [48] . To remove redundancy with the test sets , we exclude any training proteins sharing >25% sequence identity or having BLAST E-value <0 . 1 with any test proteins . In total there are 6767 proteins in our training set , from which we have trained 7 different models . For each model , we randomly sampled ~6000 proteins from the training set to train the model and used the remaining proteins to validate the model and determine the hyper-parameters ( i . e . , regularization factor ) . The final model is the average of these 7 models . We use similar but fewer protein features as MetaPSICOV . In particular , the input features include protein sequence profile ( i . e . , position-specific scoring matrix ) , predicted 3-state secondary structure and 3-state solvent accessibility , direct co-evolutionary information generated by CCMpred , mutual information and pairwise potential [45 , 46] . To derive these features , we need to generate MSA ( multiple sequence alignment ) . For a training protein , we run PSI-BLAST ( with E-value 0 . 001 and 3 iterations ) to search the NR ( non-redundant ) protein sequence database dated in October 2012 to find its sequence homologs , and then build its MSA and sequence profile and predict other features ( i . e . , secondary structure and solvent accessibility ) . Sequence profile is represented as a 2D matrix with dimension L×20 where L is the protein length . Predicted secondary structure is represented as a 2D matrix with dimension L××3 ( each entry is a predicted score or probability ) , so is the predicted solvent accessibility . Concatenating them together , we have a 2D matrix with dimension L×26 , which is the input of our 1D residual network . For a test protein , we generate four different MSAs by running HHblits [39] with 3 iterations and E-value set to 0 . 001 and 1 , respectively , to search through the uniprot20 HMM library released in November 2015 and February 2016 . From each individual MSA , we derive one sequence profile and employ our in-house tool RaptorX-Property [49] to predict the secondary structure and solvent accessibility accordingly . That is , for each test protein we generate 4 sets of input features and accordingly 4 different contact predictions . Then we average these 4 predictions to obtain the final contact prediction . This averaged contact prediction is about 1–2% better than that predicted from a single set of features . Although currently there are quite a few packages that can generate direct evolutionary coupling information , we only employ CCMpred to do so because it runs fast on GPU [4] . We compare our method with PSICOV [5] , Evfold [6] , CCMpred [4] , plmDCA , Gremlin , and MetaPSICOV [9] . The first 5 methods conduct pure DCA while MetaPSICOV employs supervised learning . MetaPSICOV [9] performed the best in CASP11 [31] . CCMpred , plmDCA , Gremlin perform similarly , but better than PSICOV and Evfold . All the programs are run with parameters set according to their respective papers . We evaluate the accuracy of the top L/k ( k = 10 , 5 , 2 , 1 ) predicted contacts where L is protein sequence length . The prediction accuracy is defined as the percentage of native contacts among the top L/k predicted contacts . We also divide contacts into three groups according to the sequence distance of two residues in a contact . That is , a contact is short- , medium- and long-range when its sequence distance falls into [6 , 11] , [12 , 23] , and ≥24 , respectively . Meff measures the amount of homologous information in an MSA ( multiple sequence alignment ) . It can be interpreted as the number of non-redundant sequence homologs in an MSA when 70% sequence identity is used as cutoff . To calculate Meff , we first calculate the sequence identity between any two proteins in the MSA . Let a binary variable Sij denote the similarity between two protein sequences i and j . Sij is equal to 1 if and only if the sequence identity between i and j is at least 70% . For a protein i , we calculate the sum of Sij over all the proteins ( including itself ) in the MSA and denote it as Si . Finally , we calculate Meff as the sum of 1/Si over all the protein sequences in this MSA . We use a similar approach as described in [11] to build the 3D models of a test protein by feeding predicted contacts and secondary structure to the Crystallography & NMR System ( CNS ) suite [32] . We predict secondary structure using our in-house tool RaptorX-Property [49] and then convert it to distance , angle and h-bond restraints using a script in the Confold package [11] . For each test protein , we choose top 2L predicted contacts ( L is sequence length ) no matter whether they are short- , medium- or long-range and then convert them to distance restraints . That is , a pair of residues predicted to form a contact is assumed to have distance between 3 . 5Å and 8 . 0 Å . In current implementation , we do not use any force fields to help with folding . We generate twenty 3D structure models using CNS and select top 5 models by the NOE score yielded by CNS[32] . The NOE score mainly reflects the degree of violation of the model against the input constraints ( i . e . , predicted secondary structure and contacts ) . The lower the NOE score , the more likely the model has a higher quality . When CCMpred- and MetaPSICOV-predicted contacts are used to build 3D models , we also use the secondary structure predicted by RaptorX-Property to warrant a fair comparison . To generate template-based models ( TBMs ) for a test protein , we first run HHblits ( with the UniProt20_2016 library ) to generate an HMM file for the test protein , then run HHsearch with this HMM file to search for the best templates among the 6767 training proteins of our deep learning model , and finally run MODELLER to build a TBM from each of the top 5 templates .
|
Protein contact prediction and contact-assisted folding has made good progress due to direct evolutionary coupling analysis ( DCA ) . However , DCA is effective on only some proteins with a very large number of sequence homologs . To further improve contact prediction , we borrow ideas from deep learning , which has recently revolutionized object recognition , speech recognition and the GO game . Our deep learning method can model complex sequence-structure relationship and high-order correlation ( i . e . , contact occurrence patterns ) and thus , improve contact prediction accuracy greatly . Our test results show that our method greatly outperforms the state-of-the-art methods regardless how many sequence homologs are available for a protein in question . Ab initio folding guided by our predicted contacts may fold many more test proteins than the other contact predictors . Our contact-assisted 3D models also have much better quality than homology models built from the training proteins , especially for membrane proteins . One interesting finding is that even trained mostly with soluble proteins , our method performs very well on membrane proteins . Recent blind CAMEO test confirms that our method can fold large proteins with a new fold and only a small number of sequence homologs .
|
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"Abstract",
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"Results",
"Conclusion",
"and",
"Discussion",
"Method"
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2017
|
Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
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A possible role for Toxoplasma gondii in the etiopathogenesis of schizophrenia is supported by epidemiological studies and animal models of infection . However , recent studies attempting to link Toxoplasma to schizophrenia have yielded mixed results . We performed a nested case-control study measured serological evidence of exposure to Toxoplasma gondii in a cohort of 2052 individuals . Within this cohort , a total of 1481 individuals had a psychiatric disorder and 571 of were controls without a psychiatric disorder . We found an increased odds of Toxoplasma exposure in individuals with a recent onset of psychosis ( OR 2 . 44 , 95% Confidence Interval 1 . 4–4 . 4 , p < . 003 ) . On the other hand , an increased odds of Toxoplasma exposure was not found in individuals with schizophrenia or other psychiatric disorder who did not have a recent onset of psychosis . By identifying the timing of evaluation as a variable , these findings resolve discrepancies in previous studies and suggest a temporal relationship between Toxoplasma exposure and disease onset .
Toxoplasma gondii is an apicomplexan protozoan with a worldwide distribution . Felines serve as definitive hosts for Toxoplasma and can support the complete life cycle of the organism including sexual reproduction and the shedding of oocysts in the feces . Most other species of warm-blooded animals support the replication of portions of the Toxoplasma life cycle including asexual reproduction and the development of tissue cysts in multiple organs including the brain . Humans can become infected with Toxoplasma through the ingestion of oocysts shed from cats into the environment or by the consumption of tissue cysts in the meat of infected food animals such as pigs , sheep , and cows . Human fetuses can also become infected through vertical transmission from the mothers , although this mode of transmission is relatively rare compared to the other modes of transmission . As in the case of other intermediate hosts , initial exposure to Toxoplasma in humans can lead to the formation of tissue cysts in multiple organs including the brain . Exposure also leads to a vigorous immune response evident from the presence of specific antibodies directed at Toxoplasma proteins . Previously , tissue cysts were not thought to cause symptoms in immune competent hosts . However recently studies have documented that tissue cysts are engaged in active metabolism and interaction with the host [1] . Accordingly , serological studies indicate that exposure to Toxoplasma can be associated with eye disease [2] as well as an increased risk of a range of neuropsychiatric diseases including schizophrenia[3 , 4] , bipolar disorder[5] , suicidal behavior[6] , anxiety disorder [7] and cognitive decline in the elderly [8] in some populations . The factors which determine why some Toxoplasma exposed individuals develop medical or psychiatric disorders while others are unaffected have not been determined but may related to the strain of Toxoplasma , host factors , or the timing of infection . Schizophrenia is the psychiatric condition that has been most extensively studied in terms of association with Toxoplasma gondii . An association between Toxoplasma and schizophrenia was first made in 1953 [9] and has been the subject of numerous studies . A recent meta-analyses consisting of 38 studies reported pooled odds ratios of 2 . 71 ( 95% confidence interval 1 . 93–3 . 78 ) relating Toxoplasma exposure to prevalence of schizophrenia . Many of the studies included in the meta-analysis involved individual living in areas with a high prevalence of Toxoplasma exposure ( >20% of the adult population ) and who were recently hospitalized . [10] However recently a number of studies have also been reported which did not find a significant association between serological evidence of Toxoplasma and risk of schizophrenia [11–13] . A meta-analysis reporting a lower corrected odds ratio has also been recently published [14] . These studies generally involved individuals living in environments with low prevalence of Toxoplasma who had long-standing schizophrenia and were receiving antipsychotic medications . The latter point is of interest since some of the more recently available antipsychotic medications have the ability to inhibit the replication of Toxoplasma organisms . [15 , 16] We postulated that , in areas of low Toxoplasma prevalence , individuals with the recent onset of the symptoms of schizophrenia would be more likely to have evidence of exposure to Toxoplasma than individuals with established schizophrenia who are receiving antipsychotic therapy .
The study population consisted or 2052 individuals with recent onset psychosis , schizophrenia , bipolar disorder , major depressive disorder , or non-psychiatric controls who were enrolled during the period January 1999 through May 2017 in the Stanley Research Program at Sheppard Pratt , Baltimore , Maryland , USA . This cohort , which is ongoing , has been recruited for the study of the association between infection , immunity , and psychiatric disorders . Detailed descriptions of the methods employed for the recruitment and analysis of the cohort have been as previously described [17–19] . The studies were approved by the Institutional Review Boards of the Sheppard Pratt Health System and the Johns Hopkins Medical Institutions following established guidelines . All participants provided written informed consent after the study procedures were explained . The inclusion criterion for recent onset psychosis was the onset of psychotic symptoms for the first time within the past 24 months defined as the presence of a positive psychotic symptom of at least moderate severity that lasted through the day for several days or occurred several times a week and was not limited to a few brief moments and which was not substance-induced . Participants meeting the criteria for a recent onset of psychosis could have a DSM-IV diagnosis[20] from among the following: schizophrenia; schizoaffective disorder; schizophreniform disorder; psychotic disorder not otherwise specified; brief psychotic disorder; delusional disorder; bipolar I disorder , most recent episode depressed; bipolar I disorder most recent episode manic; bipolar I disorder , most recent episode mixed; single manic episode; bipolar II disorder; major depressive disorder , recurrent; major depressive disorder single episode . Individuals with recent onset psychosis were further divided into those with affective psychosis , defined as having a diagnosis of bipolar disorder or major depressive disorder , and those with non-affective psychosis , defined as having a diagnosis of a schizophrenia-spectrum disorder The inclusion criterion for individuals with schizophrenia was a diagnosis of schizophrenia , schizophreniform disorder , or schizoaffective disorder . The inclusion criterion for individuals with bipolar disorder included a diagnosis of bipolar I disorder , bipolar II disorder , or bipolar disorder not otherwise specified . Those with major depressive disorder had either a single episode or recurrent episodes . Participants who met the criteria for recent onset of psychosis and another diagnosis were assigned to the recent onset group . The psychiatric participants were recruited from inpatient and day hospital programs of Sheppard Pratt and from affiliated psychiatric rehabilitation programs . The diagnosis of each psychiatric participant was established by the research team including a board-certified psychiatrist and based on the Structured Clinical Interview for DSM-IV Axis 1 Disorders [20] and available medical records . The inclusion criterion for the non-psychiatric control individuals was the absence of a current or past psychiatric disorder as determined by screening with the DSM-IV Axis I Disorders , Non-patient Edition [20]The controls were recruited from the same geographic area as the psychiatric participants . Participants in all groups met the following additional criteria: age 18–65 ( except the control participants who were aged 20–60 ) ; proficient in English; absence of any history of intravenous substance abuse; absence of intellectual disability by history; absence of HIV infection; absence of serious medical disorder that would affect cognitive functioning; absence of a primary diagnosis of alcohol or substance use disorder per DSM-IV criteria . The occurrence of psychosis not of recent onset was not an exclusion criterion for individuals in the bipolar disorder or major depression diagnostic groups . All participants were individually administered a brief cognitive battery , the Repeatable Battery for the Assessment of Neuropsychological Status ( RBANS ) Form A at the study visit . This battery measures a range of domains and yields a scaled Total Score with a nominal population mean of 100 . [21] , Participants were asked about demographic variables including maternal education as a proxy for pre-morbid socioeconomic status and were asked about their current smoking status . All of the psychiatric participants were also interviewed and rated on the Brief Psychiatric Rating Scale ( BPRS ) . [22] Psychiatric participants were also categorized as to whether or not they had a history of substance abuse ( apart from nicotine or caffeine ) based on their response to interview questions about the use of alcohol and drugs and on the medical record . Medications received at the time of study enrollment for psychiatric participants were based on the medical chart and self-report . Other demographic and clinical data including illness duration at the time of study entry were obtained by self-report or review of the medical record . Each participant had a blood sample obtained , generally at study enrollment . For 1875 ( 91 . 4% ) if the study individuals the sample was obtained within 90 days of intial screening . Plasma was separated from the blood sample by centrifugation and stored at -70 until testing . At the time of testing , the sample was thawed and test for IgG class antibodies to Toxoplasma gondii using solid phase enzyme immunoassay as previously described . Assay reagents were obtained from IBL America , Minneapolis Minn . A standard sample with a known amount of antibody was also analyzed in each assay run . For each antibody measurement , a sample was considered to be reactive if it generated a signal which was at least 0 . 8 times the value generated by the standard as previously described[18] , corresponding to approximately 10 International Units ( IUs ) . Univariate analyses were performed by means of analysis of variance for continuous variables and Pearson’s chi square for categorical variables . The odds ratios associated with seropositivity and clinical diagnosis was calculated by the use of logistic regression models employing age , gender , race , maternal education ( as a marker of socioeconomic status ) , and place of birth ( United States or Canada vs other countries ) . These covariates were selected since they have been previously shown to be associated with the prevalence of antibodies to Toxoplasma and other infectious agents . Missing data were added by imputation . All analyses were performed by STATA Version 12 , College Station , Texas . This research was approved by the Institutional Review Boards of the Sheppard Pratt Health System and the Johns Hopkins School of Medicine . All participants were at least 18 years of age and provided written informed consent .
There were a total number of 2052 individuals in the study population . These included 221 individuals with the recent onset of psychosis , 752 individuals with established schizophrenia , 444 individuals with bipolar disorder without a recent onset of psychosis , 64 individuals with major depressive disorder without a recent onset of psychosis , and 571 control individuals without a psychiatric disorder . Of the 221 individuals with recent onset psychosis , 206 ( 93 . 2% ) were hospitalized at the time of study recruitment , either in the inpatient service or day hospital . Of the 752 individuals with schizophrenia without a recent onset of psychosis , 141 ( 18 . 8% ) were hospitalized at the time of recruitment , Of the 444 individuals with bipolar disorder without the recent onset of psychosis , 281 ( 63 . 3% ) were hospitalized at the time of recruitment . A total of 59 ( 92 . 2% ) of the 64 individuals with major depressive disorder without the recent onset of psychosis were hospitalized at the time of recruitment . The demographic and clinical characteristics of the population are depicted in Table 1 and Table 2 . As noted in Table 1 , the overall prevalence of Toxoplasma IgG antibodies in the study population was 9 . 6% . Unadjusted analysis of variance indicated a significant difference among the diagnostic groups ( chi2 = 11 . 8 , p < . 017 ) . This difference was further explored by means of logistic regression models employing age , gender , race , maternal education ( as a measure of socioeconomic status ) and birth outside of the United States or Canada . As depicted in Fig 1 , this analysis indicated that Toxoplasma exposure was associated with recent onset psychosis with an Odds Ratio of 2 . 44 ( 95% Confidence Interval 1 . 36–4 . 38 , p < . 003 ) . The odds of association with Toxoplasma exposure were similar in the subgroups of individuals with recent onset psychosis who had primarily non-affective ( 2 . 49 , 95% CI 1 . 19–5 . 22 , p < . 015 ) or affective psychosis ( 2 . 40 , 95% CI 1 . 15–4 . 00 , p < . 019 ) . Toxoplasma exposure was associated with somewhat increased odds of being in the established schizophrenia or bipolar groups but these odds did not differ significantly from the controls . In this model , the prevalence of Toxoplasma was also associated with increasing age ( p < . 001 ) and birth outside of the United States or Canada ( p < . 007 ) but not with gender , race , or maternal education . Within the group of individuals with recent onset psychosis Toxoplasma exposure was associated with receiving the drug olanzapine ( chi2 = 6 . 7 , p < . 01 ) but was not associated with receipt of other medications , BPRS symptom score , RBANS cognitive score , cigarette smoking or a history of drug or alcohol abuse .
We found that individuals with recent onset psychosis had a significantly increased rate of exposure to Toxoplasma gondii as determined by antibody measurement . This increase was independent of demographic factors associated with Toxoplasma exposure such as age , place of birth and socioeconomic status . The odds ratio associated with Toxoplasma exposure in our population with recent onset psychosis was , 2 . 44 ( 95% Confidence Interval 1 . 36–4 . 38 ) . This odds ratio is similar to that reported in some recent meta-analyses examining the association between Toxoplasma and recent onset psychosis and schizophrenia [10 , 23] . It is of note that some of these meta-analyses included studies of individuals with both recent onset psychosis and established schizophrenia . However , in many cases the prior treatment status of the study individuals was not reported . On the other hand , the level of Toxoplasma exposure in our population of individuals with established schizophrenia or bipolar disorder , while somewhat elevated , did not differ significantly from that of the control population . It is of note that the individuals with these disorders were derived from the same geographic area and tested by the same methods as those employed for the analysis of individuals with recent onset psychosis , suggesting that these differences are not related to socio-demographic factors . The reasons for finding an increased rate of Toxoplasma exposure in individuals with recent onset psychosis but not established schizophrenia is not known with certainty but may be related to changes in antibody levels over time . It had previously been thought that Toxoplasma seropositivity was lifelong . However this concept has been called into question on the basis of longitudinal and population based analyses [24 , 25] leading to the suggestion that persistent exposure to Toxoplasma is required for the maintenance of antibody levels . It is thus possible that antibody levels in individuals with recent onset psychosis fall over time in the absence of re-exposure to the point that they are not different from those of controls when assessed many years following disease onset . Valproic acid and other medications used for the treatment of schizophrenia or bipolar disorder have been shown to have anti-Toxoplasma activity in cell culture[16] . This activity may contribute to the decline in Toxoplasma seropositivity over time . It is of note in this regard that this process may take several years since a previous study indicated that samples obtained within 1 year of diagnosis did not show significant changes in Toxoplasma antibody levels . [26] It is also of note that we found an association between Toxoplasma seropositivity within the group of individuals with recent onset psychosis and treatment with the second generation anti-psychotic medication Olanzapine . The reasons for this association are not known with certainty but may be related to a differential effect of this medication on Toxoplasma infection as compared to other anti-psychotic medications within the central nervous system [15 , 16] . Our finding that individuals with established schizophrenia or bipolar disorder did not have increased odds of having Toxoplasma exposure is consistent with several other studies performed in low prevalence populations where individuals were receiving medications for extended periods of time . Our findings thus serve to resolve some of the discrepancies in past studies based on differences in regard to the timing of illness onset and assessment for Toxoplasma exposure as well as the receipt of medications . Prospective longitudinal studies relating to the timing of exposure to Toxoplasma and the onset of psychiatric disorders are necessary to directly address the issue of the temporal relationship between Toxoplasma exposure and subsequent risk of psychiatric disorders . These studies should include measurements of additional class-specific and subclass specific measures of antibodies , such as measurements of IgM and IgA class antibodies and measurements of IgG subclasses , which were not available from all members of this study population . It is of note that the prevalence of Toxoplasma is decreasing in many areas of the world . In the case of our study population , the prevalence of exposure to Toxoplasma in the control population was 6 . 1% , a level consistent with recent studies of young adults living in the United States . [27] The reason for the decrease in prevalence of Toxoplasma exposure is not known with certainty but may be related to improved levels of food preparation and water purification . The effect of this decrease in Toxoplasma exposure on human diseases relating to Toxoplasma is unclear . On the one hand , the rate of these diseases may decrease due to a lower level of organisms in the environment . On the other hand , a lower level of exposure in childhood may result in a larger number of individuals who are susceptible to primary infection in later life , resulting in an increased incidence of adult onset disorders . The long-term effects of these epidemiological changes on the role of Toxoplasma on human health and human disease are thus worthy of close examination . Unlike Toxoplasma infection in immune deficient individuals which is associated with the rapid replication of the tachyzoite form of the organism , Toxoplasma infection in immune competent hosts is associated with slowly replicating tissue cysts which are relatively resistant to currently available anti-Toxoplasma medications [28] . Recently methods have been developed for the treatment of Toxoplasma tissue cysts within the brains of experimentally infected animals[29] . In addition , novel immunogenic modalities have been developed for the prevention of experimental Toxoplasma infection [30] . The finding of a definitive association between Toxoplasma exposure and human psychiatric disorder in immune competent individuals might provide the framework for the further development of these interventions and their application to the prevention and treatment of Toxoplasma associated brain disorders .
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The protozoan parasite Toxoplasma gondii has been previously associated with an increased risk of serious psychiatric disorders such as schizophrenia . However , this association has been found in some studies and not others . We examined whether the differences among previous studies might be explained by the timing of patient evaluation and testing . We found that individuals who were evaluated soon after the onset of psychosis had increased odds of exposure to Toxoplasma gondii as evidenced by the measurement of antibodies in their blood . However . we did not find an increased rate of exposure to Toxoplasma gondii in individuals who had a diagnosis of schizophrenia or bipolar disorder but who did not have recent onset psychosis . Our findings are consistent with Toxoplasma exposure occurring around the time of onset of psychiatric symptoms in individuals with schizophrenia . Our findings might lead to the evaluation of new methods for the early treatment of schizophrenia in some individuals .
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2017
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Evidence of increased exposure to Toxoplasma gondii in individuals with recent onset psychosis but not with established schizophrenia
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An overwhelming neutrophil-driven response causes both acute symptoms and the lasting sequelae that result from infection with Neisseria gonorrhoeae . Neutrophils undergo an aggressive opsonin-independent response to N . gonorrhoeae , driven by the innate decoy receptor CEACAM3 . CEACAM3 is exclusively expressed by human neutrophils , and drives a potent binding , phagocytic engulfment and oxidative killing of Opa-expressing bacteria . In this study , we sought to explore the contribution of neutrophils to the pathogenic inflammatory process that typifies gonorrhea . Genome-wide microarray and biochemical profiling of gonococcal-infected neutrophils revealed that CEACAM3 engagement triggers a Syk- , PKCδ- and Tak1-dependent signaling cascade that results in the activation of an NF-κB-dependent transcriptional response , with consequent production of pro-inflammatory cytokines . Using an in vivo model of N . gonorrhoeae infection , we show that human CEACAM-expressing neutrophils have heightened migration toward the site of the infection where they may be further activated upon Opa-dependent binding . Together , this study establishes that the role of CEACAM3 is not restricted to the direct opsonin-independent killing by neutrophils , since it also drives the vigorous inflammatory response that typifies gonorrhea . By carrying the potential to mobilize increasing numbers of neutrophils , CEACAM3 thereby represents the tipping point between protective and pathogenic outcomes of N . gonorrhoeae infection .
Neisseria gonorrhoeae , the causative agent of gonorrhea , is a re-emerging global health concern , with over a hundred million cases diagnosed each year , the recent emergence of multi-drug resistant strains that have led to its ‘superbug’ status , and a lack of success in vaccine development [1] , [2] , [3] . Symptomatic infection with N . gonorrhoeae results in acute inflammation of the urogenital tract and a purulent urethral discharge consisting almost exclusively of neutrophils . If left untreated , gonococcal infection can lead to serious chronic conditions , such as pelvic inflammatory disease and infertility , which stem from an overzealous response to the infection [2] . N . gonorrhoeae is a Gram-negative diplococcus that is highly adapted to colonization of the human urogenital tract . The initial interaction between the bacteria and epithelia is mediated by type IV pili , which retract to allow tight association with the mucosal epithelia [4] . More intimate interactions are then facilitated by adhesins including the neisserial Opa proteins binding to certain epithelial cell-expressed members of the carcinoembryonic antigen-related adhesion molecule ( CEACAM ) family: CEACAM1 , CEACAM5 , and CEACAM6 [5] , [6] , [7] , [8] , [9] . CEACAMs represent a subset of the Ig superfamily and consist of a variable number of Ig-like constant domains and an Ig variable domain-like N-terminus that allows Opa binding [10] , [11] , [12] . Attachment to apically expressed CEACAMs is sufficient to trigger bacterial engulfment and transcytosis across the epithelia to allow entry into the subepithelial space [13] , [14] . CEACAM1 is notable among the family in that , in addition to being on epithelial cells , it is also expressed on certain endothelial , lymphocytic and myeloid cells . Bacteria exploit its co-inhibitory function , which depends upon its cytoplasmic immunoreceptor tyrosine-based inhibitory motif ( ITIM ) , to suppress T cell [15] , [16] , [17] , B cell [18] , dendritic cell [19] and epithelial cell [20] responses ( reviewed in [21] ) . While binding to CEACAMs on most cell types tends to facilitate infection , Opa proteins may also bind to neutrophil-expressed CEACAM3 . When this occurs , CEACAM3 triggers an efficient opsonin-independent phagocytosis of the bacteria [22] , [23] , [24] . Ligation of CEACAM3 also promotes a Syk kinase- and phosphatidylinositol 3-kinase-dependent recruitment and downstream activation of the neutrophils' antimicrobial responses , including degranulation and oxidative burst [22] , [23] , [24] , [25] , [26] , [27] , [28] . These effects are driven by the cytoplasmic immunoreceptor tyrosine-based activation motif ( ITAM ) , which distinguishes CEACAM3 from the other CEACAMs that N . gonorrhoeae binds . Considering that CEACAM3 is human-restricted , expressed on neutrophils and lacks cell adhesion function , CEACAM3 is now generally considered to be an innate immune receptor allowing capture and elimination of bacteria that colonize epithelial tissues via other CEACAMs [23] , [24] , [29] , [30] , [31] . Neutrophils are specialized for rapid transmigration to sites of infection in response to a variety of stimuli , including chemotactic gradients and presence of bacterial components . Following recruitment to the infected tissue , neutrophils effectively phagocytose opsonized bacteria , activate production of reactive oxygen species [32] and release toxic antimicrobial peptides and proteins from cytoplasmic granules [33] , [34] . Conventionally , neutrophils were thought to have little to no controlled expression of new gene products , depending mostly on constitutively-expressed proteins and pre-loaded granules assembled during maturation . In recent years , it has become evident that properly stimulated neutrophils respond by synthesizing new proteins [35] , [36] , [37] , however surprisingly little is known about the control of gene expression . In this work , we show that heterologous expression of human CEACAMs in transgenic mouse neutrophils permits effective opsonin-independent neisserial binding and neutrophil activation in a manner reflecting that seen with human neutrophils . Moreover , we reveal that Opa-dependent CEACAM3 binding drives a potent neutrophil transcriptional response that elicits production of pro-inflammatory cytokines via a PKCδ and Tak1 serine/threonine kinase-dependent pathway triggered downstream of Syk tyrosine kinase . Furthermore , we observed that infection of human CEACAM-expressing transgenic mice with N . gonorrhoeae results in a dramatically higher neutrophil influx to the infection site when compared to wild-type mice . Together , this study establishes that bacterial binding to CEACAM3 effectively recruits more neutrophils to the infected tissues . While providing an effective strategy to combat the initial infection , this self-propagating cycle of events can also lead to the pathogenic inflammatory response that typifies symptomatic gonorrhea .
Neisserial infection is exquisitely human-specific , with major receptors for the bacterial Opa protein adhesins being certain members of the human CEACAM family . While CEACAM homologues can be found in all vertebrates [38] , only human CEACAMs have been observed to bind Neisseria . Mouse polymorphonuclear leukocytes ( PMNs ) , which express mouse CEACAM1 on their surface , do not bind N . gonorrhoeae [24] , [39] , whereas human PMNs specifically bind Opa-expressing but not Opa-deficient N . gonorrhoeae in an opsonin-independent fashion ( Figure 1A , C ) . We have recently established that recombinant human CEACAMs encoded from constitutively expressed cDNA were functionally expressed in a mouse promyelocytic ( MPRO ) cell line [24] . We considered whether ectopic expression of intact human CEACAM genes in transgenic mouse neutrophils would also confer responsiveness to N . gonorrhoeae . To address this question , we performed experiments with bone marrow-derived neutrophils from human CEACAM-expressing CEABAC2 mice [40] . These mice were engineered using a BAC that encodes human CEACAM3 , CEACAM5 , CEACAM6 and CEACAM7 , none of which have murine homologues . Using flow cytometric analysis and immunoblotting with CEACAM-specific antibodies , we confirmed that human CEACAM3 and CEACAM6 were expressed on the surface of CEABAC neutrophils , in a manner reflecting their expression on human neutrophils ( Figure 1A , B ) . When we exposed CEABAC neutrophils to N . gonorrhoeae expressing either the CEACAM-specific Opa+ or no Opa protein ( Opa− ) , they effectively bound and engulfed the Opa+ but not Opa− bacteria , whereas no such association was apparent with wild type neutrophils regardless of Opa expression ( Figure 1C , D ) . While the number of Opa-expressing bacteria captured by human CEACAM-expressing neutrophils was substantially ( ∼10-fold ) greater than what occurs with WT mouse neutrophils and/or Opa− bacteria ( Figure 1D ) , the bacteria that become engulfed are effectively killed regardless of whether or not human CEACAMs are involved in the uptake ( Figure 1E ) . These results differ from a recent study with human neutrophils which describe increased killing of Opa+ ( relative to Opa− ) bacteria [41] , however it remains unclear whether this is a neutrophil species-dependent effect or result from differences in bacterial strain or methodology used in the two studies . Previous work addressing individual CEACAM expression and its effect on neisserial infection was undertaken using transfected promyelocytic cell lines [24] . Because CEABAC transgenic neutrophils can bind and engulf N . gonorrhoeae ( Figure 1C ) , we wondered whether neutrophil-specific responses to N . gonorrhoeae were also reproduced in these cells . Human neutrophils respond to Opa-expressing N . gonorrhoeae by triggering an increased consumption of oxygen , resulting in the production of free oxygen radicals in the cell ( the ‘oxidative burst’ ) , as well as by releasing granule components to the cell surface or into the newly formed phagosome ( ‘degranulation’ ) [25] . Consistent with this , we observed that Opa-expressing N . gonorrhoeae were able to efficiently stimulate both the oxidative burst and release of primary and secondary granules ( as determined by the release of neutrophil elastase and lactoferrin , respectively ) , in infected human neutrophils ( Figure 1F ) . In stark contrast , WT mouse neutrophils are surprisingly unresponsive to N . gonorrhoeae infection , illustrating the importance of human CEACAMs for these effects . However , in CEABAC neutrophils , we observed that the oxidative burst and degranulation were heightened in response to Opa-expressing bacteria ( Figure 1G ) , consistent with the function of Opa proteins in CEACAM binding . While neutrophils were classically considered to be transcriptionally quiet , Fc receptor-mediated phagocytosis has long been known to promote IL-8 mRNA expression in neutrophils [32] . More recently , it has become clear that neutrophils have the capacity to become transcriptionally active in response to certain stimuli [35] , [36] , [37] , yet neutrophil transcriptional responses to specific infections remain poorly understood . Consequently , to investigate whether N . gonorrhoeae might elicit a transcriptional response , we isolated RNA from uninfected and infected WT and CEABAC bone marrow-derived neutrophils and compared their transcriptional profile by full genome gene array 1 hour post-infection . DAVID functional annotation [42] and manual analysis of the results revealed that the general pattern of genes expressed in response to N . gonorrhoeae were similar in the WT and CEABAC animals , however , two categories of transcriptional up-regulation were apparent . In the first group are genes that are induced to a similar level in WT and CEABAC PMNs . Of these , the largest functional classes of genes are those involved in the regulation of inflammation ( i . e . IL-10 Receptor α Subunit ( il10ra ) ; Suppressor of Cytokine Signaling 3 ( SOCS3 ) ; Inhibitor of kappa B subunits ( IκBδ , IκBζ ) ) and control of cell cycle and apoptosis ( i . e . Bcl2 , Gadd34 , Gadd45 ) ( Figure 2A ) . In contrast , the CEABAC neutrophils displayed a marked up-regulation of acute inflammatory cytokine expression , including TNFα ( 2 . 1-fold induction over wild type neutrophils ) , IL-1α ( 2 . 7-fold induction ) and the neutrophil chemoattractant and activators Gro-α/KC , MIP-1α and MIP-1β ( 1 . 5- , 3 . 3- and 3 . 5-fold induction ) ( Figure 2B ) . It is pertinent to note that we detected no down-regulation of any gene expression at that time point . Considering that regulatory genes are expressed at similar levels between WT and CEABAC PMNs , while pro-inflammatory mediators are drastically higher in CEABAC cells , we infer that the cumulative effect of these changes in gene expression would be a heightened pro-inflammatory cytokine response when the gonococcal Opa proteins engage the neutrophil-expressed CEACAM3 . To validate gene array results , and confirm that increases in transcript levels corresponded to PMN secretion of the protein products , we measured the production of MIP-1α , MIP-2 , KC and TNF-α protein in infected PMNs from WT and CEABAC mice ( Figure 3A ) . Significant ( between 3- to-10 fold ) increases in chemokine protein levels were observed in supernatants from CEABAC PMNs infected with Opa+ bacteria , compared to supernatants from CEABAC PMNs infected with Opa− bacteria . Critically , the WT neutrophil response was not affected by Opa expression , instead reflecting that seen with Opa− bacteria and CEABAC PMNs , demonstrating that both Opa and human CEACAMs are required for this effect . This increased chemokine secretion corresponded with increased levels of chemokine transcripts in these samples ( Figure 3B ) , reflecting the data obtained via the gene array experiments , and establishing that de novo transcription is driving the cytokine response . Collectively , these data provide the first evidence of a neutrophil transcription-based inflammatory response to N . gonorrhoeae infection , and point to the CEACAM-Opa interaction as a critical driver of this inflammation . To confirm that the CEACAM- and Opa-dependent transcriptional response apparent in our transgenic mouse model reflected that occurring in human PMNs , peripheral blood neutrophils isolated from healthy volunteers were infected with Opa− or Opa+ N . gonorrhoeae and then subjected to quantitative RNA analysis . Opa+ N . gonorrhoeae-infected PMNs had substantially higher levels of MIP-1α , MIP-2 , TNF-α , and IL-1α transcript in all donors tested , when compared to Opa− infected controls ( Figure 3C ) . We therefore conclude that the CEACAM-Opa interaction potentiates the inflammation observed during human PMN infection , reflecting our findings with the CEACAM-humanized mouse model . Unlike WT PMNs , CEABAC neutrophils efficiently bind and phagocytose Opa-expressing N . gonorrhoeae ( Figure 1C–D ) . This prompted us to consider whether uptake alone can account for the cytokine response of human CEACAM-expressing PMNs . To address this question , WT and CEABAC PMNs were pre-treated with cytochalasin D to inhibit phagocytosis prior to infection . While cytochalasin D pre-treatment led to a marked decrease in bacterial internalization , ( Figure S1A ) , it had no effect on MIP-1α secretion ( Figure 4A ) . Furthermore , we used PMNs from a transgenic mouse line expressing human CEACAM1 but no CEACAM3 . While the human CEACAM1-expressing neutrophils can efficiently phagocytose Opa-expressing N . gonorrhoeae [43] , the neutrophils showed little chemokine response to infection ( Figure S1B ) . In considering that reactive oxygen species ( ROS ) have been linked to the activation of various inflammatory signals [44] , we also sought to confirm whether ROS formed during the well-characterized oxidative burst response to Opa-expressing N . gonorrhoeae [24] , [25] , [28] , [41] explained the induced cytokine response . To this end , we prevented ROS production using the NADPH oxidase inhibitor diphenylene iodonium ( DPI ) and then measured cytokine production in WT and CEABAC neutrophils infected with Opa− and Opa+ bacteria . While DPI completely abolished the otherwise high levels of ROS produced upon exposure of CEABAC PMNs to Opa+ N . gonorrhoeae ( Figure S1C ) , this had no affect the chemokine response of CEABAC PMNs ( Figure 4A ) . Taken together our data suggest that Opa protein-dependent engagement of CEACAM3 drives a cytokine response that is independent of its ability to promote bacterial phagocytosis and is not mediated by the ROS produced in response to infection . A large proportion of genes identified in our gene array study ( MIP-1α , MIP-2 , TNF-α , IL-1α ) are known to be activated by NF-κB . NF-κB transcription factors are major mediators of inflammation and have been shown to stimulate transcription of pro-inflammatory cytokines in response to LPS in PMNs [45] [46] [47] . NF-κB also governs transcriptional responses downstream of various ITAM receptors in other ( non-neutrophil ) cell types [48] , including the innate immune receptor Dectin-1 [49] . This led us to investigate NF-κB activation downstream of CEACAM3 . Consistent with NF-κB being a downstream effector of CEACAM3 , IκBα was degraded more rapidly and completely in CEACAM-expressing PMNs than in the WT cells ( Figure 4B ) . The p38 mitogen associated kinase ( MAPK ) has been shown to act along side NF-κB in the activation of PMN transcriptional responses to LPS [50] [46] . Consequently , we considered whether p38 might also be involved in the CEACAM-mediated transcriptional response . Infected CEABAC neutrophils exhibit increased levels of p38 phosphorylation when compared to WT ( Figure 4C ) , indicating that they are more effectively activated in response to N . gonorrhoeae infection . In contrast , the Erk1/2 MAPKs were not phosphorylated in a CEACAM-dependent manner ( Figure 4D ) , suggesting selective activation of p38 kinase upon CEACAM ligation . To assess whether p38 activity contributed to the CEACAM-dependent cytokine response , PMNs were exposed to a p38-specific inhibitor ( SB203580 ) prior to infection . This treatment effectively blocked production of MIP-1α and MIP-2 in CEABAC PMNs infected with Opa+ N . gonorrhoeae ( Figure 4E ) , while inhibition of Erk1/2 phosphorylation had no effect on cytokine secretion ( Figure S1D ) . Together , this data supports an essential role for p38 MAPK in the CEACAM-dependent transcriptional response . It has been reported that the mitogen-activated kinase kinase kinase ( MAPKKK ) family member TAK1 can activate both p38 MAPKs and NF-κB [51] . To test the involvement of TAK1 in the p38 activation observed during neisserial infection of PMNs , we used the TAK1 inhibitor ( 5z ) -7-oxozeanol . TAK1 inhibition effectively abrogated MIP-1α and MIP-2 secretion by the Opa+ N . gonorrhoeae-infected CEABAC neutrophils ( Figure 4F ) . Importantly , neither bacterial adherence nor phagocytosis by the PMNs were affected by either the p38 or TAK1 inhibitors ( Figure 5E , F ) , confirming that the effect of these two compounds on cytokine expression was not due to their inhibition of these cellular processes . CEABAC neutrophils express both human CEACAM3 and CEACAM6 . Both receptors facilitate bacterial uptake , yet previous work has shown that the activation of neutrophil bactericidal processes , including degranulation and oxidative burst , occur via CEACAM3 alone [24] , [25] . We sought to confirm whether the pro-inflammatory response observed in CEABAC neutrophils was solely mediated by CEACAM3 , and to determine whether the inflammation depended upon the CEACAM3 ITAM-dependent signaling . Since CEACAM3 , unlike the GPI-anchored CEACAM6 , relies on phosphorylation of its cytoplasmic ITAM by Src family kinases ( SFK ) for its activation , we exploited the SFK-specific inhibitor PP2 that has previously been shown to block CEACAM3 ITAM-dependent signaling [22] , [25] , [52] , [53] . Inhibition of SFK significantly abrogated cytokine production ( Figure 5A ) , but did not affect bacterial adherence or phagocytosis ( Figure 5E , F ) . Considered together , the data suggests that CEACAM3 ITAM phosphorylation is essential for induction of pro-inflammatory response . This also indicates a divergence in the bacterial engulfment and transcriptional pathways , since the tyrosine phosphorylation-independent CEACAM3- and CEACAM6-mediated engulfment of N . gonorrhoeae [24] is not , itself , sufficient to elicit the pro-inflammatory response . Work in other systems has shown that Syk kinase is an essential mediator of ITAM-mediated responses in general [54] and CEACAM3-specific neutrophil responses in particular [24] , though there is some suggestion that CEACAM3 can signal independent of Syk [55] . Therefore , we tested whether Syk contributed to CEACAM3-dependent inflammatory signaling using the specific inhibitor , piceatannol . Inhibiting Syk function led to a significant reduction in chemokine production by CEABAC neutrophils ( Figure 5B ) , implicating a critical role for this kinase in the CEACAM3-dependent pro-inflammatory cytokine responses . Recently , the serine/threonine kinase PKCδ was shown to link signaling from the ITAM-containing innate immune receptor Dectin-1 to NF-κB activation in dendritic cells [56] . Consequently , we assessed PKCδ activation during N . gonorrhoeae infection of WT and/or CEABAC PMNs . CEABAC neutrophils showed substantially increased phosphorylation of PKCδ relative to that seen in WT PMNs ( Figure 5C ) , suggesting it is also activated downstream of CEACAM3 . Furthermore , pretreatment of CEABAC PMNs with the PKC inhibitor bisindolylmaleimide II ( BIS II ) led to the inhibition of MIP-1α production in response to Opa+ N . gonorrhoeae ( Figure 5D ) , consistent with PKCδ actively contributing to the CEACAM3-driven inflammatory response . In summary , we have outlined a novel signaling cascade downstream of CEACAM3 that is distinct from CEACAM3-mediated bacterial engulfment and activation of antimicrobial responses ( Figure 5G ) , and potentially contributes to the excessive inflammatory response typical of N . gonorrhoeae infection . The heightened expression of pro-inflammatory cytokines by CEACAM-humanized PMNs should result in increased neutrophil chemotaxis to the site of N . gonorrhoeae infection , an outcome consistent with the clinical manifestations of gonorrhea . To test this , we collected supernatants from WT and CEABAC PMNs infected with Opa+ N . gonorrhoeae , and measured their ability to affect the speed and directionality of neutrophils using a Zigmond chamber . Consistent with the increased expression of chemotactic factors when CEABAC neutrophils are infected with N . gonorrhoeae , the chemotaxis of uninfected neutrophils was significantly greater in response to culture supernatants from the N . gonorrhoeae-infected CEABAC neutrophils , as compared to supernatants from infected WT neutrophils ( Figure 6A ) . To understand the implications of these effects during in vivo infection , we measured the relative contribution of neutrophil CEACAM3 on inflammation using a subcutaneous air-pouch model , which allows the effective recovery and analysis of leukocyte recruitment to an otherwise sterile site [57] . Opa expression did not affect leukocyte recruitment into air pouches formed in WT mice . However , in CEABAC mice , the Opa-expressing gonococci elicited a significantly increased infiltration of neutrophils relative to that seen in response to Opa− bacteria ( Figure 6B ) . Giemsa-Wright staining of the CEABAC-Opa+ air pouch infiltrate showed that nearly all of the cells ( >95% ) present are PMNs ( Figure 6C ) , with many neutrophils containing intracellular gonococci . Notably , the number of PMNs present in CEABAC mice infected with Opa− bacteria reflected that seen in the WT mice , indicating that both Opa and human CEACAMs are required to drive the more intense inflammatory response . Considering the marked increase in neutrophil response in the CEABAC animals , we considered whether it was possible that cells lining the air pouch could differentially associate with N . gonorrhoeae , which would contribute to the inflammatory milieu . To test this , we administered trypsin/EDTA into an uninfected air pouch from CEABAC mice , harvested the cells that were released , and then seeded them onto glass coverslips . The next day , cells were infected with Opa+ bacteria , and bacterial binding and CEACAM expression were assessed using immunofluorescence microscopy . Cells lining the pouch did not express CEACAM and did not bind or take up the N . gonorrhoeae ( Figure 6D , top ) . When the same experiment was conducted on air pouches infected with Opa+ N . gonorrhoeae , we observed a large number of PMNs had infiltrated the air pouch lining . As expected , these PMNs expressed high levels of the human CEACAMs , and effectively bound the bacteria , unlike the adjacent fibroblast lining ( Figure 6D , bottom ) . These results are consistent with the enhanced inflammation being due to differential association of the gonococci with the CEACAM3-expressing neutrophils , without obvious effect on their interaction with the surrounding tissues . The air pouch experiments suggest that the CEACAM-dependent association between N . gonorrhoeae and the resident neutrophils promotes subsequent neutrophil recruitment , presumably due to the establishment of a chemotactic gradient . Consistent with this , the pro-inflammatory chemokines MIP-1α , MIP-2 , KC , and IL-1β were all increased in the washes from Opa+-N . gonorrhoeae infected air pouches in CEABAC mice relative to that seen in the infected WT littermates ( Figure 6E ) . To address whether neutrophils directly contribute to the higher levels of cytokines observed , we infected mice that had been depleted of neutrophils by administration of the Gr1-specific RB6-8C5 antibody prior to the introduction of N . gonorrhoeae . The levels of MIP-1α and IL-1β were significantly lower in the air pouches from PMN-depleted mice , indicating that neutrophils are the primary source for both of these chemokines ( Figure 6E ) . Interestingly , the levels of KC and MIP-2 were dramatically higher in PMN-depleted mice , indicating that these chemokines are produced by cells other than PMNs under these conditions . While these chemokines are both produced by CEABAC neutrophils in response to N . gonorrhoeae ( Figure 3A , B ) , they can also be produced by a variety of tissues [33] , including synovial fibroblasts [58] . Considering that their levels increased upon neutrophil depletion , we interpret the increased response to suggest a delay in bacterial clearance in the absence of PMNs . The increased IL-1β and MIP-1α in CEABAC mice thereby reflect a local neutrophil response whereas MIP-2 and KC levels appear to be the cumulative effect of both neutrophil and underlying tissue responses . To link the CEACAM3-dependent intracellular response evident from our cell-based experiments with inflammation in vivo , we repeated the air pouch experiment , this time assessing the effect of the TAK1 inhibitor , which was administered to mice 1 h prior to infecting the air pouch . Consistent with our model that the inhibition of CEACAM3 signaling would suppress the inflammatory response to N . gonorrhoeae , we observed a decrease in the number of infiltrating PMNs upon administration of the TAK1-inhibitor relative to the untreated animals ( Figure 6F ) .
The picture of neutrophils as ever-ready weapons of defense aiming to achieve efficient pathogen clearance has become an axiom . While still true , recent evidence suggests that they have the ability to nuance their response through de novo gene expression in response to certain microbial cues . In addition to their classical role in direct microbial killing , neutrophils can produce a range of cytokines with the potential to affect inflammation through the activation and induced chemotaxis of various leukocytes [37] , [59] . However , their specific contribution to the cytokine milieu and inflammatory response remains underappreciated in vivo . The emerging picture of neutrophils as a dynamic , responsive cell population has important implications for our understanding of the overzealous neutrophil response that typifies gonorrhea . Our findings reveal that the decoy receptor CEACAM3 , in addition to facilitating the effective capture and killing of N . gonorrhoeae , also helps drive inflammation . While recruitment of more PMNs to combat infection would seem to be an effective innate immune strategy during early infection , the persistent exposure of CEACAM3-expressing PMNs to Opa-expressing gonococci can promote a self-perpetuating and , ultimately , pathogenic response such as is associated with gonorrhea or pelvic inflammatory disease . In this work , we demonstrate that human CEACAM-expressing transgenic mouse PMNs respond to N . gonorrhoeae in a manner that parallels those of human PMNs . Unlike neutrophils from WT mice , the CEABAC neutrophils undergo a vigorous oxidative burst and degranulation response to N . gonorrhoeae . Since the pathology associated with gonococcal disease primarily arises due to tissue damage caused by the recruited neutrophils , we considered whether CEACAM-dependent interactions with the bacteria could also contribute to the inflammatory response . We observed that N . gonorrhoeae binding to human CEACAM3 leads to the acute activation of a pro-inflammatory transcriptional program that results in the production of the inflammatory mediators such as MIP-1α , MIP-2 , KC and TNF-α . While relatively little is known about signal transduction in PMNs relative to other cell types , Opa binding to CEACAM3 elicits signaling via a pathway closely reminiscent of that triggered downstream of the innate anti-fungal receptor Dectin-1 [30] , [60] , [61] . As with Dectin-1 , SFK and Syk kinase represent the first effectors downstream of CEACAM3 , and their activity is required for the PMN oxidative burst and degranulation responses to Opa-expressing gonococci [24] . While Syk was shown to serve a regulatory role in the context of PMNs [62] , we have observed that Syk contributes to the inflammatory cytokine response to N . gonorrhoeae by eliciting the PKCδ and TAK1-dependent activation of NF-κB . This CEACAM3-dependent expression of MIP-1α , MIP-2 and KC stimulates chemotaxis of uninfected neutrophils so as to augment their recruitment to the infected tissues , an effect that has the potential to contribute to both innate defense and the massive neutrophil recruitment that typifies gonorrhea ( Figure 7 ) . The trade-off of having a direct link between CEACAM3 and inflammation is that , when uncontrolled , this response results in the ongoing infiltration of neutrophils , leading to permanent tissue damage such as is observed with N . gonorrhoeae-associated fallopian tube scarring and pelvic inflammatory disease . Supporting this model , we observed CEACAM-dependent increases in neutrophil recruitment into the gonococcal-infected tissues , brought on by the CEACAM3-dependent production of chemokines with the potential to promote continuous infiltration of neutrophils . Thus , CEACAM3 activation serves as a double-edged sword , promoting the immunopathology of gonorrhea through an over-activated immune response that is meant to clear the bacteria causing the infection . While the complete ablation of neutrophil recruitment would increase the bacterial burden , a better outcome would be to limit the chemokine response without blocking bacterial binding and phagocytosis ( Figure 7 ) . As a proof of concept for this , we used a TAK1 inhibitor in vivo to block the pro-inflammatory response and , thereby , the influx of neutrophils without affecting their phagocytic capacity . Satisfyingly , this treatment decreased PMN recruitment to that seen in WT mice , effectively eliminating the CEACAM3-dependent inflammation in response to N . gonorrhoeae . It has been reported previously that the majority of neisserial isolates from infected patients have the capacity to bind to CEACAMs [5] . This may seem contradictory when considering the negative outcome for bacteria that bind to CEACAM3 on neutrophils . However , it is important to consider that , in contrast to CEACAM3 , neisserial binding to other human CEACAMs facilitates attachment to mucosal epithelia [14] , [63] , [64] , [65] and suppression of both innate [20] and adaptive [15] , [16] , [17] immune responses , activities which are central to the establishment and persistence of infection . In this respect , it is curious to contrast CEACAM1 , which is the evolutionary precursor of the CEA family , with the evolutionarily ‘new’ CEACAM3 . While CEACAM1 is present in all vertebrates and is broadly expressed on many cell types , CEACAM3 can only be found in humans and is only expressed by neutrophils . When this is considered along with the fact that CEACAM3 possesses no cell adhesion function yet has a sufficiently conserved extracellular domain that can be engaged by the neisserial Opa proteins , we and others have suggested that CEACAM3 functions as a decoy receptor that allows the capture and killing of CEACAM-targeting microbes . The apparent involvement of CEACAM3 in pro-inflammatory signaling establishes a role for neutrophils beyond basic microbial killing , and places CEACAM3 as both a potential contributor to the accelerated response to N . gonorrhoeae infection and , subsequently , to the immunopathology associated with the gonococcal disease . The evolutionary advent of CEACAM3 thus reflects the latest step in the ongoing dance between Neisseria and their only natural host , providing a snare that mobilizes our most potently bactericidal cells against this stealthy invader .
All animal experiment procedures were approved by the Animal Ethics Review Committee of the University of Toronto ( Approval #20010054 and #20010055 ) , which is subject to the ethical and legal requirements under the province of Ontario's Animals for Research Act and the federal Council on Animal Care . Generation of the CEACAM1-humanized mouse line was previously described [43] . CEABAC2 mice , generated by stable integration of a human-derived bacterial artificial chromosome ( BAC ) encoding the human CEACAM3 , CEACAM5 , CEACAM6 and CEACAM7 genes , have been previously described [40] . Wild type ( WT ) mice used are littermates of the CEABAC2 animals . All reagents were from Sigma ( Oakville , Ontario , Canada ) unless otherwise indicated . The anti-gonococcal polyclonal rabbit antibody ( UTR01 ) was described previously [18] . Rabbit anti- CEACAM polyclonal and normal serum was from Dako ( Mississauga , ON ) . CEACAM pan-specific D14HD11 , CEACAM1-specific 4/3/17 and CEACAM6-specific 9A6 antibodies were from Genovac ( Freiburg , Germany ) , and the CEACAM3-specific Col-1 antibody was from Zymed ( San Francisco , CA ) . Phospho-p38 , p38 , phospho-Erk1/2 , Erk1/2 , phospho-PKCδ and PKCδ-specific antibodies were form Cell Signaling Technology . The IκBα-specific antibody was from Santa Cruz Biotechnology ( Santa Cruz , CA ) . Fluorescent conjugates were from Jackson ImmunoResearch Laboratories ( Mississauga , ON ) , except Texas red-phalloidin , which was from Molecular Probes ( Eugene , OR ) . The Tak1 inhibitor ( ( 5z ) -7-oxozeaenol ) was from Millipore ( Billerica , MA ) , and the p38 inhibitor ( SB203580 ) and the Src family kinase-specific PP2 were from Calbiochem ( La Jolla , CA ) . Erk1/2 inhibitor ( UT0126 ) was purchased from Cell Signaling . The isogenic Opa− and Opa+ ( Opa57 ) N . gonorrhoeae MS11 strains ( N302 and N313 , respectively; [66] ) were kindly provided by Dr . T . F . Meyer , and their phenotypes have been described previously [7] . Human neutrophils were isolated from citrated whole blood taken from healthy volunteers by venipuncture using Ficoll-Paque Plus ( Amersham Biosciences; Buckinghamshire , England ) . Contaminating erythrocytes were removed by dextran sedimentation and hypotonic shock , as described previously [29] . Mouse bone marrow neutrophils were taken from 8 to 10-week old mice that were humanely euthanized by CO2 inhalation . Femurs and tibias were removed , and bone marrow was isolated and separated on a discontinuous Percoll gradient ( 80%/65%/55% ) as described previously by others [67] . Neutrophils were recovered at the 80%/65% interface . WT and CEABAC neutrophils ( 106 cells ) were lysed in boiling SDS buffer and CEACAMs detected using SDS-PAGE and immunoblots probed with indicated CEACAM-specific antibodies . For flow cytometry analysis of cell-surface CEACAM expression , 106 PMNs from CEABAC or WT littermates were spun down and fixed in 1% PFA in Hank's Buffered Saline Solution ( HBSS ) prior to immunofluorescence staining . 106 neutrophils per sample were infected with N . gonorrhoeae at multiplicity of infection [45] of 10 in 250 µl of HBSS . Infections were stopped by centrifugation at 2400 g for 3 min at 4°C , lysed in boiling SDS sample buffer , and boiled for a further 10 min . Samples were resolved by SDS-PAGE and immunoblotted . 5×105 WT or CEABAC bone marrow-derived PMNs were centrifuged onto washed mouse serum-coated coverslips at 1500 rpm for 10 min . Cells were infected at MOI of 25 ( for binding and internalization studies ) in a volume of 500 µl , re-centrifuged for 5 minutes at 500 rpm to facilitate bacterial association with cells , and then incubated at 37°C for indicated durations . Post-infection , samples were washed with HBSS , and fixed using 3 . 7% paraformaldehyde . Cells were stained for CEACAM , actin and bacteria and observed as described previously [6] . Intracellular bacteria were differentiated from extracellular via exclusion of antibody prior to membrane solubilization , as described [29] . Killing assays were adapted from Ball et al . [41] . Briefly , adherent WT and CEABAC neutrophils were infected at an MOI = 1 . At indicated time points , cells were washed and incubated with protease inhibitors for 15 minutes prior to lysis with 1% saponin and plated on GC agar . Bacterial survival was evaluated relative to CFUs present at 0 time point . For chemiluminescence-based oxidative burst assay , 5×105 cells were incubated with 25 µg/ml 5-amino-2 , 3-dihydro-1 , 4-phthalazinedione ( ‘luminol’; Sigma ) in a volume of 100 µl , and then treated with agonists in a total volume of 200 µl , in triplicate . Infections proceeded for 60 min at 37°C , after which luminescence was read using a Tecan plate reader with i-control software . For flow cytometry-based degranulation assay ( CD11b release ) , 106 PMNs were treated with agonists in 500 µl of HBSS for 30 minutes at 37°C . Infections were stopped by centrifugation at 2 , 400 g for 3 min at RT and cell pellets then fixed in 1% PFA before staining with 1 . 25 µg of PE-conjugated rat anti-mouse CD11b in a total volume of 50 µl . Myeloperoxidase ( MPO ) , elastase , and lactoferrin release assays were performed essentially as described by others . Briefly , 106 PMNs were exposed to agonists in a total volume of 500 µl and then incubated for 30 minutes at 37°C . Cells were then pelleted and supernatants collected . For MPO assays , 50 µl of supernatant was mixed with 150 µl SureBlue tetramethylbenzidine peroxidase substrate ( KPL; Gaithersberg , MD ) , and plates were read spectrophotometrically at 650 nm . For the elastase assay , 50 µl of supernatant was diluted 2-fold in PBS and incubated with 100 µl DQ elastin substrate conjugated to BODIPY FL ( from the EnzCheck Elastase kit; Molecular Probes ) , and then incubated for 24 hours at RT before reading fluorescence with 488 nm excitation and 515 nm emission . For both MPO and elastase assays , a percentage ( % ) release is shown , calculated as the amount of the protein in the supernatant divided by the total amount in 106 CHAPS-lysed cells . Lactoferrin release from PMN granules was assayed by ELISA as described by others [48] . To induce release of primary granule components into medium , cells were pre-treated with 5 µM cytochalasin B for 5 minutes at 37°C prior to agonist treatment . CEABAC and WT bone marrow neutrophils ( 107 cells ) were either infected with Opa+ N . gonorrhoeae ( MOI = 10 ) or left uninfected for 1 h . The infections were stopped by centrifugation at 2400 g for 5 min at 4°C . RNA was extracted and purified using the Qiagen RNeasy kit . Samples from 3 independent experiments were analyzed using an Illumina Mouse Whole Genome V2R2 array with 45 , 281 probes . The original data normalization and analysis were provided as a service by the Bioinformatics Department of the University Health Network ( UHN ) Microarray Centre , Toronto , ON . Data was analyzed using Genespring v11 . 0 . 1 . 66 genes showed ≥2 fold change ( FC ) in gene expression in infected PMNs relative to uninfected controls . Gene lists were analyzed using the database for annotation , visualization , and integrated discovery ( DAVID ) ( Huang da et al . , 2009 ) and manual examination . To compare WT vs . CEABAC neutrophil responses , we considered genes ≥1 . 5 FC in CEABAC over WT . 106 cells were infected with N . gonorrhoeae at MOI of 10 and incubated at 37°C for 3 h . Infections were then stopped by centrifugation at 2400 g for 5 min at 4°C , and supernatants were collected . Quantitative measurements of cytokines were performed using ELISA kits form R&D Systems ( MIP-1α , KC and MIP-2 ) and BD Biosciences ( TNF-α ) . For qRT-PCR , cells were infected as described above . At 3 h post infection , RNA was collected using Qiagen RNeasy kit and converted to cDNA using iScript RT Supermix ( Bio-Rad Laboratories ) . qPCR was carried out using SsoAdvanced SYBR Green Supermix ( Bio-Rad Laboratories ) . All transcript levels are shown as relative to those of GAPDH . Bone marrow neutrophils were isolated and suspended in HBSS with 1% gelatin ( Sigma , G7041 ) . A neutrophil suspension ( 1×106/mL ) was allowed to attach to bovine serum albumin ( BSA , Sigma A7906; 1 mg/ml ) -coated glass coverslips ( 22×40 mm , Fisher 12–543-A ) at 37°C for 10 minutes . The coverslip was inverted into a Zigmond chamber ( Neuroprobe , z02 ) and 100 µL HBSS media was added to the right chamber with 100 µL HBSS media mixed with supernatants derived from infected CEABAC or WT neutrophils added to the left chamber . Time-lapse video microscopy was used to examine neutrophil movements in Zigmond chambers . Images were captured at 20-second intervals with a Nikon Eclipse E1000 Microscope using the 40× objective . Cell-tracking software ( Retrac version 2 . 1 . 01 Freeware ) was used to characterize cellular chemotaxis from the captured images . Data comes from three independent experiments . CEABAC and WT littermate control mice ( 6–8 wk ) were anesthetized with isoflurane , and dorsal air pouches were raised by injecting 3 ml sterile air subcutaneously on days 0 and a further 2 ml on day 3 . On day 5 , the mice were anesthetized with isoflurane and injected with 1 ml PBS containing 2×106 cfu/ml of Opa− or Opa+ N . gonorrhoeae . Mice were sacrificed 6 h after the injection , and air pouches were then washed with 2 ml PBS . The cells present in the wash were counted with a hemocytometer and analyzed by Diff-Quick staining of the cytospins . The supernatants were analyzed by ELISA , as described above . In some cases , air pouch fibroblasts were obtained by instilling 0 . 05% trypsin containing 0 . 5 mM EDTA in DMEM ( 3 ml/pouch ) , as previously described [68] . These cells were seeded onto glass coverslips in a 24-well plate , cultured in DMEM-10% FBS with antibiotics overnight , and then infected with Opa+ N . gonorrhoeae the next day for 30 min . Cells were fixed and stained for immunofluorescence microscopy . Neutrophil depletion from mice was achieved by a single i . p . injection of 200 µl of sterile saline containing 250 µg of the Gr-1 specific monoclonal antibody RB6-8C5 at 24 h prior to infection . The RB6-8C5 hybridoma was generously provided by Professor Paul Allen , Department of Pathology and Immunology , Washington University School of Medicine , St . Louis .
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Gonorrhea is a sexually transmitted infection caused by the bacteria Neisseria gonorrhoeae . These bacteria have re-emerged as a public health priority due to its acquisition of resistance to multiple antibiotics , leading to fears of untreatable infection . The symptoms of gonorrhea include an intense inflammatory response that may lead to pus discharged from the infected genital tract and scarring of the reproductive tract caused by neutrophils recruited to the site of infection . Past studies have detailed molecular interactions that lead to neutrophil binding and engulfment of N . gonorrhoeae , yet it remains unclear why N . gonorrhoeae elicits such a pathogenic inflammatory response . In this study , we reveal that N . gonorrhoeae binding to the human innate decoy receptor , CEACAM3 , elicits a potent intracellular signaling cascade that leads to neutrophil expression of cytokines that actively recruit other neutrophils to the infected tissues . As they encounter the gonococci , the next wave of neutrophils becomes similarly activated , leading to the progressive expansion in phagocytic cell numbers until they overwhelm the infected tissues . While this process promotes a rapid response to a troubling pathogen early during infection , the unrestrained recruitment of neutrophils and their toxic antimicrobial arsenal also lead to the pathogenic consequences associated with gonorrhea .
|
[
"Abstract",
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"Results",
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"Materials",
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"Methods"
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[
"bacterial",
"diseases",
"infectious",
"diseases",
"gonorrhea",
"medicine",
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"health",
"sciences",
"sexually",
"transmitted",
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] |
2014
|
Global Analysis of Neutrophil Responses to Neisseria gonorrhoeae Reveals a Self-Propagating Inflammatory Program
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Chagas disease , caused by the protozoan parasite Trypanosoma cruzi , presents a variable clinical course , varying from asymptomatic to serious debilitating pathologies with cardiac , digestive or cardio-digestive impairment . Previous studies using two clonal T . cruzi populations , Col1 . 7G2 ( T . cruzi I ) and JG ( T . cruzi II ) demonstrated that there was a differential tissue distribution of these parasites during infection in BALB/c mice , with predominance of JG in the heart . To date little is known about the mechanisms that determine this tissue selection . Upon infection , host cells respond producing several factors , such as reactive oxygen species ( ROS ) , cytokines , among others . Herein and in agreement with previous data from the literature we show that JG presents a higher intracellular multiplication rate when compared to Col1 . 7G2 . We also showed that upon infection cardiomyocytes in culture may increase the production of oxidative species and its levels are higher in cultures infected with JG , which expresses lower levels of antioxidant enzymes . Interestingly , inhibition of oxidative stress severely interferes with the intracellular multiplication rate of JG . Additionally , upon H2O2-treatment increase in intracellular Ca2+ and oxidants were observed only in JG epimastigotes . Data presented herein suggests that JG and Col1 . 7G2 may sense extracellular oxidants in a distinct manner , which would then interfere differently with their intracellular development in cardiomyocytes .
Chagas disease , caused by the protozoan Trypanosoma cruzi , is an important health problem affecting about 6 to 7 million people worldwide [1] . Infection in man is defined by two distinct clinical phases . The acute phase , corresponding to the initial period of infection , is characterized by high parasitemia and tissue parasitism , followed by the chronic phase of the infection , which persists throughout the life of the host and is characterized by low tissue parasitism as well as parasitemia [2] . Chronic infection has a variable clinical course , ranging from asymptomatic cases ( indeterminate form ) , to severe clinical conditions with heart ( chagasic cardiomyopathy ) and / or digestive tract ( megacolon or megaesophagus ) maladies . In patients with cardiac and / or digestive disorders , symptoms may appear between 10 and 30 years after initial infection and are due to the persistence of parasites in specific tissues , such as cardiac and / or smooth muscle , with the development of an intense inflammatory process , deleterious to the organ ( reviewed by [3] ) . Chagas disease clinical variability is well known to depend not only on genetic factors of the parasite , whose population structure is quite variable , but also on genetic factors of the host [4–6] . Previous studies conducted by our group showed that distinct parasite populations are found in different organs of infected patients [7] , reinforcing data on the existence of a differential tissue tropism , probably related to the development of the diverse clinical forms [8–10] . Later , we studied this tissue tropism by performing mixed infections in BALB/c mice with two clonal populations of T . cruzi , Col1 . 7G2 ( T . cruzi I ) and JG ( T . cruzi II ) , and detection of parasites directly from infected tissues . A predominance of Col1 . 7G2 was found in the rectum , diaphragm , esophagus and blood while JG was predominant in the cardiac muscle [11] . Later , we showed that this tissue tropism could be influenced by the genetic background of the host , where mice with the same MHC haplotype presented the same selection profile of T . cruzi in different tissues [12 , 13] . In vitro studies using infection in cultures of cardiac explants or primary cardiomyocytes , with Col1 . 7G2 and JG , indicated that tissue selection occurs due to the direct interaction between parasite and host cell , without direct influence of the host immune system [13 , 14] . In these studies , a more accelerated and efficient intracellular development of JG with respect to clone Col1 . 7G2 was observed in explants and cultures of cardiomyocytes isolated from BALB/c , suggesting that not only invasion , but also and mainly intracellular multiplication is important to tissue selection . Additionally , it was shown that this behavior profile was dependent on the cell type studied [14] . These findings reinforce that not only the parasite , but also the host cell response to infection is involved in the differential tissue tropism of T . cruzi . However , the mechanisms that define this selection are still poorly understood . During cell infection , infective trypomastigotes adhere to the surface of the host cell , being internalized in parasitophorous vacuoles , formed by lysosomal membrane [15] . Trypomastigote later escape from the vacuole to the cytoplasm of the cell and turn into the amastigote replicative form , colonizing the host cell [16–18] . Thus , during cell infection parasite passes through different environments , which can directly or indirectly influence its behavior within the cell . Data from the literature show that infected cells are able to respond to infection by activating several genes , through the production of cytokines and reactive oxygen species ( ROS ) , which could interfere with parasite intracellular behavior [19–24] . Here we investigate how stress responses mediated by oxidants in cardiomyocyte may influence infection by T . cruzi clonal populations , JG and Col1 . 7G2 , interfering with their intracellular multiplication rates .
This study was carried out in strict accordance with the recommendations of the Guide for the Care and Use of Laboratory Animals of the Brazilian National Council of Animal Experimentation ( http://www . cobea . org . br/ ) and Federal Law 11 . 794 ( October 8 , 2008 ) . The institutional Committee for Animal Ethics of UFMG approved all the procedures used in this study . ( CEUA/UFMG–Licenses 45/2009 and 261/2016 ) Two clonal populations of Trypanosoma cruzi were used , Col1 . 7G2 and JG , belonging to T . cruzi lineages I and II , respectively . JG strain was originally isolated in 1995 by Professor Eliane Lages-Silva ( UFTM ) from a chronic patient with megaesophagus . Col . 1 . 7G2 is a clone from Colombian strain , which was originally isolated by Federici in 1969 from a chronic patient with cardiac disorders . Both T . cruzi populations were previously analyzed and characterized as monoclonal , through the analysis of the eight microsatellite loci according to previously described methodology [25] . Epimastigote forms of Col1 . 7G2 and JG were maintained in LIT ( Liver Infusion Tryptose ) medium containing 20 mg/mL of hemin and supplemented with 10% Fetal Bovine Serum and 1% Penicillin/Streptomycin , in T-25 cm3 bottles , in a 28°C incubator , and subcultured every two days [26] . Tissue culture trypomastigotes ( TCTs ) from Col1 . 7G2 and JG were obtained from the supernatant of infected LLC-MK2 monolayers and purified as described previously [27] . Primary cultures of cardiomyocytes were prepared from hearts of BALB/c mice neonates ( 0–2 days ) , according to protocol previously described [28] . 2x105 purified cardiomyocytes were plated in each well of a 24 well pate , containing a 13 mm circular glass coverslips , and maintained in a 37°C CO2 incubator for 72 hours prior to infection . Alternatively , 5x104 cells were plated in each well of a XF-24 cell culture microplate ( Seahorse Bioscience ) and maintained in a 37°C CO2 incubator for 120 hours prior to infection . Cultures of human cardiomyocytes ( Pluricardio ) were prepared from the differentiation of induced pluripotent stem cells ( iPSC ) obtained from Pluricell Biotechnologies . Cells were thawed and plated after counting by trypan blue exclusion method at a confluence of 2x105 cells per well in a 24-well plate . Cell differentiation was performed according to the company’s procedure , in 37°C CO2 incubator . All reagents required for maintenance and differentiation of cultures ( extracellular matrix and culture media ) were provided by the company . Five days after plating , after complete cell differentiation , cultures were used for the infection experiments . Immortalized embryonic fibroblasts were originally isolated from C57BL/6 mouse embryos and spontaneously immortalized in culture [29] . These cells were maintained in culture by consecutive passages in 25 cm 3 flasks in DMEM ( GIBCO ) culture medium supplemented with 10% FBS and 1% antibiotic ( penicillin/streptomycin ) . For the infection assays , 8x104 cells were plated in each well of a 24-well plate containing a 13 mm circular glass coverslips and maintained at 37°C in a CO2 incubator . For some experiments , parasites ( epimastigote stage ) were previously treated with H2O2 . H2O2 solutions were prepared daily assuming an extinction coefficient of 81M-1 cm-1 at 230 nm . For this , epimastigotes were subjected to treatment with different concentrations of H2O2 ( 5 to 100 μM ) for 6 days when the number of parasites was counted . Since 30 μM of H2O2 was the highest concentration in which JG and Col1 . 7G2 growth was still observed we used this concentration to perform the experiments . Treatment was performed by incubating 107 epimastigotes in 1mL PBS , pH 7 . 3 in the absence ( control ) or presence of 30 μM H2O2 at 28°C , for 30 minutes . Parasites were then washed and re-suspended in specific medium according to the experiment to be performed . For some experiments , cardiomyocyte cultures were treated with catalase ( Catalase-PEG C4963—SIGMA ) at a final concentration of 40U/mL . Treatment was initiated 2 hours prior to infection and maintained during and after parasite exposure . Cardiomyocyte cultures pre-treated or not with catalase , as well as fibroblast cultures were exposed to purified JG or Col1 . 7G2 TCTs re-suspended in high-glucose DMEM at a multiplicity of infection ( MOI ) of 50 . The infection was performed for 40 minutes at 37°C . After infection , monolayers were washed at least four times with PBS and either fixed with 4% ( w/v ) paraformaldehyde in PBS ( 0h–to determine the rate of parasite invasion ) or re-incubated for 4 , 8 , 12 , 24 , 48 or 72 hours prior to fixation and processing for immunofluorescence assays ( to determine parasitophorous vacuole escape– 4 , 8 and 12 h or parasite intracellular multiplication rates– 24 , 48 and 72 h ) . Alternatively , after parasite exposure ( 40 minutes at 37°C ) , cultures were washed and re-incubated for 48 and 72 hours before ROS measurements . After treatment , infection and fixation , coverslips containing attached cells were washed with PBS , incubated for 20 minutes with PBS containing 2% ( w/v ) bovine serum albumin ( BSA ) ( Sigma-Aldrich ) and processed for an inside/outside immunofluorescence invasion assay as described previously [27] . Briefly , cells were fixed and extracellular parasites were immune-stained using a 1:500 dilution of rabbit anti-T . cruzi polyclonal antibodies in PBS containing 2% ( w/v ) BSA ( PBS/BSA ) followed by labeling with Alexa Fluor-546 conjugated anti-rabbit IgG antibody ( Invitrogen ) . For evaluation of parasitophorous vacuole escape , after extracellular parasite staining , cells were permeabilized using a solution containing 2% ( w/v ) BSA and 0 . 5% ( v/v ) saponin ( Sigma-Aldrich ) in PBS ( PBS/BSA/saponin ) for 20 minutes . Host cell lysosomes were then immunostained using a 1:50 dilution of rat anti-mouse LAMP-1 hybridoma supernatant ( 1D4B; Developmental Studies Hybridoma Bank , USA ) in PBS/BSA/saponin for 45 minutes followed by labeling with Alexa Fluor-488 conjugated anti-rat IgG antibody ( Invitrogen ) , as described previously [30] . Subsequently , DNA from both host cells and parasites were stained for 1 min with 10 μM of DAPI ( Sigma-Aldrich ) , mounted on glass slide and examined on an Olympus BX51 , Zeiss , Apotome or Nikon Eclipse Ti . A general measure of oxidant formation were performed using CM-H2DCFDA ( 5- ( and-6 ) -chloromethyl-2' , 7'-dichlorodihydrofluorescein diacetate , acetyl ester—Molecular Probes ) probe , which fluoresces upon oxidation . For this , cell cultures , 48 and 72 hours post infection with JG or Col1 . 7G2 , were washed once with PBS and exposed to CM-H2DCFDA at a final concentration of 10 μM in PBS . Immediately after the addition of CM-H2DCFDA , the plate was read on a Varioskan Flash ( Thermo Scientific ) at 37°C for monitoring the probe’s oxidization rate , with excitation and emission wavelengths of 485 and 520 nm , respectively . The data were analyzed using the program SkanIt Software 2 . 4 . 5 . The probe oxidation curves were used to calculate the slope and are expressed as Relative Fluorescence Units ( RFU ) /min . Neonatal cardiomyocyte cultures plated in an XF-24 well culture microplate ( Seahorse Bioscience ) were infected with TCTs from JG or Col1 . 7G2 , as described above for 48 hours . One hour before the experiment , media was replaced with unbuffered Dulbecco’s Modified Eagle Medium ( DMEM , pH 7 . 4 ) supplemented with 4 mM L-glutamine , 5 mM glucose and 10 mM Pyruvate ( Gibco ) . Olygomycin ( 5 μM , an inhibitor of ATP synthase ( complex V ) ) , Carbonyl Cyanide-p-trifluoromethoxyphenylhydrazone ( FCCP 5 μM , uncoupling agent ) and a mix of antimycin A ( AA , complex III inhibitor ) and rotenone ( Complex I inhibitor ) at a final concentration of 5 and 1 μM , respectively were injected sequentially through ports in the seahorse flux pack cartridges . Oxygen consumption rates ( OCR ) were analyzed for control and infected cardiomyocytes [31] . At least 5 replicates of each condition per plate and three independent replicates were analyzed . The non-mitochondrial oxygen consumption obtained after AA/Rotenone addition were subtracted to all OCR values . The mitochondrial respiratory control index ( RCI ) was calculated as the OCR value with FCCP divided by the OCR value with oligomycin ( FCCP/Oligomycin ) . For the identification and quantification of anti-oxidant enzymes produced by the different T . cruzi populations , 1x107 epimastigote forms previously incubated or not with 30 μM H2O2 ( 30 min ) were fixed with 3 . 7% ( v/v ) formaldehyde in PBS , centrifuged at 12 , 000 g at room temperature ( RT ) , resuspended in a solution containing 0 . 1% ( v/v ) Triton in PBS and incubated for 30 minutes at RT for permeabilization . After permeabilization , samples were centrifuged and incubated overnight at 4°C with a 1/100 dilution of each of the rabbit polyclonal antibodies raised towards the different antioxidant enzymes analyzed ( Ascorbate peroxidase , APX; Mitochondrial Peroxiredoxin , MPX; Trypanothione reductase , TR; Trypanothione synthetase , TS; mitochondrial iron superoxide dismutase A , FeSOD-A and cytosolic iron superoxide dismutase B , FeSOD-B ) , in PBS containing 0 . 1% ( w/v ) BSA and 0 . 5% ( v/v ) Tween ( PBS/BSA/Tween ) . After this , samples were centrifuged , washed in PBS/BSA/Tween and incubated for 90 minutes with Alexa-Fluor 488-labeled anti-rabbit IgG secondary antibody ( anti-APX , MPX , TR and TS ) or anti-mouse IgG ( anti-SODA and SODB ) diluted 1:100 in PBS/BSA/Tween . After incubation with the secondary antibody , the samples were centrifuged , washed with PBS/BSA/Tween , re-suspended in the same solution and read on BD FACSCan or BD FACSCalibur flow cytometer . Acquired data were analyzed using the BD CellQuest Pro 6 . 0 or FlowJo program . For intracellular calcium measurements , 5x107 parasites/mL were loaded with 5 μM fura-2AM at 28–30°C in fura buffer ( 116 mM NaC1 , 5 . 4 mM KC1 , 0 . 8 mM MgSO4 , 5 . 5 mM glucose , 1 mM CaC12 , and 50 mM Hepes , pH 7 . 0 ) . After 1h , cells were washed and re-suspended in PBS and exposed or not to H2O2-treatment as described earlier . Afterwards cells were washed once in PBS , re-suspended in fura buffer and fluorescence determined in 107 cells/mL in fura buffer in a Hitachi F2500 fluorescence spectrophotometer with continuous stirring ( excitation at 340 and 380 nm and emission at 510 nm ) [32 , 33] . For determination of epimastigote oxidant production in control and/or after H2O2 treatment , parasites ( 3 x108/mL ) were loaded in Krebs-Henseleit buffer ( KH buffer , 15 mM NaCO3 , 5 mM KCl , 120 mM NaCl , 0 . 7 mM Na2HPO4 , 1 . 5 mM NaH2PO4 ) at 28°C with 5 μM MitoSOX ( 3 , 8-phenanthridinediamine , 5- ( 6-triphenylphosphoniumhexyl ) -5 , 6-dihydro-6- phenyl , Molecular Probes ) . After 10 min of incubation with the probe , the cells were washed and re-suspended in KH buffer . Cells were then incubated with H2O2 for 30 min and washed , as described . The detection of oxidized MitoSOX ( oxMitoSOX ) in 5x107 cells/mL was performed in this buffer in the presence of 40 μM digitonin and 5 mM succinate to determine the production of these species by the mitochondrial respiratory chain . The fluorescence was detected using a Cytation 5 microplate reader with excitation and emission wavelengths of 510 and 580 nm , respectively [34] .
In order to confirm previous results obtained from primary embryonic cardiomyocyte cultures infected with JG or Col1 . 7G2 [14] , cultures obtained from neonatal BALB/c mice were submitted to infection with the same T . cruzi populations and invasion and intracellular multiplication rates were analyzed . A different behavior regarding cell invasion was observed . JG infection rate was in this case higher than Col1 . 7G2 . The number of infected cells was about 4 . 5 times higher for cultures exposed to JG , when compared to cultures infected with Col1 . 7G2 ( Fig 1A ) . Intracellular multiplication rates , on the other hand , were in accordance with previous results from Andrade and colleagues ( 2010 ) [14] . Seventy-two hours post infection we observed that the number of intracellular parasites in JG infected cultures were higher than the number of intracellular parasites in cultures infected with Col1 . 7G2 ( Fig 1B ) . 72 hours after exposure to the parasites , cultures infected with JG showed an approximately 2 . 5-fold increase in the number of intracellular parasites relative to those cultures infected with Col1 . 7G2 ( Fig 1B ) . Fig 1C shows representative images of the number of intracellular parasites in cardiomyocyte 72 hours post invasion with each of the parasite populations . These results indicate that independently of the invasion rate , JG shows a better intracellular development in these cells when compared to Col1 . 7G2 ( as noted by the slope of the curve ) . As it is known , when T . cruzi trypomastigotes invade the host cell it first resides in a parasitophorous vacuole , formed by lysosomal membrane , and later escapes from this vacuole falling into the host cell cytosol , where it transforms into the amastigote replicative form . Therefore the kinetics of parasitophorous vacuole escape could alter the transformation of internalized trypomastigotes into amastigote forms and consequently parasite intracellular development . In order to determine the kinetics of parasitophorous vacuole escape for JG and Col1 . 7G2 in primary neonatal cardiomyocyte cultures , infected cultures were washed and fixed at 0 , 4 , 8 or 12 hours after exposure to the parasites , as described . Parasites labeled with DAPI and lacking anti-T . cruzi antibody labeling were considered as intracellular parasites . To evaluate the proportion of intracellular parasites associated with the parasitophorous vacuole , the cells were also labeled with anti-LAMP-1 antibody , a protein present on the lysosomal membrane . Thus , intracellular parasites that co-localized with this marker were counted as inside the vacuole , the other intracellular parasites were considered free in the cytoplasm . The number of parasites associated with the lysosomal marker , LAMP-1 , shortly after ( 0h ) , 4 , 8 and 12 hours after cell exposure to parasites is shown in Fig 2 . No significant difference was observed in the kinetics of vacuole escape between JG and Col1 . 7G2 . Soon after the invasion , for both T . cruzi populations , around 50% of the internalized parasites are associated with LAMP ( Fig 2A ) . Four hours after parasite removal , the number of parasites associated with LAMP reaches 100% . This is due to the fact that the abundance of lysosomal markers associated to the vacuole increases in the first moments after the invasion , facilitating its visualization . Later , 8 to 12 hours post invasion , the number of parasites associated with LAMP starts to drop for both JG and Col1 . 7G2 infections , indicating that the parasites are escaping from the vacuole into the cytosol ( Fig 2A ) . Representative images of parasites inside ( 4 hours ) or outside the vacuole ( 12 hours ) , for both JG and Col1 . 7G2 , are shown in Fig 2B . In order to identify other possible factors that could account for the differential growth rate of JG and Col1 . 7G2 in neonatal cardiomyocytes , we evaluated the levels of production of oxidants in these cells upon infection with the two T . cruzi clonal populations . It is known that cardiomyocyte infection by the parasite can induce the production of ROS , which can modulate the intracellular development of the parasite [35 , 36] . Analysis of the oxidant levels produced upon infection with JG and Col1 . 7G2 in cardiomyocyte cultures was done using the CM-H2DCFDA probe added to infected cultures , as described in material and methods . When oxidized , CM-H2DCFDA fluoresces and the amount of fluorescence produced is an indirect measure of the cellular production of ROS . CM-H2DCFDA fluorescence was measured 48 or 72 hours post infection , the period corresponding to the intracellular multiplication phase of the parasite . Forty-eight hours post infection no significant difference in the amount of oxidized probe was observed for those cultures infected with Col1 . 7G2 , relative to the control ( uninfected cultures ) ( Fig 3A ) . On the other hand , at the same time the levels of CM-H2DCFDA oxidation were about 1 . 6 fold higher for JG infected cultures when compared to the control or cultures infected with Col1 . 7G2 , indicating increased oxidant production after infection with JG ( Fig 3A ) . At 72 hours , both JG and Col1 . 7G2 infected cultures showed significantly higher levels of CM-H2DCFDA oxidization when compared to control non-infected cultures . ( Fig 3A ) . However , the levels of oxidized CM-H2DCFDA in JG-infected cultures were still significantly higher than that observed for cultures infected with Col1 . 7G2 ( Fig 3A ) . It had been shown that oxidant production by T . cruzi infected cardiomyocytes could come from mitochondrial dysfunction [23] . Thus , we evaluated the mitochondrial function in cultures of primary mouse cardiomyocytes infected or not with trypomastigote forms of Col1 . 7G2 or JG . The respiratory control index ( RCI ) allows the evaluation of the mitochondrial capacity of substrate oxidation with low proton loss . Thus , the higher the RCI the lower is mitochondrial dysfunction and oxidant production . RCI measurements 48 hours post infection revealed greater mitochondrial impairment in cultures infected with JG . While cardiomyocytes infected with Col1 . 7G2 showed a small increase in the RCI when compared to control non-infected cultures , cardiomyocyte cultures infected with JG showed a significantly lower RCI when compared to control or Col1 . 7G2 infected cultures ( Fig 3B ) . These results are in agreement with the higher rates of CM-H2DCFDA probe oxidation , indicating greater mitochondrial dysfunction and consequently higher production of oxidizing species cardiomyocyte cultures infected with JG . To assess the ability of JG and Col1 . 7G2 to cope with ROS produced upon infection in cardiomyocytes , the basal levels of different parasite anti-oxidant enzymes were assayed . Polyclonal antibodies directed to each of the anti-oxidant enzymes were used to label the parasites and the amount of labeling was read in a flow cytometer . Fig 4A shows the histograms of fluorescence intensities obtained in the epimastigote stage , for each T . cruzi population , for the different enzymes . The higher the expression of the enzymes the higher the number of cells presenting high levels of fluorescence . APX , MPX and TS anti-oxidant enzymes were found in higher amounts in the epimastigote forms of Col1 . 7G2 when compared to the same forms of JG in control conditions ( Fig 4A ) . To determine if the profile of the antioxidant enzyme production by JG and Col1 . 7G2 would be the same after exposure of the parasites to oxidative stress , epimastigote forms from JG and Col1 . 7G2 were treated with H2O2 prior to the evaluation of enzyme expression . Even after exposure to the oxidant , a higher content of antioxidant enzymes was found for epimastigote forms of clone Col1 . 7G2 . In this condition , higher expression of MPX , Fe-SODA and TR were found in Col1 . 7G2 epimastigotes when compared to JG ( Fig 4B ) . Therefore , higher amounts of anti-oxidant enzyme was only observed for Col1 . 7G2 , never for JG , either before or after exposure to an oxidative environment , indicating that JG could be more susceptible to oxidative stress . The results obtained above show that JG induces more ROS in infections of BALB/c neonatal cardiomyocyte cultures and has less anti-oxidant enzymes contents when compared to Col1 . 7G2 . Nonetheless , intracellular multiplication of JG in these cells is faster when compared to Col1 . 7G2 . These data suggest that , ROS production and oxidative stress generated during infection in cardiomyocytes may trigger JG intracellular development . To test this hypothesis we decided to investigate whether decreasing reactive oxygen species , such as hydrogen peroxide ( H2O2 ) by treatment of cardiomyocyte cultures with catalase during T . cruzi infection , could interfere with the intracellular development of JG and or Col1 . 7G2 in these cells . For this , cultures of BALB/c neonatal cardiomyocytes were incubated or not with catalase , as described in the methodology . After treatment with catalase , a statistically significant decrease in the intracellular growth rate of JG was observed . JG infected cells had lower number of intracellular parasites along the course of infection when compared to non-treated cells ( Fig 5A and 5C ) . Seventy-two hours post infection , the number of JG intracellular parasites for cultures treated with catalase was around 1 . 5 times lower than that obtained for control non-treated cultures , indicating a poorer intracellular development in a less oxidative environment ( Fig 5A ) . On the other hand , treatment of cultures with catalase did not interfere with Col1 . 7G2 intracellular growth ( Fig 5B and 5C ) , since the number of intracellular parasites along the course of infection was very similar in both treated and catalase treated conditions . These results suggest that the oxidative stress generated by the infection plays an important role in stimulating the intracellular development of the JG strain . The data obtained for primary cultures of cardiomyocytes from BALB/c mice suggest that the oxidative stress generated during infection benefits the growth of JG in these cultures . In order to verify if this data could be reproduced in cardiomyocytes from a different source , we performed cultures of human cardiomyocytes obtained from induced pluripotent human stem cells . First , the cultures of human cardiomyocytes were submitted to the same infection methodology with Col1 . 7G2 and JG and the rates of invasion and intracellular multiplication were evaluated . In these cultures , the rate of invasion observed for the two T . cruzi clonal populations , JG and Col1 . 7G2 , was similar to the results previously obtained by Andrade et al . ( 2010 ) , where Col1 . 7G2 had a higher number of infected cells when compared to cultures infected with JG ( Fig 6A ) . With respect to parasite growth , 72 hours post-infection , JG-infected cultures showed higher intracellular proliferation rates ( 2 . 14 times ) when compared to cultures infected with Col1 . 7G2 ( Fig 6B ) , reproducing the results obtained by Andrade et al . ( 2010 ) [14] and data obtained here for BALB/c neonatal cardiomyocyte cultures ( Fig 1B ) . JG growth in human cardiomyocyte cultures was about 2 . 14 times greater than Col1 . 7G2 ( Fig 6B ) . Since the profile of JG and Col1 . 7G2 intracellular development in human cardiomyocytes reproduced the data obtained from infections in neonatal BALB/c cardiomyocyte cultures , we decided to investigate the induction of oxidants upon infection of these cells . Evaluation of oxidant production was also performed by incubation of cells with the probe CM-H2DCFDA , 48 hours post infection . Again , no significant difference was observed in the amount of oxidized probe for those cultures infected with Col1 . 7G2 , relative to the control ( uninfected cultures ) ( Fig 6C ) . On the other hand , at the same time a significantly higher amount of probe oxidation , about 1 . 52 fold higher , was observed for those cultures infected with JG , relative to the control or about 1 . 29 fold higher when compared to cultures infected with Col1 . 7G2 , also indicating higher production of ROS upon infection of these cells with JG ( Fig 6C ) . Additionally , we also investigated whether inhibition of oxidative stress would affect JG or Col1 . 7G2 infection in these cultures . While JG multiplied better than Col1 . 7G2 in non-treated cultures ( Fig 6B ) , its growth was lower than Col1 . 7G2 in catalase treated cultures ( Fig 6D ) . We also compared JG and Col1 . 7G2 intracellular growth obtained from experiments performed in human cardiomyocyte non-treated cultures ( Fig 6B ) with the new data obtained from the experiments performed with human cardiomyocytes treated with catalase ( Fig 6D ) , which are shown in Fig 6E . As observed , a decrease in JG intracellular growth , but not in Col1 . 7G2 is found upon catalase treatment . These results imply that JG is also more responsive than Col1 . 7G2 to the repressive effects of catalase when infecting human cardiomyocyte cultures and reinforce the idea that the oxidative stress generated by the infection plays an important role in the intracellular development of at least some T . cruzi strain . We next investigated whether infection in a different cell type , would alter JG and Col1 . 7G2 intracellular behavior . For this , we performed infections with JG and Col1 . 7G2 in immortalized mouse embryonic fibroblasts ( MEFs ) and evaluated parasite intracellular growth and oxidant production upon infection . Fig 7A shows the number of intracellular parasites per infected cell over a total period of 72 hours of infection in MEFs . As can be observed , there was no significant difference in the number of intracellular parasites between Col1 . 7G2 and JG in any of the analyzed points , being the growth curve of both T . cruzi populations similar to each other . In order to confirm that these cells did not respond to infection with oxidant generation , analysis of CM-H2DCFDA oxidization , 48 hours post infection with JG or Col1 . 7G2 , was performed . For both cultures no statistically significant difference was observed in the levels of oxidized CM-H2DCFDA among control non-infected cultures and those infected with Col1 . 7G2 or JG ( Fig 7B ) . The above results suggest that oxidative stress may play in JG strain a role in the intracellular development of the parasite and may , in specific situations , be beneficial to its intracellular development . In the latter , oxidative stress could work as a signal triggering parasite intracellular growth [36 , 37] . It has been shown in the literature that the increase in free intracellular Ca2+ levels in the cytoplasm of T . cruzi may represent an important signal , leading to an increase in the infective capacity of this parasite [33] . It has also recently been shown that the decrease of IP3 receptor expression in the parasite leads to a decrease not only in the infectivity , but also in parasite intracellular growth [38] . Thus , we decided to verify whether exposure of Col1 . 7G2 and JG to oxidative stress , by incubation with H2O2 , could induce calcium signals in these parasites . Baseline levels of intracellular calcium , before treatment with H2O2 ( control ) , were significantly higher for Col1 . 7G2 , when compared to JG ( Fig 8A ) . However , upon H2O2 treatment , only JG was capable of increasing the Ca2+ levels , as observed for Trypanosoma brucei [39] ( Fig 8A ) . Another important signaling molecule is superoxide radical ( O2•- ) . It has been shown that high levels O2•- is deleterious to cells , however in adequate concentrations O2•- may function as a stimulator of cell growth , as well as to inhibit apoptotic pathways [40 , 41] . Thus , we also investigated the influence of H2O2 treatment on O2•-/H2O2 levels in epimastigote forms of JG and Col1 . 7G2 following MitoSOX probe oxidation . Baseline levels of MitoSOX oxidation for Col1 . 7G2 were very low , significantly lower than those observed for JG ( Fig 8B ) . On the other hand , oxidant treatment of JG led to an increase in MitoSOX oxidation ( Fig 8B ) . The above result may indicate that oxidant treatment may , by some unknown mechanism , enhance parasite O2•- production in the JG T . cruzi strain . Both intracellular O2•- and or H2O2 may be in part , responsible for the cellular signaling that boost parasite proliferation .
One of the great questions regarding T . cruzi infection is what defines the development or not of serious clinical forms resulting from the infection . As mentioned previously , T . cruzi infection in humans has a very variable clinical course , in which infected individuals may be asymptomatic or even develop severe clinical symptoms , presenting cardiac , digestive or cardio-digestive disorders ( reviewed by [42] ) . Understanding the mechanisms involved with the pathogenesis of this disease is essential for better control of the infection . Evidence from the literature shows that this clinical variability is related to a differential tissue tropism of parasite populations , which depends directly on the parasite-host cell interaction , without direct interference of the immune system [11 , 13 , 43 , 44] . Cellular infection can be divided into two stages: invasion and intracellular multiplication . According to previous data from our group , intracellular multiplication seems to be of fundamental importance for the definition of this selection [14] . Studying the behavior of two clonal populations Col1 . 7G2 ( T . cruzi I ) and JG ( T . cruzi II ) of T . cruzi during infection in primary cultures of BALB/c embryonic cardiomyocytes it was observed that JG , a T . cruzi strain with strong tropism to BALB/c hearts , presented higher intracellular multiplication rates in these cells when compared to Col1 . 7G2 [11 , 14] . In order to investigate the factors influencing this differential intracellular behavior we used as a study model the in vitro infection of primary cultures of BALB/c cardiomyocytes with the same T . cruzi clonal populations used in the previous studies , JG and Col1 . 7G2 . However , this time the cardiomyocytes were isolated from neonatal mice . Regarding invasion rates , the data obtained here diverged from the data previously published by Andrade et al . ( 2010 ) [14] . This divergence may be related to the fact that , although from the same type of animal , the stage of differentiation of the cells was distinct from the work published earlier [14] . Cardiomyocytes isolated from neonatal mice may express distinct proteins from the ones obtained from mouse embryos , which could account for the differences in invasion rates observed for these two cells [45] . Nonetheless , in BALB/c neonatal cardiomyocytes , JG still presented a higher multiplication rate when compared to Col1 . 7G2 . These data reinforce the idea that the intracellular development of the parasite , as suggested before [14] , may be more important for the determination of T . cruzi tissue tropism than cellular invasion itself . This hypothesis is also supported by the data obtained here from JG and Col1 . 7G2 infections in human cardiomyocyte cultures derived from iPSCs . Upon infection in these cells , even though Col1 . 7G2 invasion rates were higher than JG , parasite intracellular growth was greater for JG infected cultures . Several factors could affect the intracellular development of T . cruzi , among them its intracellular traffic . During cell infection , T . cruzi uses the cell membrane repair mechanism to promote its internalization in non-professional phagocytic cells , forming a vacuole containing lysosomal markers and content [46 , 47] . The acidic content of the vacuole allows the parasite to gradually escape into the cytoplasm of the cell , where it completes its transformation into the amastigote form and initiates its intracellular multiplication [15 , 48–51] . It was possible that a faster escape could advance the transformation of the parasite into the amastigote form and thus allow it to start its multiplication sooner . In fact , trans-sialidase superexpressor parasites , which escape faster from their parasitophorous vacuoles , differentiate into the amastigote earlier than wild type parasites [52] . Our data showed that , there was no difference in the rate of parasitophorous vacuole escape between Col1 . 7G2 and JG . Therefore this could not account for the differences in parasite intracellular development observed in the cardiomyocytes . Data from the literature show that infected cells are able to respond to infection by activating several genes , which could interfere with the intracellular behavior of the parasite [19 , 20 , 22 , 24] . Thus , we decided to evaluate the response of the host cell to infection , trying to correlate this data with the intracellular development of T . cruzi . For this , we investigated whether the production of ROS upon infection could be responsible for the differential intracellular growth of JG and Col1 . 7G2 in the studied cardiomyocyte cultures . It had already been shown that infection of cardiomyocytes with T . cruzi leads to a disturbance in the membrane potential of the mitochondria generating ROS [23] . In fact , by using the CM-H2DCFDA probe , we observed an increase in ROS production in primary cultures of BALB/c and human cardiomyocytes infected with Col1 . 7G2 ( 72 hours ) or JG ( 48 and 72 hours ) post infection , when compared to control uninfected cultures . Additionally , for JG infected cultures , a higher amount of ROS was produced 48 hours post infection , indicating a faster and stronger response of cardiomyocytes infected to this clonal population . The high increase in ROS detected in BALB/c cardiomyocyte cultures 48 hours post infection with JG was likely generated by mitochondrial dysfunction as revealed by the analysis of the respiratory control index ( RCI ) in BALB/c cardiomyocyte infected cultures , although other sources cannot be ruled out . At this time post infection , cultures infected with JG presented a significant decrease in the RCI . The RCI is the best general measure of mitochondrial function in cell populations that have sufficiently active glycolysis to support metabolism , while mitochondrial function is manipulated [31] . Thus , a decrease in RCI does indicate mitochondrial dysfunction . These results are in agreement with previous data from the literature showing that upon infection with T . cuzi mitochondrial potential is disturbed , inducing ROS production [23] . On the other hand , we could not detect mitochondrial dysfunction in Col . 17G2 infected cardiomyocytes 48 hours post infection . In agreement with this , at this time post infection , we could also not detect an increase in ROS in Col1 . 7G2 infected cardiomyocytes , when compared to control non-infected cultures . We are not sure why Col1 . 7G2 did not cause changes in cardiomyocyte mitochondrial RCI 48 hours post infection , but it may have to do with differences in the strains used . It is well known that T . cruzi populations do vary in their behavior during infection in cells , which may account for changes in their ability to interfere with mitochondrial function . In fact , although lower than that observed upon JG infection , we did observe changes in the RCI 72 hours post infection . So it is possible that upon infection with this strain there is a delay in the induction of mitochondrial dysfunction and generation of oxidative stress . In fact , there is data in the literature showing that hearts of BALB/c mice infected with Colombian strain do present a significant increase in the oxidative stress [53] . T . cruzi has a sophisticated system of antioxidant defenses to protect parasite from oxidative stress [54] . Interestingly , for epimastigote forms , none of the anti-oxidant enzymes evaluated were more expressed in JG when compared to Col1 . 7G2 . In fact , when there was a difference in enzyme expression , the higher expression was found in Col1 . 7G2 . This was also the case for parasites that were previously exposed to oxidative stress by incubation with H2O2 , which had been already shown to induce an increase in anti-oxidant enzyme levels [55] . In fact , for Coll . 72G parasites previously exposed to H2O2 , we observed an increase in Fe-SODA and MPX levels , showing that H2O2 was effective in inducing an increase in enzyme expression . So far , JG induced more ROS production in cardiomyocytes and was likely to be more susceptible to this generated oxidative stress . ROS has been shown to have a dual effect on cells . Although data from the literature show that an increase in ROS can compromise the intracellular growth of several pathogens , including T . cruzi , the opposite has also shown to be true [56–61] . It has recently been demonstrated that the oxidative stress generated by T . cruzi infection can lead to an increase in the replication rate of this parasite [36 , 37] . One of the possible explanations for the increase in the rate of parasite replication upon induction of oxidative stress could be the bioavailability of iron for use by the parasite [36 , 62] . It is known that iron is important for several metabolic events , such as DNA replication , mitochondrial respiration and anti-oxidant defense [63] . Thus , although amastigote forms of the parasite have been shown to be capable of binding and importing transferrin [64] in the intracellular environment , the concentration of this protein is very low . It is possible that free iron is more easily acquired in this way and then contributes to a better adaptation of this parasite to the intracellular environment . In the case of trypanosomatids , superoxide dismutases , important anti-oxidant enzymes , are iron-dependent [65] . Alternatively , the presence of oxidative stress could generate specific signals that would contribute to a more adequate response of the parasite in the cell , stimulating its faster replication . In fact , Finzi et al . ( 2004 ) also showed that pre-treatment of T . cruzi epimastigote forms with low concentrations of H2O2 increased parasite proliferation [66] . Considering the above , in our case , ROS seems to be important to give JG advantage during infection in cardiomyocytes . This is reinforced by the fact that inhibition of ROS by incubation of mouse and human cardiomyocytes with catalase inhibits JG intracellular growth . In fact , the inhibition of JG growth seemed even more prominent in human cardiomyocyte cultures . However distinct batches of catalase were used in the two experiments , which could account for this difference . Nonetheless , these results imply that at least for some strains ROS may be involved in parasite intracellular growth . Additionally , this is also corroborated by the data obtained from infected fibroblasts , which in our experimental conditions do not produce ROS in response to infection . In these cells JG did not present any growth advantage when compared to Col1 . 7G2 . Previous studies have shown that a recombinant strain of T . cruzi , an E . coli MutT superexpressor ( an enzyme involved in DNA repair ) , is more efficient in cell colonization compared to wild type parasites . In that work it was suggested that 8-oxo-GMP , generated by degradation of 8-oxo-GTP by MutT , could serve as signal to produce parasites more adapted to the intracellular environment [67] . It has also been shown that low concentrations of ROS were sufficient to promote better infection in in vitro and in vivo experiments [37] . Overall , our results suggest that ROS may have , in some specific circumstances , a helpful role in T . cruzi cell proliferation in non-professional phagocytes , which had not been shown before . Recently , Vilar-Pereira and colleagues [53] have studied the role of antioxidants in cardiac function during T . cruzi infection in mice . For this they evaluated the production of ROS in the hearts of BALB/c mice infected with Colombian strain , by intravital microscopy at the chronic stage , before and after the treatment with different antioxidant agents . In this case , as mentioned before in this discussion , they found high amounts of oxidative stress in hearts of non-treated mice , possibly due to the fact that the experiments were performed in vivo at later time points , after several rounds of parasite infection . Additionally they showed electrical and mechanical dysfunction in these infected mice [53] . Treatment with different antioxidants was able to in fact improve hart function . However , they also demonstrated that only treatment with resveratrol was able to reduce parasite burden , but not treatment with the other antioxidant drugs . This is in contrast with previous findings from the same group showing that heart parasite burden is decreased in response to antioxidant treatment [36] . However in the latter they have used T . cruzi Y strain . Colombian and Y strain , such as the clone of Colombian strain ( Col1 . 7G2 ) and JG used in our study , belong to two different T . cruzi lineages , T . cruzi I and II , respectively . It is possible that parasites from different lineages do respond differently to ROS . In this case , for T . cruzi II strains ROS may not have an effect in controlling or signaling to this parasite and that the effect of resveratrol may be by another signaling pathway , while T . cruzi I strains would be responsive to ROS . Our data supports this hypothesis since treatment does affect the T . cruzi I population , but not T . cruzi II . Whether T . cruzi II strains do not really respond to ROS or whether this response depends on the amount or the type of response triggered by the ROS production still remains to be elucidated . There are several data in the literature showing that the presence of oxidative stress could generate signaling molecules . Here we show that parasite treatment with H2O2 , leads to an increase in intracellular levels of calcium and also probably in O2•- and/or H2O2 production in JG , but not in Col1 . 7G2 T . cruzi clone , reinforcing that JG is more responsive to ROS , at least in this condition . Both molecules have been shown to interfere with cell death and replication [41 , 68] . In relation to calcium levels , it has been shown that in epimastigotes the regulation of intracellular calcium is important for multiplication and metacyclogenesis [69] . In the literature it has also been shown that ROS are capable of increasing intracellular Ca2+ in parasites such as Trypanosoma brucei [39] . To the best of our knowledge this is the first time that it is shown that T . cruzi , in this case JG strain , can also respond to oxidative stress by altering intracellular calcium levels . In this case , the increase in calcium levels observed for JG was not sufficient for induction of cell death , but could be important for signaling some pathway related to cell proliferation . With respect to O2•- , there are reports showing that its increase may induce programmed cell death in T . cruzi and that parasites overexpressing mitochondrial Fe-SODA are more resistant [57] . However , there are reports in the literature showing that an increase in the concentration of this molecule may also signal for increased cell proliferation , as well as to work as an inhibitor of apoptotic pathways [40 , 41] . In Dictyostelium discoideum , for example , the overexpression of SOD , with consequent consumption of O2•- , leads to the inhibition of multicellular aggregates [41] . What would determine whether ROS is responsible for death or proliferation would certainly be related to the amount to which parasites are exposed and the ability of the parasite to sense and trigger the intracellular signaling . The data presented in this work suggest a mechanism responsible for the better development of JG , dependent on the parasite response to oxidant production , in cardiomyocyte cultures and may contribute to the understanding of the behavior of T . cruzi populations during infection in the host .
|
Chagas disease , caused by the protozoan parasite Trypanosoma cruzi , presents a variable clinical course , varying from asymptomatic to serious debilitating pathologies with cardiac , digestive or cardio-digestive impairment . It has been suggested that parasite differential tissue tropism is responsible for the development of the distinct clinical forms . Differences in parasite tissue tropism have been shown previously , using mixed infections in mice with two distinct T . cruzi populations , Col1 . 7G2 ( T . cruzi I ) and JG ( T . cruzi II ) . In these infections hearts were preferentially colonized by JG . Increased JG adaptation to cardiac muscle was later confirmed in infection studies using isolated cardiomyocytes , where it was shown that selection was dependent on parasite intracellular development . However the mechanisms that determined this differential parasite intracellular growth was not described . Here we investigated whether host cell response upon T . cruzi infection was able to modulate parasite multiplication rate inside cells . We showed that , upon infection , cardiomyocytes increase the production of oxidative species , especially in cultures infected with JG and inhibition of oxidative stress severely interfered with the intracellular multiplication rate of JG . Data obtained suggests that JG and Col1 . 7G2 may sense extracellular oxidants in a distinct manner , which would enable JG to develop better inside cardiomyocytes .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"medicine",
"and",
"health",
"sciences",
"respiratory",
"infections",
"oxidative",
"stress",
"enzymes",
"microbiology",
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"parasitic",
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"protozoans",
"pulmonology",
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"biology",
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"mitochondria",
"bioenergetics",
"epimastigotes",
"cellular",
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"organelles",
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"trypanosoma",
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] |
2017
|
Cardiomyocyte oxidants production may signal to T. cruzi intracellular development
|
The evolutionarily conserved family of AP-2 transcription factors ( TF ) regulates proliferation , differentiation , and apoptosis . Mutations in human AP-2 TF have been linked with bronchio-occular-facial syndrome and Char Syndrome , congenital birth defects characterized by craniofacial deformities and patent ductus arteriosus , respectively . How mutations in AP-2 TF cause the disease phenotypes is not well understood . Here , we characterize the aptf-2 ( qm27 ) allele in Caenorhabditis elegans , which carries a point mutation in the conserved DNA binding region of AP-2 TF . We show that compromised APTF-2 activity leads to defects in dorsal intercalation , aberrant ventral enclosure and elongation defects , ultimately culminating in the formation of morphologically deformed larvae or complete arrest during epidermal morphogenesis . Using cell lineaging , we demonstrate that APTF-2 regulates the timing of cell division , primarily in ABarp , D and C cell lineages to control the number of neuroblasts , muscle and epidermal cells . Live imaging revealed nuclear enrichment of APTF-2 in lineages affected by the qm27 mutation preceding the relevant morphogenetic events . Finally , we found that another AP-2 TF , APTF-4 , is also essential for epidermal morphogenesis , in a similar yet independent manner . Thus , our study provides novel insight on the cellular-level functions of an AP-2 transcription factor in development .
The AP-2 family of transcription factors is associated with proper development of mammals by maintaining a balance between cell proliferation and cell death [1 , 2] . Five members of the AP-2 family have been identified in vertebrates: AP-2α , AP-2β , AP-2γ AP-2δ and AP-2ε [3–8] . All AP-2 transcription factors have a central basic region followed by a highly conserved helix-span-helix ( HSH ) motif at the carboxyl terminus [9] . The HSH is essential for dimerization and together with the adjacent basic region achieves a sequence-specific DNA binding function [10] . The less conserved proline- and glutamine-rich region at the amino terminus is required for transcription activation [11] . AP-2 transcription factors bind primarily to the palindromic core sequence 5’-GCCN3GGC-3’ and serve a dual role as transcriptional activators or repressors [1] . AP-2 knockout mice display a wide spectrum of anomalies in early development such as craniofacial , neural tube and body wall defects , and polycystic kidney disease associated with uncontrolled apoptosis [12–14] . The phenotypic defects correspond to the diverse and overlapping expression patterns of murine AP-2 family genes in the neural crest cells , forebrain , facial and limb mesenchyme , and various types of epithelial cells [4 , 5 , 15 , 16] . In humans , mutations in TF AP-2-alpha ( TFAP2A ) have been associated with branchio-oculo-facial syndrome ( BOFS ) , a congenital birth defect characterized by craniofacial abnormalities , skin and eye defects as well as hearing problems [17] . Char Syndrome , a congenital disease characterized by patent ductus arteriosus and facial and hand anomalies , was linked to mutations in TF AP-2-beta ( TFAP2B ) [18] . Multiple point mutations and deletions in BOFS and Char Syndrome patients have been mapped to the conserved basic region of the DNA binding domain in AP-2α and AP-2β [17–20] . However , the molecular mechanisms by which these mutations manifest in the disease symptoms are not well understood . In C . elegans , there are four AP-2 TF family members: APTF-1 , APTF-2 , APTF-3 and APTF-4 . APTF-1 functions in the GABAergic neuron RIS to induce sleep-like quiescence in C . elegans [21] . Other APTF members have not yet been studied . Using whole genome sequencing , we identified a mutant allele which gave rise to a single amino acid change in the basic region of APTF-2 . Here , we describe the role of APTF-2 during C . elegans embryonic development , specifically during epidermal morphogenesis that involves the formation of a single epithelial layer that envelops the animal . We found APTF-2 is important for epithelial dorsal intercalation and ventral enclosure and mutation of aptf-2 results in larva with body morphology defects as well as embryonic lethality . Cell lineaging revealed misregulation of cell division timing , possibly leading to the phenotypic defects . Thus , C . elegans could serve as a model to study molecular and cellular consequences of mutations in the family of AP-2 TF analogous to those mutations in human AP-2 TF underlying BOFS and Char syndrome diseases .
In a genetic screen for maternal-effect mutations that have an impact on C . elegans development Hekimi et . al . isolated mal-1 ( qm27 ) as a mutation that causes extensive embryonic and larval lethality , with surviving homozygous mutants displaying morphological defects characterized by dorsal protrusions on the head and/or shortened body length [22] ( Figs 1A and S1A and Tables 1 and S1 ) . Genetic mapping predicted the approximate location of mal-1 ( qm27 ) on chromosome IV [22] , but the molecular identity of the mal-1 gene has remained unknown . Whole genome sequencing of a mal-1 ( qm27 ) strain identified a missense mutation in aptf-2 , one of four AP-2-like transcription factors in C . elegans . This mutation changes a highly conserved glutamic acid residue within the basic region of the DNA binding domain into a lysine residue ( Fig 1B and 1C ) . Previous findings have indicated the basic region as a mutation hotspot for BOFS and Char Syndrome [17–20] . We also analysed gk902 , a deletion allele of aptf-2 generated by the International C . elegans Gene Knockout Consortium . Similar to qm27 , gk902 worms also displayed maternal effect embryonic lethality with 99 ± 0 . 5% of embryos not hatching and the few hatching larva displaying head and/or tail morphological defects and arresting as larva ( Table 1 , S1 Table ) . The gk902 and qm27 alleles failed to complement each other , as the progeny of trans-heterozygote aptf-2 ( gk902 ) /aptf-2 ( qm27 ) had a level of embryonic lethality in between homozygote aptf-2 ( qm27 ) and homozygote aptf-2 ( gk902 ) , consistent with them being mutations in the same gene ( Fig 1D and S2 Table ) . Moreover , expression of APTF-2::GFP from an integrated array driven by the aptf-2 promoter , completely rescued the embryonic lethality in both aptf-2 ( gk902 ) and aptf-2 ( qm27 ) strains ( Fig 1D , S2 Table , S1 Movie ) , confirming the embryonic lethality in these strains is due to the mutations in aptf-2 . Consistent with Hekimi et . al . [22] we found that qm27 homozygous progeny of +/qm27 worms are phenotypically normal , indicating maternal rescue . To characterize the developmental defects in aptf-2 ( qm27 ) embryos leading to their lethality we used 4D differential interference contrast ( DIC ) microscopy to follow isolated embryos positioned with either their dorsal or ventral side facing the microscope objective . We identified three major defects , all related to epidermal morphogenesis: failure in dorsal epidermal cell intercalation , failure of ventral epidermal cell enclosure , and arrest during elongation ( Table 2 ) . A small percentage of embryos also exhibited leakage of cells out of the body of the embryo during elongation ( Table 2 ) . The exact cause for elongation arrest is not easily discerned , but we noted that one third of the ventrally-oriented embryos that arrested during elongation had previous ventral enclosure defects and nearly all of the dorsally-oriented embryos that arrested in elongation displayed earlier defects in dorsal intercalation . We confirmed the phenotypes observed in DIC microscopy by imaging aptf-2 ( qm27 ) embryos expressing fluorescently-tagged cell-cell junction markers E-cadherin/HMR-1 and alpha-catenin/HMP-1 . As shown in Fig 2 , S2 and S3 Movies , these markers confirmed the failure of epidermal cells to dorsally intercalate ( Fig 2A ) , ventrally migrate ( Fig 2B ) , and elongate the embryo ( Fig 2C ) . Previous studies have shown that ventral enclosure defects are often preceded by failure of ventral neuroblasts to seal the cleft at the end of gastrulation . We imaged gastrulation cleft closure in wild-type and aptf-2 ( qm27 ) embryos by DIC and by expression of the neuroblast marker KAL-1::GFP and found that the ventral cleft in the mutant embryos was larger to begin with , took up to four times the amount of time to close and in some cases did not completely close before the onset of epidermal ventral enclosure ( S1 Fig ) . We next examined the embryonic phenotypes of the null mutant aptf-2 ( gk902 ) by DIC microscopy . We found 60% of the embryos died prior to epidermal morphogenesis , and approximately half of these early embryonic deaths were associated with the appearance of many ectopic apoptotic cells ( Fig 3A and Table 3 ) . The remaining 40% of embryos that made it to epidermal morphogenesis all exhibited defects in dorsal intercalation , a quarter of them had ventral enclosure defects , and they all arrested during elongation ( Fig 3B , 3C and 3D and Table 3 ) . The massive apoptosis phenotype was completely rescued by the expression of APTF-2::GFP ( S2 Table ) , suggesting that it is a result of the complete loss of APTF-2 function . However , this phenotype was never observed in the partial loss of function allele qm27 . Neither was it observed in aptf-2 ( RNAi ) nor following injection of aptf-2 dsRNA into aptf-2 ( qm27 ) . Using TargetOrtho [23] , a phylogenetic footprinting tool to identify transcription factor targets , we identified within the C . elegans genome 1631 putative AP-2 TF binding sites in the 3KB upstream promoter region of 872 genes ( S1 Text ) . Protein domain analysis of these genes revealed enrichment in F-box , Homeobox , EF-hand , SET and CUB domain proteins , as well as others , and gene onthology analysis of biological processes showed enrichment in genes associated with embryonic development , tissue morphogenesis , locomotion , regulation of growth rate , and reproduction , among others ( see S1 Text for full list ) . Among the putative AP-2 TF regulated genes classified as associated with epithelium development our attention was caught by die-1 . The zinc finger transcription regulator DIE-1 is autonomously required in the posterior dorsal hypodermis for intercalation , for morphogenesis in other embryonic tissues , and for normal postembryonic growth and vulval development [24 , 25] . Given the defects we observed in epidermal morphogenesis we tested whether the expression of die-1 is altered in aptf-2 mutants . Indeed , we found that two out of seven aptf-2 ( qm27 ) embryos showed aberrant localization of DIE-1::GFP . Furthermore , we measured a 22 . 5% reduction in mean intensity of DIE-1::GFP in the nucleus of mutant embryos with proper nuclear localization ( 2340 a . u . ± 75 . 93 , n = 5 ) compared to wild type ( 3018 a . u . ± 63 . 68 , n = 4 ) ( Fig 4 ) . Analyzing the DIC movies of embryonic development we found that in addition to the various defects in epidermal morphogenesis the aptf-2 ( qm27 ) embryos developed more slowly than wild-type embryos at the same temperature . To quantify the delay and find out whether there is a particular stage in development that is slower or if all of embryogenesis is inherently slower we chose easy-to-recognize developmental milestones in dorsally or ventrally oriented embryos and measured the time it took for an embryo to progress from one milestone to the next ( S3A and S3B Table ) . We also measured the same developmental times in aptf-2 ( qm27 ) embryos stably expressing wild-type APTF-2::GFP . The results , graphically presented in Fig 5 , show that all stages of development are slower , to varying degrees , in aptf-2 ( qm27 ) embryos , and the developmental timing is mostly rescued in embryos ectopically expressing APTF-2::GFP . Specifically , ventral cleft closure is three times slower and elongation to 2 fold stage is one and a half times slower , while early development until Ea/Ep ingression is only slightly slower . To better understand the developmental defects in aptf-2 ( qm27 ) embryos we performed cell lineage analysis by following a nuclear marker , HIS-72::GFP , using 4D fluorescence microscopy . The cell division patterns in wild-type and aptf-2 ( qm27 ) embryos were captured , then analysed and edited using StarryNite and AceTree , respectively ( n = 2 for wild-type and n = 6 for aptf-2 ( qm27 ) embryos ) . Cell division defects were consistently detected in three lineages: ABarp , C and D ( Fig 6 ) . The color markings drawn on the wild-type lineage trees illustrate the frequency of defects that occurred in the six aptf-2 ( qm27 ) mutant embryos analysed . Strikingly , failure in aptf-2 ( qm27 ) cell division occurs mostly in three lineages: ABarp , C and D with the Caaaa division absent in all six aptf-2 ( qm27 ) embryos analysed . The missing divisions resulted in the absence of epidermal seam cells and neuroblasts in the AB lineage and the absence of epidermal cells from the main body syncytium ( hyp7 ) , body wall muscle cells in the C and most of the D lineage ( Fig 6 and S4 Table ) . In other cell lineages cell divisions appeared to be normal , except for an occasional division absent in the ABala or MSa lineages ( S2–S14 Figs ) . We used embryos co-expressing HIS::mCherry and the translational fusion of APTF-2::GFP driven by the aptf-2 promoter to follow the subcellular localization of APTF-2 in specific cells during embryogenesis ( Fig 6A ) . We found that in most cells APTF-2 is found uniformly in the nucleus and the cytoplasm . However , in certain cells at specific times during development , APTF-2 was enriched within the nucleus . Based on the lineaging of two embryos for 210 minutes we found significant nuclear enrichment of the APTF-2::GFP signal in neuroblasts and epidermal cells in AB lineage during ventral cleft closure and in epidermal cells in C lineage preceding dorsal intercalation ( Fig 7B and S15 Fig ) . However , there does not appear to be a strong correlation between nuclear enrichment of APTF-2 and defects in cell division . While a high degree of nuclear enrichment was found in the C and ABarp lineages , in which the absence of cell division in aptf-2 ( qm27 ) embryos occured in 6/6 embryos , a high degree of nuclear enrichment was also found in ABpra and ABpla lineages that did not experience any defects in cell division . Similarly , in the D lineage , which did not show much nuclear enrichment , the failure in cell division was frequently observed . In light of the specific nuclear enrichment of APTF-2 in the cell lineages where we observed defects in cell division timing in the aptf-2 ( qm27 ) hypomorph , we wondered whether the mutant protein has a defect in nuclear enrichment . To test this possibility we introduced into the APTF-2::GFP construct the same point mutation present in the qm27 allele . As shown in Fig 8A , the mutant protein had no problem in becoming enriched in neuroblast nuclei during ventral cleft closure . To the contrary , once the mutant APTF-2 entered the nucleus , it appeared to remain enriched in the nucleus for longer than the wild-type protein . This raised the question whether abnormal nuclear retention of APTF-2 could explain the defects in aptf-2 ( qm27 ) . To address this question we engineered an APTF-2::GFP flanked by two nuclear localization signals from SV40 and EGL-13 and expressed it in aptf-2 ( qm27 ) and aptf-2 ( gk902 ) embryos . In contrast with wild-type APTF-2::GFP , APTF-2::NLS::GFP was continuously and exclusively nuclear in all cells in which it was expressed ( Fig 8B ) . Importantly , expression of the constitutively nuclear APTF-2 was able to significantly rescue embryonic lethality of aptf-2 ( qm27 ) and aptf-2 ( gk902 ) ( Fig 8C and S5 Table ) . These findings suggest that the aberrant nuclear localization of mutated APTF-2 does not explain its functional defects . The worm genome encodes for four AP2-like transcription factors ( S16 Fig ) . APTF-1 is expressed in only five head interneurons and is required for a sleep-active neuron to induce lethargus in molting larvae [21] . To test whether APTF-3 and/or APTF-4 may play a role in embryonic development we depleted zygotic and maternal products of the genes by RNAi and tested for embryonic lethality in the progeny . Knockdown of aptf-3 did not result in any embryonic lethality . In contrast , knockdown of aptf-4 resulted in 26 ± 3% embryonic lethality . Moreover , hatched aptf-4 ( RNAi ) larvae often exhibited body morphology defects reminiscent of the defects observed in aptf-2 mutants ( Fig 9A ) . The deletion allele aptf-4 ( gk582 ) resulted in 100% larval arrest of homozygous worms , precluding analysis of embryonic phenotypes . Closer examination of embryonic development by 4D DIC and fluorescence microscopy revealed defects in dorsal intercalation , ventral cleft closure , and elongation ( Fig 9B–9D , S4 Movie ) . To test whether APTF-2 and APTF-4 work independently or cooperatively in the regulation of epidermal morphogenesis we tested the combined effect of aptf-4 KD in the background of aptf-2 ( qm27 ) . We found the embryonic lethality upon co-depletion of aptf-2 and aptf-4 to be higher than the sum of the lethality of single depletions , suggesting synergy between aptf-2 and aptf-4 ( Fig 8E and S6 Table ) . As AP-2 transcription factors are believed to function as heterodimers in some cases [26] , one possibility is that aptf-2 and aptf-4 work cooperatively . 4D DIC movie analysis revealed that 100% of the dorsally oriented dual-depleted embryos had dorsal intercalation defects and arrested during elongation and 57% of the ventrally oriented dual-depleted embryos displayed ventral cleft closure defects and 100% of them arrested in elongation ( S7 Table ) . We used expression data for APTF-4 from the EPIC dataset ( http://epic . gs . washington . edu/ ) to compare the nuclear expression pattern between APTF-2::GFP and APTF-4::GFP ( S17 Fig ) . Both APTF-2::GFP and APTF-4::GFP showed similar nuclear enrichment in the AB and C lineages , consistent with their cooperativity in embryogenesis .
Vertebrates and C . elegans AP-2 TF genes share high sequence similarities in their functional domains , although the duplications leading to four family members appear to have occurred independently in C . elegans and in vertebrates ( S16 Fig ) . In this study , we report that partial loss of aptf-2 or aptf-4 resulted in body morphological defects . Patients with BOFS suffer from skin defects while complications associated with Char Syndrome result from derangement of neural-crest-cell derivatives [17 , 18] . Our findings from the characterization of aptf-2 ( qm27 ) share similarity with the pathological manifestation of BOFS and Char Syndrome patients in epidermal and neuronal tissues . The mutation in the aptf-2 ( qm27 ) allele lies in the basic region of the DNA binding domain , a region that was defined as a mutation hotspot for BOFS and Char Syndorme in the human TFAP2A and TFAP2B genes [17–20] . At least 24 mutations in the basic region have been identified for BOFS and five for Char Syndrome [18 , 20 , 27] . It is challenging to determine the genotype-phenotype relationship in BOFS and Char Syndrome patients due to the small sample size and the large spectrum of mutations affecting TFAP2A and TFAP2B . With recent advances in site-targeted mutagenesis in the C . elegans genome , it is an exciting possibility to generate worm strains carrying mutations of conserved residues in BOFS and Char Syndrome . The aptf-2 ( gk902 ) allele results in a frame shift , generating a null allele . The massive apoptotic phenotype observed following a complete loss of APTF-2 in aptf-2 ( gk902 ) embryos is drastically different from the epidermal morphogenesis defects observed when APTF-2 activity is partially compromised as with the aptf-2 ( qm27 ) allele . This suggests different thresholds of AP-2 transcriptional activity are required for different cellular functions . Interestingly , in Char Syndrome patients , hypomorphic mutations in TFAP2B result in congenital heart defect , whereas a complete deletion of the mouse ortholog , AP-2β , leads to polycystic kidney disease due to excessive apoptosis of renal epithelial cells [14 , 18] . In murine models , depletion of AP-2γ resulted in defective epidermal development due to delayed expression of epidermal differentiation genes [28] . This is consistent with our observation that aptf-2 mutants showed epidermal morphogenesis defects . Neural crest defects in mouse , zebrafish and Xenopus embryos have been attributed to loss of AP-2 transcription factors [1 , 29 , 30] , parallel to the neuroblast migration defect we observed in the C . elegans embryo . Earlier expression studies of AP-2 transcription factors were largely conducted in mice , Drosophila and Xenopus by observing in-situ hybridization and staining patterns [5 , 16 , 31–33] . Our work in the live C . elegans embryo provided spatio-temporal information at a resolution not described previously . We observed APTF-2::GFP to be enriched in the nuclei of neuroblasts and epidermal cells during ventral enclosure and dorsal intercalation respectively , lack of which ( in the case of the mutant ) resulted in aberrant cell division in the epidermal and neuroblast lineages . Thus , our work identified lineage-specific regulation of cell division timing by APTF-2 . Similar mechanisms could be at play in mammals . Interestingly , we observed that nuclear enrichment of APTF-2 does not always correlate with regulation of cell division , as in the case of D , suggesting that a lower level of nuclear APTF-2 may be required for the division in this lineage . In contrast , nuclear APTF-2 enrichment was observed in ABpra and ABpla and yet an absence of cell division was not been observed in these lineages in aptf-2 ( qm27 ) embryos , indicating that either a stronger APTF-2 depletion is required to see cell division defects or APTF-2 plays a different role in these two lineages . Although various members of the vertebrate AP-2 transcription family have been shown to have overlapping expression patterns , knockout studies in mice revealed specific and localized phenotypic defects . For example , Moser et . al . showed that the AP-2α and AP-2β expression in mouse embryos overlap significantly , [16] , but the single knockout models of each gene did not share any phenotypic defects , suggesting non-redundant roles of the two genes [14] . In contrast to the vertebrate system , our results showed both similar phenotypes and similar expression pattern , mostly in AB and C lineages of aptf-2 and aptf-4 in the worm . The fact that their effect is synergistic suggests they may partially function through the same pathway . For wild-type APTF-2::GFP , expression in the majority of cells was evenly distributed between the nucleus and cytoplasm and was enriched in the nucleus of neuroblasts during ventral cleft closure and in epidermal cells preceding dorsal intercalation . It is possible that APTF-2 functions to regulate gene expression at a basal level , while enrichment in the nucleus of specified cells during epidermal morphogenesis upregulates genes required for proliferation of the neuroblasts and epidermal cells . This would be consistent with observations in Drosophila , where different levels of AP-2 have been shown to result in a variety of morphological defects [32] . AP-2 transcription factors are known to play a dual role as transcription activators and repressors [33] . Pfisterer et . al . identified multiple genes repressed by AP-2α known to induce apoptosis and retards proliferation [34] . There has also been evidence in Xenopus epidermal development regarding the importance of AP-2 TF in promoting the expression of epidermal specific genes [31] . We used TargetOrtho to identify putative APTF-2 targets . Among the candidates , we tested die-1 , a well known regulator of epidermal dorsal intercalation , and observed the reduction of DIE-1 nuclear signal in aptf-2 ( qm27 ) embryos , suggesting that DIE-1 is likely a target of APTF-2 . Future work must determine APTF-2 target genes in neuroblasts and epidermal cells in order to further elucidate its function during morphogenesis . In conclusion , we have characterized a hypomorphic mutant of C . elegans APTF-2 and have shown it to share genetic and anatomical similarities with human Char Syndrome and Bronchio-occular-facial Syndrome . We propose mutations in C . elegans AP-2 TF genes can serve as disease models to study the cellular mechanisms and tissue dynamics that lead from mutant genotype to disease phenotype .
Strains were maintained at 20°C under standard conditions [35] . Wild-type Bristol strain N2 was used as a control . The aptf-2 ( qm27 ) IV line was retrieved in an EMS screen conducted by Hekimi et al . [22] and aptf-2 ( gk902 ) was generated by the C . elegans Reverse Genetics Core Facility at the University of British Columbia and was maintained as heterozygotes using the nT1[qIs51] ( IV;V ) balancer . For analysis using GFP reporters , F2 progeny exhibiting aptf-2 phenotypes and carrying the markers were selected from crosses between aptf-2 ( qm27 ) and the following strains: FT250 xnIs96 [pJN455 ( hmr-1p::hmr-1::GFP::unc-54 3'UTR ) + unc-119 ( + ) ] [36] , SU265 jcIs17[hmp-1p::hmp-1::gfp , dlg-1p::dlg-1::dsRed , rol-6p::rol-6 ( su1006 ) ] [37] , OH904 otIs33[kal-1p::gfp] [38] , RW10029 zuIs178 [his-72 ( 1kb 5' UTR ) ::his-72::SRPVAT::GFP::his-72 ( 1KB 3' UTR ) + 5 . 7 kb XbaI—HindIII unc-119 ( + ) ] . stIs10024 [pie-1::H2B::GFP::pie-1 3' UTR + unc-119 ( + ) ] ( a gift from Waterston lab ) and JIM119 zuIs178 [his-72 ( 1kb 5' UTR ) ::his-72::SRPVAT::mCherry::his-72 ( 1KB 3' UTR ) + 5 . 7 kb XbaI—HindIII unc-119 ( + ) ] . stIs10024 [pie-1::H2B::mCherry::pie-1 3' UTR + unc-119 ( + ) ] ( a gift from Waterston lab ) . die-1::gfp reporter strain was a gift from Hardin lab [25] . To construct plasmids containing wild-type or mutated aptf-2 , the aptf-2 promoter ( 2 kb sequence upstream of aptf-2 start codon ) followed by the aptf-2 coding sequence were amplified from N2 and aptf-2 ( qm27 ) animals , respectively and inserted into XbaI and AgeI sites upstream of gfp in the original pPD95 . 75 vector . The wild-type aptf-2-containing plasmid was injected into the gonad of aptf-2 ( qm27 ) hermaphrodite animals to examine its potency in rescuing aptf-2 ( qm27 ) phenotypes , whereas the plasmid containing mutated aptf-2 was injected into N2 . This resulted in the following transgenes: msnEx15 [aptf-2p::aptf-2::gfp; rol-6 ( su1006 ) ]; aptf-2 ( qm27 ) and msnEx239 [aptf-2p::mutated aptf-2::gfp; rol-6 ( su1006 ) ] . Ten L4 larvae expressing wild-type aptf-2 were subjected to a UV source ( BioRad ) for 15 seconds to integrate the extrachromosomal array into the genome . Three hundred F2 worms were then singled and incubated for three weeks and subsequently examined for expression and embryonic lethality . Those expressing the transgene and giving rise to 100% viable progeny were selected and outcrossed . The resulting strain , RZB104 ( aptf-2 ( qm27 ) ; msnIn104[aptf-2p::aptf-2::gfp; rol-6 ( su1006 ) ] ) , was used throughout this study . To construct aptf-2 tagged with a nuclear localization signal ( NLS ) , the amplified 4 . 3 kb genomic sequence containing the aptf-2 promoter and the coding region was inserted into XbaI and XmaI sites in pNL74 . 4 [39] , a modified pPD95 . 75 containing SV40 and EGL-13 NLS flanking the N and the C terminal of the gfp sequence , respectively . The plasmid was injected into the gonad of N2 hermaphrodites and resulted in transgene msnEx103 [aptf-2p::aptf-2-NLS::gfp; rol-6 ( su1006 ) ] ) . The transgenic animals were then crossed with aptf-2 ( qm27 ) or aptf-2 ( gk902 ) to assess the ability of NLS-tagged APTF-2 to rescue the aptf-2 mutants . Microinjection was performed as described by Mello and Fire [40] . Injection mix included 100 μg/μl salmon sperm DNA digested with PvuII , 20 μg/μl rol-6 ( su1006 ) digested with SbfI and 5–10 μg/μl each construct digested with SbfI . Genomic DNA was extracted from mal-1 ( qm27 ) mutant worms using standard method and subjected to whole genome sequencing using Illumina platform and annotated using MAQGene [41] . The whole genome sequencing and its annotation were performed by Hobert lab ( Columbia University ) . Candidate genes altered in mal-1 ( qm27 ) were narrowed down using genetic mapping results done by Hekimi et al . [22] . Point mutation in aptf-2 gene was confirmed by amplification of aptf-2 gene in aptf-2 ( qm27 ) mutant worms , subcloning into pJET vector ( Thermo Scientific ) and followed by conventional sequencing ( First Base ) . For complementation assay , aptf-2 ( gk902 ) /nT1[qIs51] males was crossed with aptf-2 ( qm27 ) hermaphrodites . Non-GFP F1 animals were singled and incubated to lay embryos for 24 hours . The F1 animals were genotyped for the gk902 deletion and only the cross progeny between qm27 and gk902 alleles was scored for embryonic lethality of their F2s . For brood size analysis , ten L4 larvae of wild-type , aptf-2 ( qm27 ) and aptf-2 ( gk902 ) were singled and incubated for 24 hours . Each animal was shifted to a new plate every day for 5 consecutive days to the point that no more embryos were laid . The total number of embryos laid was determined as the brood size . The number of hatched animals was calculated and used to determine the percentage of embryonic lethality . Larvae that did not grow into adult in 48–92 hours after hatching were considered as being arrested . aptf-2 ( qm27 ) and aptf-2 ( gk902 ) larvae of any stage were subjected to phenotypic analysis to determine the presence and the position of the morphological defects . Besides wild-type , aptf-2 ( qm27 ) and aptf-2 ( gk902 ) animals whose embryonic lethality was determined as described above , the embryonic lethality of the remaining strains were determined as follows: ten to fifteen gravid hermaphrodites were placed on the plate and incubated at 20°C for several hours to lay more than 100 embryos . Hermaphrodites were then removed and the number of embryos laid was counted . Twenty-four hours later , the number of larvae hatched was determined . Each experiment was repeated at least five times . Larvae or embryos collected from gravid hermaphrodite were mounted onto 3% agarose-padded glass slide , closed with a coverslip and sealed with wax . DIC images shown in Figs 1A , 3A , 3B , 3C , 8A , 8C , 8E and S1A were captured using a Nikon Ti Eclipse widefield microscope equipped with DIC 1 . 40NA oil condenser and a charged-coupled device camera Cool Snap HQ2 ( Photometrics ) . All other images and movies were acquired using a spinning disk confocal system composed of a Nikon Ti Eclipse microscope with a CSU-X1 spinning disk confocal head ( Yokogawa ) , DPSS-Laser ( Roper Scientific ) at 491 and 568 nm excitation wavelengths and an Evolve Rapid-Cal electron multiplying charged-coupled device camera ( Photometrics ) . For both microscopes , Metamorph software ( Molecular Devices ) was used to control acquisition . Projected images were created using Fiji . All imaging was done at 20°C in an environmental chamber encompassing the microscope stage heated by a JCS temperature controller ( Shinko Technos Co , Japan ) within a microscope room kept at 18°C by a CITEC precision air conditioning unit . aptf-4 dsRNA was synthesized as described [42] and injected into the gonad of twenty wild-type or aptf-2 ( qm27 ) L4 larvae . Each animal was singled into a separate plate and its embryonic lethality was examined 24 hours post injection . Protein sequence of the AP-2 transcription factor family members in the following metazoan species were aligned using Constraint-based Multiple Protein Alignment Tool ( COBALT ) [43]: A . queenslandica ( sponge ) , T . adhaerens ( Placozoa ) , C . elegans ( nematode ) , N . vectensis ( sea anemone ) , D . melanogaster ( fruit fly ) , S . purpuratus ( sea urchin ) , C . intestinalis ( tunicate ) , B . floridae ( lancelete ) , D . rerio ( fish ) , X . tropicalis ( frog ) , G . gallus ( chicken ) , H . sapiens ( human ) . The resulting alignment was used to build and visualize a phylogenetic tree ( neighbor-joining method ) using Geneious ( Biomatters Ltd . ) . Illustration of the gene and protein architecture was drawn using Illustrator for Biological Sequences [44] . AP-2 has been shown to bind to the palindromic consensus sequence 5'-GCCN3GGC-3' , as well as the binding motif 5'-GCCN3/4GGG-3' [2] . We used either the 9bp or 10bp motif as an input for TargetOrtho [23] . From the program output we selected only putative targets that are conserved in at least 4 Caenoharbditis species , and are located within the 3 kb region upstream of the start codon . Functional annotation was performed using DAVID Bioinformatics Resources 6 . 7 [45 , 46] and the threshold we used for enrichment was an EASE score equal or smaller than 0 . 05 . For cell lineaging , six aptf-2 ( qm27 ) embryos expressing nuclear signal of GFP::HIS-72 and two embryos co-expressing APTF-2::GFP and mCherry::HIS-72 were analysed for at least 270 minutes according to the protocol described in [47–49] . The lineage tree was built using AceTree [50] and compared to that of wild-type . To visualize the temporal enrichment of the nuclear APTF-2::GFP signal during embryogenesis , the minimum/ maximum threshold values were set to display the 75% highest signal . All movies used for lineaging in this paper can be downloaded from http://epic2 . gs . washington . edu/Epic2 . Statistical analyses were done using Prism 6 ( GraphPad Software , La Jolla , CA ) . Two-tailed Student’s t-test was applied to compare the values .
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Mutations in the evolutionarily conserved family of AP-2 transcription factors are associated with multiple birth defects in Char syndrome and Brancio-oculo-facial syndrome . These DNA-binding proteins are known to regulate the proliferation , differentiation and death of specific cells during embryonic development but how point mutations in the AP-2 DNA-binding domain lead to these diseases during development is currently unknown . We have identified a mutation in one of the AP-2 orthologs of the nematode Caenorhabditis elegans , APTF-2 , which falls in the same mutation hotspot as in human Char syndrome and Brancio-oculo-facial syndrome patients . Compromised APTF-2 activity in C . elegans results in embryonic lethality and embryos that survive to hatching displays body morphological defects , reminiscent of the aforementioned human diseases . Using time-lapse microscopy , we found that misregulation of cell division in the skin , muscle and neuronal cell lineages is the primary cause of developmental arrest . Our study provides insight into the regulation of cell division timing by AP-2 transcription factors and provides a model to study human diseases associated with AP-2 mutations .
|
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2016
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The AP-2 Transcription Factor APTF-2 Is Required for Neuroblast and Epidermal Morphogenesis in Caenorhabditis elegans Embryogenesis
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Algorithms to diagnose gambiense human African trypanosomiasis ( HAT , sleeping sickness ) are often complex due to the unsatisfactory sensitivity and/or specificity of available tests , and typically include a screening ( serological ) , confirmation ( parasitological ) and staging component . There is insufficient evidence on the relative accuracy of these algorithms . This paper presents estimates of the accuracy of five algorithms used by past Médecins Sans Frontières programmes in the Republic of Congo , Southern Sudan and Uganda . The sequence of tests in each algorithm was programmed into a probabilistic model , informed by distributions of the sensitivity , specificity and staging accuracy of each test , constructed based on a literature review . The accuracy of algorithms was estimated in a baseline scenario and in a worst-case scenario introducing various near worst-case assumptions . In the baseline scenario , sensitivity was estimated as 85–90% in all but one algorithm , with specificity above 99 . 9% except for the Republic of Congo , where CATT serology was used as independent confirmation test: here , positive predictive value ( PPV ) was estimated at <50% in realistic active screening prevalence scenarios . Furthermore , most algorithms misclassified about one third of true stage 1 cases as stage 2 , and about 10% of true stage 2 cases as stage 1 . In the worst-case scenario , sensitivity was 75–90% and PPV no more than 75% at 1% prevalence , with about half of stage 1 cases misclassified as stage 2 . Published evidence on the accuracy of widely used tests is scanty . Algorithms should carefully weigh the use of serology alone for confirmation , and could enhance sensitivity through serological suspect follow-up and repeat parasitology . Better evidence on the frequency of low-parasitaemia infections is needed . Simulation studies should guide the tailoring of algorithms to specific scenarios of HAT prevalence and availability of control tools .
The diagnosis of gambiense human African trypanosomiasis ( HAT , sleeping sickness ) in routine conditions is complex [1] . Because infection prevalence is usually low ( <1–2% ) , diagnostic tests require a high sensitivity and specificity to achieve adequate positive predictive value ( PPV ) . Furthermore , accurate classification into stage 1 ( haemo-lymphatic ) and 2 ( meningo-encephalitic ) is crucial: the stage 1 treatment , pentamidine , is inefficacious for stage 2 due to limited blood brain barrier penetration [2] , while , of the two stage 2 treatments , melarsoprol is highly toxic [3] and eflornithine-nifurtimox is cumbersome to administer . No single HAT diagnostic test currently offers satisfactory sensitivity and specificity . Diagnostic algorithms therefore combine several tests and feature a screening , confirmation and staging component . The Card Agglutination Test for Trypanosomiasis ( CATT ) [4] , highly sensitive when performed in whole blood ( CATT-wb ) but insufficiently specific ( <96% ) , is used for screening . After CATT-wb or CATT plasma screening , various parasitological confirmation tests are applied either alone or in sequence on blood and/or neck gland aspirate , so as to maximise specificity while maintaining acceptable levels of sensitivity . Various dilutions of the CATT in plasma ( between 1∶4 and 1∶16 ) may also be performed ahead of parasitology to reduce the number of individuals needing parasitological testing . Parasitological positives ( T+ ) undergo lumbar puncture and are classified as stage 2 if parasites are found in cerebrospinal fluid ( CSF ) , or if a given threshold of CSF white blood cell ( WBC ) density ( ranging from 5 to 20/µL ) is exceeded [5] . Individuals with strong CATT reactions ( dilutions ≥1∶4 ) but no parasitological evidence of infection ( T− ) are generally considered serological suspects . Some control programmes follow-up suspects for up to one year , repeating parasitological tests . Others consider them non-cases or treat them presumptively . The underlying infection prevalence affects the relative efficiency of these different strategies [6] , [7] , [8] . The accuracy of HAT diagnostic algorithms has not been documented in detail , partly because their complexity precludes straightforward analysis . Here , we present estimates of the accuracy of five different diagnostic algorithms used by Médecins Sans Frontières ( MSF ) in past gambiense HAT control programmes using summary estimates of reported accuracy of individual HAT tests and a probabilistic model .
The five algorithms ( shown in Figures 1 to 5 ) were used in projects in the Republic of Congo ( Gamboma , Plateaux Region , 2001–2003; Mossaka , Cuvette Region , 2003–2005; Nkayi , Bouenza Region , 2003–2005 ) ; Southern Sudan ( Kiri , Kajo Keji County , Central Equatoria , 2000–2007 ) ; and Uganda ( Adjumani District , 1991–1996; Arua and Yumbe Districts , 1995–2002 ) . The Southern Sudan project made progressive modifications to its algorithm , but only the first ( old ) and the last ( new ) algorithms used by that project are assessed here . As initial screening tests , all algorithms used the CATT-wb , and the Congo and Sudan algorithms also used systematic gland palpation among CATT-wb negatives . Parasitology ( performed on the field during active screening ) included microscopic examination of aspirate from punctured palpable cervical glands ( GP ) [9] , done in all algorithms , complemented by capillary tube centrifugation ( CTC or the Woo test [10]; theoretical detection limit 100 parasites/mL , reported limit 500–600/mL ) or the Quantitative Buffy Coat ( QBC; 15/mL , 15–300/mL ) technique [11] in Southern Sudan , and the mini anion exchange centrifugation technique ( mAECT; 5/mL , 15–100/mL ) [12] or QBC in Uganda . Furthermore , the Southern Sudan algorithms used the QBC as the parasitological test during passive screening ( testing of patients spontaneously presenting to a HAT treatment centre ) , and the CTC during active screening . All programmes initially did systematic follow-up of serological suspects , but this was eventually stopped in Congo and Kiri due to low follow-up rates and high workload; in Kiri , this strategy was replaced with systematic treatment of suspects positive at CATT dilution ≥1∶16 , later restricted to villages with observed prevalence ≥2% . The Congo algorithm treated CATT≥1∶8 positive but T− individuals as cases regardless of CSF WBC density . Staging of HAT in T+ ( and CATT≥1∶8 positive in Congo ) individuals was done at the fixed treatment centre by lumbar puncture and double centrifugation of the CSF ( CSF-DC ) . If CSF-DC revealed no parasites , staging was based on WBC density thresholds . These thresholds were either >5 or >10/µL as per country guidelines [13] . With the exception of Congo , all algorithms performed LP in T− but CATT dilution ( ≥1∶4 or ≥1∶16 ) positive individuals for simultaneous confirmation and staging . For these patients , the WBC density threshold was increased to >20/µL; furthermore , those not meeting stage 2 criteria were not automatically considered stage 1 cases , but rather suspects , creating a differential in sensitivity according to whether the case was stage 1 or stage 2 . Differences among algorithms reflect adherence to national HAT guidelines ( for example , in Congo the WBC threshold was higher ) ; the availability on the market of certain parasitological tests at different times ( for example , the mAECT is a more recent development and interruptions in the production line have occurred ) ; different operational strategies ( in Congo MSF aimed to cover a large , sparse territory with single active screening visits with the overriding objective of maximum coverage and thus sensitivity ) ; and , to some extent , decisions by individual programme coordinators or MSF sections ( in the past decade , an inter-sectional working group has worked toward greater standardisation ) . Medline PubMed searches were conducted with the MeSH terms “Trypanosomiasis , African/diagnosis” , and with combinations of [“trypanosomiasis”/“trypanosomosis”/“trypanosome”/“sleeping sickness”] and [“screening”/“confirmation”/“diagnosis”/“stage”/“staging”/“diagnostic”/“card agglutination test”/“CATT”/“gland”/“woo”/“capillary tube centrifugation”/“mini-anion exchange”/“buffy coat”/“cerebrospinal fluid”/“lumbar puncture”/“white blood cell”/“leucocyte”/“polymerase chain reaction”/“IgM”] . The bibliographic trail of each paper was followed to its exhaustion where appropriate , and several reviews [1] , [14] , [15] were consulted . The search was limited to the period from January 1970 to June 2007 . Studies were included in the review only if they had tested the accuracy of T . brucei gambiense diagnosis among untreated cases , and if they featured an acceptable diagnostic gold standard , defined as follows: ( i ) for screening and confirmation tests , testing with GP or CTC and at least one of the following: QBC , mAECT , enzyme linked immunosorbent assay ( ELISA ) , Kit for In Vitro Identification ( KIVI ) , or animal inoculation; ( ii ) for the specificity of the CATT-wb , testing of individuals not living in HAT endemic areas; ( iii ) for staging tests , testing of CSF , among T+ cases only , with polymerase chain reaction ( PCR ) , in vitro culture , or immunological markers of infection including raised IgM levels [16] . Studies that were not designed for testing validity , but contained sufficient data for accuracy estimation , were included . In some studies , we considered the experimental test used by investigators as the gold standard , and vice versa: in these cases , we inverted the two and re-calculated accuracy . The accuracy of CATT dilutions was only evaluated from studies among CATT-wb positives , since the algorithms only performed such dilutions after the CATT-wb screening , i . e . the parameter of interest was relative accuracy compared to the CATT-wb . Reports of CATT accuracy from foci where parasites frequently lack the LiTat1 . 3 gene [1] ( Nigeria , Cameroon ) were excluded . Details on studies meeting inclusion criteria are provided in Text S1 , and the amount of information available for each diagnostic test is summarised in Table 1 . An additional nine studies were excluded from either the sensitivity or specificity reviews because the gold standard was inadequate [17] , [18] , [19] , [20] , [21] , [22] or the study design did not allow for diagnostic accuracy estimation [23] , [24] , [25] . One study of staging accuracy [26] was excluded because the IgM threshold used was deemed too high . Individual estimates of test accuracy were combined into probability distributions for further modelling . Distributions for the accuracy of successive CATT dilutions were constructed by fitting polynomial functions to plots of available sensitivity or specificity point estimates versus the natural logarithm of the dilution , with observations weighted proportionately to each study's sample size ( Figure S1a , Figure S1b in Text S1 ) . The fitted values and their 95% confidence intervals at each dilution of interest were used to construct binomial distributions . Probability distributions for other tests were constructed as follows . First , exact binomial probability distributions were built around the point estimate of each study . Second , each study's distribution was weighted proportionately to the study's sample size . Third , the individual study distributions were summed , and the resulting distribution was scaled so that the area under the curve totalled unity . An illustration is provided for the CTC ( Figure 6 ) . For the QBC , there was only one published estimate of sensitivity , from a small study ( n = 11 ) . The technique is reported to have similar sensitivity to the mAECT [12] , [20] , which is plausible given their comparable detection limits: therefore , the same distribution was used for the QBC as for the mAECT . Finally , the specificity of parasitological tests for confirmation was fixed at 100%: the presence of trypanosomes is unequivocal , and trained microscopists should ordinarily not report false positives . For the purpose of planning for long-term transmission control , it might be useful to consider minimum requirements to guarantee success even if conditions in reality are less favourable than published evidence suggests . Accordingly , more conservative accuracy estimates were obtained by applying a set of worst-case scenario assumptions ( Table 2 ) . These assumptions sought to account for the fact that even the most sensitive tests ( QBC , mAECT ) are likely to miss low parasitaemias ( <5–15 trypanosomes/mL ) . Studies of T- suspects , based on PCR assays for T . brucei s . l . [27] featuring 100% specificity in controls from non-endemic regions [28] , [29] , [30] , [31] , have reported 22% positivity in Cameroon [30]; 19–37% in the Ivory Coast [29]; and 15% in Equatorial Guinea and Angola [32] . R software was used to program the different algorithms into a sequence of conditional probabilities , so as to calculate sensitivity , specificity , and staging accuracy ( defined as the probability of being correctly classified into either stage ) of the algorithm as a whole , given any values of accuracy for individual tests . Equations for the accuracy estimation of each algorithm are provided in Text S1 . Because some algorithms used CSF-DC and WBC count for confirmation as well as staging , sensitivities vary according to whether the true positive case is in stage 1 or stage 2 , and were thus computed separately . Furthermore , scenarios with and without follow-up of serological suspects were evaluated , i . e . assuming none or all such cases are re-tested according to the stipulated schedule ( in practice , the follow-up rate varies by site [33] ) . The sensitivity and specificity of any given test for the baseline scenario were specified by the probability distributions constructed above , summarised in Table 3 . The model was run 10 000 times for each algorithm and for both the baseline and worst-case ( incorporating the adjustments in Table 2 ) scenarios . During each run , a random value was sampled from each input probability distribution . Median sensitivity , specificity and staging accuracy were then computed based on the output distribution of results from the 10 000 runs , along with their 95% percentile interval ( i . e . the interval comprising 95% of the run results ) . The resulting negative and positive predictive values ( NPV , PPV ) were also calculated assuming 0 . 1% , 1% or 10% infection prevalence . The ratio of non-cases needlessly treated to true cases treated ( over-treatment ratio ) was also calculated for each algorithm and prevalence scenario , assuming a stage 1 to stage 2 ratio of two among prevalent infections detected actively in never-before screened communities , consistent with empirical observations in most MSF projects ( Francesco Checchi , unpublished observations ) . However , this assumption is of negligible importance: the converse ( a ratio of 0 . 5 ) would result in nearly identical estimates ( data not shown ) , since differences in sensitivity between stage 1 and stage 2 are small and of limited influence given that HAT is a low-prevalence infection ( PPV and NPV are largely determined by specificity ) .
Accuracy estimates for the baseline scenario are shown in Table 4 . Sensitivity including suspect follow-up was highest in Congo , and considerably lower than elsewhere for the new Kiri algorithm , which screened out cases negative at a high CATT dilution ( <1∶16 ) . Specificity was 99 . 9% or 100% everywhere with the exception of Congo ( 99 . 1% ) . The theoretical sensitivity gain from suspect follow-up was considerable: about 3–4% everywhere , but 10–20% in Kiri , where T− , CATT dilution ≥1∶4 positives were followed up . There was no appreciable specificity cost from suspect follow-up . Algorithms were predicted to misclassify about one in ten of the stage 2 cases as stage 1; conversely , about one third of stage 1s were treated as stage 2 , with the exception of Congo , where the higher WBC threshold ( >10/µL ) resulted in a small increase in stage 2 misclassification , but only 13% stage 1 misclassification ( note however the wide percentile intervals ) . In the worst-case scenario ( Table 5 ) , sensitivity was 10–15% lower everywhere except for Congo ( where conservative assumptions mostly did not affect the CATT≥1∶8 dilution test ) , and around 50% for the new Kiri algorithm . Specificity decreased below 99 . 8% except for the new Kiri algorithm . Stage misclassification affected more than half of stage 1 cases . Overall , the Congo and new Kiri algorithms offered opposite extreme characteristics: the former guaranteed very high sensitivity but had low specificity; the latter was highly specific even under worst-case scenario assumptions , but had low sensitivity . NPV was uniformly high ( Table 6 ) . Because of low specificity , the predicted PPV of the Congo algorithm was also low at most plausible prevalence levels ( <50% for any prevalence <1% ) , resulting in a high over-treatment ratio . Because PPV is extremely sensitive to minimal changes in specificity , predicted PPVs with high specificity values should be interpreted with caution ( e . g . in Uganda , median specificity was 99 . 94% , but was rounded to 99 . 9% , which results in a 20% decrease in PPV at prevalence 0 . 1% ) . Only the new Kiri algorithm achieved perfect PPV at any prevalence ( however , the resultant elimination of over-treatment was counterbalanced by a policy of treating serological suspects with pentamidine in high-prevalence villages ) .
This study suggests that diagnostic algorithms previously used by MSF had a sensitivity of 85–90% in a baseline scenario analysis , except for an algorithm in Southern Sudan in which only individuals CATT≥1∶16 positive underwent blood and CSF parasitological exams . At least theoretically , and irrespective of its efficiency and cost-effectiveness , the follow-up of serological suspects does yield an appreciable increase in sensitivity; however , this benefit may largely be negated in the field because of low suspect follow-up rates ( suspect follow-up is costly as it often requires active patient tracing ) . Among other studies of HAT diagnostic algorithms ( all starting with CATT-wb positivity ) , Miezan et al . [34] found sensitivities of 94 . 8% , 98 . 3% and 91 . 4% for the [GP+CTC+CSF-DC] , [GP+mAECT+CSF-DC] and [GP+mAECT] combinations , respectively; Robays et al . projected sensitivity 76 . 6% for the mAECT [35]; Lutumba et al . estimated a sensitivity of 86% for the [GP+CTC] combination [36] . All algorithms also appeared to have an acceptable PPV except for Congo's , where serological diagnosis probably resulted in a high frequency of stage 1 false positives ( see below ) . Furthermore , reliance on the conventional HAT staging approach ( parasitology and WBC threshold of >5 leucocytes/µL ) may have captured the vast majority of stage 2 cases but misclassified about one third of stage 1 cases as stage 2: this harm-benefit ratio is nonetheless likely to be favourable , since the risk of death from undetected stage 2 HAT is probably 100% [37] , while the risk of death due to stage 2 drug toxicity among stage 1 cases misclassified as stage 2 is less than 5% , and <2% wherever eflornithine-nifurtimox has replaced melarsoprol as first-line treatment . Misclassification of stage 2 cases could partly be avoided by introducing some clinical criteria in the algorithm ( e . g . patients with typical signs and symptoms of stage 2 , and who are classified as stage 1 , should be retested or treated empirically ) . Our findings refer to the relatively favourable conditions of HAT diagnosis provided for by a well-resourced non-governmental organisation with access to the best available technology , ability to train and supervise staff and considerable field logistics . Many HAT programmes , particularly those implemented by national control programmes after humanitarian agencies and other donors discontinue support , do not dispose of such resources , and must use simpler algorithms , sometimes relying on blood smears and cervical node microscopy alone for parasitological testing in remote active screening campaigns . Such simple algorithms are likely to feature a much lower accuracy than those we have evaluated here: national programmes should receive continued technical and material support in order to offer adequate HAT diagnosis . While worst-case scenario estimates may be implausibly low , the question of whether current tests miss a larger proportion of cases than currently thought , as suggested by PCR data , should be explored further . While in non-endemic areas PCR appears extremely specific , among CATT-wb negatives in endemic areas PCR positives do occur: 4/73 ( 5 . 5% ) in Ivory Coast [29] , 3/222 ( 1 . 4% ) in Cameroon [30] , and 1/36 ( 2 . 8% ) in Equatorial Guinea and Angola [32] . These observations could be explained as ( i ) false PCR positives due to cross-reactivity with other antigens , including DNA from non-gambiense T . brucei s . l . transiently infecting the host; or ( ii ) true T . b . gambiense infections undetectable by other tests due to low parasite density . The former explanation is supported by the finding that a study in an Ivory Coast focus employing a PCR assay specific for T . b . gambiense yielded no PCR positives [31] , while all studies with high PCR positivity relied on non-gambiense specific assays . However , the Ivory Coast assay used had a detection limit comparable to the mAECT , and may have failed to detect cases of low parasitaemia ( by contrast , the non-gambiense specific Cameroon assay developed by Penchenier et al . [30] has a reported limit of 1/mL ) . The latter explanation requires the existence of infections that maintain extremely scanty parasitaemia and are not or only mildly pathogenic [37] . Better evidence should come from the development of T . brucei gambiense specific molecular assays that also have a detection limit appreciably lower than parasitology , and their application to long-term follow-up of T− serological suspects [38] . Estimating the true sensitivity of tests would require knowledge of the typical distribution of parasitaemias in human hosts , but this is difficult to measure precisely because of the detection limit of current methods ( presumably , if a large database of known parasite densities were assembled , the resulting distribution could be treated as truncated , and extrapolated below the minimum detection limit ) . Data on cattle are available , but may not apply to humans due to differences in host-parasite interactions . In the mean time , we suggest that worst-case assumptions be used for determining requirements of programmes aiming for long-term control or local elimination . Specificity is key to maximising PPV . Very low HAT infection prevalence ( e . g . <0 . 2% ) is common in many communities screened actively , implying poor PPV , considerable over-treatment , and inflated prevalence estimates for even the most specific algorithms considered here . However , in many programmes the majority of cases are detected passively . The prevalence of infection among individuals spontaneously presenting to the fixed HAT centre is higher , and was above 2% in all MSF programmes where these algorithms were used ( Table 7 ) . These observed prevalence figures suggest that PPV is generally high during passive screening ( >95% everywhere except Congo ) . Assuming reasonable laboratory quality , all parasitological tests are likely to be 100% specific , and reliance on these alone for confirmation should guarantee perfect PPV . By contrast , this study suggests that use of a CATT 1∶8 dilution positive test as criterion for confirming infection , irrespective of parasitological results , entails a heavy specificity price . Field data appear to corroborate this finding . Among true cases , the proportion diagnosed via the CATT 1∶8 dilution ( serologically ) should in theory not depend on HAT stage ( serological tests in blood are believed by some to be less sensitive in stage 2 , but no published evidence for this was found ) . On the other hand , among false positives , most cases diagnosed serologically would be classified as stage 1 , since during staging all would be negative for CSF-DC and most would have normal WBC density . A preponderance of stage 1 is thus indicative of considerable over-diagnosis . Within the three Congo sites , serological cases were 1559/2857 ( 54 . 6% ) of naïve ( previously untreated ) cases , of which 1364/1559 ( 87 . 5% ) were in stage 1 , compared to 624/1298 ( 48 . 1% ) of cases confirmed parasitologically . Furthermore , serological cases were 244/629 ( 38 . 8% ) of cases detected passively , and 1244/2152 ( 57 . 8% ) of cases detected actively . In a simple logistic regression model , both stage 1 classification and active screening were associated with serological diagnosis ( odds ratios 7 . 45 [95%CI 6 . 13–9 . 05] and 1 . 35 [95%CI 1 . 10–1 . 66] respectively ) . Altogether , these observations suggest considerable over-diagnosis of HAT ( nearly all classified as stage 1 ) in Congo . Inojosa et al . found a similarly low PPV of an algorithm based on the CATT 1∶8 dilution in Angola ( 13 . 2% with 0 . 07% prevalence ) [22] . Diagnosis through CATT serology does improve sensitivity considerably; however , we suggest that its use be restricted to ( i ) passive screening and ( ii ) active screening in remote communities with suspected high prevalence where there is likely to be only one opportunity for screening , and where melarsoprol is not used as first-line therapy or the algorithm minimises misclassification of stage 1 cases . Furthermore , we recommend use of a 1∶16 dilution in lieu of 1∶8 . Control programs that use algorithms with serological criteria aim to reduce transmission at the expense of over-treatment . However , the individuals diagnosed solely on serology should not be regarded as HAT cases for the calculation of prevalence , as this would result in an overestimation of disease burden and obscure prevalence changes over time . They should be clearly distinguished from genuine cases in programme reporting and surveillance . The main reason for lack of sensitivity of the parasitological tests is likely to be low parasite density . As HAT parasitaemia is known to undulate on a daily basis , some laboratories perform repeat blood parasitological tests so as to increase chances of detecting parasites . Repeat tests could be a simple way to improve sensitivity . Better evidence on the typical period between peak and trough parasitaemia would be helpful to optimise the timing of blood sampling . Clearly , keeping suspects for days at the treatment centre in order to repeat tests would present serious acceptability challenges; however , a single overnight might be feasible , and , furthermore , the selection of suspects in whom to perform repeat tests might also be restricted to those displaying typical signs and symptoms of HAT . These findings also have implications for burden estimation , since they introduce a need to adjust observed prevalence or incidence data for imperfect sensitivity , PPV below 100% due to low specificity ( particularly for active screening data ) , and unequal stage 1 and stage 2 misclassification probabilities . The literature review revealed a dearth of quality studies of HAT test accuracy , with the exception of the CATT-wb . Many were imprecise ( only two presented a sample size rationale ) and featured less than optimal gold standards . The mAECT , used in a variety of programmes , appears to be supported by only one large study , and for the QBC only one study was found . This uncertainty may introduce information bias in the construction of accuracy distributions . More specifically , the adoption of specificity estimates for the CATT from populations from non-endemic areas may have led to overly optimistic estimates ( this was partly addressed in the worst case scenario analysis ) . Our method of constructing accuracy distributions attempts to use existing data with minimal assumptions about their parametric form . Arguably , meta-analysis could have been used instead , with distributions provided by the confidence intervals of the summary estimates from pooled studies . However , preliminary analysis showed evidence of heterogeneity in study estimates for several HAT tests: under these conditions , meta-analysis is discouraged . Furthermore , there is lack of consensus on appropriate methods for meta-analysis of diagnostic test studies [39] , [40] . Bayesian approaches to diagnostic accuracy estimation [41] , [42] , which do not require a gold standard , could be a useful alternative to the method used here , and should also be explored . More generally , this study's theoretical estimates overlook some practical realities of field work . For example , algorithms are sometimes not performed as indicated ( e . g . gland palpation may be skipped due to heavy workload ) ; some diagnostic decisions are taken on clinical grounds ( though probably rarely ) , overriding laboratory results; and patient attrition is an issue ( e . g . suspect follow-up rates are generally low ) . Thus , the algorithms' accuracy in routine conditions may be higher or lower than our estimates , the latter being more likely . Algorithms using non-parasitological diagnosis have lower specificity leading to varying degrees of overtreatment . Overestimation of disease burden could be avoided by excluding individuals diagnosed serologically from the case counts . Differences between active and passive screening should be considered . Ways to improve sensitivity include follow-up of serological suspects and repeat blood parasitological testing . This study highlights the urgent need to pursue research on new HAT diagnostics [43] . Improved tests should ideally replace most of the present algorithms , and be feasible in outpatient settings ( e . g . as simple serological rapid tests ) , thus enabling integration of HAT services [44] . In the present scenario of falling prevalence , any new tests will need to be practically 100% specific . However , high sensitivity will remain necessary to maximise the chances of elimination . No single algorithm will be appropriate for all epidemiological settings: rather , our study demonstrates the value of estimating the accuracy of the algorithm as a whole , and could be replicated in a variety of prevalence scenarios , or integrated in a cost-effectiveness analysis that would help control programmes , particularly those working with limited resources , optimise the use of available diagnostics .
|
Gambiense human African trypanosomiasis ( HAT , sleeping sickness ) usually features low prevalence . The two stages of the disease require different treatments , and stage 2 is fatal if untreated . HAT diagnosis must therefore be highly sensitive ( i . e . , detect as many true cases as possible ) and specific ( i . e . , minimize false positives ) . HAT diagnostic algorithms are complex and involve several tests to screen for , confirm and stage infection . We analyzed five algorithms used by Médecins Sans Frontières HAT programmes . We combined published data on the accuracy of each test in the algorithm with a computer program that simulates all possible algorithm branches . We found that all algorithms had reasonable sensitivity ( 85–90% ) ; specificity was high ( >99 . 9% ) except for the Republic of Congo , where confirmation did not rely on microscopic evidence , resulting in frequent false positives ( but also higher sensitivity ) . Algorithms misclassified about one third of stage 1 cases as stage 2 , but stage 2 classification was highly accurate . The use of serology alone for confirmation merits caution . HAT diagnosis could be made more sensitively by following up serological suspects and repeating microscopic examinations . Computer simulations can help to adapt algorithms to local conditions in each HAT programme , such as the prevalence of infection and operational constraints .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"neglected",
"tropical",
"diseases"
] |
2011
|
Accuracy of Five Algorithms to Diagnose Gambiense Human African Trypanosomiasis
|
When malaria parasites infect host red blood cells ( RBC ) and proteolyze hemoglobin , a unique , albeit poorly understood parasite-specific mechanism , detoxifies released heme into hemozoin ( Hz ) . Here , we report the identification and characterization of a novel Plasmodium Heme Detoxification Protein ( HDP ) that is extremely potent in converting heme into Hz . HDP is functionally conserved across Plasmodium genus and its gene locus could not be disrupted . Once expressed , the parasite utilizes a circuitous “Outbound–Inbound” trafficking route by initially secreting HDP into the cytosol of infected RBC . A subsequent endocytosis of host cytosol ( and hemoglobin ) delivers HDP to the food vacuole ( FV ) , the site of Hz formation . As Hz formation is critical for survival , involvement of HDP in this process suggests that it could be a malaria drug target .
Malaria is the most lethal parasitic disease and a dominant public health issue in more than 100 nations . While malaria infection begins with the invasion of hepatocytes by the Plasmodium sporozoites inoculated by an infected mosquito , the common clinical symptoms of malaria , which includes high fever , chills and anemia , are due to the subsequent infection and rapid multiplication of the parasite inside the RBC . To sustain its rapid pace of development , the parasite digests host hemoglobin , which represents 90% of the total protein present inside an RBC [1]; approximately 75% of which is degraded during the erythrocytic stages of development [2] . While hydrolysis of hemoglobin makes amino acids available for parasite development , this process also releases its lipophilic prosthetic group–heme , which is extremely toxic to the parasite . Therefore , along with a continuous degradation of hemoglobin , a concomitant detoxification of heme is necessary for an uninterrupted growth and proliferation of the parasite . Parasite effectively detoxifies heme , primarily by its conversion into an insoluble crystalline material called Hz . It is estimated that up to 75% of the free heme is processed into Hz [3] , [4] . In its human host , heme detoxification is one of the homeostasis processes , performed by a combination of proteins like hemopexin and heme oxygenase [5] , whose homologs have not been found in the parasite genome . Disruption of Hz formation is the most widely used strategy for controlling malaria ( Reviewed in [6] ) . For example , chloroquine primarily acts by binding to free heme with 1:2 stoichiometry , which prevents its detoxification into Hz [7] , [8] . Similarly , one of the antimalarial activities of artemisinin involves its interaction with heme , leading to the formation of heme adducts that cannot be detoxified [9] . While the parasite-specific nature of this process has led to the development of several more drugs that interact with heme ( i . e . the substrate ) , due to an incomplete knowledge of parasite factors involved , antimalarials that can target the process itself , have not been developed . The underlying mechanism , though poorly understood , is believed to be highly conserved as Hz formation occurs in all the species of Plasmodium during their intraerythrocytic development , irrespective of the host species they infect . To date , parasite factors responsible for Hz formation are a subject of intense debate . In vitro , a protein [10] and a lipid-driven [11] , [12] processes for Hz synthesis have been described by several research groups . Additionally , an autocatalytic process , where preformed Hz promotes the conversion of free heme into Hz , has also been proposed [13] . While it's been argued that the currently known parasite factors are not the major force behind the Hz production activities of Plasmodium [14]–[16] , others believe that lipids could be the primary mediator of Hz formation in the parasite [17] , [18] . Here we describe HDP , a parasite protein , which is a potent producer of Hz and demonstrate that it reaches its intracellular destination utilizing a novel trafficking route that has not been seen for any of the known malaria proteins .
P . falciparum HDP is a single copy , three-exons encoded [19] , 205 amino acids long polypeptide ( PlasmoDB # PF14_0446; GenBank Acc# NP_702335; Fig . S1 , S2 ) . In P . falciparum parasites , we found that the HDP gene was actively transcribed during the intraerythrocytic stages of the lifecycle ( Fig . S1A ) . To study its role in the lifecycle of the parasite , the coding sequence of HDP was cloned and expressed in E . coli . On expression , the recombinant protein was localized in the inclusion bodies from which it was purified to homogeneity , by a two-step column chromatography ( Fig . S1C , D ) . Purified HDP was utilized for investigating HDP-heme interactions . First , we measured the affinity of HDP towards heme by isothermal titration calorimetry ( Fig . 1A ) . The analysis revealed that HDP binds heme with high affinity ( Kd = 80 nM ) , and possesses 2 . 7 heme binding sites . Having established its ability to interact with heme , we evaluated HDP's potential to convert heme into Hz . In a Hz-production assay [10] , where HDP was present in enzyme-like concentrations ( 0 . 5 µM ) and heme at several hundred fold molar excess ( 300 and 600 µM ) , the protein rapidly converted up to 50% of heme into hemozoin , in a concentration dependent manner ( Fig . 1B ) . HDP acted rapidly , generating most of the Hz within the first 20 minutes . The reaction achieved completion , typically within the first hour , showing little change in Hz levels over longer incubation periods ( Fig . 1B ) . At the highest concentration of heme ( 600 µM ) tested , HDP converted 261 µM of heme into Hz , leading to a conversion rate of 783 µM/hr/0 . 5 µM of protein . This translates into 1566 molecules of heme sequestered into Hz per hour/molecule of HDP ( Fig . 1B ) . To explore if the activity of the recombinant HDP represents the function of the wild-type protein , we immunoprecipitated native HDP from the extracts of P . falciparum–infected RBCs . Protein-specific antibodies were raised using the recombinant HDP as an immunogen . The native protein was purified by immunoprecipitation from the infected RBC extracts ( Fig . S7B ) and though being a dimer , was found to be active , producing Hz at levels comparable to the recombinant protein ( Fig . 1C ) , thus suggesting that in-vivo , HDP could indeed be involved in Hz production . Purification of native HDP by immunoprecipitation all but eliminated the possibility of lipids or HRP2 being present as contaminants in the native HDP fraction isolated from the parasite . Parasite-produced Hz is identical to β-hematin and its unique and well characterized powder X-Ray Diffraction ( XRD ) pattern serves as its signature [3] . To authenticate that HDP-produced crystalline material truly represents Hz , it was subjected to XRD analysis . Diffraction pattern of HDP-produced crystallites was dominated by an intense reflection at 7 . 35° 2θ ( Fig . 1D ) and the entire profile matched the pattern calculated from the previously published profile of β-hematin [3] . This confirmed that the HDP-produced substance crystallizes in the same unit cell and structure as Hz . We also evaluated the size and morphology of HDP-produced Hz crystals by scanning electron microscopy . HDP-produced Hz was essentially constituted of randomly stacked crystallites of 0 . 1–0 . 2 µm in length and approximately 0 . 05 µm in width ( Fig . 1D-inset ) . Hz crystallites of similar dimensions are found in parasite's FV [8] . We identified HDP orthologs in seven other species of Plasmodium [20] , [21] and its homologs in two species each of Theileria [22] and Babesia [21] and in Toxoplasma gondii [23] genome ( Fig . S2 ) . The protein showed 60% sequence identity within the Plasmodium genus , but had considerable divergence outside , as the overall sequence identity was less than 15% . We subsequently evaluated if the function of HDP is conserved across Plasmodium genus , by comparing the activities of HDP with its ortholog from P . yoelii , a mouse malaria parasite . Coding sequence of P . yoelii HDP ( PyHDP ) was amplified by RT-PCR , cloned , expressed in E . coli and the protein was purified to homogeneity ( data not shown ) . PyHDP generated Hz at levels indistinguishable from its P . falciparum ortholog ( Fig . 1E ) , suggesting that the functionality of HDP could indeed be conserved across Plasmodium genus . The carboxyl terminus region ( amino acids 88-205 ) of Plasmodium HDP sequences have homology ( e-value 3e-10 ) to fasciclin-1 , an ancient and highly diverse adhesive domain , present in proteins of prokaryotic [24] and eukaryotic [25] origin ( Fig . S2 and Fig . S1B ) . To check if this domain alone is responsible for the Hz producing activities we prepared two truncated versions of HDP ( Fig . S1B ) . HDP3 encoded amino acids 88-205 of the full-length protein , representing the fasciclin domain , while HDP2 encoded amino acids 1–87 and lacked the fasciclin domain ( Fig . S1B ) . The two constructs were expressed in E . coli and the purified recombinant proteins ( Fig . S1C , D ) were evaluated for their propensity to produce Hz ( Fig . 1F ) . We found that both , HDP2 and HDP3 were unable to produce Hz , suggesting that fasciclin domain alone is incapable of synthesizing Hz and an intact protein is required for this activity ( Fig . 1F ) . As part of the purification strategy , HDP and its truncated versions also encode a hexa-histidine tag ( His6-tag ) . The Hz activity found in the full-length HDP could not be attributed to the presence of the polyhistidine tag as both HDP2 and HDP3 also encoded the tag but were unable to produce Hz and a recombinantly produced P . falciparum circumsporozoite protein containing a polyhistidine tag at its carboxyl terminus did not produce Hz . Interaction of full-length HDP with heme produced a Soret peak at 414 nm , whose intensity increased with an increase in concentration of heme in the reaction ( Fig . 1G ) . In contrast , HDP2 and HDP3 showed 60–75% decrease in their capacity to bind heme , in comparison to the full-length protein ( Fig . 1G ) . Thus , the absence of Hz production activity by the two truncated versions was due to a substantial decrease in their potential to interact with heme . Heme-binding activity of HDP was not associated with His6-tag , as the tag alone showed negligible binding ( to heme ) . Thus , a full-length HDP is required for heme binding and Hz production activities of the protein . In vivo , Hz formation occurs in an acidic ( pH 4 . 5–5 . 2 ) milieu [26] of the FV . Therefore , we investigated the optimal pH requirement for the activity of HDP . We found that HDP produced Hz at pH 5 . 2 or lower ( Fig . 1H ) , showing complete loss of activity with an increase in pH . We subsequently tested the effect of chloroquine ( CQ ) , a known antimalarial drug that acts by binding to heme [7] , [8] , on HDP-mediated Hz production . We found that the reaction was inhibited with an IC50 of 11 µM ( Fig . 1I ) . However , this inhibition was due to the interaction of CQ with heme , as the drug had no measurable interaction with HDP ( data not shown ) . Parasite extracts are known to retain their Hz production activities even after boiling [13] . To evaluate if HDP could be contributing towards this phenomenon , we incubated HDP at 94°C for 10 minutes and subsequently evaluated its propensity to produce Hz . The protein produced Hz , with no measurable decrease in activity with respect to control that was incubated at room temperature for 10 minutes ( Fig . 2A ) ; thus suggesting that HDP could have been the thermostable moiety present in the extracts . Structural analysis of the heat-treated protein by circular dichroic spectroscopy showed a spectrum that was qualitatively similar to the untreated protein , thus suggesting an inherent thermostability within the HDP structure ( Fig . 2B ) . In vitro , histidine rich proteins [10] of P . falciparum and neutral lipids [12] , [17] , [18] can produce Hz . We compared the potency of HDP with the Hz production activities of Histidine Rich Protein-2 ( HRP2 ) , Monopalmitic glycerol ( MPG ) , Mono-oleoyl glycerol ( MOG ) and Oleic acid ( OA ) . We varied the concentrations of these mediators while keeping the substrate ( heme ) constant at 300 µM , giving rise to molar ratios widely utilized in previous studies [10] , [12] . Hz production increased , in a concentration dependent manner , with an increase in concentration of HDP , MPG and MOG in the reaction ( Fig . 2C ) . HDP-mediated production rose rapidly , producing 71 µM of Hz at the highest concentration of protein ( 0 . 6 µM ) tested . In contrast , at the highest concentration of MPG and MOG ( 300 µM ) tested , which was equal to the concentration of heme in the reaction , 17 and 30 µM of Hz was produced , respectively . In comparison , only 0 . 1–0 . 2 µM of HDP ( Fig . 2C ) was required to produce the same amount of Hz . Thus , HDP was 1500–2000 folds more efficient than MPG and MOG in converting heme into Hz . At their highest concentration , HRP2 and OA could only produce a maximum of 8 and 4 µM of Hz , respectively ( Fig . 2C ) . Negligible amounts ( <0 . 1 µM ) of Hz was produced in the absence of any of these mediators . As Hz formation occurs inside the FV , to be functionally relevant , HDP should be present inside this organelle . Though the protein lacks a classical N-terminal signal sequence or any known targeting signal [27] , [28] that could predict its possible sorting and transport to its destined site , we detected the presence of HDP , in close proximity of Hz , within the FV ( Fig . 3E ) , where it co-localized with Plasmepsin II , a protease present in the food vacuole ( Fig . S3C–E ) . Therefore , to comprehend its trafficking , we analyzed its expression through intraerythrocytic stages of development in P . falciparum parasites . We discovered that from the early ( ring ) stages of infection , HDP is secreted to the host cell cytosol , before any detectable amount of Hz was visible inside the parasite ( Fig . 3A ) . The protein accumulated inside the infected RBC cytosol ( Fig . 3B , F ) and was not exported out of the infected RBC , as it could not be detected in the concentrated culture supernatant by immunoblot ( data not shown ) . Subsequently , as parasite development progressed , we found that HDP ( Fig . 3B ) , along with host hemoglobin , is trafficked to the FV , via the cytostome-mediated pathway ( Fig . 3F ) . We detected the uptake of HDP through the cytostome ( Fig . 3B , G ) , its presence in the transport vesicles ( Fig . 3C , H ) and subsequent delivery to the FV ( Fig . 3D ) , where large amounts of this protein could be found in close proximity of the Hz crystal ( Fig . 3E and Fig . S3D , F ) . The recognition of HDP by the antibodies was specific , as >95% of the immuno-gold reactivity was lost when antibodies were pre-incubated with the recombinant protein ( Fig . S4 ) and they also did not recognize un-infected RBCs ( data not shown ) . The trafficking of HDP to the cytosol of the infected RBC did not occur through a classical secretory pathway as it could not be blocked when early ring stage parasites were treated with Brefeldin A ( Fig . S5 ) . This novel and circuitous trafficking route has never been observed for any of the known Plasmodium proteins . Hence , to validate this routing , we developed genetically modified parasite lines that episomally expressed HDP as a c-Myc tagged fusion ( Fig . 4 ) . Optimal trafficking requires recognition of specific motifs in the target protein [27] and can be affected if a tag is present in close proximity of the targeting signal [29] . As HDP does not encode any of the known targeting signals identified in Plasmodium [27] , [28] , the optimal site for the attachment of c-Myc tag could not be predicted . Therefore , we developed both , amino ( c-MycHDP ) and carboxyl ( HDPc-Myc ) termini fusions for investigating its trafficking ( Fig . 4H ) . Upon expression , we found that both , c-MycHDP ( Fig . 4A ) and HDPc-Myc ( Fig . 4D ) , were secreted into the cytosol of infected RBC . This not only validated our previous observation that HDP is exported into the infected RBC cytosol but also suggested that the protein encodes a hitherto unidentified targeting signal , which facilitates its export to the host cell cytosol . HDP does not undergo any proteolytic processing during its export as the c-Myc tag , attached to either end of the protein , was found to be intact ( Fig . 4I ) . Like native HDP , the “inbound trafficking” of the two tagged fusions could be seen via their cytostomal uptake ( Fig . 4A , D ) and vesicular transport ( Fig . 4B , E ) that led to the delivery of fusion proteins to the FV , where they could be found in close proximity of Hz ( Fig . 4C , F ) . The recognition of the two tagged fusions ( by anti c-Myc monoclonal antibodies ) was specific as wild-type 3D7 parasites showed no immunogold staining ( Fig . 4G ) . Thus , c-Myc based fusions corroborated that HDP has an unusual trafficking route that has never been observed for any of the known Plasmodium proteins ( schematic model depicted in Fig . S6 ) . Western blot analysis of the trophozoite-infected RBC extract revealed that HDP was present predominantly as a dimer , while the FV preparation showed both the monomeric and dimeric form of the protein ( Fig . S7A ) . The presence of HDP in the FV was not due to a contaminating cytosolic fraction , as the preparation was negative for lactate dehydrogenase , a cytosolic enzyme ( Fig . S7G ) . Due to a continuous influx of HDP to the FV ( Fig . 3E , F ) , its concentration in this organelle cannot be accurately measured . However , as the protein is first secreted into the RBC cytosol , by using infected RBC extracts we measured total HDP produced by the trophozoites by dot blot analysis ( Fig . S7C–E ) followed by a densitometric quantitation ( Fig . S7F ) using ImageQuant software ( GE Biosciences ) . Intensity ( in arbitrary units ) of the spots representing infected RBC extracts was plotted against the intensity from the defined amounts of HDP . Albeit semi-quantitative , it allowed us to estimate the relative amount of HDP produced by the parasite . Though hemoglobin levels in an infected RBC will not increase , our measurement , being a snapshot of HDP levels that could be attained inside an infected RBC , does not take into the account any subsequent production or degradation of HDP that could have occurred during the trophozoite stage of development . The analysis revealed that 1 million parasites express approximately 40 fmol of protein ( Fig . S7C–F ) . Therefore , each trophozoite could be producing up to 40 zeptomoles ( zmol ) of HDP . As an erythrocyte has a volume of 0 . 1 picoliter , concentration of HDP inside an infected RBC could reach 0 . 4 µM . To determine if HDP is critical for parasite survival , we targeted its locus in the P . falciparum genome . Our two attempts to disrupt the HDP coding sequence did not produce parasite of the desired phenotype ( Fig . 5A ) . After three selection cycles under drug pressure over a 4 month period , we could not detect site specific recombinants and the plasmid was found to be maintained episomally ( Fig . 5B ) . Native HDP was also detectable using immunofluorescence indicating that the HDP locus was not disrupted ( Fig . 5C ) . To demonstrate that this outcome is not due to an error in the transfection process , we utilized a gene replacement approach where we transfected P . falciparum parasites with a plasmid encoding a promoter-less full length HDP in fusion with the 25 kDa yellow fluorescent protein ( YFP ) ( Fig . 6A ) . This would allow us to detect the emergence of transfectants and follow the trafficking of the chimeric protein [27] . While stable integrants developed after three cycles of drug selection , as confirmed by southern blot analysis , HDP locus was found to be intact , and integration of HDP-YFP cassette had occurred elsewhere in the genome ( Fig . 6B ) . No YFP expressing parasites were visible using live cell imaging with the native HDP still detectable by immunofluorescence . This non-specific integration eliminated the possibility of any error in the transfection process and suggested that either the locus is recalcitrant to recombination or the protein chimera produced after a successful recombination event is non-functional and the resulting loss of HDP activity is detrimental for the parasite . We explored this possibility by episomally expressing HDP-YFP protein chimera in the parasite ( Fig . 7A ) . We found that , unlike the c-Myc based fusions , the protein chimera accumulated within the parasite as the YFP-associated fluorescence was not detected in the cytosol of infected erythrocytes ( Fig . 7B ) . This abrogation was due to YFP as its fusion at the amino terminus of HDP ( YFP-HDP ) also produced a similar phenotype , with fusion protein exclusively trapped within the parasite ( Fig . 7C , D ) . YFP , when expressed alone , also remained within the parasite ( Fig . 7E , F ) . As both , c-Myc and YFP-based HDP fusions were expressed using identical promoter and terminator sequences , an unimpaired transport of the c-Myc tagged fusions , but , selective impairment of YFP-based fusions , indicated that the attachment of a 238 amino acids long YFP tag to a 205 amino acids HDP polypeptide has obliterated the recognition of critical motif ( s ) required for its export into the host cytosol . A similar phenomenon has been reported for Plasmodium protein RIFIN , where attachment of a GFP tag at its carboxyl terminus blocked its export into the infected RBC cytosol [29] . Thus , it is conceivable that in our gene replacement experiments , specific integration events led to the expression of HDP-YFP fusion , which could not be exported to the host cell cytosol and the resulting deprivation of the HDP-associated activities negatively influenced the survival of these genetically-modified parasites .
Malaria gene PF14_0446 ( HDP ) was one of the several hypothetical proteins selected for a malaria functional genomics study , to understand their role in malaria pathogenesis . The selection of these genes occurred through an in silico analysis , where the Plasmodium genome was parsed using several bioinformatical tools that predict the potential of a protein to be secreted ( SignalP [30] , SecretomeP [31] ) , possession of transmembrane domains and/or anchor sequences ( TMHMM [32] ) , and the presence of known membrane and/or extracellular domains ( SMART [33] , CDD [34] ) . These analyses identified several hundred proteins and the feasibility aspects of cloning and expression led us to exclude sequences with low complexity regions and extremely large size ( >150 kDa ) , which are difficult to express , purify and hence study . Specifically , for PF14_0446 , it predicted that the hypothetical protein lacks a classical signal sequence and a transmembrane domain , but encodes fasciclin domain and could be secreted through the non-classical pathway of secretion . PF14_0446 ( along with several other hypothetical proteins ) was cloned in an E . coli expression vector , expressed and purified to homogeneity . The purified recombinant protein was utilized for raising antibodies , which were subsequently used for the immunolocalization studies performed on parasite-infected RBCs . Our quest to understand the role of PF14_0446 began when we found that on expression , PF14_0446 was present in two distinct locations within the infected RBCs . This initial observation led us to further analysis , where we found that not only the protein was present in the cytosol of infected RBCs and in the FV , but it could also be detected in transit vesicles , which are responsible for the transport of host hemoglobin to the FV . Hence , we investigated the possible role of this protein in the FV and soon found that it had heme-binding properties ( Fig . 1A ) . Though PF14_0446 has no homology to any of the known heme binding proteins , however , we found that it interacted and bound heme with high affinity ( 80 nM ) , with each polypeptide capable of binding 2 . 7 heme moieties . This affinity is at least 4 times higher than HRP2 , whose affinity for heme is in 340–940 nM range [35] . A strong interaction of PF14_0446 with heme led us to investigate if the protein could be involved in Hz production . Using an established Hz formation assay [10] , we investigated this possibility and found that the polypeptide showed robust Hz production . Hence , we named it as Heme Detoxification Protein or HDP , a label which reflects towards its putative function in the parasite . We subsequently found that each molecule of recombinantly produced protein could convert 1566 molecules of heme into Hz hr−1 , and the parasite-derived HDP had comparable activity . Our estimation of HDP levels in trophozoite infected RBC revealed that up to 40 zmol of HDP could be present inside the cells . As a cytosolic ingredient , 75% of the host hemoglobin is endocytosed and transported to the FV . A similar percentage of HDP , being uniformly distributed in this milieu ( Fig . 3F ) , will presumably be transported to the FV , making 30 zmol of the protein available for Hz production . Since a mature trophozoite contains 0 . 55–0 . 6 fmol of heme as Hz [36]; with the conversion rate of 1566 molecules/hour ( Fig . 1B ) , we believe that HDP could indeed be a playing an important role in Hz production in the parasite . Though this rate does suggest the inherent potential of HDP in making Hz in vivo; however , the exact percentage of its contribution cannot be determined , because of an incomplete knowledge of the in vivo hemoglobin processing steps , especially the extent of proteolysis required for the release of heme ( substrate ) from its globin moiety , which remains unknown . Emerging evidences from several studies on parasite proteases involved in hemoglobin degradation suggests that parasite utilizes “just in time” concept to maintain its inventory of components required to undertake a systematic degradation of host hemoglobin and Hz formation [37] , [38] . For example–delivery of parasite protease plasmepsin II to the food vacuole occurs along with the delivery of hemoglobin [38] and HDP , as we have shown in this study . Similarly , degradation of the inner membrane of the transit vesicle is believed to be contributing towards the pool of lipid that are subsequently found to be encapsulating the Hz . Mounting evidence from the genetic manipulation studies involving malaria proteases suggest towards redundancy , which generates an added layer of complexity for deciphering the rate at which heme could be released during hemoglobin proteolysis [39] , [40] . A constant influx of the “hemoglobin processing tools” along with the substrate ( hemoglobin ) thus suggests that at the minimum , the rate of Hz production in the parasite is dependent on the rates at which– ( i ) hemoglobin and its processors are imported into the FV ( ii ) proteolysis of hemoglobin that leads to the release of heme ( iii ) influx of HDP and lipids occurs in the FV ( iv ) HDP and lipids act upon released heme and ( v ) their half life in the FV . Nonetheless , a potent in vitro Hz activity , adequate production levels , its indispensability from the parasite genome and an insight into its transport and delivery to the FV does suggest that in vivo , HDP could be an important contributor in achieving Hz levels found in the parasite . Parasite factors responsible for Hz production have been a subject of intense debate . Slater and Cerami suggested the presence of a heme polymerase in the malaria parasite [41] and a subsequent demonstration of Hz production by HRP2 and HRP3 from P . falciparum parasites lead to the possibility of these proteins being the driving force behind Hz production [10] . However , ( i ) lack of HRP2 and HRP3 in other Plasmodium species , ( ii ) survival of P . falciparum parasites in their absence [42] and ( iii ) the secretion of most of the HRP2 into the host circulation [43] , diminished their potential as the major producer of Hz in Plasmodium parasites . In contrast , we found HDP to be present in all the species of Plasmodium ( sequenced to date ) , functionally conserved , and its locus being recalcitrant to recombination , suggesting that it could be critical for the survival of the parasite . We also found that an intact HDP was required for Hz production , indicating that the fasciclin domain encoded in the protein alone cannot produce Hz . As HDP encodes 2 . 7 heme binding sites and its truncated versions ( HDP2 and HDP3 ) retained heme binding activities , albeit at much reduced levels , it suggested that heme binding involves both the regions of HDP and only an intact protein can facilitate Hz production . Interestingly , we also identified HDP homologs in Babesia , Theileria and Toxoplasma genomes; however , due to low sequence identity with members of Plasmodium genus , they should not be presumed as Hz producers . As HDP is also expressed at other stages of the lifecycle , it is possible that the protein could have other functions that might be in common with its homologs in Babesia , Theileria and Toxoplasma parasites . In the parasite , a mixture of saturated and unsaturated fatty acids and neutral lipids can be found inside the food vacuole [17] . Within the food vacuole , Hz crystal is encapsulated within neutral lipids primarily composed of a mixture of mono- and diacyl glycerols [17] . In vitro , neutral lipids MPG and MOG are some of the most potent producers of Hz [12] , [17] and were therefore utilized for comparison with the activity of HDP . Although micromolar conversion rates , as seen with HDP , are possible utilizing lipids , invariably , as reported by Fitch [12] , Sullivan [17] and Egan [18] and shown here , these mediators are required at concentrations that are either similar [12] , equal [12] , [17] or in excess [18] of heme . However , only 0 . 15 molecules of lipid have been found to be associated with each molecule of heme [17] . We also found neutral lipids to be efficient in converting heme into Hz , albeit only when present at equimolar concentrations . In contrast , 1500–2000 fold lower concentrations of HDP could produce comparable amounts of Hz , thus suggesting that on a molar basis HDP is the most potent Hz producer in the parasite . The difference in Hz activity between lipid and HDP couldn't possibly be due to unfavorable reaction conditions for lipids as under similar conditions , Pisciotta et al found lipids to capable of rapidly producing Hz crystals [17] . The presence of 2 . 7 heme binding sites in the protein , a high affinity for heme and the rapid rate of conversion suggests that in vivo , HDP is involved in the formation of Hz dimer . Its involvement couldn't possibly be limited to a simple nucleation step as an increase in the concentration of either heme or HDP in the reaction leads to an increase in Hz formation . It can be hypothesized that in vivo , HDP rapidly mediates the formation of Hz dimers and possibly chaperones and delivers them to the lipid nanospheres where stacking of these dimers leads to the Hz crystal . This could potentially involve an interaction between HDP and lipids . Recently , Egan has proposed the possibility of an involvement of a protein chaperone in incorporating heme into the lipid bodies [44] . Furthermore , modeling studies also suggest that hydrogen bonding of the protonated propionic acid groups required for the final assembly of the Hz crystal is strongly favored in the hydrophobic lipid environment [18] . In evidence , >98% of the heme content in the lipid bodies was present as Hz crystals and the stoichiometry of heme:lipid found in these nanospheres [17] when utilized in vitro , produced very little Hz . Alternately , a synergistic interaction between lipids and HDP could be responsible for in vivo Hz production and remains to be investigated . Along with a distinct biochemical activity , we found that HDP has a unique trafficking route . Though the protein does not encode any of the known host cell targeting signals [27] , [28] , which could facilitate its transport across the parasite plasma membrane ( PM ) , parasitophorous vacuole ( PV ) or the PV membrane ( PVM ) , we found that HDP was readily secreted into infected RBC cytosol before any Hz could be detected in the parasite; thus suggesting the presence of novel targeting signals being encoded in the parasite genome . In malaria parasite , a continuous outbound trafficking to the PM of host RBC is equally matched with a concomitant inbound trafficking of the host hemoglobin . Subsequently , in a clear demonstration of functional convergence , we found that as parasite endocytosed hemoglobin through a cytostomal-mediated pathway , HDP was also internalized and co-transported to the food vacuole . Interestingly HRP2 , which is also secreted into the cytosol of infected RBC by the parasite , is not internalized by the cytostome and a direct routing of HRP2 from the parasite cytoplasm to the food vacuole has been proposed [45] . It is possible that HDP encodes signal ( s ) that facilitate its uptake through the cytostome . Though a mechanism , where a Plasmodium protein is first exported into the host cell cytosol only to be subsequently imported by the parasite machinery has never been reported for any of the known malaria proteins , the parasite does incorporates Plasmpesin II , a protease involved in hemoglobin degradation , into its plasma membrane , which during hemoglobin uptake becomes part of the cytostome and transit vesicle [38] . Thus , a cytostome-based routing seems to be the parasite's preferred mechanism for delivering contents to the food vacuole . To our knowledge , this is the first report of a pan-Plasmodium heme detoxifying protein that is highly efficient in mediating the conversion of heme into Hz . As HDP had no homology to any of the known heme binding proteins , it would not have been possible to predict its role in hemozoin formation by a bioinformatic approach alone . This study is a text book example of not only the presence of non-predictable activities in a protein , but also shows that following genome sequencing of pathogens , identification of novel therapeutic targets will require experimental support by classical biochemical and cell biological approaches . Identification of HDP not only fills an important gap in our understanding of the mechanism of Hz production in malaria parasite , but the novel “Outbound-Inbound” trafficking of HDP also reveals an interesting insight into the inner workings of the parasite . Transcriptomic [19] and proteomic [46] studies of malaria parasite indicate that HDP is also expressed at mosquito and liver stages of the lifecycle , suggesting that the protein could have more than one function in the lifecycle of the parasite . Identification of new drug targets is vital for developing the next generation antimalarial drugs . With our discovery , drugs that specifically interact with HDP and obliterate its detoxification activities could potentially be developed .
Coding sequence of HDP was amplified by RT-PCR using total RNA from the P . falciparum ( 3D7 strain ) erythrocytic stage parasites . The amplified fragment was cloned in pET101 , a V5 epitope and polyhistidine-tag encoding , T7 promoter-based E . coli expression vector , giving rise to plasmid pHDP . Protein , expressed in BL21 cells , was localized in inclusion bodies , which were isolated as described previously [47] . Purified inclusion bodies were solubilized in 50 mM CAPS buffer ( pH 11 . 0 ) containing 1 . 5% N-lauryl sarkosine and 0 . 3 M NaCl , for 30 minutes and the solubilized protein was separated by centrifugation ( 10 , 000×g; 30 minutes ) . Protein was purified by affinity chromatography on His-Trap , a high performance nickel affinity column ( GE Health Care ) using an imidazole gradient in 50 mM CAPS pH 11 . 0 containing 0 . 3% N-lauryl sarkosine and 0 . 3 M NaCl . Protein-containing fractions were pooled and purified to homogeneity by gel filtration chromatography on Superdex 200 10/300 GL column ( GE Health Care ) , equilibrated in 25 mM CAPS ( pH 11 . 0 ) containing 135 mM NaCl . PyHDP was amplified by RT-PCR using total erythrocytic stage P . yoelii RNA and cloned in pET101 plasmid . Plasmids encoding proteins HDP2 and HDP3 were generated by sub-cloning using pHDP as template . Their expression and purification was performed as described above . DNA encoding P . falciparum HRP 2 was cloned in pET101 and its expression and purification was performed as described previously [10] . Binding affinity of HDP for heme was evaluated by Isothermal titration calorimetry where freshly prepared heme solution was incrementally added to 5 µM HDP ( in 50 mM MES , pH 5 . 6 ) present inside the ITC cell . Data was collected at 30°C at a 420 rpm stir rate using 10 µl injections of the 100 µM heme into the protein solution . The resulting measurements , delta H vs . molar ratio , were fit to a single binding site model using the MicroCal Origin analysis software . The assay was performed as previously described [10] with the following parameters . Unless otherwise stated all hemozoin formation assays were performed at 37°C for 1 hr in a 1ml reaction volume with 0 . 5 µM HDP and 300 µM heme . HDP heme interactions were measured spectrophotometrically as described [10] . Hemin stock solution in 0 . 1N NaOH was added simultaneously into two cuvettes , one containing a solution of 10 µM protein ( HDP , HDP2 or HDP3 ) or polyhistidine tag in 0 . 1 M sodium acetate buffer , pH 5 . 2 , and the other containing only buffer ( reference cuvette ) , in 2 µM increments . After each addition of heme , the samples in the two cuvettes were mixed and allowed to stand for 5 minutes . Difference in absorption spectra ( over 200–800 nm range ) between the reference and experimental cuvette was recorded using a spectrophotometer ( GE Healthcare ) . Heme binding curve was constructed by plotting the change in absorbance at the Soret peak ( 414 nm ) versus the heme concentration using the non-linear regression function in Sigma Plot Software ( Systat Software Inc . ) . P . falciparum infected erythrocytes were purified over a magnetic column , fixed in 4% paraformaldehyde/0 . 1% glutaraldehyde in 100 mM PIPES/0 . 5 mM MgCl2 , pH 7 . 2 for 1 hour at 4°C and used for immunoelectron microscopy as described [38] . Controls omitting the primary antibody were consistently negative at the concentration of gold-conjugated secondary antibodies used in these studies . Transfected parasites expressing c-Myc fusions were probed using anti-cMyc monoclonal antibodies 9E10 . P . falciparum 3D7 parasites was cultured in human O+ erythrocytes as described previously . To disrupt the HDP genomic locus , a 509 bp locus targeting sequence beginning at the first methionine of HDP was PCR amplified using primers with in frame stop codons . This fragment was cloned into pHD22Y using the Kpn I restriction enzyme site to yield pHDPKO . The stop codons in the forward and reverse primers would prevent expression of the truncated HDP in the event of site specific recombination . Ring stage parasites at 10% parasitemia were transfected by electroporation with 100 µg of super coiled pHDPKO using low voltage/high capacitance conditions [48] . In an attempt to replace the genomic HDP locus with a HDP-YFP gene chimera , the plasmid pHDP-YFP was constructed using the pPM2GT plasmid as a backbone [38] . PM2 was replaced with a targeting sequence comprising the entire promoter-less HDP gene using the unique Xho I and Avr II restriction enzyme sites . Subsequently , the GFP was replaced with YFP and a spacer peptide was maintained in frame between HDP and YFP , as in the original pPM2GT plasmid [38] . The promoter less nature of this chimera allowed detection of site specific integrants as only integrants at the HDP locus would express YFP . The pHDP-YFP plasmid was transfected into ring stage parasites as described above . All transfectants were selected in the presence of 10 nM WR99210 ( a gift from Dr . Jacobus , Jacobus Pharmaceuticals , Princeton NJ ) and subjected to three drug selection cycles , each consisting of 21 days of growth in absence of WR99210 followed by reselection of parasites in the presence of 10 nM WR99210 . The genotypes of parasites resulting from the pHDPKO and the pHDP-YFP transfections were analyzed by probing blots of Eco RV-Bam HI and Eco RV-Xho I digested total parasite DNA , respectively with a PCR amplified 509 bp fragment of HDP that has been cloned in the transfection vector . The signal was generated with an Alk Phos direct labeling and detection kit as per manufacturer's instruction ( GE Healthcare ) . The vector for the transient expression of chimeric proteins was designed based on a well documented episomal segregation system reported in P falciparum parasites [49] . The segregation sequence , Rep 20 , was amplified from P falciparum genomic DNA and cloned into the Spe I site of the pBluescript SK ( + ) vector to yield the plasmid P1 . The HDP-YFP fusion was amplified from pHDP-YFP using primers with Cla I and Eco RI sites and subcloned into the above plasmid yielding P2 . Sequence representing Plasmodium berghei dhfr 3′UTR was amplified from P . berghei strain ANKA using primers with Eco RI and Pst 1 sites and subcloned into the P2 plasmid to yield the plasmid P3 . The 5′UTR of Plasmodium chaubaudi dhfr gene was amplified from pGFPREP2 ( gift from Michael Klemba ) using primers with Xho I and Cla I sites and subcloned into the plasmid P3 to yield plasmid P4 . The drug resistance marker hDHFR was amplified from the pHHT-TK vector and subcloned into the P4 plasmid using the Kpn I and Xho I site to create the final vector pHDPYFP . Site directed mutagenesis was utilized to insert a Nhe I site between the HDP and YFP sequence in pHDPYFP such that the HDP sequence was flanked by Cla I and Avr II while the YFP sequence was flanked by the Nhe I and Eco RI restriction enzyme sites , respectively , to yield the C terminal fusion expression vector pHDPYFP-NheI . To generate the N terminal fusion , pYFPHDP , the HDP sequence was amplified using a forward primer with Nhe I site and reverse primer with Eco RI site . This PCR product was sub-cloned into the modified base vector pHDPYFP-Nhe I yielding plasmid P5 . Plasmid P5 was verified by sequencing and was utilized for the second step of subcloning . YFP was amplified using a forward primer with the Cla I site and the reverse primer with the Avr II site . This product was then sub-cloned as a Cla I-Avr II fragment to yield pYFPHDP . For generating the control pYFP expressing vector , the YFP sequence was PCR amplified using a forward primer with a Cla I site and the reverse primer with the Eco RI site . This product was sub-cloned into the Cla I-Eco RI site of pHDPYFP-Nhe I to yield the pYFP control plasmid . Primers used for all subcloning steps were designed such that all the sequences were maintained in frame thus allowing expression of the YFP alone and , the C and N terminus YFP tagged proteins . For generating plasmids with c-myc epitope tagged at the N or C terminus of HDP , pHDPYFP vector was utilized as the base vector . For the N terminus fusion , the HDP gene was PCR amplified using a primer containing the Cla I site with an in frame c-myc sequence , and a reverse primer containing the Eco RI site . This product was then digested and sub-cloned into the Cla I-Eco RI site of pHDPYFP to yield the pc-MycHDP . Similarly for the C terminus tagged HDP , the forward primer specific to HDP containing the Cla I site and the reverse primer with the in-frame c-myc sequence with a 5′ Eco RI site were used for PCR amplification of HDP and sub-cloned into the Cla I-Eco RI site of the base vector to yield pHDPc-Myc plasmid . All the plasmids were sequenced before each subcloning step to verify the constructs . Transfections were carried out with ring stage parasites as described above and drug resistant parasites were selected using 10 nM WR99210 . All the transfection experiments were performed at least two times using 2 independent clones of each plasmid . Western blots of transfected parasites were performed using monoclonal antibody against the c-myc tag . Protocol S1 describes methods employed for X-Ray diffraction , Scanning Electron Microscopy , CD spectroscopy , Preparation of parasite extract , Purification of native HDP , Isolation of food vacuole and Estimation of HDP .
|
Each year , more than one million people , most of them children under the age of 5 , succumb to malaria , a devastating disease caused by Plasmodium parasites . The parasite resides inside the red blood cells of the host , where , during its development , it proteolyzes vast amounts of host hemoglobin . This degradation also releases heme , which is extremely toxic to the parasite . To protect itself ( from the toxic effects of heme ) , the parasite converts free heme into hemozoin . This parasite-specific mechanism is widely accepted as the weakest link in its lifecycle and is targeted by several of the currently available antimalarial drugs , which prevent hemozoin formation by binding to heme . However , due to an incomplete understanding of the parasite processes that lead to hemozoin formation , a drug that specifically targets the parasite factors responsible for hemozoin production has never been developed . Here we identify and characterize Heme Detoxification Protein , a unique Plasmodium protein , which we show as the potent producer of hemozoin . We demonstrate that this protein is highly conserved across the Plasmodium genus , is extremely efficient in producing hemozoin , and is delivered to the food vacuole , the site of hemozoin formation , via a unique trafficking route . We also demonstrate the critical nature of this protein and suggest that it could be targeted to develop novel antimalarial drugs .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/protozoal",
"infections",
"infectious",
"diseases/tropical",
"and",
"travel-associated",
"diseases"
] |
2008
|
HDP—A Novel Heme Detoxification Protein from the Malaria Parasite
|
Leishmania mexicana can cause both localized ( LCL ) and diffuse ( DCL ) cutaneous leishmaniasis , yet little is known about factors regulating disease severity in these patients . We analyzed if the disease was associated with single nucleotide polymorphisms ( SNPs ) in IL-1β ( −511 ) , CXCL8 ( −251 ) and/or the inhibitor IL-1RA ( +2018 ) in 58 Mexican mestizo patients with LCL , 6 with DCL and 123 control cases . Additionally , we analyzed the in vitro production of IL-1β by monocytes , the expression of this cytokine in sera of these patients , as well as the tissue distribution of IL-1β and the number of parasites in lesions of LCL and DCL patients . Our results show a significant difference in the distribution of IL-1β ( −511 C/T ) genotypes between patients and controls ( heterozygous OR ) , with respect to the reference group CC , which was estimated with a value of 3 . 23 , 95% CI = ( 1 . 2 , 8 . 7 ) and p-value = 0 . 0167 ) , indicating that IL-1β ( −511 C/T ) represents a variable influencing the risk to develop the disease in patients infected with Leishmania mexicana . Additionally , an increased in vitro production of IL-1β by monocytes and an increased serum expression of the cytokine correlated with the severity of the disease , since it was significantly higher in DCL patients heavily infected with Leishmania mexicana . The distribution of IL-1β in lesions also varied according to the number of parasites harbored in the tissues: in heavily infected LCL patients and in all DCL patients , the cytokine was scattered diffusely throughout the lesion . In contrast , in LCL patients with lower numbers of parasites in the lesions , IL-1β was confined to the cells . These data suggest that IL-1β possibly is a key player determining the severity of the disease in DCL patients . The analysis of polymorphisms in CXCL8 and IL-1RA showed no differences between patients with different disease severities or between patients and controls .
Leishmania mexicana can cause a wide spectrum of clinical diseases , ranging from a localized cutaneous ulcer at the infection site , which is characteristic for patients with localized cutaneous leishmaniasis ( LCL ) , to a disseminating disease , where intensely parasitized macrophages form nodules that spread throughout the skin and ultimately invade the oropharyngeal and nasal mucosae , which is characteristic for patients with diffuse cutaneous leishmaniasis ( DCL ) . Whereas LCL patients have a cellular immune response associated with macrophage-activating cytokines such as IFN-γ , DCL patients lack an effective cellular immune response , permitting an uncontrolled replication of the parasites within macrophages and other phagocytic cells . Little is known regarding the factors involved in modulating the disease outcome; one of the possible factors are early inflammatory mediators [1]–[5] . An excessive inflammatory response can lead to increased neutrophil infiltration , which has been associated with disease progression [6] , [7] . The observation that enhanced neutrophil recruitment contributes to disease susceptibility has been confirmed in experimental mouse models , which showed that an improvement in disease outcome was associated with a decrease in neutrophil immigration into the lesions [8] . One of factors responsible for neutrophil infiltration is IL-1β [9] . This cytokine also induces other innate mediators such as acute phase proteins and chemokines such as IL-6 and CXCL8 ( IL-8 ) , respectively [10] . Production of active IL-1β by monocytes is promoted by inflammasomes in response to diverse stimuli such as infections [11] , [12] . NALP3 , which belongs to the large family of intracellular Nod-like receptors ( NLRs ) , associates by oligomerization with other intracellular proteins to form a complex known as the inflammasome , which converts inactive procaspase 1 to active caspase 1 . This enzyme then cleaves the inactive IL-1β precursor to a secreted active IL-1β [13] . Single nucleotide polymorphisms ( SNPs ) of IL-1β have been associated with susceptibility towards various inflammatory diseases , such as gastric cancer [14] , [15] , periodontal disease [16] , inflammatory bowel diseases [17] and nasal polyposis [18] , among others . IL-8 ( −251 ) has been associated with an increased risk to develop H . pylori-associated gastroduodenal disease [19] . Vairaktaris et al . ( 2005 ) [20] suggested that IL-8 ( −251 ) may be a major contributor to genetic risk factor in oral cancer . IL-1RA ( +2018 ) has been shown to be associated with a significant increase in the risk of developing fibrosing aveolitis [21] . Even though elevated levels of mRNA IL-1β have been reported in biopsies of patients with American cutaneous leishmaniasis [22] , neither IL-1β ( −511 ) , CXCL8 ( −251 ) nor IL-1RA ( +2018 ) , have been associated with disease in leishmaniasis . In this work we analyzed these SNPs in mononuclear cells of patients with different clinical forms of cutaneous leishmaniasis . Additionally , we analyzed the in vitro production of IL-1β by patient monocytes , the expression of IL-1β in the sera and the cytokine distribution in the cutaneous lesions of both groups of patients . We found that polymorphism in IL-1β ( −511 C/T ) is associated with a higher risk to contract the disease when the patients are infected with Leishmania mexicana . We were also able to demonstrate that patients with the more severe form of the disease that harbor a larger number of Leishmania mexicana parasites , show an enhanced in vitro production of IL-1β by monocytes , an increased serum expression of IL-1β and a diffuse distribution of IL-1β in the lesions . The analysis of polymorphisms in CXCL8 and IL-1RA showed no differences between patients and controls ( data not shown ) .
This study was conducted according to the principles expressed in the Declaration of Helsinki . The study was approved by the Institutional Ethics Committee of the Medical Faculty of the National Autonomous University of Mexico ( FMED/CI/RGG/013/01/2008 ) and guidelines established by the Mexican Health Authorities were strictly followed . All patients provided written informed consent for the collection of samples and subsequent analysis . For the analysis of IL-1β polymorphism a total of 58 LCL patients , 6 DCL patients and 123 control cases were included . Patients were unrelated individuals and were clinically diagnosed as LCL or DCL by Giemsa-stained smears of the lesions and Montenegro skin hypersensitivity test taken at the sanitary jurisdiction office of the Cunduacán Municipality in Tabasco State , located in southeastern Mexico . The diagnosis was confirmed by an ELISA test for Leishmania in our laboratory . The controls had no history of the disease and were negative in the ELISA test for Leishmania . Both , patients and controls lived in La Chontalpa - a region in the state of Tabasco , Mexico , with a population of Maya ancestry mainly characterized as Mexican-mestizo . This area is endemic for leishmaniasis and patients were chosen based on the requirement that they had been locals for at least three generations so the admixture analysis could be done assuming the usual parental populations . Blood samples were taken from patients and controls and peripheral blood mononuclear cells ( PBMC ) were obtained by density-gradient centrifugation with Ficoll-Hypaque ( Sigma-Aldrich St . Louis , MO , USA ) . Mononuclear cells were suspended in 1 mL of TRIZOL Reagent ( Invitrogen Carlsbad , CA , USA ) , mixed and incubated for 5 min at RT . Then , 0 . 2 mL chloroform were added ( Sigma ) . The resulting solution was mixed and centrifuged at 19357×g for 15 min at 4°C . The transparent phase was discarded and 0 . 5 mL of absolute ethanol were added ( Sigma ) . The resulting solution was mixed and centrifuged at 19357×g for 10 min at 4°C . The supernatant was discarded and 1 mL sodium citrate 100 mM ( Sigma ) was added to wash the pellet , it was mixed 30 min at RT and centrifuged twice at 2151×g for 5 min at 4°C . The pellet was washed with 1 mL ethanol 75% , mixed during 20 s and centrifuged at 2151×g for 5 min at 4°C . The ethanol was dried at RT and the pellet was suspended in RNase free water . The presence of SNPs was analyzed for IL-1β −511 ( rs16944; TaqMan C_1839943_10 ) , IL-1RA +2018 ( rs419598; TaqMan C_8737990_10 ) and CXCL8 −251 ( rs4073; TaqMan C_11748116_10 ) using 20 ng genomic DNA for the PCR analysis . Allelic discrimination was done using VIC and FAM fluorogenic TaqMan probes and the 5′ nuclease assay . The PCR conditions included a step at 50°C for 2 min , a polymerase activation step at 95°C for 10 min followed by 40 cycles at 95°C during 15 s and 60°C for 1 min . These assays were done in a 7900 HT Fast Real Time PCR System . The call rates we established for the analysis were 90% individually ( for every sample ) and for every SNP . Experimentally the call rate we found was 99% for IL-1β , 99 . 5% for IL-1RA and 92% for CXCL8 ( IL-8 ) . For genotyping , the statistical analysis was done with Universal R software . For every SNP in the analysis , the genotype and allele frequencies were calculated and contingency tables were produced . The Hardy Weinberg equilibrium was calculated only in the control group using the Pearson Chi-squared test . The genotype frequencies were compared among cases and controls . The homozygote , heterozygote and serological ORs were calculated with both homozygote groups of reference . The statistical significance of these was evaluated using a Chi-squared test for association with a p-value of p≤0 . 05 as the threshold . Since each of these SNPs was selected for biological reasons before the data was collected , multiple comparison issues were not considered appropriate . Woolf [23] confidence intervals were also calculated . Based on this , we found statistical evidence that for the IL-1β polymorphism , the heterozygote group has a higher risk for disease development than the two homozygote ones . The statistical analysis of the data for parasite numbers , Western-blot and ELISA tests , where different numbers of patients and controls were included , was done using the Mann Whitney test and p≤0 . 05 was considered significant . These statistical analyses were done using the Prism 5 software ( GraphPad Software , San Diego , CA , USA ) . The serum expression of IL-1β was analyzed by Western-blot in 9 LCL patients , 7 DCL patients and 4 controls . Venous blood was drawn and allowed to clot at 37°C for 2 h . Serum was separated by centrifugation at 576×g for 10 min at 4°C . Sera were diluted 1∶2 with glycerol and stored at −20°C . For the Western-blot analysis , protein concentration was determined using DC Protein Assay Reagents Package ( Bio-Rad Laboratories , Hercules , CA , USA ) and 120 µg of serum protein were analyzed by SDS–PAGE in 15% acrylamide gels . Proteins were transferred onto Immobilon-P membranes using a semidry electroblotting apparatus . The membranes were blocked with 5% milk in Tris-buffer saline-Tween 20 ( TBST: 10 mM Tris–HCl , pH 7 . 4 , 0 . 15 M NaCl , and 0 . 05% Tween 20 ) for 1 h at RT . Blots were incubated with cleaved IL-1β ( Asp116 ) polyclonal antibody ( 17 kDa , mature form of human IL-1β ) ( 2021S , Cell Signaling Technology , Danvers , MA , USA ) diluted in TBST with 5% BSA at 4°C overnight with shaking . Anti-rabbit IgG , HRP-linked ( Cell Signaling Technology ) diluted 1∶3000 in 5% non-fat dry milk was used as secondary antibody with shaking at RT for 1 h . Blots were developed using Luminata Forte Western HRP substrate ( Millipore Corporation , Billerica , MA , USA ) and exposed to X-ray films . The densitometric analysis was performed by recording the intensity of the bands with a MultiImage Analyzer ( Alpha Innotech Corporation ) based on the percentage of integrity density value ( IDV ) . For the analysis of the in-vitro production of IL-1β by monocytes isolated from human PBMC , blood samples were taken from 5 patients with cutaneous leishmaniasis with varying degrees of disease severity which included 3 LCL patients , one DCL patient with a lesser degree of dissemination and one DCL patient who was severely infected , having numerous nodules covering the entire body surface . As for controls , blood samples from 7 healthy individuals were used , of which 3 were born and lived within the same geographical area as the LCL and DCL patients , but had been never developed the disease . The other 4 blood samples were obtained from healthy blood donors of the General Hospital of the Ministry of Health in Mexico City . Cells were separated by gradient centrifugation using Ficoll-Hypaque and mononuclear cells were isolated from the interface and washed . For the purification of monocytes , magnetically-labelled CD14 microbeads ( Miltenyi Biotec , Bergisch Gladbach , Germany ) were used . CD14+ monocytes were washed and plated in 24-well culture-plates . The IL-1β production by non-stimulated monocytes was analyzed as follows: 1×106 cells were incubated for 18 h at 37°C and 5% CO2 in 1 mL RPMI-1640 ( Gibco , Grand Island , NY ) medium , supplemented with 10% heat-inactivated FBS , endotoxin free ( Gibco ) . The cell-free supernatants from cultures were harvested and the concentrations of the cytokine were determined by ELISA . 96-well microtiter plates ( Costar , Corning , NY ) were coated and sealed overnight at 4°C with assay diluent and unconjugated anti-cytokine capture antibody ( 88–7010 eBioscience ) . The wells were washed 5 times with wash buffer , blocked at RT for 1 h with assay diluent and washed again . The standard curve was performed with 2-fold serial dilutions ( from 3 . 9 to 500 pg/mL ) and samples were incubated overnight at 4°C and washed . Avidin-HRP diluted in assay diluent was added and incubated at RT for 30 min and washed 7 times with wash buffer . Each well was incubated for 15 min at RT with substrate solution and the stop solution was added . The plate was read in a μQuant spectrophotometer ( BIO-TEK , Vermont , USA ) at 450 nm using the KC4 v3 . 4 program for the analysis of samples . Skin punch biopsies ( 4–6 mm ) were taken from the lesions of 6 DCL patients and 11 LCL patients; 8 of these LCL patients had 1 lesion ranging between 1 and 1 . 5 cm and 3 of the LCL patients had multiple lesions [3 to 6] ranging between 1 and 2 cm . The tissues were embedded in OCT compound and snap-frozen . They were cut into 4-µm thick slices , fixed in acetone PA ( J . T . Baker ) for 10 min at RT and hydrated in Tris-HCl 0 . 01M , NaCl 0 . 15M pH = 7 . 4 . Samples were blocked for endogenous peroxidase ( Peroxo-Block , Invitrogen ) and for nonspecific staining ( protein block solution , Abcam , Cambridge , UK ) . Thereafter , samples were stained with anti-IL-1β ( 1∶100 , ab8320 , Abcam ) or mouse anti-Leishmania mexicana immune sera for 1 h at RT and secondary antibodies were used as specified by the manufacturer ( mouse and rabbit specific HRP/AEC detection IHC kit , ab94705 , Abcam ) . The slides were counterstained with Mayer's haematoxylin ( Biogenex , CA , USA ) . Normal skin without lesions was used as a negative-control . Digital images of tissue sections were captured using a light microscope and a color AxioCam MRc5 camera ( Zeiss , Germany ) . In order to obtain the number of parasites in lesions of LCL and DCL patients , 7 pictures of each tissue were taken with a final area corresponding to 1 mm2 . Additionally , 6 LCL patient lesions were stained with anti-L . mexicana antibodies for the parasite count . These 6 biopsies had previously been taken for routine diagnostic purposes . Taken together , parasites were counted in a total number of 17 LCL patients with lesions ranging between 1 and 1 . 5 cm .
Within the control group , all SNPs were found to be in Hardy Weinberg equilibrium ( HWE ) with a p-value of p = 0 . 0226 and for cases ( including LCL and DCL patients ) they were in HWE with a p-value of p = 0 . 024 . We also calculated the HWE with cases and controls as one population with the Haplowiew 4 . 1 software where the HWE test failed yielding a p-value of p = 0 . 4998 . The comparison of the genotype frequencies between LCL patients and controls for the IL-1β polymorphism showed that the homozygote frequencies were higher in the controls for both of the alleles , whereas the heterozygote frequency was higher in LCL patients compared to controls ( 60 . 3% y 38 . 2% , respectively ) see TABLE 1 . This suggests that we may have a risk associated to the development of the disease for the heterozygous genotype as opposed to a single allele risk association . As mentioned above , the odd ratios resulting of comparing the heterozygote C/T to the homozygote groups were found to be significant . The OR that compared it to the homozygote C/C was 3 . 23 [p-value = 0 . 0167 , 95% CI = ( 1 . 2 , 8 . 7 ) ]; the OR that had the homozygote T/T as reference group was 2 . 19 [p-value = 0 . 0274 , 95% CI = ( 1 . 08 , 4 . 4 ) ] . All other ORs calculated are shown in TABLE 2 . In contrast , the results for CXCL8 −251 and IL-1RA +2018 were not statistically significant ( data not shown ) . Since the sample size of DCL patients is only 6 , it is questionable to draw any conclusions from this sample . As an exploratory step for further research , we repeated the procedure above using all leishmaniasis patients ( 58 LCL and 6 DCL ) as the case group . Results for IL-1β were again statistically significant: OR = 3 . 7 when the heterozygote C/T is compared to the homozygote C/C [p = 0 . 006 , 95% CI = ( 1 . 38 , 9 . 85 ) ] and OR = 2 . 4 when the heterozygote C/T is compared to the homozygote T/T [p = 0 . 012 , 95% CI = ( 1 . 19 , 4 . 6 ) ] . There seems to be no change in the conclusions drawn for the LCL patients . However , this might be due entirely to the sample size of the DCL group . No analysis was performed using only DCL patients as cases , due to the small sample size . Based on the discussion of Sasieni ( 1997 ) [24] , we decided not to use the allelic OR . The second-order analysis ( gene-gene association ) of the samples used in this study showed no significant results ( data not shown ) . The analysis of IL-1β expression in sera of LCL and DCL patients showed a different expression between both groups of patients . LCL patients showed a lower expression of this cytokine ( Figure 1A , lanes 5–13 ) and DCL patients showed enhanced expression of IL-1β ( Figure 1A , lanes 14–20 ) . In contrast to patients with leishmaniasis , controls showed only minimal amounts of IL-1β ( Figure 1A , lanes 1–4 ) . A statistically significant difference was found ( Figure 1B ) when comparing IL-1β expression in sera from LCL patients vs controls ( p = 0 . 01 ) , DLC patients vs controls ( p = 0 . 0052 ) and when comparing DCL patients vs LCL patients ( p = 0 . 019 ) . The analysis of IL-1β production revealed that non-stimulated monocytes from patients with cutaneous leishmaniasis had a significant increase of their production of IL-1β when compared with healthy controls ( p = 0 . 015 ) ( Figure 2 ) . The individual analysis of the IL-1β production by monocytes from patients showed that the degree of IL-1β production could be related to the severity of the disease , since it was highest in patients with DCL ( 478 pg/mL in the DCL patient with the more severe form and 423 pg/mL in the patient with the less severe form ) , as compared to LCL patients in whom the production of IL-1β was between 50 to 336 pg/mL . The analysis of IL-1β in lesions of LCL and DCL patients showed that the cytokine distribution varied between both groups of patients: in LCL lesions , we observed two possible patterns of IL-1β expression , according to parasite numbers in the lesions . In one group ( Figure 3A ) the cytokine was localized on the cell surface , showing an intense stain . This type of stain was found in lesions of LCL patients that harbored few parasites ( Figure 3B ) . The second group of LCL patients showed a diffuse distribution pattern of IL-1β staining ( Figure 3C ) , which correlated with the diffuse staining of abundant remnants of parasites ( Figure 3D ) . It is noteworthy that the first group of LCL patients only had one small ulcer , less than 1 cm in diameter , whereas the second group of LCL patients had 3 to 6 active lesions which varied between 1 and 2 cm in diameter . In contrast , all DCL patients showed a diffuse distribution of IL-1β throughout the lesions ( Figure 3E ) all of which were also heavily infected with intact Leishmania mexicana parasites ( Figure 3F ) . These results show that the characteristics of the distribution of IL-1β in the tissue varies according to parasite numbers: LCL patients with few parasites in their lesions only show cell membrane staining , whereas all DCL patients , with abundant intact parasites in their lesions as well as some LCL patients with abundant destroyed Leishmania parasites , show a diffuse pattern of IL-1β staining . The number of IL-1β positive cells in the tissues was different for each patient ( 18 to 410 cells ) and did not have any correlation with the time of evolution of the disease nor with the numbers parasites ( data not shown ) . The number of parasites was significantly different in the lesions of LCL and DCL patients ( p = 0 . 0003 ) ( Figure 4 ) .
The aim of the present study was to determine single nucleotide polymorphisms of IL-1β ( −511 ) , CXCL8 ( −251 ) and IL-1RA ( +2018 ) in patients with cutaneous leishmaniasis infected with Leishmania mexicana . We evaluated two groups of persons ( cases and controls ) that lived in the same endemic region . This study for the first time demonstrated polymorphism in the gene IL-1β −511 in Mexican-mestizo patients from Tabasco , a state with high prevalence of patients with cutaneous leishmaniasis . Our results show that 90% of the individuals infected with Leishmania mexicana had , either a heterozygote genotype ( CT ) , or were homozygous for the minor allele ( TT ) . Of these , 60% had the heterozygous genotype ( CT ) , as compared to only 38% for the healthy controls . These data suggest that the presence of this polymorphism in a heterozygous genotype may favor disease development in patients infected with Leishmania mexicana . Disease susceptibility or resistance has been correlated to genetic variations [25] . Specifically , polymorphism in the gene for IL-1β ( −511 ) has been associated with increased inflammation [26] . This cytokine activates the vascular endothelium , enhancing adhesion molecule expression , which , in combination with local vasodilatation , slows blood flow , permitting the tethering of neutrophils to the vessel wall . Locally released CXCL8 acts as an activator and chemoattractant for neutrophils [27] , which can produce significant damage due to the release of pro-inflammatory granules and enzymes [28] . Inflammation has been shown to be a hallmark in cutaneous leishmaniasis and various polymorphisms , related to increased or extended inflammation , have been associated with the disease [29]–[31] . Neutrophils have been shown to play an important role in leishmaniasis . They are decisive for the early establishment of the disease following delivery of parasites by the bite of the sand fly [6] and their enhanced recruitment has been shown to contribute to disease susceptibility [8] . The facilitating role of neutrophils has been associated with their capacity to phagocytose the parasites and rapidly transport them from the infection site , thus avoiding the toxic effects of complement and the local immune responses [7] . The inflammatory response aids Leishmania-infected phagocytic cells to enter lymphatic vessels , favoring parasite distribution towards peripheral tissues [32] . It is therefore tempting to speculate that augmented IL-1β production possibly facilitates disease progression in patients with DCL by enhancing the inflammatory response and thereby aiding parasite dissemination . Thus we suggest that IL-1β ( −511 C/T ) genotype heightens the risk of developing the disease due to the fact that this polymorphism is located in the promoter region of the IL-1β gene , which has been related to enhanced cytokine production and enhanced inflammatory disease . We propose that patients with this genotype are likely to be associated with an enhanced production of the pro-inflammatory cytokine IL-1β , when the patient is infected with Leishmania mexicana . The enhanced in vitro production of IL-1β by monocytes , and the augmented expression of this cytokine in sera of patients heavily infected with Leishmania mexicana , possibly strengthen the importance of IL-1β as a factor to develop the more severe form of the disease , although we cannot rule out that the enhanced IL-1β production is a consequence , rather than a cause , of the more severe form of the disease . Our data are in accordance with the literature [33] regarding the presence of the pro-inflammatory cytokine IL-1β in severe tissue lesions . Additionally , disease exacerbation has also been related to IL-1β in the BALB/c mouse model [34] . Furthermore it has been reported that IL-1β−/−C57BL/6 mice , infected with Leishmania major , were resistant to experimental cutaneous leishmaniasis [35] . The enhanced production of IL-1β by monocytes and serum of patients with the more severe form of the disease led us to analyze the cytokine in tissue lesions of patients with varying disease severity . We found that the distribution of IL-1β varied in tissue lesions in accordance with the numbers of parasites present in those lesions . Thus , in heavily infected lesions of some of the patients with LCL and in all of the DCL patients , the secreted IL-1β was found diffusely distributed within the lesions , whereas in LCL patients with a lower number of parasites , IL-1β was found to be within the cells . To the best of our knowledge , this differential distribution of IL-1β , according to varying degrees of inflammatory lesions , has not been described in the literature . IL-1β production can be induced by microbial products via TLR ligands . Our group has previously shown that Leishmania mexicana lypophosphoglycan ( LPG ) is a TLR2 ligand , leading to cell activation [36] . It is thus feasible , that the enhanced presence of the parasite relates to an increased IL-1β production . The differential distribution could be related to the possible presence of an alternative ( noncaspase-1 ) mechanism of generating active forms of IL-1β extracellularly in tissues . This alternative activating pathway has been reported for a number of molecules including serine protease-3 released by infiltrating neutrophils , as well as for other proteases such as elastase , matrix metalloprotease 9 and granzyme A released from cytotoxic T cells and mast cell chymase , which can process the IL-1β precursor into an active cytokine [37] , [38] . It is noteworthy that neutrophils secrete serine protease-3 together with extracellular traps , which have been shown to be released when the cells are stimulated with Leishmania or LPG [39] , [40] . The overall consequence of the diffusely distributed IL-1β in tissue lesions that are heavily infected with Leishmania mexicana is not clear , since in LCL patients IL-1β was associated with parasite destruction , whereas in DCL patients the parasite was not destroyed , despite the equal distribution of IL-1β . It is therefore tempting to speculate that IL-1β is not directly involved in parasite killing , but rather in aiding the mobility of phagocytosed Leishmania to be transported outside of the lesions . In DCL patients with impaired leishmanicidal capacities , IL-1β possibly aids parasite distribution by enhancing the inflammatory response . Thus , enhanced IL-1β production and distribution seems more critical in patients that have underlying problems limiting their leishmanicidal capacity , such as in patients with DCL . These results open a new perspective regarding the dynamics of IL-1β release in tissues heavily infected with Leishmania mexicana . In conclusion , our data show that leishmaniasis patients with IL-1β polymorphism have a heightened risk to develop the disease . Additionally we show that patients with a more severe form of the disease show an enhanced IL-1β production . Yet it remains to be established if the polymorphism relates directly with disease severity in patients infected with Leishmania mexicana . We propose that this might be the case , based on reports that the polymorphism is located in the promoter region of the IL-1β gene which has been shown to lead to enhanced IL-1β production [26] . Our data help shed new light on the genes involved in the disease outcome . Further studies aimed at analyzing allelic and genotypic distributions in the Mexican population will help clarify the differences we observed between cases and controls in polymorphisms implicated in susceptibility to leishmaniasis in our population . Only a few genes that determine susceptibility in the complex relationship between the parasite and the host immune response have been identified [41] . The analysis of IL-1β and other proteins that participate in inflammation like caspase-1 and -5 or NALP3 , in a larger group of patients , could possibly help define to what extent polymorphisms and enhanced production of IL-1β contribute to various clinical forms of leishmaniasis . Accession links for numbers/ID numbers for genes and proteins mentioned in the text: IL-1β: Protein: http://www . uniprot . org/uniprot/P01584 Gene: http://www . ncbi . nlm . nih . gov/protein/NP_000567 . 1 ( CXCL8 ) IL-8: Protein: http://www . uniprot . org/uniprot/P10145 Gene: http://www . ncbi . nlm . nih . gov/protein/AAH13615 . 1 IL-1RA: Protein: http://www . uniprot . org/uniprot/P18510 Gene: http://www . ncbi . nlm . nih . gov/protein/CAA36262 . 1
|
Leishmania mexicana is an intracellular parasite that causes two polarly opposed diseases: One is a self-limited disease , characterized by ulcerative lesions associated with a low infectious load , as found in patients with localized cutaneous leishmaniasis ( LCL ) . And the other pole is characterized by a progressive disease where abundant parasites spread uncontrollably throughout the skin inside heavily infected phagocytic cells , as occurs in patients with diffuse cutaneous leishmaniasis ( DCL ) . The cause of this severe form of the disease is unknown , although the early encounter between the parasite and the inflammatory response of the host possibly plays a decisive role in the disease outcome . We here show that polymorphism in the gene encoding IL-1β ( −511 C/T ) represents a variable influencing the risk to develop the disease for patients infected with Leishmania mexicana . In vitro experiments showed that monocytes of DCL patients secreted significantly higher levels of the proinflammatory cytokine IL-1β as compared to LCL patients . DCL patients also had augmented levels of IL-1β in serum , and the cytokine was diffusely distributed throughout lesions , which was correlated with the numbers of parasites in the lesions . We propose that IL-1β possibly plays a key role in establishing the disease severity in patients infected with Leishmania mexicana .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"immunopathology",
"infectious",
"diseases",
"inflammation",
"clinical",
"immunology",
"immunity",
"innate",
"immunity",
"leishmaniasis",
"immunity",
"to",
"infections",
"immunology",
"parasitic",
"diseases",
"immune",
"response"
] |
2012
|
Disease Severity in Patients Infected with Leishmania mexicana Relates to IL-1β
|
Spatio-temporal dynamics of intracellular calcium , [Ca2+]i , regulate the contractile function of cardiac muscle cells . Measuring [Ca2+]i flux is central to the study of mechanisms that underlie both normal cardiac function and calcium-dependent etiologies in heart disease . However , current imaging techniques are limited in the spatial resolution to which changes in [Ca2+]i can be detected . Using spatial point process statistics techniques we developed a novel method to simulate the spatial distribution of RyR clusters , which act as the major mediators of contractile Ca2+ release , upon a physiologically-realistic cellular landscape composed of tightly-packed mitochondria and myofibrils . We applied this method to computationally combine confocal-scale ( ~ 200 nm ) data of RyR clusters with 3D electron microscopy data ( ~ 30 nm ) of myofibrils and mitochondria , both collected from adult rat left ventricular myocytes . Using this hybrid-scale spatial model , we simulated reaction-diffusion of [Ca2+]i during the rising phase of the transient ( first 30 ms after initiation ) . At 30 ms , the average peak of the simulated [Ca2+]i transient and of the simulated fluorescence intensity signal , F/F0 , reached values similar to that found in the literature ( [Ca2+]i ≈1 μM; F/F0≈5 . 5 ) . However , our model predicted the variation in [Ca2+]i to be between 0 . 3 and 12 . 7 μM ( ~3 to 100 fold from resting value of 0 . 1 μM ) and the corresponding F/F0 signal ranging from 3 to 9 . 5 . We demonstrate in this study that: ( i ) heterogeneities in the [Ca2+]i transient are due not only to heterogeneous distribution and clustering of mitochondria; ( ii ) but also to heterogeneous local densities of RyR clusters . Further , we show that: ( iii ) these structure-induced heterogeneities in [Ca2+]i can appear in line scan data . Finally , using our unique method for generating RyR cluster distributions , we demonstrate the robustness in the [Ca2+]i transient to differences in RyR cluster distributions measured between rat and human cardiomyocytes .
The cardiac myocyte possesses a highly organized assembly of membrane networks , contractile proteins , ion channels and buffering systems . The heartbeat is the result of tightly regulated electrical , chemical , and mechanical processes that repeatedly occur at the subcellular scale across the millions of cells that make up the heart—a phenomenon called excitation-contraction coupling ( ECC ) [1–3] . ECC begins with the electrical activation and depolarization of the cell membrane and its transverse-tubular extensions ( t-tubules ) that invaginate the inner depths of the cell , thus causing a small flux of Ca2+ ( through voltage-dependent L-type Ca2+ channels ) into the dyadic cleft—the space between the t-tubules and the extensive internal Ca2+ storage network called the sarcoplasmic reticulum ( SR ) . This Ca2+ triggers the opening of a set of ion channels located on the SR called the ryanodine receptors ( RyRs ) causing a large flux of Ca2+ to enter the dyadic cleft from the SR . Finally , the resulting increase in intracellular Ca2+ concentration ( [Ca2+]i ) activates the surrounding contractile machinery , thus effecting a contractile response . We aim to investigate the effect that experimentally measured spatial distributions of myofibrils , mitochondria , and RyR clusters have on Ca2+ release and diffusion in the cardiac cytosol . Structural imaging using confocal , super-resolution , and electron microscopy [4–11] are providing insights into the structural organization of the cardiac cell at different spatial scales . These datasets are increasingly being used to generate accurate , spatially-extended computational models of the cell in order to investigate intracellular Ca2+ dynamics that current [Ca2+]i imaging technologies cannot resolve [12–15] . However , because these models are generated from a single structural dataset , the spatial resolution of the model and the different organelle components included are restricted by the spatial resolution and organelle components available in the structural data . In addition , the robustness of these computational models to variations in structural organization is hard to assess , since the model geometry is strongly dependent on the datasets at hand . This study presents a new method for generating a spatially accurate 3D computational model of cardiac cell myofibrils , mitochondria , and clusters of ryanodine receptors . The method uses spatial statistics techniques [16 , 17] to characterize and model the spatial distribution of RyR clusters relative to the contractile machinery . The statistical model then enables the fusion of data on the spatial distribution of RyR clusters from high-contrast confocal-resolution images ( ~ 200 nm ) with data on the organization of myofibrils and mitochondria available from 3D electron microscopy images ( to a resolution of ~30 nm ) . Using this method , we generated a 3D half-sarcomere spatial model of the organization of myofibrils , mitochondria , and RyR clusters in an adult Wistar rat left ventricular cardiomyocyte . Inhomogeneities in the spatio-temporal dynamics in the first 30 ms—the rising phase—of the [Ca2+]i transient have been examined and used as a measure of t-tubule degradation ( and other disease-related structural remodeling events ) in many previous studies on structure-function relationships in cellular cardiology and heart failure [18–21] . Spatio-temporal variations in the rising [Ca2+]i transient could result in reduced contractile power . Furthermore , cellular processes such as the calcineurin-NFAT pathway to cardiac hypertrophy , apoptosis , stress-response , and energy metabolism are [Ca2+]i dependent [21] . Therefore , using this model , we simulated the rising phase of the [Ca2+]i transient—using biophysical equations to account for Ca2+ buffering and Ca2+ indicator-dye kinetics—and assessed two aspects of the relationship between cell structure and [Ca2+]i dynamics: ( i ) the effect of the realistic spatial organization of myofibrils , mitochondria , and RyR clusters on the spatial heterogeneity of [Ca2+]i; ( ii ) and the sensitivity of these effects to variations in RyR cluster organization that have been measured in previous experimental studies [8 , 9 , 22] . We further demonstrate the power of this structurally realistic model in systematically assessing the degree of heterogeneity that can be introduced in the cell-wide Ca2+ transient by the arrangement of the cell’s contractile machinery and Ca2+ release sites . Specifically , we explored the degree to which structure-induced heterogeneities in [Ca2+]i , that we predicted computationally , would be visible in simulated line-scan images . Our model showed that: ( i ) spatial heterogeneity in [Ca2+]i can partly be caused by the non-uniform distribution and clustering of mitochondria in relation to the myofibrils and the sarcolemma; ( ii ) spatial heterogeneity in [Ca2+]i can also be caused by localized aggregation of RyR clusters observed in the structural data; ( iii ) variations in RyR cluster organization could give rise to observable differences in line scan data; and ( iv ) differences in the spread and density of RyR clusters between different mammalian species ( as reported in the literature ) have only a marginal effect on [Ca2+]i at the peak of the transient , thus highlighting the robustness of the ECC system to structural variations in RyR cluster distributions . Furthermore , our mathematical model showed that in order to observe a reduction in regional fluorescence in line scan images ( as reported in studies on disease-related alterations to t-tubules and RyR cluster activity ) , RyR clusters within a 1 . 29 μm diameter neighborhood ( corresponding to 4 to 6 RyR clusters ) must remain un-activated in an action-potential evoked transient . The following sections present the results of the [Ca2+]i simulations on the hybrid-scale spatial model that were analyzed to derive the above stated findings . The basic study design and the biophysical model are outlined in the materials and methods . The method for generating the hybrid model and the biophysical equations for the simulations are detailed in S1 and S2 Texts , respectively . We make special note that we have made the hybrid-scale geometric model and [Ca2+]i simulation codes available at our publically accessible repository: https://github . com/vraj004/cardiac_ecc . We have also made the RyR cluster simulation algorithm and the experimental data that were used to develop the algorithm and simulations available at: https://github . com/vraj004/RyR-simulator . We encourage cardiac computational scientists to make use of our resources in their research of cardiac biophysics at the subcellular scale . We conclude the study with a discussion of the limitations of the current analysis and future directions .
Confocal microscopy has provided several important insights on the organization of RyR clusters and their Ca2+ release kinetics that have helped develop several quantitative models of Ca2+ biophysics [29–31] . One aim of this study was to explore the effect that the structural organization of RyR clusters around the contractile machinery and mitochondria had on spatio-temporal dynamics of [Ca2+]i; current spatially extended models of cardiac cell structure use simplified representations of the organization of myofibrils and mitochondria [32–36] . Furthermore , although myofibrils and mitochondria can be visualized under confocal microscopes ( with appropriate antibody labels ) , the light diffraction limit prevents accurate segmentation of myofibril bundles and mitochondria [7] . Therefore , we aimed to explore [Ca2+]i dynamics in a geometric model that was neither limited by the spatial resolution of confocal microscopy ( with regards to the contractile machinery and mitochondria ) , nor by the lack of contrast and small field of view that is inherent in electron microscopy ( and therefore makes cell-wide RyR cluster visualization infeasible ) . We developed a novel algorithm that generates realistic confocal-scale RyR cluster distributions around nanometer-resolution 3D templates of myofibril and mitochondrial organization acquired using 3D electron tomography . This approach enabled us to create a hybrid-scale spatial model of the distribution of myofibrils , mitochondria , and RyR clusters ( see Fig 1 ) that can be used with biophysical models of Ca2+ release and buffering to examine the dynamics of [Ca2+]i at the nanometer scale . Three key observations could be made from the analysis of the spatial distribution of RyR clusters and the development of the algorithm that enable simulations of realistic distributions of RyR clusters on any given organization of myofibrils and mitochondria: The number of clusters in a cell and the nearest-neighborhood distance distribution are consistent ( 0 . 59±0 . 16 μm ) between each of the cells we studied ( see S1 Text , S1 and S2 Tables and S9 Fig ) . These metrics are also consistent with reported metrics from previous studies [8 , 9 , 23] We tested the hypothesis that an algorithm will generate RyR cluster distributions that are similar in characteristics to experimentally measured spatial distributions observed in a given cell , provided that the simulated nearest-neighborhood distribution and the number of RyR clusters matched the experimentally measured values in the cell ( S10 and S11 Figs ) . Given , from ( 1 ) , that the nearest-neighborhood distance and number of clusters are consistent across cells , we also showed that these two parameters were sufficient to recapitulate distributions of RyR clusters in all of the cell geometries we had imaged using the confocal microscope; the specific distribution of myofibrils within each cell does not affect the accuracy of the RyR cluster simulation . For the particular tomogram that we used as a template of high-resolution myofibril and mitochondrial organization ( Fig 1C and 1D ) , the cross-sectional area of the cell is approximately 94 . 8 μm2 . With an average density of 1 . 3 couplons/μm2 of cell-cross-section ( based on measured densities across z-discs in confocal datasets , S2 Table ) , we simulated 123 RyR clusters on the tomogram-derived template cross-section . The tomogram cross-section was extruded to create a half-sarcomere computational model ( see Materials and Methods and S2 Fig ) of RyR clusters , mitochondria , and myofibrils that was spatially consistent with structural imaging data ( Fig 1D and 1E ) . Further details of the RyR simulation steps and the generation of the computational model are provided in the Materials and Methods section and in S1 Text . Unlike studies that simulate the distribution of RyR clusters as regularly spaced release sites of Ca2+ [32 , 34 , 35] , close examinations of Fig 1D shows clusters are not regularly spaced . These structural heterogeneities in the distribution of Ca2+ release sites can have an impact on the spatial dynamics of [Ca2+]i . In addition , unlike existing models that incorporate idealized , regularly spaced representations of the contractile machinery and mitochondria [32–33] , our model captures the experimentally observed heterogeneity as seen in Fig 1C . The following biophysical simulations of Ca2+ release and diffusion examine the role that these structural heterogeneities may play in the spatiotemporal dynamics of [Ca2+]i . Details of the computational model and the biophysical equations are described in Materials and Methods and S2 Text . Briefly , the finite element model in Fig 1 is composed of 222 , 312 nodes making up 1 , 307 , 928 trilinear simplex tetrahedral elements . Computational nodes within a 100 nm radius of the simulated positions of RyR clusters were assigned as Ca2+ source nodes . 2 pA of Ca2+ was injected into the cell at each of the RyR cluster zones using a realistic Ca2+ release profile similar to previous studies 29 , 31 , 32] ( see S3 Fig ) . Along with the spatio-temporal dynamics of [Ca2+]i , the diffusion of Fluo-4 ( F4 ) and Ca2+ bound Fluo-4 ( F4Ca ) were also simulated as coupled partial differential equations to simulate Ca2+-dye binding kinetics and diffusion . Troponin C was distributed homogeneously through the myofibrillar space and acted as a stationary buffer of the diffusing Ca2+ . We restricted the simulations to incorporate minimal RyR cluster gating kinetics ( for example , calcium-induced calcium release was not included ) and minimal Ca2+ buffering components to explore the sensitivity of [Ca2+]i dynamics to structural organization alone . The simulations were conducted for the first 30 milliseconds ( ms ) of the ECC cycle , representing the rising phase of the Ca2+ transient . The remaining , re-uptake phase of the ECC cycle was not considered in this study because our aim was to explore the role of the spatially realistic organization of the included components of the cell; modeling the re-uptake phase would require , among other things , a realistic distribution of sarco-endoplasmic reticulum calcium pumps ( SERCA ) . The initiation of release from each RyR cluster was stochastically varied to simulate the experimentally observed stochasticity in the coupling latency between RyR clusters and L-type Ca2+ channels [31 , 37] . The biochemical rates and initial concentrations of [Ca2+]i and other buffer components are outlined in Table 1 and were based on published values [29 , 38] . Fig 2 and S1 and S2 Movies show the spatio-temporal dynamics of freely diffusing [Ca2+]i and [F4Ca]i at the z-disc of the half-sarcomere model . Fig 2A shows that the average cytosolic [Ca2+]i transient rises to approximately 1 μM and the relative F4Ca transient ( F/F0 ) rises approximately 5-fold . These values are within the range of many experimental measurements of Ca2+ transients in healthy rat ventricular myocytes found in the literature [22 , 24–28] . Fig 2B shows time-lapse snapshots of the freely diffusing Ca2+ and F4Ca . At the end of 30 ms , [Ca2+]i has range of values between 0 . 3 and 12 . 7 μM; the F4Ca F/F0 signal ranges from 3 to 9 . 5 . Careful examination of the 30 ms snapshots of the [Ca2+]i and [F4Ca]i signals shows several features that give rise to “hot-spots” . Some hot-spots occur due to the close proximity of several RyR clusters ( red arrows ) , while others occur due to Ca2+ release into regions bounded by clusters of mitochondria ( black arrows ) . Fig 2C shows line-scans of [Ca2+]i ( middle ) and [F4Ca]i ( right ) taken along the line-position on the left figure . The peak [Ca2+]i of ~10 μM is close to a release site and is of a magnitude similar to that reported in the literature previously [29–31] . Dark blue strips represent the inside of mitochondria; we assumed that intra-mitochondrial Ca2+ is only marginally affected by the Ca2+ transient and that the mitochondrial uniporter plays a negligible role as a cytosolic Ca2+ buffer [27 , 39 , 40] . We examined whether the spatial pattern of [Ca2+]i and [F4Ca]i at 30 ms was also a function of the stochasticity in RyR cluster triggering . With the given RyR cluster distribution and mesh in Fig 1 , four different sets of RyR cluster opening times were sampled from an exponential distribution with a characteristic decay constant of 6 . 7 ms ( see S2 Text ) . S4 Fig shows that at the end of the 30 ms , the spatial pattern of [F4Ca]i ( and [Ca2+]i not shown ) is not dependent on the release times of the RyR clusters . Instead , the spatial pattern is characteristic of the organization of the cell components in the mesh . We finally illustrate the impact that heterogeneous distributions of mitochondria and RyR clusters have on the heterogeneity of the [Ca2+]i transient . Fig 3 shows the F/F0 signal at 30 ms ( A ) with the default simulation settings; ( B-C ) with mitochondrial regions replaced with cytosolic properties; and ( D ) with RyR clusters being forced to have a nearest-neighbor at the mean nearest-neighborhood distance that was measured experimentally , but with zero variance as opposed to being distributed with nearest-neighborhood distances of the experimentally measured mean and variance . Note that ( C ) shows ( B ) without the mitochondria rendered and clearly shows the increase in homogeneity in the F/F0 signal . The red points depict the distribution of RyR clusters that are similar in characteristics to experimental data . ( D ) shows the effect of imposing a regular distribution of RyR clusters—by way of positioning nearest-neighbors of every cluster at a fixed distance . The encircled regions show that the F/ F0 signal is less intense where RyR clusters are less closely positioned . These results thus confirm that structural heterogeneities in the cell can introduce spatial heterogeneities in [Ca2+]i . Similar to previous studies [15] , we examined the effect of buffering by Fluo-4 by simulating [Ca2+]i release and diffusion in the absence of Fluo-4 . S5 Fig shows that without Fluo-4 , bulk [Ca2+]i increases and the heterogeneous distribution of [Ca2+]i is not greatly affected . However , clusters of RyRs that are in close proximity of each other amplify the hot-spots more because of the lack of buffering by Fluo-4 . The computational algorithm for generating RyR clusters can be used to simulate many possible distributions of RyR clusters that fall into the family of statistically equivalent distributions to the experimentally observed data . We tested whether different RyR cluster distributions from the family of possible distributions would affect the bulk cytosolic transients or the spatial heterogeneity of [Ca2+]i . Fig 4 shows that different RyR cluster distributions do not alter the net [Ca2+]i transient , but affect where “hot-spots” in [Ca2+]i arise . As such , the RyR cluster algorithm provides valid RyR cluster distributions . Furthermore , the result shows that the distribution of RyR clusters ( in addition to organization of mitochondria ) also affect the spatial pattern of [Ca2+]i . These results have not been captured in previous modeling studies [14 , 32 , 35] because this is the first model that accurately captures realistic spatial distributions of RyR clusters as well as the mitochondria and myofibrils . The line scan of the F/F0 signal in Fig 2C shows marked heterogeneity compared to any line scan that is available in literature [12–15] . Cannell et . al [41] examined non-uniformities in line scan plots that were oriented in the longitudinal direction of the cell and inferred that some of the heterogeneity in the rising transient could be explained by the presence of non-ECC components such as mitochondria . We have shown in greater detail , albeit in the transverse direction , that heterogeneities not only arise from the mitochondria , but can also arise from heterogeneities in the positioning of Ca2+ release sites and confined spaces created by groups of mitochondria or the sarcolemma . Here we aimed to quantify the degree to which the heterogeneities we have predicted would contribute to the heterogeneity in the rising transient observed in line scan plots . Fig 5B shows the F/F0 signal on the plane transverse to the cell cross-section at the line scan depth shown in Fig 5A for t = 30 ms; line scans images were generated for the three RyR cluster distributions in Fig 4 . The transverse-plane [F4Ca]i ( Fig 5B , Model Image Panel ) , visualized with a modified colour look up table , shows gaps corresponding to mitochondria , as well as spatial heterogeneity in the F/F0 signal within the cytosol . The model line scan profiles below ( Fig 5D ) show the changing intensity across the middle of the transverse plane ( along the yellow line ) , with zero fluorescence within mitochondrial regions . An experimentally measured confocal point spread function ( PSF ) was then convolved with the model images to simulate confocal visualizations of the signals for each RyR cluster distribution . The pixel resolution of the model images was 0 . 02 μm in X and Y and therefore , the images were also scaled down 10 times to match the typical pixel resolution with which line-scans are acquired . The images in Fig 5C and corresponding simulated confocal line profiles in Fig 5D show that the drop in intensity within mitochondrial regions is less apparent in the confocal-resolution line scans . Fig 5E is an estimate of the density of RyR clusters per unit volume , within a 1 . 0 μm radius spherical neighborhood , across the length of the line . Comparison with the confocal line plots in Fig 5D shows that high intensities in a confocal line scan from a RyR cluster distribution correlate with a higher density of RyR clusters in the local neighborhood . Therefore we believe that the heterogeneity during the rising phase of the [Ca2+]i transient is a composite of non-ECC structural components , such as the mitochondria , as well as the number of Ca2+ release sites in the vicinity of the line . In addition , it is worth emphasizing that the variations to the RyR cluster distribution in the three simulations are within the experimentally observed and statistically quantified variations in our RyR cluster distribution data ( as described in S1 Text ) . As such , Fig 5C and 5D show that experimentally observed variations to structural organization of RyR clusters could give rise to variations in heterogeneity at line scan resolution . Several animal models of heart failure exhibit spatial heterogeneities in line scan profiles . Heart-failure is known to cause defects in t-tubule organization that consequently affect the association of RyR clusters with the t-tubules that is necessary for effective CICR [19 , 24 , 42–44] . The dissociation of RyR clusters from the t-tubules appears as a drop in fluorescence intensity along the line scan , suggesting that RyR clusters have not been activated by the action potential [19 , 42] . Using our spatially-realistic and biophysics-based model , we set out to directly investigate the number of RyR clusters and the area of their neighborhood that must be un-activated in order to reproduce a regional drop in fluorescence as in a disease state . Fig 6 shows the in-plane fluorescence ( left ) , the simulated transverse line scan images ( right , upper panel ) and the line scan profile ( right , lower panel ) as we increased the number of RyR clusters that remained un-activated through the rising phase of the [Ca2+]i transient ( shown as red spheres in the left column; regions under investigation are encircled in black ) . The top row is the default , healthy model and the subsequent rows show the drop in fluorescence in the local regions where RyR clusters were prevented from releasing Ca2+ . Differences in the line scan profile are observable when 1 RyR cluster is un-activated ( second row ) , but the symptom of “disease” on the line scan image is only observable when the local fluorescence remains at the basal value ( i . e . , with F/F0 ≈ 1 . 0 ) . This corresponds to 4 or 6 RyR clusters remaining un-activated as shown in the last row of Fig 6 . In addition , because the spatial model is consistent with structural microscopy data , we can infer that the 4 to 6 RyR clusters span a 1 . 29 μm diameter neighborhood . We have demonstrated how our method for generating realistic distributions of RyR clusters enables us to examine heterogeneities in [Ca2+]i due to the RyR cluster distribution . Fig 4 shows that we can also simulate variations in the RyR cluster distribution , which are equivalent to variations seen in structural imaging data . These variations affected the spatial profile of [Ca2+]i , but had no effect on the range of [Ca2+]i in the cytosol . As such , [Ca2+]i is robust to variations in RyR cluster organization observed within our experimental data of RyR cluster distributions in adult rat ventricular myocytes . A previous comparison of RyR cluster distributions in rat and human cardiomyocytes [9 , 23] found that RyR clusters were less densely populated ( 40% drop ) and more spread out ( mean nearest-neighborhood distance ≈ 0 . 79 μm ) in human cardiomyocytes . We hypothesized that this drop in the density of clusters would give rise to a more heterogeneous distribution of [Ca2+]i . We simulated a human-equivalent distribution of RyR clusters ( 87 clusters with a mean nearest-neighborhood distance of 0 . 79 μm ) within the electron-tomogram template distribution of myofibrils and mitochondria from the Wistar rat myocyte; the comparative studies between rat and human myocytes showed that the volume fraction of mitochondria and myofibrils were not different between the two species [9] . Ca2+ release and diffusion was simulated on this human-type myocyte to explore [Ca2+]i heterogeneity . Ca2+ release current from each of the 87 clusters was increased to 2 . 8 pA to compensate for the drop in the number of clusters in the model and maintain a whole-cell average [Ca2+]i of 1 μM that is also measured in human myocytes [45] . This compensation in RyR [Ca2+] release is also consistent with recent experimental findings that the cardiac Ca2+ store and release systems maintain long-term balance in Ca2+ through alterations to SR Ca2+ content and the strength and duration of Ca2+ release from RyR clusters [46 , 47] . Fig 7 shows a comparison of the spatial distribution of free [Ca2+]i ( top panel ) and Fluo-4-bound Ca2+ , [F4Ca]i ( bottom panel ) in the rat ( left column ) and human ( right column ) models . The range of [F4Ca]i and [Ca2+]i are the same in both species and although the locations of local hot-spots may be in different regions in the two models , the spatial profiles are similar . This analysis illustrates the robustness of [Ca2+]i dynamics to a significant change in RyR cluster distribution properties .
Several microscopy methods are required to visualize different aspects of cardiac cell structure . Confocal and super-resolution methods give the advantages of high-contrast ( due to immunostaining ) and large fields of view [4 , 7 , 14] . However , potential crosstalk between different antibody label signals limits the number of proteins and organelles that can be visualized from one cell . In contrast , 3D electron tomography and more recently developed serial-block-face imaging methods provide higher resolution , but relatively poor contrast [8 , 11] . As such , the different microscopy methods complement each other and could be used in conjunction to generate a unified view of the cell . Our method ( detailed in S1 Text and Fig 8 ) of analyzing the spatial relationships between ion channels and the surrounding cellular machinery enables us to generate a unified view of different cardiac cell components from different microscopy methods . Although correlated microscopy methods are in development [48] , our method also provides an added benefit of capturing the variations in the organization that are observed in experimental data , both among healthy populations and across different disease states . As such , computational analysis of spatial relationships between different components of the cell is an important aspect of cardiac structure analysis . Our algorithm for RyR cluster simulations can be applied to generate computer models of RyR clusters and contractile machinery with other templates of myofibril and mitochondrial organization taken from EM tomography as well as serial-block-face imaging and confocal imaging technologies . The approach of modeling RyR clusters as point processes could be translated not only to other ion channels in the cardiac cell ( e . g . , L-type Ca2+ channels and sodium-calcium exchangers ) , but also to ion channels in all cell types in general . Our spatially-accurate model enabled us to explore how structural components of the cell contribute to spatial non-uniformities observed in the rising [Ca2+]i transient [41] . In our analysis of distributions of RyR clusters , we found that RyR clusters aggregate into groups and can therefore give rise to local elevations in [Ca2+]i ( see Figs 2 , 3 and 4 ) . These heterogeneities in RyR cluster distribution could also give rise to spatial heterogeneities in line scan images of the [Ca2+]i transient ( see Fig 5 ) . More idealized models of RyR cluster distributions as a regular grid of ion channels [32 , 35] would not be able to capture these effects . We also examined the effect of heterogeneous distributions of mitochondria—which act as barriers—on spatiotemporal [Ca2+]i dynamics . Fig 3 shows that assigning mitochondria to have the same diffusive properties as the cytosol reduces the occurrence of local elevations in [Ca2+]i . We did not incorporate the Ca2+ buffering capacity of mitochondria in our simulations . Recent studies indicate that the experimentally measured mitochondrial Ca2+ uptake rates are at least two orders of magnitude lower than those required to significantly and rapidly affect cytosolic calcium levels under physiological conditions [39 , 40] . Therefore , incorporating a component of mitochondrial Ca2+ uptake mechanism is unlikely to alter the concentration gradients ( and dampen a 3- to 100-fold heterogeneity in cytoplasmic Ca2+ ) that is predicted when modelling mitochondria as passive barriers to Ca2+ diffusion . We tested the model’s sensitivity to buffering by incorporating calmodulin and ATP . S6A and S6B Fig show that the heterogeneity in the F/F0 signal at the end of the 30 ms simulation drops with CaM and ATP buffering . A look at the distribution of Calmodulin-bound Ca2+ ( bottom right ) shows that the heterogeneity introduced by the structural organization now manifests in the buffered CaM-Ca distribution . We also investigated the sensitivity of the observed [Ca2+]i heterogeneity to the biophysical detail in RyR gating . As detailed in S2 Text , we implemented a previously published two-state Markov model of RyR gating to account for: Ca2+ dependent RyR gating; sensitivity of RyR gating to Ca2+ in the junctional sarcoplasmic reticulum ( JSR ) ; and stochastic behavior of individual ion-channel gating [49 , 50] . Intracellular Mg2+ is also known to affect RyR gating kinetics . Experimental and modeling studies such as [51–53] have demonstrated the inhibitory effect of Mg2+ in lipid bilayer studies by performing RyR gating experiments at different concentrations of Mg2+ . The parameters of our chosen model account for physiological levels of Mg2+ and recapitulate several of the experimentally observed spark properties under physiological conditions . Each of the clusters in our whole-cell model was assumed to contain 50 individual RyRs . A deterministic approximation of the two-state Markov model was used to simulate average behavior of the cluster of RyRs [54] . Each cluster was triggered to release Ca2+ from the JSR into the dyadic space by raising the mean open probability from 0 to 0 . 02 , which is equivalent to a single RyR channel opening due to the L-type Ca2+ stimulus . S6C Fig shows that our observations of heterogeneity in the Ca2+ transient and Calmodulin-bound Ca2+ still hold . These results , together with Figs 2 , 3 and 4 clearly confirm that the spatial organization of RyR clusters and mitochondria introduce heterogeneity to the Ca2+ transient . Previous studies typically assume that the rising [Ca2+]i transient is homogeneous under control or normal physiological conditions . We have for the first time shown with a structurally realistic model , how the “normal” structural organization of RyR clusters alone can introduce spatial heterogeneities in the rising Ca2+ transient . Our simulations of missing sparks on the confocal line scan image ( see Fig 6 and S7 Fig ) demonstrated that a 1 . 29 μm diameter neighborhood of RyR clusters—corresponding to 4 to 6 RyR clusters—must remain un-activated to produce a line scan image with a local drop in fluorescence . This shows the power of a structurally realistic model in enabling the exploration of the effects of systematic modifications to structure on the local control of [Ca2+]i dynamics . A previous experimental analysis [37] of the relationship between single L-type Ca2+ release channels and RyR channels had shown that a single L-type channel can trigger 4 to 6 RyR channels; here we have quantified the contribution of RyR release at a higher spatial scale ( in several cluster groups of RyRs , each cluster containing many single RyRs [55] ) . Our result is limited to the rising phase of the action potential evoked transient . Simulations involving longer than 30 ms duration would need to include proteins involved in Ca2+ reuptake to simulate the observed recovery of spatial uniformity [42] . As such , our current observation is valid for the initial phase of the transient . Our comparison ( see Fig 7 ) of the spatiotemporal dynamics of [Ca2+]i between a simulated rat and a simulated human cardiomyocyte—defined by the different RyR cluster distributions measured in literature [9 , 23]–suggests that the Ca2+ diffusion mechanism and the organization of myofibrils and mitochondria provide significant robustness to [Ca2+]i dynamics . In particular , a 40% drop in density of RyR clusters has virtually no effect on the spatial profile of [Ca2+]i . This comparison of the cluster distribution of human versus rat RyR is an important example of how parameterization of structure enables systematic analysis of the sensitivity of cardiac function to specific aspects of cell structure . Such analysis is not possible when generating a model from a single dataset . Our simulations assumed that all RyR clusters were activated by the action potential . The impact of the difference in t-tubule organization between human and rat cardiomyocytes has not been thoroughly investigated in this study . However , the observation that t-tubules in the human myocyte are more coarsely arranged than in the rat myocyte is consistent with the more dispersed , and less dense RyR cluster parameters that we used to simulate human myocytes in this study [9] . Previous structural studies have also observed a small proportion of RyR clusters that were not associated with t-tubules and therefore may not be activated by the action potential [56] . However , these were largely in the periphery , and we anticipate that this sub-population will have limited effect on the current computational observation . In addition , although our “best-case” scenario of all RyR clusters being activated may not be completely realistic , varying strengths of release from each RyR cluster could compensate for any local loss of RyR cluster Ca2+ , thus adding more robustness to the ECC system . Our current analysis focused on the possible role that realistic distributions of RyR clusters , mitochondria and myofibrils could play in the spatio-temporal dynamics of [Ca2+]i . The ability to model RyR cluster distributions enabled us to explore an aspect of cardiac cell structure as a model parameter within experimental bounds . The degree of influence that this structural parameter may have on cell biophysics was systematically investigated with simplified and biophysically detailed models of [Ca2+]i dynamics and buffering . Inherently , electron tomograms are low contrast , which can hamper the identification of boundaries between myofibrils . Being aware of the fact that myofibrils can bundle together and also twist through the cell volume [57] , we segmented myofibrils as precisely as possible given the quality of our image dataset . More careful characterization of myofibril and mitochondrial regions in tomograms and new serial-block-face imaged samples [11] will enable us to improve on the current segmentations . Nevertheless , it is worth noting that we anticipate minor refinements to the current findings because our simulation of the average cell [Ca2+]i transients are consistent with experimental records of Ca2+ in cardiomyocytes . There are many more structural components in the cell , one of which is the t-tubule network that traverses between the myofibrillar and mitochondrial regions . As the field of view in the tomogram used for this study is small , only a few t-tubule openings could be observed . A more complete geometric model would incorporate t-tubules and will potentially introduce more heterogeneity as already observed in previous simulation studies that examined Ca2+ release and diffusion around realistic t-tubule geometries [12 , 15] . Furthermore , more high-throughput methods for imaging cardiac cell myofibrils and mitochondria [11] will enable us to extend the current half-sarcomere model to encapsulate realistic organizations of the myofibrils and mitochondria in the longitudinal direction as well . With the advent of super-resolution microscopy , higher-resolution information on the distribution of RyRs is coming to light [4 , 7 , 55] . Finer details on the spread of individual RyR channels within clusters of RyRs are now being investigated . As such , incorporating this new information will refine our current findings . We aim to apply our method for modeling RyR cluster distributions to this new data and examine how these different spatial scales of information integrate to give rise to the whole cell transient . A full ECC cycle would incorporate other sources and sinks of Ca2+- particularly sarcoplasmic reticulum Ca2+ ( SERCA ) pumps . It is our medium-term goal to systematically analyze the spatial distribution of other key ECC proteins and to incorporate them into our hybrid-scale spatial model of the cardiac cell . As we have demonstrated in this study , the ability to characterize the spatial arrangement of structural components using statistical models enables us to examine structure as a model variable that current image-derived models cannot do . As cells undergo structural remodelling through many signaling mechanisms , parameterization of spatial relationships between structural components is an important step towards quantifying the dynamic relationship between structure and function in both health and disease .
All animal procedures followed guidelines approved by the University of Auckland Animal Ethics Committee ( for animal procedures conducted in Auckland , Application Number R826 ) and the University of California San Diego Institutional Animal Care and Use Committee ( for animal procedures conducted in UCSD , Protocol SO6215 ) . We developed a novel algorithm—using spatial point process statistics techniques [16 , 17]—that generates realistic confocal-scale RyR cluster distributions around nanometer-resolution 3D image stacks of myofibrils and mitochondria organization acquired using 3D electron tomography . We have created an online repository at https://github . com/vraj004/RyR-simulator , containing the source code for the RyR cluster simulation algorithm and necessary input files for simulating RyR cluster distributions on the confocal and electron-tomogram derived geometries . We encourage readers to use the cluster simulation algorithm for fusing with their own image data . We have also created an online repository at https://github . com/vraj004/cardiac_ecc , which contains the files defining the tetrahedral mesh depicted in Fig 1D and 1F . These files can be imported into any computational program that recognizes TetGen formats . The TetGen software also allows for re-export of TetGen files to other commercially recognizable formats such as stl ( stereolithography ) for easy visualization [62] . The repository also contains all the necessary input files and codes to conduct the [Ca2+]i simulation studies presented in this paper . CellML files defining the Ca2+ release profile from each RyR cluster have also been provided ( see S3 Fig ) .
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Calcium ( Ca2+ ) acts as a signal for many functions in the heart cell , from its primary role in triggering contractions during the heartbeat to acting as a signal for cell growth . Cellular function is tightly coupled to its ultra-structural organization . Spatially-realistic and biophysics-based computational models can provide quantitative insights into structure-function relationships in Ca2+ signaling . We developed a novel computational model of a rat ventricular myocyte that integrates structural information from confocal and electron microscopy datasets that were independently acquired and includes: myofibrils ( protein complexes that contract during the heartbeat ) , mitochondria ( organelles that provide energy for contraction ) , and ryanodine receptors ( RyR , ion channels that release the Ca2+ required to trigger myofibril contraction from intracellular stores ) . Using this model , we examined [Ca2+]i dynamics throughout the cell cross-section at a much higher resolution than previously possible . We estimated the size of structural maladaptation that would cause disease-related alterations in [Ca2+]i dynamics . Using our methods for data integration , we also tested whether reducing the density of RyRs in human cardiomyocytes ( ~40% relative to rat ) would have a significant effect on [Ca2+]i . We found that Ca2+ release patterns between the two species are similar , suggesting Ca2+ dynamics are robust to variations in cell ultrastructure .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Examination of the Effects of Heterogeneous Organization of RyR Clusters, Myofibrils and Mitochondria on Ca2+ Release Patterns in Cardiomyocytes
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Cytological and genetic evidence suggests that the Bacillus subtilis DNA uptake machinery localizes at a single cell pole and takes up single-stranded ( ss ) DNA . The integration of homologous donor DNA into the recipient chromosome requires RecA , while plasmid establishment , which is independent of RecA , requires at least RecO and RecU . RecA and RecN colocalize at the polar DNA uptake machinery , from which RecA forms filamentous structures , termed threads , in the presence of chromosomal DNA . We show that the transformation of chromosomal and of plasmid DNA follows distinct pathways . In the absence of DNA , RecU accumulated at a single cell pole in competent cells , dependent on RecA . Upon addition of any kind of DNA , RecA formed highly dynamic thread structures , which rapidly grew and shrank , and RecU dissipated from the pole . RecO visibly accumulated at the cell pole only upon addition of plasmid DNA , and , to a lesser degree , of phage DNA , but not of chromosomal DNA . RecO accumulation was weakly influenced by RecN , but not by RecA . RecO annealed ssDNA complexed with SsbA in vitro , independent of any nucleotide cofactor . The DNA end-joining Ku protein was also found to play a role in viral and plasmid transformation . On the other hand , transfection with SPP1 phage DNA required functions from both chromosomal and plasmid transformation pathways . The findings show that competent bacterial cells possess a dynamic DNA recombination machinery that responds in a differential manner depending if entering DNA shows homology with recipient DNA or has self-annealing potential . Transformation with chromosomal DNA only requires RecA , which forms dynamic filamentous structures that may mediate homology search and DNA strand invasion . Establishment of circular plasmid DNA requires accumulation of RecO at the competence pole , most likely mediating single-strand annealing , and RecU , which possibly down-regulates RecA . Transfection with SPP1 viral DNA follows an intermediate route that contains functions from both chromosomal and plasmid transformation pathways .
Natural genetic transformation is an efficient mechanism of horizontal gene transfer between bacteria , and thus of the acquisition of novel genetic material . At the onset of stationary phase , Bacillus subtilis cells can become competent ( up to 20% of all cells ) , specified through the induction of proteins mediating the binding of environmental DNA to the cell surface , and upon its processing , transporting the single-stranded ( ss ) DNA into the cytosol [1] , [2] . Recombination proteins integrate homologous or “partially” homologous foreign DNA into the chromosome , or allow the establishment of autonomously replicating molecules ( plasmid or viral DNA ) . The competence-specific DNA-uptake proteins and a large set of additional proteins are under the control of the master competence transcription factor , ComK [3] , [4] . DNA uptake occurs in a highly processive manner [5] at a single cell pole , as exemplified by visualization of ComGA and ComFA , two presumed ATPases involved in DNA translocation [6] , [7] . Environmental double-stranded ( ds ) DNA somehow crosses the cell wall to bind to the ComEA membrane protein , and is nicked ( and thus fragmented ) by the NucA endonuclease . Then , one strand is transported across the membrane via ComEC , whereas the other strand is degraded to nucleosides outside the cell [1] , [2] . Hence , the DNA uptake machinery takes up linear ssDNA molecules , which are then available to the intracellular recombination machinery . More than 12 genes have been shown to be involved in genetic recombination in B . subtilis . The absence of RecA , the central recombination protein that mediates strand invasion between homologous linear ssDNA and supercoiled dsDNA ( forming D-loop intermediates ) and strand exchange , leads to a reduction in transformation with chromosomal DNA by more than 4 orders of magnitude [8] , [9] . A defect in any gene classified within the α ( recF , recO and recR ) , β ( addA and addB ) , γ ( recH and recP ) , δ ( recN ) , ε ( recU ) or ζ ( recJ , recS and recQ ) epistatic group reduces the frequency of chromosomal transformation only 4-fold or less in an otherwise wild type ( wt ) background [10] , [11] , suggesting that alternative pathways may help or modulate RecA to achieve this process . This conclusion is in agreement with in vivo data showing that in the simultaneous absence of RecA modulators ( i . e . in a addAB recO double mutant strain ) , chromosomal and plasmid transformation are blocked [12] . On the other hand , the transformation frequency with plasmid DNA is reduced more than 20-fold in recO or in recU mutant cells , but is only moderately ( less than 4-fold ) reduced in all other rec mutants tested , and is not at all reduced in recA mutant cells [12] , [13] , [14] . These data suggest that a redundancy of factors involved in transformation and different pathways exist during transformation [11] . However , the use of different B . subtilis genetic backgrounds and/or of different DNA substrates in the past has complicated the interpretation of genetic data . Three different pathways for transformation have been proposed . Firstly , if taken up DNA contains sufficient homology to the chromosome ( <than 20% divergence in several hundred bp ) , ssDNA may be directly incorporated into the chromosome via intermolecular recombination ( chromosomal transformation ) [15] , setting up heteroduplex DNA ( with one parental DNA strand getting degraded ) ( Figure 1A ) . Upon re-entering into the vegetative state , one daughter cell receives a chromosome copy derived from the incorporated DNA , and may thus become transformed , while the other cell receives the parental DNA . Secondly , if taken up ssDNA lacks homology with the chromosome it must be annealed to form a circular dsDNA molecule ( Figure 1B ) and be self-replicative ( i . e . contain an origin of replication ) . Interestingly , only multimeric , but not monomeric , plasmid DNA can lead to transformation [14] , [16] . A third scenario may occur in case of viral transfection . It has been shown that the average length of the entering ssDNA is around 12-kb ( reviewed by [17] ) , while phage SPP1 is composed of 45 . 5-kb DNA . Therefore , in order to form a full-length phage dsDNA molecule from incoming ssDNA fragments , these must be recombined intermolecularly to yield a partially annealed full-length molecule which can then be replicated ( Figure 1C ) . The terminal repeats may be recombined intramolecularly to form a circular molecule that can be proficient for replication . In the absence of homology with recipient DNA or of an autonomous replication unit , taken up DNA is degraded [17] . The visualization of proteins involved in competence in B . subtilis has recently provided a new tool to study transformation in time and space . During the state of competence , the DNA uptake machinery , SsbB ( also termed YwpH ) , DprA ( Smf ) , CoiA ( YjbF ) [6] , [18] , and RecA , colocalizes at a single cell pole , whereas RecN oscillates between the poles [19] . Internalized linear ssDNA appears to stop the oscillation of RecN , which is a ssDNA-binding protein [20] , [21] , and DprA is important for loading of RecA to incoming ssDNA [22] . Thread-like structures of RecA are observed to emanate from the competence pole [19] . These have been proposed to guide ssDNA onto the nucleoid that contains the chromosome , in order to mediate strand exchange with the recipient DNA . In support of this idea , a non-functional RFP-RecA fusion , which accumulates at the competence pole , but fails to form threads after addition of DNA , is entirely deficient in transformation [19] . Therefore , transformation with DNA appears to be a spatially highly organized process . Genetic data suggest that RecO and RecU ( analogue of Escherichia coli RuvC ) are not essential during chromosomal transformation , and their significant role played during plasmid transformation is poorly understood [15] . Both RecO and RecU have an important function during DNA double strand break ( DSB ) repair [21] , [23] , [24] , [25] , [26] . Here , RecO promotes loading of RecA onto SsbA-coated ssDNA , and RecU catalyzes the resolution of HJs [27] , [28] . To verify the genetic requirements during transformation , we analyzed the relevance of RecA , RecO , and RecU and other proteins in transformation with three different substrates , chromosomal , plasmid and viral DNA , within a single genetic background . We also investigated the involvement of Ku protein , which is involved in DNA end joining during DSB repair [29] . We show that RecO , RecA and RecU proteins localize dynamically and differentially at the competence pole , dependent on the DNA substrate added to the cells , and in accordance with this , that the proteins perform different roles in promoting recombination of incoming DNA , which also depends on the nature of incoming DNA . Our work shows that recombination proteins appear at different time points and steps during DSB repair and transformation , showing that they obtain different functional specificities during the two processes .
Transformation efficiencies have been assayed for different types of DNA and in various different B . subtilis strains , all of which carried inducible prophages , which complicates all analyses [10] . We therefore investigated the function of B . subtilis DNA recombination and repair proteins during transformation in the same phage-free background ( strain BG214 lacks the ICEBs1 transposon and prophage SPβ , and PBSX cannot be induced ) , and with three different DNA substrates ( chromosomal , plasmid and viral DNA ) in parallel . Previously , the transformation defects of ΔrecA , ΔrecO , ΔrecR , recF15 , ΔrecU and ΔrecN cells have been analysed using different conditions ( replicons , markers , DNA concentrations , etc . ) or viral transfection ( also termed viral transformation ) ( reviewed in [11] ) , but were re-evaluated here for a direct comparison . The assays were normalized to actual DNA uptake and to cell viability ( see Material and Methods ) . The selected DNA substrates allowed us to study presumably different recombination events: ( i ) recombination of internalized chromosomal ssDNA with the host chromosome based on the existence of homology with recipient DNA ( intermolecular recombination , Figure 1A ) , ( ii ) conversion of internalized ssDNA to dsDNA and circularization by intramolecular recombination in the case of replicative plasmid DNA ( Figure 1B ) , or ( iii ) internalization of fragmented ( i . e . less than unit-length ) viral SPP1 ssDNA , which has to be converted to dsDNA , recombined to generate full-length viral DNA , and circularized ( both , inter- and intramolecular recombination ) ( Figure 1C ) . The frequency of appearance of chromosomal transformants was ∼10 , 000-fold decreased in the ΔrecA strain , whereas chromosomal transformation efficiency in the ΔrecO , ΔrecR , recF15 , ΔrecU , recU71 , ΔruvAB , ΔrecN or Δku ( also termed ΔykoV ) deficient strains did not change more than 2- to 3-fold relative to the wild type strain ( Table 1 ) . These results reinforce the idea that RecA is required for intermolecular recombination , and show that presynaptic ( RecN , RecF , RecO , or RecR ) or postsynaptic ( RecU and RuvAB ) functions are not required for this pathway in an otherwise wt background , or may have redundant roles in chromosomal transformation , because negative effects are seen with some double mutations [10] . The efficiency of plasmid transformation was not affected in the absence of RecA ( Table 1 ) . Plasmid establishment was marginally impaired in recF15 , ΔrecR or ΔrecN competent cells ( 2-fold ) , and slightly impaired ( ∼4-fold ) in ΔruvAB cells compared with wild type cells ( Table 1 ) . However , plasmid establishment was reduced ∼6-fold in Δku cells and 25- to 35-fold in ΔrecO , recU71 or ΔrecU cells ( Table 1 ) . These results show that RecO and RecU are required for plasmid transformation and that Ku plays a minor role in this pathway , whereas other presynaptic proteins ( RecN , RecF and RecR ) are not required in an otherwise wild type background . The defect seen in ΔruvAB cells may be caused by a reduction of the resolution of HJs , but RecU seems to play an additional role in plasmid transformation , because recU mutant cells are 5-times more deficient in plasmid transformation than ruvAB mutants . This is consistent with the observation that the recU71 strain , which encodes a RecU variant ( RecU R71A ) proficient in strand annealing and HJ resolution , but deficient in RecA modulation [30] , is as defective in plasmid transformation as a recU deletion strain ( Table 1 ) . We therefore argue that the main function of RecU during plasmid transformation is not HJ resolution . It has been shown that the average length of incoming donor ssDNA is ∼12-kb [17] . Mature SPP1 DNA is a linear 45 . 5-kb long dsDNA molecule with 4% of terminal redundancy [31] , hence , internalized SPP1 ssDNA is fragmented into 3 or more pieces by the DNA uptake machinery . Intracellular reconstitution of SPP1 DNA may therefore involve both intermolecular recombination to reconstitute a full-length molecule , and intramolecular recombination to achieve circularization [15] . Consistent with this , transfection of SPP1 DNA was affected in recombination mutants involved in both chromosomal ( recA ) and plasmid transformation ( recU , recO and ku ) . The frequency of SPP1 transfection was reduced ∼100-fold in ΔrecA , ∼35-fold in ΔrecO , ∼30-fold in recU71 , ∼25-fold in ΔrecU , or ∼5-fold in Δku cells ( Table 1 ) . SPP1 transfection was marginally impaired in ΔrecN or ΔruvAB competent cells ( less than 2-fold relative to the rec+ value ) or not reduced in ΔrecR or recF15 competent cells ( Table 1 ) . These results demonstrate that: ( i ) RecA-mediated strand exchange is required for intermolecular recombination during chromosomal transformation , rather than for protection of incoming ssDNA from nuclease attack , ( ii ) RecO , RecU and to some extent Ku are involved in plasmid transformation , and ( iii ) phage transfection follows a route comprising viral- and host-encoded functions from both pathways . In cells grown to competence , a functional GFP-RecA fusion ( see Material and Methods ) colocalizes with competence ComGA protein to a single cell pole in ∼20% of all cells ( this is the fraction of competent cells ) , or is associated with the nucleoids in the remaining cells [19] ( Figure 2A ) . Addition of chromosomal DNA to competent cells leads to the formation of filamentous GFP-RecA structures , termed threads , which are very variable in length and shape ( Figure 2B ) . To investigate whether the threads are dynamic structures , we performed time-lapse microscopy , capturing images of cells grown to competence 10 to 30 min after addition of DNA within 1 min time intervals . Figure 2C and Videos S1 , S2 , S3 , and S4 show examples of such experiments . A GFP-RecA thread , which changes its shape within each 1 min time interval , can be seen to extend from a single cell pole into the cell ( Figure 2C ) ( left panel ) . At min 8 , two apparently separate structures arise , one close to the cell pole and the other extending away from the competence cell pole . In all of the 26 movies taken , GFP-RecA threads showed highly dynamic localization , arising at one cell pole and extending into the cytosol , but never reaching the other cell pole . We have also observed discrete GFP-RecA foci that rapidly and continuously ( for at least 20 min ) moved through the cells ( data not shown ) , but the nature of these assemblies is unclear . In Figure 2C , right panel , extension of a thread from a single focus can be seen to occur between min 2 to min 9 , with peak extension between min 4 and 5 . We were able to only capture 3 of such extension events from a single focus ( with>300 cells analyzed ) , indicating that extension from the pole occurs very rapidly . In Video S4 , GFP-RecA threads can also be seen to rapidly grow as well as shrink between 1 min intervals . Maximum extension of 0 . 6 ( ±0 . 2 ) µm/min was measured in 6 time lapse series , which is similar to the observed spreading of E . coli RecA onto dsDNA in vitro [32] . These experiments reveal rapid growth and shrinkage of RecA threads in vivo , and reinforce the idea that RecA threads guide incoming ssDNA from the pole onto nucleoids for homology search , ensuring maximum efficiency of transformation . The fact that RecA does not play a major role in plasmid transformation raises the question if RecA threads are also formed during uptake of supercoiled plasmid DNA ( which was taken as a source for oligomeric ssDNA ) . There was no visible change of pattern with regard to the formation of RecA threads after addition of plasmid DNA . Of the competent cells ( ∼20% of cells grown to competence ) , ∼65% showed RecA signals containing polar foci , ∼12% contained foci at various intracellular positions ( other then the poles ) , and ∼23% showed GFP-RecA threads after addition of plasmid DNA ( Figure 2D ) . Similarly , after addition of chromosomal DNA , ∼63% of the competent cells contained polar foci , ∼13% foci at other positions , and ∼24% formed threads ( Figure 2B ) . Thus , formation of RecA threads is not specific for the kind of DNA substrate entering the cell during transformation . During DSB repair RecO is necessary to load RecA onto SsbA coated ssDNA [28] . Our genetic data show a RecR- and RecF-independent role for RecO during plasmid transformation ( see Table 1 ) . To analyze if RecO shows a particular pattern of localization after addition of DNA to competent cells , a functional RecO-YFP fusion was used ( see Material and Methods ) . The same amount of chromosomal , plasmid or viral DNA was added in these experiments ( 0 . 1 µg/ml ) . Under this condition , transformation with chromosomal DNA was 200 to 1000 times more efficient ( transformants per µg of DNA added ) compared with plasmid transformation , although DNA concentrations curves for plasmid and chromosomal transformation revealed that both are first order processes ( data not shown ) . RecO-YFP was dispersed throughout cells grown to competence ( Figure 3A ) and addition of chromosomal DNA did not alter this pattern: none of 600 cells analyzed contained visible RecO-YFP foci ( Figure 3B ) . Strikingly , RecO-YFP formed a single focus at one cell pole in 5% of the cells grown to competence , as soon as 5 min after addition of supercoiled plasmid DNA . Up to 16 . 9% ( 102 out of 600 cells ) of the cells showed a polar focus or two polar foci 30 min after addition of supercoiled plasmid DNA ( Figure 3D , 26% of the cells having RecO foci contained two polar foci , indicated by grey triangles ) . These findings reveal a striking substrate- and time-dependent recruitment of RecO to the DNA uptake machinery . To verify , that the RecO foci correspond to sites where the competence machinery is present , we combined the RecO-YFP strain with a ComGA-CFP fusion . In ∼18% of cells grown to competence ( 99 out of 550 cells analyzed ) , RecO-YFP colocalized with ComGA to a single cell pole ( in 72% of these cells ) or to both cell poles ( in 28% of these cells ) ( Figure 3E ) , or was present throughout the remaining cells . 2 cells out of 550 showed one polar ComGA-CFP focus but no RecO-YFP focus , and 3 cells had two polar ComGA-CFP foci , but only one RecO-YFP focus was present , colocalizing with one ComGA-CFP focus ( Figure 3E , indicated by green and orange triangles ) . These data show that RecO foci largely colocalize with the DNA uptake machinery upon addition of plasmid DNA . Plasmid preparations from E . coli cells contain monomeric as well as multimeric plasmid forms . Only multimeric plasmid DNA has been shown to lead to transformation of B . subtilis cells [16] , [33] , so we generated monomeric as well as multimeric plasmid preparations . In contrast to transformation with chromosomal DNA , 8% of the cells grown to competence ( i . e . 40% of all competent cells ) showed RecO-YFP foci at the pole 30 min after addition of linearized monomeric plasmid DNA ( Figure 4B , 32 foci in 400 cells ) . Similarly , addition of linearized dimeric plasmid DNA induced foci in 8 . 8% of the cells ( data not shown ) . However , 30 min after addition of trimeric and higher multimeric plasmid DNA ( all higher multimers were pooled because they could not be clearly separated ) , 13 . 5% of the cells ( i . e . ∼68% of all competent cells ) showed polar RecO-YFP foci ( Figure 4C , 54 foci in 400 cells analysed ) . Thus , RecO-YFP foci are induced by monomeric or dimeric plasmid DNA , and significantly ( 2×2 chi2 value 6 . 3 with significance value of 0 . 012 ) increased in number after addition of multimeric plasmid DNA . A major difference between plasmid and chromosomal transformation is the fact that upon addition of the same amount of DNA ( as was done in these studies ) , the amount of identical DNA fragments taken up by a single competent cell is more than 1000-fold higher with plasmid than with chromosomal DNA . To test if a chromosomal DNA fragment with a size even smaller than monomeric plasmid DNA can also induce the formation of RecO-YFP foci , we generated a 3 . 5 kb DNA fragment carrying a tetracycline resistance gene flanked by 1 kb regions homologous to the chromosome on each side , which integrates into the non-essential ypbR locus by a double cross-over , in a RecA-dependent manner . As expected , the frequency of recombination was similar to that with plasmid DNA , i . e . lower than with chromosomal DNA . 10 to 30 min after the addition of this PCR-amplified DNA to cells grown to competence , 10 . 5% of the cells showed RecO-YFP foci ( 63% with one polar focus , 34% with two polar foci , and 4% with three foci , 470 cells analysed , data not shown ) , showing that also small dsDNA fragments can efficiently induce the formation of RecO-YFP foci . We also investigated the genetic requirements for the recruitment of RecO to the cell pole . The formation of RecO-YFP foci in response to plasmid DNA was abolished in comK mutant cells ( data not shown ) and in mutant cells lacking the DNA uptake channel ComEC ( Figure 3C ) . These experiments support the idea that RecO assembles at the pole due to incoming ssDNA with self-annealing potential transported through ComEC . To address the question whether polar localization of RecO after addition of plasmid DNA depends on other recombination proteins , we moved the recO-yfp fusion into a ΔrecN strain or we placed the ΔrecA mutation into a recO-yfp strain . The formation of RecO-YFP foci was somewhat reduced in ΔrecN cells ( 9 . 5% , 62 foci in 650 cells analyzed ) ( data not shown ) , but remained fairly constant in ΔrecA cells ( 16 . 3% , 106 foci/650 cells ) upon addition of multimeric plasmid DNA ( Figure 4A ) . These data suggest that during plasmid transformation , RecO acts independently of RecA , and is mildly influenced by RecN . Similarly , during DSB repair , the recruitment of RecO to DNA breaks is influenced by RecN , but is independent of RecA [23] , [34] . We also investigated , if the addition of phage DNA ( 45 . 5 kb DNA from SPP1 ) might recruit RecO to the cell pole . Clear RecO-YFP foci were detected in 2% of cells grown to competence 30 min after addition of 0 . 1 µg/ml of SPP1 DNA ( 7 foci/340 cells analyzed , Figure 4D ) , showing that to a lesser degree than plasmid DNA , but in contrast to chromosomal DNA , uptake of phage DNA results in polar RecO accumulation . DNA uptake occurs at an average speed of 80-nt/s [35] , so several 1 , 000 bases can be present few minutes after addition of DNA within the cell to induce the formation of GFP-RecA threads and/or RecO-YFP foci , which are visible after only 5 min . Therefore , we tested if incoming ssDNA could be a substrate for RecO . To investigate whether RecO can mediate the annealing of complementary ssDNA , we directly monitored DNA annealing of a heat-denatured 440-nt long DNA , or this substrate complexed with SsbA ( Figure 5 ) . RecO protein ( at a ratio of 1 RecO/14-nt ) enhanced the annealing of complementary ssDNA molecules , and similarly , RecA·dATP·Mg2+ ( 1 RecA monomer/3-nt ) catalyzed the annealing of complementary ssDNA substrates ( Figure 5A ) . Contrarily , SsbA , at a ratio of 1 tetramer/38-nt , inhibited the spontaneous annealing reaction ( Figure 5C ) . When the ssDNA substrate was pre-incubated with SsbA a different outcome was observed ( Figure 5A and 5B ) . RecO protein ( 1 RecO/14-nt ) efficiently promoted the annealing of complementary ssDNA substrates ( Figure 5A , lanes 5-9 ) . Similar results were observed if the RecO ratio was reduced to 1 RecO/28-nt ( data not shown ) . However , RecA·dATP·Mg2 failed to catalyze the annealing of complementary ssDNA substrates complexed by SsbA ( Figure 5B ) . Thus , RecO has potent ssDNA annealing activity in vitro , in the absence of any cofactor , and SsbA bound to ssDNA markedly stimulated this activity . However , SsbA exerted a negative effect on RecA·dATP·Mg2+-mediated DNA strand annealing . We investigated the possibility of a colocalization of RecU and RecA during natural competence , because we showed that ΔrecU cells are impaired in plasmid transformation whereas ΔruvAB cells are not , and that RecU acts as a RecA modulator in a RuvAB-independent manner [36] . In cells grown to competence , we found that a functional RecU-YFP fusion ( see Material and Methods ) forms a focus at a single cell pole or two foci , each at a pole , in 18% ( 110 cells having foci/600 cells , with 27% of these having two foci ) of cells grown to competence ( Figure 6A ) . Polar RecU-YFP foci colocalized with polar ComGA-CFP foci in more than 95% of the cells containing foci ( Figure 6B , 350 cells analyzed ) , showing that RecU assembles at the DNA uptake machinery in the absence of transforming DNA . This is consistent with the absence of polar RecU-YFP foci in comK mutant cells ( Figure 6C ) . Interestingly , the formation of a RecU focus was also dependent on RecA protein . The number of cells containing polar RecU foci was reduced by 92% in the absence of RecA compared to wild type cells ( >200 cells analyzed , Figure 6D ) , and the fluorescence intensity of the few foci was much lower than in wild type cells . This is consistent with the findings that RecU physically interacts with RecA and acts as a modulator of RecA [30] , [36] , and is involved in plasmid transformation and viral transfection ( see Table 1 ) . These observations markedly differ from RecU assembly during DNA DSB repair . Here , the accumulation of RecU-YFP foci , at late times after DSB induction , is strictly dependent on the presence of the RuvAB complex [25] . Strikingly , RecU-GFP foci dissipated from the pole after addition of any kind of DNA . Only 4% of all cells grown to competence contained polar ( or any ) RecU-GFP foci 15 min after addition of DNA ( Figure 6E , 200 cells analyzed ) , while after 30 min , foci were not detectable in all 250 cells analyzed ( Figure 6F ) . Like RecA ( see above ) , RecU was statically located at the DNA uptake apparatus in the absence of external DNA ( data not shown ) , but apparently changes its pattern of localization in response to incoming ssDNA .
In cells grown to competence , RecA and RecU are present at the DNA uptake machinery , and RecN oscillates between the poles [19 , this work] , whereas RecO is dispersed throughout the cytosol ( Figure 7-0 ) . Upon addition of any kind of DNA RecN localizes to the pole that contains the DNA uptake machinery ( Figure 7-I ) , and RecA and RecU lose their static position at the cell pole ( Figure 7-I ) . RecN specifically binds to the 3′-OH end of ssDNA in vitro and protects it from exonuclease attack [20] , [21] , but plays a minor role in transformation in the phage free strain background . Modulators of RecA must displace the single-stranded binding proteins ( e . g . , SsbA , SsbB ) and help loading of RecA onto ssDNA , which has been demonstrated for DprA [22] . Thus , RecA binds to incoming ssDNA and forms threads that emanate from the uptake machinery [19] . Further investigating RecA thread formation , we found that RecA threads are highly dynamic structures that change their length and orientation within a 1 min time scale . Maximum extension of filaments was measured to be 0 . 6 ( ±0 . 2 ) µm/min , similar to the observed speed of spreading of RecA on dsDNA in vitro [32] , suggesting that filament growth and shrinkage may be mediated by RecA coating of and dissociating from incoming ssDNA . These finding reinforce the idea that RecA threads are actively searching for homology of the incoming DNA with the recipient chromosome . RecA/donor ssDNA invade recipient duplex DNA , forming a D-loop structure . Interestingly , RecU also dissipated from the pole after addition of DNA ( Figure 7-I ) . In agreement with the association at the cell pole of RecA and RecU , and their loss of this static position after DNA addition , both proteins have been shown to physically interact with each other [30] . Possibly , RecU protein tracks along with RecA threads that move away from the cell pole and may enhance RecA-mediated D-loop formation , which is consistent with data showing that RecU enhances RecA-promoted DNA strand invasion [27] , [36] . However , D-loop intermediates cannot be resolved by the RecU HJ-resolvase in vitro [27] . From the results obtained we can also infer that in DNA transformation , 4-strand recombination intermediates ( HJs ) are not formed , because HJ resolution through RecU is not required for transformation and in the absence of the RuvAB translocase , chromosomal transformation is also not affected . Clearly , an as yet unknown D-loop resolvase and a ligase are needed to mediate full incorporation of taken up homologous DNA ( Figure 1A ) . Replication of the generated heteroduplex will generate one transformed daughter cell . The uptake of plasmid DNA follows the same pathway and kinetics through the membrane via the uptake machinery than that of chromosomal DNA [1] , [2] . In the presence of internalized plasmid ssDNA , RecA also forms threads , showing that RecA is loaded onto any kind of incoming ssDNA . However , the RecA threads are unproductive if the incoming ssDNA shares no significant homology ( larger than 50-nt ) with recipient DNA , as is the case for plasmid DNA . In the absence of sufficient homology , RecU may promote the disassembly of RecA from the taken up ssDNA , which should then become coated by a single-strand binding protein ( e . g . , SsbA , SsbB , DprA ) . Strikingly , incoming plasmid DNA triggers the recruitment of RecO to the competence machinery . Possibly , RecO accumulates at the competence pole through direct protein-protein interaction with SsbA bound to incoming ssDNA , consistent with in vitro data showing that RecO physically interacts with SsbA [28] . All other proteins induced by competence possibly covering the entering ssDNA ( namely , DprA/Smf and SsbB ) are present at the competence pole even in the absence of incoming DNA , and thus cannot cause the switch of recruitment of RecO in response to incoming plasmid DNA . It is also possible that an unknown factor causes the accumulation of RecO at the competence machinery . However , we propose that RecO accumulates due to its annealing activity . Taken up ssDNA must anneal to form dsDNA fragments for plasmid establishment ( Figure 7-II ) . The likelihood that both complementary Watson and Crick strands are taken up is several orders of magnitude higher during uptake of a similar amount of plasmid DNA ( ∼15 kb ) than of chromosomal DNA ( 4 , 200 kb ) . RecO is a dimer in solution and binds cooperatively to ssDNA with high affinity [28] , but has drastically lower affinity to dsDNA ( C . M . and B . C . , unpublished ) . Additionally , RecO has much higher annealing activity with complementary ssDNA strands complexed with SsbA than RecA in vitro ( Figure 5 ) , therefore , incoming plasmid DNA provides a high amount of substrate for RecO . Interestingly , the number of competent cells having visible polar RecO-YFP foci was higher after addition of oligomeric DNA compared with monomeric DNA . Repetitive ( homologous ) sequences increase the annealing potential , supporting the view that RecO accumulates due to its activity in strand annealing . To further test this idea , we investigated the effect of the addition to cells grown to competence of a 3 . 5 kb construct that integrates into the recipient chromosome by a double-cross over event ( in a RecA-dependent manner ) . RecO-YFP foci accumulated at the cell poles in a number of cells in between that for monomeric or for multimeric plasmid DNA , further supporting the notion that RecO accumulates at the DNA import machinery due to a high amount of complementary DNA strands . RecU has also been shown to possess strand-annealing activity in vitro [27] , [30] , and is also important for plasmid transformation . We propose that the main role of RecU in plasmid transformation is to down regulate RecA activity rather than to mediate strand annealing . Indeed , it was shown that the RecU requirement during plasmid transformation can be overcome by deleting recA [30] . Electron microscopy analyses revealed that: ( i ) purified RecU does not promote RecA disassembly from ssDNA , but discrete RecU blobs embedded in a RecA nucleoprotein filament reduces RecA dynamic assembly , and ( ii ) RecU alone does not polymerizes onto ssDNA [36] . Down-regulation of RecA may be important for efficient plasmid DNA establishment , because RecA is inefficient in catalyzing DNA strand invasion on linear dsDNA , in contrast to supercoiled DNA , and may hinder the formation of circular plasmid dsDNA . We also found a novel function for Ku protein during transformation with plasmid ( but not with chromosomal ) DNA . Ku might protect DNA ends that arise during DNA annealing ( Figure 7-II ) from nuclease attack . A Ku-GFP fusion was dispersed throughout cells grown to competence ( data not shown ) , and its expression was markedly increased during competence , compared with growing cells , supporting an important function for Ku during plasmid horizontal gene transfer . As a second step , annealed duplex and partially duplex DNA must circularize to establish a plasmid molecule ( Figure 7-II ) . As previously documented for RecOEco [37] , we propose that RecO promotes the annealing of a homologous region of the same molecule complexed by SsbA , to generate a circular molecule ( Figure 7-II ) . This intramolecular recombination only generates unit-length molecules if the substrate has internal redundancy . Consistent with this idea , it has been shown that plasmid transformation can be achieved with single trimer or higher multimer molecules , but not with monomeric plasmid DNA [16] , [33] . Once an oligomeric plasmid molecule is circularized and replicated , the host-encoded resolution system should resolve it to monomeric plasmid DNA . These proposed steps provide an economic avenue to reassemble plasmid DNA with few proteins , and independently of RecA . During phage transfection with mature viral DNA , the functions of RecA , RecO , RecU and Ku are required . Unlike chromosomal and plasmid transformation , viral transfection requires the recombination of 2 to 4 DNA molecules to yield a 45 . 5 kb viral DNA [38] . Phage DNA must first anneal to form dsDNA segments , similar to plasmid transformation ( Figure 7-III ) . Interestingly , RecO also accumulated at the pole after addition of SPP1 DNA , but in fewer cells compared with plasmid DNA , most likely because the different segments of the viral DNA have less annealing potential than the oligomeric plasmid DNA . As a second step , overlapping fragments must recombine to form a full-length phage DNA molecule . This intermolecular recombination event requires RecA and the phage recombination machinery ( e . g . strand annealing protein , G35P , and 5′to 3′exonuclease G34 . 1 ) [39] , [40] . The terminal repeat regions ( Figure 1C ) then recombine , perhaps via single-strand annealing , to generate a circular phage molecule that can replicate . Thus , genetic transformation follows different pathways , which in the case of phage transfection contains steps from both chromosomal and plasmid transformation . Contrarily to natural transformation , DSB repair appears to follow one discrete avenue . Cell biological experiments have documented that upon induction of DSBs , recombination proteins are recruited to the DNA damage site on the nucleoid in a relatively fine tuned temporal order ( setting up a so-called repair center ) , with RecN assembling first , followed by RecO ( which is important for loading of RecA onto SsbA-coated ssDNA ) , and RecA itself , and later RecF and RecU [15] , [23] , [25] , [41] . Thus , the recombination machinery can switch between DNA repair and incorporation or establishment of foreign DNA within the cell , and assembles differentially according to the different DNA substrates taken up from the environment .
E . coli XL1-Blue ( Stratagene ) was grown in Luria–Bertani ( LB ) rich medium supplemented with 50 µg/ml ampicillin where appropriate . B . subtilis strains were grown in LB rich medium at 37°C , or in defined minimal medium for microscopy . The strains used in this study are described in Table 2 . The recN , recO , or recU genes were fused at their 3′- end with the cfp or the yfp gene and the fused gene was integrated into the chromosome by single crossover integration to replace the wt gene as previously described [23] , [25] . Thereby the recN- , recO- or recU-yfp gene fusions were present at the native locus and transcribed from their native promoters , which are not induced during competence development [3] , [4] . RecN-YFP , RecO-YFP or RecU-YFP expressing cells were as resistant to methylmethane sulfonate and to MMC as the wt strain [23] , [25] and had transformation efficiencies like wt cells ( data not shown ) , showing that the fusions were fully functional . The recA gene was fused at the 5′-end to the gfp gene , the fused gene was placed under the control of the xylose inducible promoter and ectopically integrated into the amy locus . Then the wt recA gene was deleted [19] . The resulting GFP-RecA strain was as sensitive to MMC as the wt strain [23] , [25] and had transformation efficiencies like wt cells ( data not shown ) , showing that the fusion is fully active . To move the recN-cfp , recO-yfp or recU-yfp fusion in different mutant backgrounds , transformation with chromosomal DNA was used ( Table 2 ) . For the colocalization experiments , strain DK2 ( recO-yfp ) was transformed with chromosomal DNA from comGA-cfp , generating strain DK84 . For the colocalization experiments , strain DK53 ( recU-yfp ) was transformed with chromosomal DNA from comGA-cfp , generating strain DK88 . A Ku-YFP fusion was constructed by cloning the PCR amplified 3′ end ( 500 bp ) of the ykoV gene into pSG1164 , which was integrated into the chromosome via single crossover , such that the expression of the downstream ykoU gene was driven by the xylose promotor . The Ku-YFP fusion was fully functional , as all above stated YFP fusions . Competent cultures were grown as described previously [42] . Competent B . subtilis cells were transformed with pUB110 plasmid DNA , chromosomal DNA from a met+ strain ( SB19 DNA ) or bacteriophage SPP1 DNA . The yield of kanamycin-resistant transformants ( plasmid transformation ) , met+ transformants ( chromosomal transformation ) , and SPP1 transfectants was corrected for DNA uptake ( assayed through the determination of uptake of radioactively labeled DNA into cells grown to competence through DNaseI degradation of the labeled DNA ) and for cell viability ( viability counts ) , and the values obtained were normalized relative to that of the rec+ strain , which is taken as 100 [9] , [43] . RecO , RecA and SsbA proteins were purified as previously described [28] , [36] . To determine whether RecO anneals complementary ssDNA coated with SsbA , buffer A ( 50 mM Tris-HCl [pH 7 . 5] , 1 mM DTT , 80 mM NaCl , 2 mM EDTA , 50 µg/ml bovine serum albumine [BSA] , 5% glycerol ) was used , whereas in RecA-SsbA reactions , buffer B ( 50 mM Tris-HCl [pH 7 . 5] , 1 mM DTT , 40 mM NaCl , 10 mM magnesium acetate , 2 mM dATP , 50 mg/ml BSA , 5% glycerol ) was used , and the DNA complexes were monitored upon deproteination . The heat-denatured 440-nt ssDNA ( 7 mM in nt , pGEM-3Zf ( + ) EcoRI[5]-AflIII[445] DNA fragment ) when indicated was pre-incubated with SsbA ( 90 nM ) for 10 min at 30°C . Then RecO ( 500 nM ) or RecA ( 1 . 3 mM ) was added and the reaction incubated by a variable time . The samples were deproteinized as described [27] , separated in a native ( n ) 6% polyacrylamide gel electrophoresis ( nPAGE ) , and the gels dried prior to autoradiography and quantification as previously described [27] . Fluorescence microscopy was performed on an Olympus AX70 microscope . Cells were mounted on agarose pads containing S750 growth medium on object slides . Images were acquired with a digital MicroMax CCD camera; signal intensities were measured using the Metaview program . DNA was stained with 4′ , 6-diamidino-2-phenylindole ( DAPI; final concentration 0 . 2 ng/ml ) , and membranes were stained with FM4-64 ( final concentration 1 nM ) . Chromosomal DNA ( from B . subtilis or E . coli ) or plasmid DNA ( various replicative plasmids ) were added to 100 µl of cells grown to competence , resulting in a final concentration of 0 . 1 µg/ml of DNA . For purification of mono or multimeric plasmid DNA , plasmid pDG148 was digested with EcoRI , and was purified after agarose gel electrophoresis . Monomeric plasmid DNA was incubated with LrpC protein and DNA ligase to enhance formation of dimeric and higher multimeric DNA [44] The ligated DNA was purified from low melting agarose using phenol-chloroform extraction .
|
Many bacteria can actively acquire novel genetic material from their environment , which leads to the rapid spreading of , for example , antibiotic resistance genes . The bacterium Bacillus subtilis can differentiate into the state of competence , in which cells take up ssDNA through a DNA uptake complex that is specifically localized at a single cell pole . DNA can be integrated into the chromosome , via RecA , or can be reconstituted as circular dsDNA , if derived from plasmid or from viral DNA . We show that RecO , RecU , and Ku proteins , but not RecA , are important for plasmid transformation , and differentially accumulate at the polar DNA uptake machinery . Upon addition of any kind of DNA , the assembly of RecU at the competence pole dissipated , while RecA formed filamentous structures that rapidly grew and shrank within a 1 minute time scale . RecO visibly accumulated at the competence machinery only upon addition of plasmid DNA , but not of chromosomal DNA . In vitro , RecO was highly efficient at enhancing the annealing of complementary strands covered by SsbA , without the need for any nucleotide cofactor . The findings show that competent cells possess a dynamic recombination machinery and provide visual evidence for the existence of different pathways for transformation with chromosomal DNA or with plasmid DNA .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"genetics",
"and",
"genomics/microbial",
"evolution",
"and",
"genomics",
"developmental",
"biology/microbial",
"growth",
"and",
"development",
"cell",
"biology/microbial",
"growth",
"and",
"development",
"biochemistry/replication",
"and",
"repair",
"molecular",
"biology/dna",
"repair"
] |
2009
|
Evidence for Different Pathways during Horizontal Gene Transfer in Competent Bacillus subtilis Cells
|
Buruli ulcer , the third mycobacterial disease after tuberculosis and leprosy , is caused by the environmental mycobacterium M . ulcerans . Various modes of transmission have been suspected for this disease , with no general consensus acceptance for any of them up to now . Since laboratory models demonstrated the ability of water bugs to transmit M . ulcerans , a particular attention is focused on the transmission of the bacilli by water bugs as hosts and vectors . However , it is only through detailed knowledge of the biodiversity and ecology of water bugs that the importance of this mode of transmission can be fully assessed . It is the objective of the work here to decipher the role of water bugs in M . ulcerans ecology and transmission , based on large-scale field studies . The distribution of M . ulcerans-hosting water bugs was monitored on previously unprecedented time and space scales: a total of 7 , 407 water bugs , belonging to large number of different families , were collected over one year , in Buruli ulcer endemic and non endemic areas in central Cameroon . This study demonstrated the presence of M . ulcerans in insect saliva . In addition , the field results provided a full picture of the ecology of transmission in terms of biodiversity and detailed specification of seasonal and regional dynamics , with large temporal heterogeneity in the insect tissue colonization rate and detection of M . ulcerans only in water bug tissues collected in Buruli ulcer endemic areas . The large-scale detection of bacilli in saliva of biting water bugs gives enhanced weight to their role in M . ulcerans transmission . On practical grounds , beyond the ecological interest , the results concerning seasonal and regional dynamics can provide an efficient tool in the hands of sanitary authorities to monitor environmental risks associated with Buruli ulcer .
Mycobacterium ulcerans is the causative agent of Buruli ulcer . This devastating necrotic human skin disease is the third most common mycobacterial disease , after tuberculosis and leprosy . The detection rates of Buruli ulcer were found to increase gradually and steadily . The range of the disease extends from 10°N to 10°S latitude in Africa and spans 16 endemic countries , 10 potential endemic countries and 20 non endemic countries . The majority of cases are localized in Africa , with cases also reported in Asia , Australia and South America . In Africa , Buruli ulcer occurs mainly in poor rural communities [1]–[5] . As a consequence , very often treatment is sought and prescribed too late . Treatment of later stages requires extensive surgery at major hospitals , involving prolonged and very expensive stays , with 25% of those who experienced Buruli ulcer -in particular children- becoming permanently disabled [6]–[7] . More recently , it was possible to cure the disease at an early stage with antibiotics , without the need for surgery . The administration of a combination of rifampin and an aminoglycoside for four to eight weeks led to the healing of early lesions , without radical surgery . This antibiotics-based treatment is now the recommended standard regimen in areas where information about Buruli ulcer was made accessible , resulting in early diagnosis of the disease [8]–[9] . In 1998 , the World Health Organization launched the Global Buruli Ulcer Initiative to intensify surveillance , disease control , treatment and also to promote understanding of the ecology and the mode of transmission of M . ulcerans . There is at present no clear understanding of the exact mode ( s ) of transmission of M . ulcerans . Populations affected by Buruli ulcer are those living close to humid and swampy zones . Indeed the foci of the disease are associated with the creation or the extension of swampy areas , such as construction of dams or lakes for the development of agriculture ( irrigation ) [2]–[3] , [10]–[17] . Over the last few decades , different mechanisms have been proposed for the transmission of M . ulcerans from aquatic environments to human skin , ranging from aerosol contamination ( an hypothesis invoked in Australia but never confirmed ) [12] to insect-dependent transmission . The role of insects is indeed suggested by various studies over the past ten years . Recently , M . ulcerans DNA was detected in 0 . 04% of mosquito populations [18]–[20] . One possible transmission route is through the subversion of Aedes and Anopheles aquatic larvae ( inhabiting M . ulcerans-loaded water ) as hosts , with the human blood-feeding adults delivering M . ulcerans in the skin . However at present this hypothesis has not been confirmed experimentally , with no detection of M . ulcerans in the saliva or salivary glands . As the blood-feeding adults emerging from aquatic larvae cannot account for M . ulcerans transmission in any general way , different investigators have proposed that biting water bugs could act as vectors for M . ulcerans . In 1999 , Portaels was first to raise this hypothesis , and also to isolate M . ulcerans from water bug tissues [21]–[22] . Our pioneering experimental , laboratory-based , studies on mice have given weight to this hypothesis . These studies showed that M . ulcerans was able to colonize the salivary glands of water bugs , which could then transmit M . ulcerans to mice through biting [23]–[28] . Other field investigations allowed detecting M . ulcerans DNA in the water bugs captured in Buruli ulcer endemic areas [21] , [28]–[30] . On the other hand , a field study conducted in Ghana [30] did not support the role of biting Hemiptera or other invertebrates as possible M . ulcerans hosts/reservoirs or vectors . This study rather pointed out the need for further research to better understand M . ulcerans transmission [31] . In this context , our first study on the ability of water bugs to transmit bacterium through biting was confirmed recently in an invertebrate model [32] . Water bugs are familiar insects in aquatic habitats throughout the world . They are present in all Buruli ulcer endemic areas . They belong to the order of Hemiptera , containing several families . There are basically two kinds of water bugs: the semi-aquatic bugs , which live upon the water surface and the true water bugs , which live beneath the water surface . These invertebrates live in a wide variety of natural habitats , lakes and rivers ranging from small to large and also small ponds . Most water bugs can be characterized as predatory feeders , preying on aquatic invertebrates ( insect larvae , snails , etc . ) [33] . Water bugs can also feed on small vertebrates such as fishes and amphibians . In addition , a water bug family was reported to feed on plant material [33] . Most water bug species are able to fly , flying mainly at night when attracted by light , a feature that could account for M . ulcerans dissemination in the environment as suggested by Portaels and Meyers [34] . In this direction , M . ulcerans DNA was detected recently in water bugs collected out of their aquatic environment , thus demonstrating their flying capacity ( Marsollier , personal communication ) . In tropical areas , water bug biodiversity and biology are poorly documented , making it difficult ( i ) to define their role as M . ulcerans hosts and vectors and ( ii ) to characterize the relations between M . ulcerans and these aquatic insects . In this context , the present investigations had three objectives:
Regular sampling of aquatic insects was performed between October 2007 and July 2008 , in two areas of the Centre Province of Cameroon: a Buruli ulcer endemic area in the Nyong River basin ( Akonolinga , 3 . 77334N 12 . 24135E ) and a Buruli ulcer non endemic area ( Mbalmayo , 3 . 51552N 11 . 50085E ) situated 100 km downstream ( Figure 1 ) . The two areas , along the Nyong River , were selected on the basis of their accessibility all year long ( i . e . including in rainy season ) and of the availability of relevant epidemiological studies . Prevalence of Buruli ulcer endemic site ( Akonolinga district ) is estimated at 0 . 47% [16] , [35]–[36] and no case of Buruli ulcer has been reported at this day in Mbalmoyo . Both populations are primarily involved in fishing , which is supplemented by riverbank agriculture in the endemic site . The population densities are 21 h/km2 and 40 h/km2 in the endemic and non-endemic sites , respectively . Six and two large sampling collections were carried out respectively in the endemic site ( October , November , December , January , April and July ) and in the non-endemic site ( April and July ) . Water bodies were sampled from the main water sources: domestic washing , bathing , fishing and recreational sources . It is also noticeable that the sites under study corresponded to meeting points for the population , to cross the Nyong River in dugout canoes . Sampling was conducted between 8:00 am and 12:00 noon for all sites , with the same sampling methods . As aquatic bugs are associated in general with aquatic plants , the exploration was restricted to this ecological niche , along the bank of the Nyong River . In order to minimize escape of insects , a canoe was used to access the capture site . The insects were captured with a square-net ( 32×32 cm and 1 mm in mesh size ) from the surface to a depth of 1 meter , and over a distance of 1 meter . Each month , 5 samplings were performed on each of 3 consecutive mornings . A given sample corresponds to the mix of all insects collected after 10 sweeps . All insects were preserved in 70% ethanol for laboratory identification . The adults as well as nymph insects were numbered individually for taxa identification . To detect M . ulcerans DNA , the insects were sorted into pooled groups , including fewer than 10 specimens from the same family . The water bugs were classified in phylum Arthropoda , class Insecta , order Hemiptera and suborder Heteroptera . The main criteria for Heteroptera identification were as follows : The classification of the collected samples into families was performed based on the application of the heteroptera family determination criteria to each specimen [37] . Additional Belostomatidae ( Appasus sp . ) were selectively gathered by sweep sampling . They were transported to the laboratory in plastic containers with an air pump ( Pafex 3 aerator , Pafex ) in fresh water . It should be noted that these collected insects were not included in the counting of water bugs to study variation of water bug density and detection of M . ulcerans in water bug tissues . The saliva was collected by a method similar to that used for mosquito saliva [38]–[39] , with appropriate modifications . As a difference to the case of mosquito salivation , there was no need to remove legs and wings in order to sedate the insect and to inoculate a solution in the thorax region . The body of the water bug was grasped with metallic blunt pincers and its rostrum was placed into a conventional plastic pipette tip containing 10 µl of sterile water . With such manipulation white saliva fluid could be observed after 2 minutes time . From each individual saliva sample , 5 µl were used for quantitative PCR and 5 µl kept for Ziehl-Neelsen staining and mouse tail inoculation experiments in PCR positive cases ( Figure S1 ) . Pooled insect bodies were ground and homogenized in 50 mM NaOH solution . Tissue homogenates were heated at 95°C for 20 min . The samples were neutralized by 100 mM Tris-HCl , pH 8 . 0 . DNA from homogenized insect tissues was purified using Power Soil DNA isolation kit ( MO Bio lab , Carlsbad , CA ) , according to manufacturer's recommendations . 5 µl of each individual saliva sample was resuspended in 50 µl of 50 mM NaOH , heated and neutralized as described above . No purification was needed because no PCR inhibitor was present after DNA extraction from saliva . To eliminate DNA traces after each extraction , homogenizers were decontaminated overnight in 1 M NaOH and rinsed in distilled water before sterilization at 130°C for 20 min . Oligonucleotide primer and TaqMan probe sequences were selected from the GenBank IS2404 sequence [40] and the ketoreductase B ( KR ) domain of the mycolactone polyketide synthase ( mls ) gene ( Table 1 ) from the plasmid pMUM001 [40]–[43] . PCR mixtures contained 5 µl of template DNA , 0 . 3 µM concentration of each primer , 0 . 25 µM concentration of the probe , and IQSupermix ( Bio-Rad Lab ) in a total volume of 25 µl . Amplification and detection were performed with Thermocycler ( MX3000P , Stratagene ) using the following program: 1 cycle of 50°C for 2 min , 1 cycle of 95°C for 15 min , 40 cycles of 95°C for 15 s and 60°C for 1 min . DNA extracts were tested at least as duplicates , and negative controls were included in each assay . Quantitative readout assays were set up , based on external standard curve with M . ulcerans ( strain 1G897 ) DNA serially diluted over 8 logs . Samples were considered positive only if both IS2404 sequence and the gene sequence encoding the ketoreductase B domain ( KR ) of the mycolactone polyketide synthase were detected , with threshold cycle ( Ct ) values strictly <35 cycles . The university laboratory is enrolled in quality control of clinical specimens , along with three partners: Angers University Hospital , Pasteur Centre of Yaoundé ( Cameroon ) , and Institut Pasteur of Bangui ( Central African Republic ) . The quality assurance program of the laboratory has been also involved in the analysis of environmental samples , under the coordination of the WHO Collaborating Centre for Mycobacterium ulcerans ( Victorian Infectious Diseases Reference Laboratory in Melbourne ) . Positive PCR saliva of Appasus sp . were pooled according to the sampling month and diluted in PBS ( final volume 160µl ) . To detect the acid-fast bacilli , smears of suspensions ( 10µl of saliva suspension pool ) were stained by the Ziehl-Neelsen procedure and examined using an oil immersion lens ( 100× ) in an Olympus binocular microscope ( model CH30 Olympus ) ( Figure S1 ) . Six week old female BALB/c mice ( Charles River France , http://www . criver . com/ico ) were maintained under conventional conditions in the animal house facility of the Centre Hospitalier Universitaire , Angers , France ( Agreement A 49 007 002 ) , adhering to the institution's guidelines for animal husbandry . From each saliva pool , 3 mice were inoculated subcutaneously with 50 µl of suspension , using 26-gauge needles . The first lesions appeared after the fourth month of inoculation , with inflammatory lesions of the tails of three mice ( two mice were inoculated with positive PCR saliva from the April pool , and one mouse from the July pool ) . Two weeks later , a small oedema was observed and mice were sacrificed . Tissue specimens from mice were weighed , minced with disposable scalpels in a Petri dish and ground with a Potter–Elvehjem homogeniser , size 22 , ( Kimble/Kontes , Vineland , NJ ) , in 0 . 15 M NaCl to obtain a tenfold dilution . Smears of suspensions ( 10 µl ) were stained by the Ziehl Neelsen procedure . DNA was extracted from this material and purified to detect and quantify M . ulcerans by quantitative PCR , as described above . Tissue suspensions were decontaminated using an equal volume of N-acetyl-L -cysteine sodium hydroxide ( 2% ) , as previously described [44] , and 0 . 2 ml of each suspension was inoculated onto two Löwenstein–Jensen slants and incubated at 30°C ( Figure S1 ) . The number of water bugs collected per sampling was modelled using a negative binomial regression , with a random intercept to allow for within-day correlations of samples collected the same day . In this model , the effect of “month of collection” was studied as a fixed effect by introducing dummy variables associated with months of collection . Pearson Chi-square tests were used to compare proportions , and in particular the proportion of insects belonging to a given family ( e . g . , Belostomatidae , Notonectidae , … ) by month of the study , the proportion of insect pools positive for the presence of M . ulcerans DNA by month of the study , the proportion of insect pools positive for the presence of M . ulcerans DNA by insect family , and the proportion of saliva samples of Appasus sp . ( Belostomatidae ) positive for M . ulcerans DNA by month of the study .
The inventory of water bug families in Centre Province of Cameroon was undertaken in Buruli ulcer endemic and non endemic areas , along the Nyong River . Among 7 , 407 collected specimens , seven aquatic Heteroptera families ( Four true aquatic bugs and three semi-aquatic bugs ) present in both areas were identified: Belostomatidae , Notonectidae , Nepidae , Corixidae , Gerridae , Mesoveliidae and Hydrometridae ( Table 2 and Figure 2 ) . The two most diversified families in our study were the families Notonectidae and Belostomatidae . Seven undetermined morphotypes were present in the Notonectidae family , two belonging to Anisopinae subfamily and five to Notonectinae subfamily . Appasus sp . , Lethocerus and another unidentified morphotype were present in the Belostomatidae family . Only one subfamily was identified in Nepidae and Corixidae families , respectively Micronectinae and Ranatrinae . All families identified in this study can be characterized as carnivorous predatory fluid-feeders , with the exception of the Corixidae family ( plant feeders ) . Three families ( Belostomatidae , Notonectidae , Nepidae ) , among the six carnivorous ones , are able to bite humans and to fly . Cameroon has a tropical climate which varies from equatorial in the South to Sahelian in the North . The equatorial South , where the Buruli ulcer endemic area is located , has two wet seasons and two dry seasons . One wet season occurs between March and June and the main wet season occurs between August and November . One dry season occurs between June and August and the main dry season occurs between December and March . The population dynamics of water bugs was investigated in an endemic area for Buruli Ulcer ( district of Akonolinga ) . In order to get comparable results , insects were captured at periodic intervals by the same operator ( with standardized sampling methods ) , in the same water body each time . Large fluctuations of water bug density were observed among the samples ( Figure 3A ) . The highest number of collected insects per sampling was recorded in January , during the long dry season ( median = 369 ) , whereas in other months , the median number of captured insects per sampling varied between 25 and 94 specimens ( p<0 . 001 , according to the negative binomial regression model estimating the count of insects per sampling ) . With respect to water bug families , the following variations in the sample composition were observed: out of seven families , four families ( Belostomatidae , Notonectidae , Gerridae , Nepidae ) were collected throughout the study period ( Figure 3B ) , whereas the three other families ( Corixidae , Mesoveliidae and Hydrometridae ) were found only in January and/or April ( Figure 3B ) . The most abundant family was Notonectidae ( 67% of total collected water bugs ) . The proportions for the other families were: 14 . 2% ( Belostomatidae ) , 10 . 5% ( Gerridae ) , 5 . 6% ( Corixidae ) , 1% ( Hydrometridae ) and 0 . 1% ( Mesoveliidae ) . The relative abundance of families fluctuated over the year . For example , Belostomatidae and Notonectidae represented respectively 59 . 8% and 34 . 3% of total insects in October , and 10 . 1% and 88 . 4% in November ( Figure 3B ) . Moreover it was observed that in January Corixidae reached the highest abundance ( 10 . 2% out of total water bugs ) , whereas in January and April the highest water bug diversity was noticed ( Figure 3B ) . All these data suggest that the long dry season corresponds to the period during which highest water bug diversity and abundance occur . Detection of M . ulcerans in samples collected in Buruli ulcer endemic and non endemic sites was performed by PCR targeting the IS2404 insertion and the KR domain which encodes a polyketide synthase . From 3647 water bugs collected in the endemic area , 68 pools out of 616 ( 11% ) were positive for both markers , IS2404 and Ketoreductase ( Figure 4A ) . In addition M . ulcerans DNA was detected in five out of seven analyzed insect families . The rate of colonization in these pools was around 10% , except for the Corixidae family ( Micronectinae ) captured only in January , for which the rate reached 43 . 7% ( p = 0 . 008 , Pearson Chi-square test ) ( Figure 4B ) . Of note , this result was confirmed for individual Corixidae specimens ( n = 72 ) . However , given the very low number of collected water bugs from Mesoveliidae and Hydrometridae families ( 33 and 9 specimens , respectively ) , it is difficult to draw clear conclusions , in this case , about their possible subversion as hosts for M . ulcerans . The rate of insect colonization by M . ulcerans fluctuated between 1 . 4% and 33 . 9% according to the sampling period , with a peak in July ( 33 . 9% ) ( p = 0 . 008 , Pearson Chi-square test ) ( Figure 4A ) . Moreover , in the present study , no correlation was established between abundance of water bugs and rate of colonization of water bugs by M . ulcerans . All families -notably Belostomatidae , Notonectinae and Gerridae- displayed very similar fluctuations in colonisation rates by M . ulcerans ( Figure 4C ) , with the exception of Nepidae ( for which the sample size was limited ) . From 422 water bugs caught in a Buruli ulcer non endemic area , no pool out of 80 was found positive ( Table 3 ) . Significantly , in these same April and July periods , 11 . 5% and 33 . 9% , respectively , pools were found positive in the endemic site situated 100 kms away . Only living Belostomatidae insects of the genus Appasus sp . ( Figure 5A and B ) were allowed to salivate , for technical reasons . The saliva of these insects was first monitored for the presence of M . ulcerans DNA ( Figure 5A and B ) . The individual saliva samples analysed by IS2404 and KR PCR were found positive in 51/293 of cases ( 17 . 4% ) , with a peak in July . Similar patterns were observed with homogenate tissue of Appasus sp . ( Figure 5C ) . Interestingly , few acid-fast bacilli were observed in saliva samples of three individual positive pools ( November , April and July ) . Their viability was evaluated by inoculation of PCR positive saliva into the tails of 21 Balb/c mice . Using quantitative PCR , quantity of inoculated bacilli was determined to range between 1×102 and 5×103 bacilli per ml . Four months after the subcutaneous injection , three mice displayed lesions typical of M . ulcerans , in which acid-fast bacilli were detected . Quantity of bacilli was estimated by quantitative PCR to range between 6×104 and 3×105 bacilli per ml of grounded tissue . This result suggests growth of Mycobacterium ulcerans in mouse tail . It can be noticed , however , that conventional methods failed to isolate the bacilli by culture from mouse tissues presenting clinical lesions .
The aim of this study was to assess the role of water bugs as hosts and vectors of M . ulcerans , in the complete environmental context . To this end , we carried out an extensive field study on unprecedented temporal and spatial scales , monitoring the distribution of water bugs harboring M . ulcerans and the dissemination of M . ulcerans in the environment . We assessed water bug diversity and determined the frequency of insect tissue colonization by M . ulcerans in the various seasons , in an area in which Buruli ulcer is endemic ( Akonolinga , Cameroon ) . For the purposes of comparison , the study also covered an area in which Buruli ulcer is not endemic . In short , the specificities of the study are: ( i ) focusing entirely on water bugs; ( ii ) the collection of samples from the same water body in all four seasons and ( iii ) large-scale sample collection in Buruli ulcer endemic and non endemic areas , with subsequent analysis of the captured water bug specimens ( 7407 specimens collected , 696 pools analyzed ) . We document here , for the first time , fluctuations in the density of water bug families in an area in which Buruli ulcer is endemic , over the course of a year . The highest density of water bugs is recorded in January , during the long dry season . Variations of water bug density described here are in agreement with those in another study in a tropical area ( Costa Rica ) [45] . The causes of these fluctuations remain unclear , but several possible factors have been identified , including abrupt changes in environmental conditions or prey density [33] , [45]–[46] . Seven water bug families were identified in Buruli ulcer endemic and non endemic areas , including many unknown species . This latter point is not surprising , as determination keys for water bug species are not yet available for West Africa . One key finding of our study was the striking difference between the endemic and non endemic areas in terms of the density of water bugs , with the density in the endemic area more than 10 times higher that in the non endemic area . It can be noticed that this observation is not in accordance with results in another published study [31] . However , the conclusions of this previous study were drawn based on data for a significantly smaller number of specimens ( only 200 water bugs; 2% of the invertebrates collected [31] ) . M . ulcerans DNA was detected in five of the seven families of water bugs in the endemic area . The mean rate of colonization was about 10% . However , large fluctuations were observed in the rate of insect colonization by M . ulcerans ( 1 . 4 to 33 . 9% ) . As observed for other hosts of microorganisms [47]–[48] , there was no correlation between water bug density and rates of water bug colonization by M . ulcerans . We detected no M . ulcerans DNA in insects from the non endemic area , despite the high rates of colonization reported for the nearby endemic area . One key difference between the endemic and non endemic areas concerned human activity . Despite their close physical proximity , the non endemic area was largely unaffected by human activity , whereas , in the endemic area , the bank of the Nyong River had been deforested , for agricultural and fishing activities ( Figure 1B and C ) . Interventions disrupting the environment have been identified , in several studies , as factors potentially favoring the establishment of M . ulcerans in remodeled environments [13]–[15] , [49] . The observed fluctuations in colonization rate may be accounted for by changes in the level of water in the Nyong River , which falls markedly in the dry season . Our results are supported by the findings of an epidemiological study performed in 1993 [50] , in which low water levels in the dry season were found to favor the transmission of M . ulcerans to humans . Several factors may be involved in this phenomenon , including greater access to nutrients ( resulting in an increase in M . ulcerans density ) and the abundance of aquatic vegetation favoring M . ulcerans biofilm formation [26] , [30] , [51] ( increasing the level of contact between M . ulcerans and water bugs ) . The water bugs from the family Corixidae were the only phytophagous insects inventoried here . These water bugs were detected only in January , when they were present in high abundance , and displayed the highest rate of colonization by M . ulcerans ( 43 . 7% ) . The high frequency of colonization by M . ulcerans in Corixidae supports the hypothesis that aquatic plants may be the primary reservoir of M . ulcerans , as previously suggested [26] . This specific family may be involved in spreading the bacillus to other trophic levels , as they are eaten by other water bugs , aquatic invertebrates and vertebrates . These observations suggest that M . ulcerans may colonize different levels within the trophic chain ( aquatic plants , invertebrates and vertebrates ) , as already considered [21] , [30] , [52]–[53] . In addition , three water bug families are known to be good flyers [33] , [45] , and were identified as M . ulcerans hosts in our study . These water bugs may therefore be involved in disseminating M . ulcerans in the environment , as previously proposed by Portaels and Meyers [34] . We showed that water bug saliva could harbor bacilli . M . ulcerans may therefore be present in the saliva under natural conditions , with the bacilli colonizing the salivary glands of the insect . This could provide a route for M . ulcerans transmission in natural conditions , in accordance with previous experimental demonstrations in laboratory conditions [24] , [28] . It should be noted that the bacilli present in the saliva of Appasus sp . induced an M . ulcerans-containing lesion following the inoculation of mouse tail . However , it was not possible to isolate these bacilli by conventional culture methods . The lack of appropriate culture media and decontamination procedures adapted to the isolation of M . ulcerans ( from the environment ) thus remain a major handicap , hindering investigations of the ecology and mode of transmission of this mycobacterium . The various results presented above provide further evidence that water bugs are hosts and vectors of M . ulcerans , and provide insight into the environmental context underlying transmission . However , no definitive conclusion can yet be drawn concerning the precise importance of this route of transmission . The presence , in human sera , of antibodies binding water bug salivary gland extracts may be accounted for by the exposure of humans to water bug bites [27] . Indeed , reports of the exposure of humans to blood-feeding arthropods , which are known to act as hosts and vectors for parasitic microorganisms , are becoming increasingly frequent [38]–[39] . To gain a complete picture of the transmission route it would have been desirable to explore the relationship between the incidence of the disease in humans and the rate of colonization of water bugs by M . ulcerans , over a one-year period . Such exploration was however hampered by the amount of accessible information , with several important parameters not available : ( i ) incubation time between exposure to M . ulcerans and the appearance of the first clinical lesions ( currently estimated at between a few weeks and several months ) ; ( ii ) the slow progression of clinical lesions , resulting in patients being diagnosed at different stages of the disease ( rarely at early stages ) and ( iii ) the small number of Buruli ulcer patients diagnosed with early lesions between October 2007 and July 2008 in Akonolinga ( 84 Buruli ulcer patients , including 15 with early lesions ) . In conclusion , this study sheds light on the natural history of M . ulcerans within its ecosystem . The observed fluctuations in insect colonization rates suggest that there may be a particularly favorable period for the development of M . ulcerans in natural conditions , and a favorable period for the transmission of M . ulcerans to humans ( as previously suggested [50] , [58] and observed for Plasmodium sp . [47] , [59]–[60] ) . It is also noticeable that the results here can be put to advantage for practical applications , with surveillance and prevention purposes [27] , [61] . More precisely , our work suggests that the detection of M . ulcerans in water bug saliva could be used as an environmental indicator of the risk of M . ulcerans transmission to humans . It would then be possible to set up environmental surveillance ( detection of M . ulcerans DNA in water bug tissue and saliva ) in non endemic areas close to Buruli ulcer endemic areas . Health messages concerning environmental risk factors could be specifically targeted at populations newly exposed to the risk of M . ulcerans infection , as is already the case for protective factors ( wearing long clothing during farming activities and use of bed nets ) [16] .
|
Buruli ulcer , caused by Mycobacterium ulcerans , is a devastating skin disease . Most cases of Buruli ulcer occur in poor rural communities . As a result , treatment is frequently sought too late and about 25% of those infected—particularly children—become permanently disabled . Outbreaks of Buruli ulcer have always been associated with swampy areas . However , the route ( s ) of bacillus transmission is ( are ) still unclear . This Mycobacterium species resides in water where it colonizes many ecological niches such as aquatic plants , herbivorous animals and predatory/carnivorous insects . For several years the role of water bugs as hosts and vectors of M . ulcerans was suspected and was demonstrated under laboratory conditions . The aim of this work was to further assess the role of water bugs as hosts and vectors of M . ulcerans in environmental context . This work identifies several water bug families as hosts of M . ulcerans in Buruli ulcer endemic area . The detection of bacilli in saliva of human biting insects provides further evidence for their role in M . ulcerans transmission . Interestingly , three of these insects are good flyers , and as such could participate in M . ulcerans dissemination .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"ecology/community",
"ecology",
"and",
"biodiversity",
"microbiology/applied",
"microbiology",
"ecology/ecosystem",
"ecology"
] |
2010
|
Seasonal and Regional Dynamics of M. ulcerans Transmission in Environmental Context: Deciphering the Role of Water Bugs as Hosts and Vectors
|
Leprosy is a chronic infectious disease neglected , caused by Mycobacterium leprae , considered a public health problem because may cause permanent physical disabilities and deformities , leading to severe limitations . This review presents an overview of the results of epidemiological studies on leprosy occurrence in childhood in Brazil , aiming to alert health planners and managers to the actual need to institute special control strategies . Data collection consisted of an electronic search for publications in eight databases: Literatura Latino-Americana e do Caribe em Ciências da Saúde ( LILACS ) , Scientific Electronic Library Online ( SciELO ) , PuBMed , Biblioteca Virtual em Saúde ( BVS ) , SciVerse Scopus ( Scopus ) , CAPES theses database , CAPES journals database and Web of Science of papers published up to 2016 . After apply selection criteria , twenty-two papers of studies conducted in four different regions of Brazil and published between 2001 and 2016 were included in the review . The leprosy detection rate ranged from 10 . 9 to 78 . 4 per 100 , 000 inhabitants . Despite affecting both sexes , leprosy was more common in boys and in 10-14-year-olds . Although the authors reported a high cure proportion ( 82–90% ) , between 1 . 7% and 5 . 5% of the individuals developed a disability resulting from the disease . The findings of this review shows that leprosy situation in Brazilian children under 15 years is extremely adverse in that the leprosy detection rate remains high in the majority of studies . The proportion of cases involving disability is also high and reflects the difficulties and the poor effectiveness of actions aimed at controlling the disease . The authors suggest the development of studies in spatial clusters of leprosy , where beyond the routine actions established , are included news strategies of active search and campaigns and actions of educations inside the clusters of this disease . The new agenda needs to involve the precepts of ethical , humane and supportive care , in order to achieve a new level of leprosy control in Brazil .
Leprosy is a chronic infectious disease caused by Mycobacterium leprae . Since the disease may cause permanent physical disabilities and deformities , leading to severe limitations in individual’s ability to perform daily activities , this disease is considered a public health problem worldwide [1 , 2] . The incubation period of M . leprae is very long , in some cases up to ten years , and for this reason the majority of cases only become clinically detectable in adulthood . The occurrence of leprosy in children under 15 years of age suggests early exposure and persistent transmission of the agent [3] . Leprosy control has improved markedly around the world over the past thirty years . During this period the leprosy prevalence fell from 21 . 1 per 10 , 000 inhabitants in 1983 to 0 . 24 per 10 , 000 inhabitants in 2000 . This decline occurred due to the generalized use of multidrug therapy ( MDT ) , in addition to nationwide campaigns and an improvement in the quality of health services directed to leprosy treatment in endemic countries [1] . In 2016 , the World Health Organization ( WHO ) launched a new global strategy entitled “The Global Leprosy Strategy 2016–2020: Accelerating towards a leprosy-free world” [4] . The total number leprosy new cases registered by the WHO in 2016 was 214 , 783 ( 2 . 9 per 100 , 000 inhabitants ) , 95% of which are concentrated in only 14 countries of high endemicity where over 1 , 000 new leprosy cases are notified each year [1] . These countries are geographically situated within the tropics , with India in first place and Brazil coming second in terms of the number of cases detected annually . In 2017 , the total number of leprosy new cases in Brazil was 22 , 940 , of which 1 , 718 were in children under 15 years of age , corresponding to 7 . 5% and detection rate of 3 . 72 cases per 100 , 000 inhabitants [5] . One of the goals of the Global Leprosy Strategy 2016–2020 is to further reduce global and local leprosy burden , aiming to reduce to zero the number of children with disabilities due to this disease . However , in the last five years in Brazil , the percentage of children <15 years old that has grade 2 disability ( G2D ) ranged from 2 . 9% ( 2013 ) to 4 . 1% ( 2017 ) , with an average proportion of 3 . 7% , reflecting long delay in diagnosis [5] . One of characteristics of the distribution of leprosy is the occurrence in clusters , and in Brazil the leprosy detection rate in the all population and in the under 15 years of age , varies greatly among regions and cities . A region is considered hyperendemic when the leprosy detection rate in under 15 years of age is above 10 per 100 , 000 inhabitants [6] , in many areas , the values of this indicator reach higher levels those considered hyperendemic [5] . In 2016 , the detection rate of new cases in this country reached 12 . 2 per 100 , 000 inhabitants , considered “high” according to the reference parameters established by the Ministry of Health [5] . In the northern region , this indicator in the general population was 28 . 7 per 100 , 000 inhabitants , and of 8 . 92 per 100 , 000 inhabitants under 15 years of age . In the Midwest , 30 . 01 new cases per 100 , 000 inhabitants were registered for the general population and 6 . 42 per 100 , 000 inhabitants under 15 years of age . In the Northeast of the country , the detection rate in the general population was 19 . 29 per 100 , 000 inhabitants , while in those under 15 years of age was 5 . 78 per 100 , 000 inhabitants [7 , 8] . Based on fact that leprosy in children under 15 years of age is hiperendemic in Brazil and that produce important negative effect on life of the affected children and their families , the research question that guided this systematic review was: Does the epidemiological studies on leprosy in childhood , in Brazil , have warning to the policy makers and health managers that the severity of negative effects of this disease is demanding immediate attention ? This review presents an overview of the results of epidemiological studies on leprosy occurrence in children under 15 years , in Brazil , aiming to alert health planners and managers to the need to institute special control strategies for this disease , which is one of the most neglected problems of public health .
The review was conducted between May 17 and August 10 , 2016 using the databases listed in Table 1 . Equivalent keywords or subject terms were identified using health sciences descriptors ( DeCS ) , a trilingual structured vocabulary created by the Latin American and Caribbean Center on Health Sciences Information ( LILACS/BIREME ) [10] , in the three languages ( Portuguese , English and Spanish ) included in this review . A simulated search by language was then conducted to verify which terms would achieve the optimal results in each database . The appropriateness of the language used in the search was assured by preserving the three languages as filters in the databases . Although the term “children under 15 years of age” was used as a keyword in various studies conducted in Brazil and internationally , no such equivalent was found in the DeCS , with “minors” being the closest term found . Therefore , in addition to the terms child and adolescent , the term “children under 15 years of age” was also used . Likewise , after a preliminary reading of the international papers , it was found that two forms were used in international papers when referring to “children under 15 years of age”: “under 15 years” and “younger than 15 years” . Therefore , the following search terms were used and restricted to the fields “title” , “abstract” and “keywords”: Brazilian databases: BVS , CAPES theses database and Scielo: Hanseníase AND “Epidemiologia” AND “Criança”; Hanseníase AND “Epidemiologia” AND “Adolescente”; “Hanseníase AND “Epidemiologia” AND “Menores de 15 anos” . International databases: LILACS , CAPES journals , PubMed , Scopus , Web of Science: "Leprosy" AND "Epidemiology" AND “Child” , "Leprosy" AND "Epidemiology" AND “Adolescent” , "Leprosy" AND "Epidemiology" AND “Under 15 years” OR “Younger than 15 years” , “Lepra” AND “Epidemiología” AND “Niño” , “Lepra” AND “Epidemiología” AND “Adolescente” , “Lepra” AND “Epidemiología” AND “menor de 15 años” . The protocol defined the following inclusion criteria: complete papers and theses available in the selected databases in English , Portuguese or Spanish . Since there were few scientific papers specifically on leprosy in children under 15 years of age , a decision was made not to restrict the beginning of the search period to any specific year , thereby including all the articles , dissertations and theses found up to the cut-off date of August 2016 , in which the type of epidemiological study was described in the Methods section . The exclusion criteria consisted of papers involving animals; articles published as a short communication or poster; papers in which the methodology used was not described; any other type of documents; and duplicates . The data extracted from the selected papers were transferred to an Excel 6 . 0 version spreadsheet using double data entry and evaluated independently by two reviewers ( MCAV and KVFA ) . All disagreements were settled by a third reviewer ( MGT ) . The relevant data that were collected in the publications selected for the systematic review were: authors , year of publication , journal , study site , study period , study design , population , age group , sex , education , type of housing , leprosy detection rate , epidemiological characterization , operational classification , clinical classification , vaccination with Calmette-Guérin Bacillus ( BCG ) scar , smear test result , disability degree at diagnosis , disability degree at cure , Hansen's reaction , close contact with leprosy patient , contact examination , 2nd BCG in contacts , detection mode , reason for discharge , complete treatment , relapse and sequelae . A scale was created to evaluate the quality of the articles selected for this systematic review ( S1 Table ) . This scale was based on and adjusted according to the proposals made by Downs and Black [11] and Boas and Neto [12] . Scores were awarded for the selected items on a 17-point scale and analyzed according to the mean score awarded for the quality of the articles .
A total of 2 , 075 papers were identified in the databases following a search based on the selected keywords . Subsequently , 1 , 880 articles were excluded because: they did not meet the study objectives , they dealt with subject matter other than that proposed , duplicates , the papers were not available in their entirety , the age group included in the study was older than that established for this review , or the objective of the study was not included in the keywords , title and/or abstract . Fig 1 consists of a flowchart depicting the selection of the articles in accordance with the PRISMA guidelines . The 22 studies selected for inclusion [3 , 13–33] were published between 2001 and 2016 , and the most productive year was 2010 ( 04 papers ) . The predominant database was the BVS from which eight papers were retrieved and included in the review . Geographically , the papers identified came from four regions of the country: the Northeast , Southeast , Midwest and North , as described in Table 2 . All studies included in this systematic review were based on scientific research ( n = 22 ) . Most of the studies were linked to universities ( n = 20 ) and only two were from the Brazilian Ministry of Health . The studies were financed by the authors' own resources ( n = 14 ) , by the National Scientific and Technological Development—CNPq ( n = 06 ) and Ministry of Health ( n = 02 ) . S2 Table 2 describes the papers in greater detail: author , year of publication , type of study , study population , study period , objective , main findings and score according to the methodology validation scale . The studies were ecological , cross-sectional or case series descriptive . Sample sizes ranged from 24 to 2 , 455 individuals of both sexes . Most of the studies provided descriptions of the participants according to age ( 0–4 years , 5–9 years and 10–14 years ) , sex , detection rate , epidemiological classification , operational classification , clinical classification and degree of disability . Of the 14 publications in which leprosy was presented proportionally by sex , males were more affected in 8 . With respect to the distribution of cases according to age group , the greatest number of cases occurred in 10-14-year-olds ( n = 10 ) . Only 13 papers provided the clinical classification of the disease and in 6 of these articles the most common was tuberculoid leprosy . Operational classification was described in 16 studies , with the paucibacillary form being predominant in 14 . The classification of the epidemiological situation of the studies place was described in 17 articles , with 11 reporting hyperendemic levels in children under 15 years of age , with detection rates that ranged from 10 . 9 to 78 . 4 per 100 , 000 inhabitants . Of these 19 papers , 5 reported prevalence in the states of Alagoas , Minas Gerais , Mato Grosso , Pará and Rio de Janeiro , with the level being highest in Mato Grosso at 25 . 9 per 100 , 000 inhabitants in 2014 . The proportion of cases diagnosed with grade 2 disability ( n = 13 ) ranged from 1 . 7% to 5 . 5% . However , the percentage of individuals in this group who had not undergone evaluation ( n = 5 ) ranged from 2 . 4% to 19 . 20% . Only five articles reported the proportion of grade 2 disabilities following cure ( ranging from 0 . 5% to 11 . 1% ) and only three reported on the proportion of the sample that was not evaluated , citing percentages that ranged from 18% to 61 . 5% . Household contact , with the family being the main source of transmission , was reported in three publications . According to the reports , 40% of the children had parents with leprosy , 20–36% a grandparent , 18% an uncle or aunt , and 4% had siblings with the disease . The examination of contacts was reported in four publications , with 24 . 2% to 90% of contacts having been examined . The principal form of detection reported ( n = 8 ) was through spontaneous demand at healthcare facilities ( 13 . 8% to 79 . 6% ) , followed by referral from another healthcare service ( 12 . 4% to 75 . 6% ) . Other forms of detection such as collective examinations ( n = 6 ) and the examination of contacts ( n = 7 ) were also reported , with percentages ranging from 1% to 6 . 6% and from 8 . 9% to 20 . 4% , respectively . The presence of a BCG vaccination scar and of a second dose of this vaccine for the contacts was described in only two studies , with results showing that the presence of a scar from the first dose of this vaccine was high; however , revaccination of contacts was very low , between 13 . 8% and 15 . 5% . Five studies reported on acid-fast microscopy results , with this test having been performed in 20 . 6% to 94 . 6% of cases and with positivity ranging from 4 . 3% to 15% . In 4 . 4% to 79 . 3% of cases , this test was not performed . Only two papers described the occurrence of a leprosy reaction . In one of these articles , reaction occurred in 33 . 4% of patients: immediately following diagnosis in 24 . 4% and following cure in 9% . The other study simply mentioned that 44 . 1% of the patients did not develop a leprosy reaction . Complete treatment involving six doses of multidrug therapy ( MDT ) was administered in 41 . 7% to 66 . 7% of cases , with 12 doses of MDT being administered in 11 . 8% to 45 . 8% of cases . In another 2 . 14% to 21 . 5% of cases , treatment regimens were longer or unknown . Recurrences were recorded in 3 . 4% of children . Complete cure ranged from 81 . 9% to 90% of cases . Few studies emphasized the importance of drawing the attention of health planners and managers to the need to develop special actions for childhood .
In spite of these limitations , the results of this study will be useful , especially for public health , since they will help to alert the decision makers to the need in identifying the care needs of those under 15 years of age affected by the disease due to social stigma and the leprosy physical repercussions in the children . Although it has not been the object of evaluation of most of the studies , several authors point out that one of the problems of leprosy control is the fragility of surveillance , since the action of health services is predominantly individualized , with a low proportion of search active contacts . The detection of new cases depends on the spontaneous demand of the individual , who mostly seek the health service in advanced stage of the disease , which increases the risk of permanent damage . [3 , 5 , 19 , 23] . The presence of the contacts and the communities in the greatest risk of disease , should be found of the pillars of collective actions , continues being one of the main force to overcome those in the Brazilian leprosy control program . Besides , the treatment of leprosy patients still not meet the target established ( 98% ) by Brazilian Ministry of Health and WHO [25] . In view of this adverse scenario , we suggested the development of studies in spatial clusters of leprosy , where beyond of the control and surveillance actions established by the Brazilian Ministry of Health , are included news strategies of active search adding social contacts , campaigns and actions of educations inside these areas aiming early diagnoses and treatment . If many new cases in children will be discovered in these communities , it is understood that the search must be expanding to others neighboring area to uncover the primary sources of infection to prevent new cases in childhood . For this , it is necessary a debate and initiatives needs to be carried out to establish an agenda aimed at strengthening the active surveillance of this disease . This agenda needs to involve the precepts of ethical , humane and supportive care in order to achieve a new level of leprosy control in Brazil .
|
Leprosy remains as a severe health problem in Brazil and its transmission in children under 15 years of age occurs mainly through intradomiciliary contacts . The number of leprosy cases in this age group is considered an important indicator for the surveillance of this disease . To understand how the epidemiological studies in Brazil have shown the situation of young people affected by leprosy , we performed a systematic review of the literature , searching for published articles about the situation of leprosy in this age group . We reviewed 22 studies published during 2001 to 2016 and concluded that the negative effects of leprosy still remain high in most of studied places in Brazil . This disease was more common in boys , aged between 10 to 14 years old , with a remarkable proportion of disabilities due to leprosy . These disabilities can limit their routine activities and reflect failure in the public medical care . We hope that our review should contribute to arguments in order to improve the control of this disease in children .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"children",
"medicine",
"and",
"health",
"sciences",
"disabilities",
"tropical",
"diseases",
"geographical",
"locations",
"database",
"searching",
"bacterial",
"diseases",
"age",
"groups",
"neglected",
"tropical",
"diseases",
"families",
"research",
"and",
"analysis",
"methods",
"public",
"and",
"occupational",
"health",
"infectious",
"diseases",
"south",
"america",
"epidemiology",
"research",
"assessment",
"brazil",
"people",
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"places",
"systematic",
"reviews",
"database",
"and",
"informatics",
"methods",
"leprosy",
"population",
"groupings"
] |
2018
|
Leprosy in children under 15 years of age in Brazil: A systematic review of the literature
|
The increased reliability and efficiency of the quantitative polymerase chain reaction ( qPCR ) makes it a promising tool for performing large-scale screening for infectious disease among high-risk individuals . To date , no study has evaluated the specificity and sensitivity of different qPCR assays for leprosy diagnosis using a range of clinical samples that could bias molecular results such as difficult-to-diagnose cases . In this study , qPCR assays amplifying different M . leprae gene targets , sodA , 16S rRNA , RLEP and Ag 85B were compared for leprosy differential diagnosis . qPCR assays were performed on frozen skin biopsy samples from a total of 62 patients: 21 untreated multibacillary ( MB ) , 26 untreated paucibacillary ( PB ) leprosy patients , as well as 10 patients suffering from other dermatological diseases and 5 healthy donors . To develop standardized protocols and to overcome the bias resulted from using chromosome count cutoffs arbitrarily defined for different assays , decision tree classifiers were used to estimate optimum cutoffs and to evaluate the assays . As a result , we found a decreasing sensitivity for Ag 85B ( 66 . 1% ) , 16S rRNA ( 62 . 9% ) , and sodA ( 59 . 7% ) optimized assay classifiers , but with similar maximum specificity for leprosy diagnosis . Conversely , the RLEP assay showed to be the most sensitive ( 87 . 1% ) . Moreover , RLEP assay was positive for 3 samples of patients originally not diagnosed as having leprosy , but these patients developed leprosy 5–10 years after the collection of the biopsy . In addition , 4 other samples of patients clinically classified as non-leprosy presented detectable chromosome counts in their samples by the RLEP assay suggesting that those patients either had leprosy that was misdiagnosed or a subclinical state of leprosy . Overall , these results are encouraging and suggest that RLEP assay could be useful as a sensitive diagnostic test to detect M . leprae infection before major clinical manifestations .
Leprosy is a slowly progressive spectral disease caused by Mycobacterium leprae , an intracellular bacterium that has a tropism for macrophages in skin and Schwann cells in peripheral nerves . In 1966 , Ridley and Jopling classified a five forms spectrum disease that at one end of the spectrum is tuberculoid ( TT ) leprosy , where patients mount a strong cell-mediated immune response against M . leprae resulting in the reduction and eventual clearance of the infecting bacteria . At the other end is the lepromatous ( LL ) , a condition characterized by highly infected and disseminated skin lesions with high levels of anti-M . leprae antibodies in serum and a weak cell-mediated immune response towards M . leprae antigens [1] , [2] . In between these two polar forms , unstable borderline cases with specific clinical , immunological and pathological characteristics exist and are subdivided into borderline tuberculoid ( BT ) , borderline borderline ( BB ) and borderline lepromatous ( BL ) . In addition , among bacterial pathogens , infection of peripheral nerves is a unique property of M . leprae and patients can exhibit a rare form known as pure neural leprosy , PNL [3] . Moreover , very early skin lesions may be presented as relatively nonspecific perineural infiltrates in which rare acid-fast bacilli can be detected , but without sufficient infiltrates to classify them; these are called indeterminate ( I ) . The disease is challenging to diagnose since there is no gold standard method to detect M . leprae or its cell components ( DNA , lipids or proteins ) . The major difficulty in leprosy diagnosis concerns tuberculoid , indeterminate or PNL forms where acid-fast bacilli ( AFB ) in slit smears are very rare or absent . Historically , one of the limitations to develop new diagnostic tests was the inability to grow M . leprae in vitro . Animal models such as mouse footpad [4] and armadillos [5] helped to overcome this problem and aided improvements in leprosy research . Since then , a wave of significant progress in understanding the molecular structure of M . leprae has been achieved including the completion of the genome sequencing of the leprosy bacillus [6] . Given that , simple and specific PCR assays for detection of small numbers of bacteria in clinical samples have been proposed . During the past 20 years , PCR methods have been developed to amplify different gene targets of M . leprae . These include genes encoding various M . leprae proteins such as the 36-kDa antigen [7] , the 18-kDa antigen [8] , or the 65-kDa antigen [9] , Ag 85B [10] , 16S rRNA [11] and the repetitive sequences ( RLEP ) [12] . Recently , quantitative PCR ( qPCR ) assays which are based on real-time quantitative fluorescence detection are replacing conventional end-point PCR in many laboratories . They have improved specificity and sensitivity for quantification of bacterial DNA or cDNA content directly in clinical samples , in addition to more rapid turnaround time , which surpasses the conventional PCR technique using gel or colorimetric detection sensitivity [10]–[13] . In fact , as much as 40–50% of cases missed by standard histology and other clinical or laboratory methods can be confirmed by the use of conventional molecular methods , and one would speculate whether qPCR would improve this rate of diagnosis [14] . However , also to be considered is the fact that PCR-based diagnosis has a considerable level of failure in confirmed leprosy cases after clinical or laboratory standards . This is probably due to variability of clinical forms , i . e . the reduced amounts of M . leprae among paucibacillary patients reflect the need to further optimize molecular methods . The performance of PCR assays for M . leprae detection , however , has only been evaluated through comparative studies: comparing two different gene targets [15] or reproduction of standardized PCR assays by few groups [8] , [10] , [11] , [13] . Hence , standardization of the PCR assays for quality assurance of leprosy diagnosis is still lacking . Identification and establishment of standardized procedures to provide adequate clinical material , nucleic acid extraction protocol , primer target , amplicon size , PCR inhibition and control of amplicon contamination , fluorescence threshold determination , standard curve quality control , and estimated chromosome counts cutoffs will assure a more reliable and reproducible diagnosis of the disease . Assays with standardized procedures can be also of immense help for others dermatological differential diagnosis , for instance , leishmaniasis , cutaneous tuberculosis , sarcoidosis , where pathological examination is inconclusive . In the present study , we have developed and evaluated decision tree classifiers [16] from absolute chromosome count estimates based on standard curves built from qPCR assays for leprosy diagnosis , which account for biological and clinical heterogeneity ( TT vs LL ) . Four previously described TaqMan® qPCR assays were compared for the identification of M . leprae in 62 skin biopsies from patients diagnosed with leprosy , skin biopsies from patients initially suspect of having leprosy , or healthy skin of non-leprosy subjects . The comparisons were made based on the following gene targets: Ag 85B [10] , sodA and 16S rRNA [12] and RLEP [13] and a confirmatory diagnosis from patients previously diagnosed by a committee of experts ( pathologists and dermatologists ) based on clinical and laboratorial tests at the outpatient unit of the Oswaldo Cruz Institute , Fiocruz . We intentionally include a higher proportion of paucibacillary samples , especially the cases where rarely M . leprae ( DNA or bacilli ) is detected . These cases correspond to the indeterminate , pure neural and tuberculoid forms , i . e . , exactly when the leprosy diagnosis is more challenging . Thus , the intent here was to identify and select the most sensitive and specific PCR assay useful for differential and early diagnosis of leprosy .
The main goal of this study was to comparatively evaluate four different TaqMan® qPCR assays for leprosy diagnosis using a range of clinical samples that could bias the results . To develop standardized protocols and to overcome the bias resulted from arbitrarily analysis of the assays , we propose the use of decision tree classifiers to estimate optimum cutoffs . The following gene targets were used to determine the presence and levels of M . leprae: Ag 85A , sodA and 16S rRNA and RLEP . Punch skin biopsy ( 6 mm3 ) specimens from patients were obtained at the outpatient unit of the Oswaldo Cruz Institute , Fiocruz , Rio de Janeiro , Brazil . The patients were classified clinically , bacteriologically , and histopathologically , according to the Ridley-Jopling scale ( R&J ) [1] . A total of 62 skin biopsies were included in this study ( Table 1 and Table S1 ) . Multibacillary ( MB ) patients ( LL , BL and BB ) had bacteriological indexes ( BI ) ranging from +1 to +5 . 5 while all paucibacillary ( PB ) patients ( including BT , I , and PNL forms ) had negative BI . The logarithmic index of bacilli in the biopsy ( LBI ) [17] of MB patients was also evaluated and ranged from 1 to 6 . Ten skin biopsy specimens from individuals that had suspicion of leprosy , but were further evaluated and clinically diagnosed with other skin diseases and five biopsies from normal healthy skin were also included as endemic controls ( Table S1 ) . Before the study was undertaken , all individuals participating in this study were informed of the purpose of the study , and written consent was obtained from all participants . The study was approved by the FIOCRUZ Ethical Committee . DNA was extracted from half of the 6 mm3 skin biopsy specimens using proteinase K digestion as described elsewhere [10] with modifications . Briefly , biopsy specimens were thawed at room temperature , minced and digested for 12 h at 60°C with proteinase K ( 300 µg/ml ) in 100 mM Tris-HCl ( pH 7 . 4 ) , 150 mM NaCl , and 10 mM EDTA ( pH 8 . 0 ) . In order to help break M . leprae cell wall , biopsy samples were then added to FastRNA® Blue tubes and homogenized twice in the FastPrep® FP 24 instrument ( Qbiogene , Carlsbad , CA , USA ) at a speed setting of 6 . 5 for 45 sec×2 with 5 min rest between homogenizations . The homogenates were extracted with phenol∶chloroform∶isoamyl alcohol . DNA was precipitated with isopropanol , washed in 70% ethanol , dried at room temperature , and resuspended in approximately 30 µl RNase Free H2O . The levels of M . leprae Ag 85B [10] , sodA [12] , 16S rRNA [12] , and RLEP [13] in skin biopsy specimens were estimated using TaqMan® qPCR amplification . Purified total DNA ( 200 ng ) in 2 µl were added to a total PCR reaction volume of 25 µl containing TaqMan® 2× master mix , 500 nM of each primer and 100 nM of each probe for sodA or 16S rRNA PCR assays , 200 nM of each primer and 100 nM of the probe for RLEP PCR assay or 300 nM each primer and 100 nM probe for 85B PCR assay . Reaction mixtures were prepared in duplicates and subjected to 50°C for 2 min , 95°C for 10 min , and 40 cycles of 95°C for 15 sec and 60°C for 1 min using a 7000 real-time PCR system ( Applied BioSystems , Carlsbad , CA , USA ) . Fluorescent accumulation data for skin biopsies specimens were analyzed by the ABI PRISM 7000 Sequence Detection System software ( Applied Biosystems , Carlsbad , CA , USA ) , and ΔRn values extracted . Cycle threshold ( Ct ) determination from ΔRn data was conducted in the open source software R version 2 . 9 . 1 ( available at http://www . R-project . org/ ) . Standard curves were generated for each qPCR assay using five titration curves with 10-fold dilutions of purified M . leprae DNA from nude mouse footpads ( kindly provided by Dr . Phillip Suffys ) with doses ranging from 1 ng to 10 fg . Fluorescent accumulation data for titration curves and were analyzed by the ABI PRISM 7000 Sequence Detection System software ( Applied BioAssays , Carlsbad , CA , USA ) , and ΔRn values extracted . Cycle threshold ( Ct ) determination from ΔRn data was also conducted in the open source software R version 2 . 9 . 1 . Ct values were plotted against input log-doses ( base 10 ) and standard curves determined by a linear regression , and the coefficient of determination ( R2 ) used as quality control . Then , the fitted standard curves were used to estimate M . leprae chromosome counts for skin biopsies specimens , considering one M . leprae genome to be equivalent to 3 fg [12] . Classification trees for this project used the open source software R version 2 . 9 . 1 implementation of the Quinlan's C4 . 5 algorithm [16] available in the packages ‘rpart’ and ‘caret’ ( available at http://cran . r-project . org/web/packages/ ) , for training and evaluation , respectively . Decision tree classifiers were trained with the set of estimated M . leprae chromosome counts derived from standard curves from the four different TaqMan® qPCR diagnostic assays previously described , and classes were assigned as C1 and C2 indicating that the skin biopsy specimen belongs to a confirmed leprosy patient or to a non-leprosy patient , respectively . Training parameters included: ( 1 ) prior probabilities for classes C1 and C2 equals 0 . 5; ( 2 ) 20 , as the minimum number of observations that must exist in a node , in order for a split to be attempted; ( 3 ) 10 , as the minimum number of observations in any terminal leaf node; and ( 4 ) Gini impurity as a measure of how often a randomly chosen element from the set would be incorrectly labeled if it were randomly labeled according to the distribution of labels in the subset . A series of 5 tree classifiers were built with different compositions of the input data . Four classifiers were built with single attributes , given by the chromosome counts from each diagnosis assay , while the fifth tree were built with all 4 attributes available , and then pruned in order to minimize the expected 10-fold cross-validation prediction accuracy . Pruning included a complexity parameter of 0 . 05 , informing the program that any split which does not improve the fit by 0 . 05 will likely be pruned off by cross-validation , and that hence the algorithm need not pursue it . Also , performances of the built tree classifier were estimated by its specificity , sensitivity , and by the trapezoidal approximation of the area under the receiver operating characteristic ( ROC ) curve ( AUC ) , a graphical plot of the sensitivity , or true positive rate ( sensitivity ) , vs . false positive rate ( 1−specificity ) , for the decision tree classifier as its discrimination cutoffs were varied . AUC can be seen as a measure of commitment between sensitivity and specificity . R code is available under request to authors .
Standard curves were built from the linear regression of Ct value estimates from five titration curves with replication with 10-fold dilutions of purified M . leprae DNA ranging from 1 ng to 10 fg for each qPCR assay ( Table 2; Figure 1 ) . Quality control was guaranteed by the high coefficient of determination values achieved , ranging from 98 . 2% to 99 . 7% ( Figure 1 ) . Moreover , to control any possible PCR inhibition , TaqMan® qPCR targeting the human TNF gene was also performed and all samples tested positive ( data not shown ) indicating no inhibition . Optimal fluorescence thresholds were chosen based on the common practice that it should be positioned on the lower half of the fluorescence accumulation curves plot from the 10-fold dilutions and was used both to calculate the cycle thresholds ( Ct ) for standard curves fitting and to calculate Ct for a total of 62 skin biopsy samples , 47 from untreated leprosy patients and 15 from patients suffering from other dermatological diseases and healthy donors . Considering the relation of one M . leprae genome at each 3 fg dilution [10] , doses estimated for each skin biopsies specimen from all qPCR assays were converted to chromosome counts and used as input to train classification trees for optimization of qPCR specific chromosome counts cutoffs used in leprosy diagnosis ( Figure 2 ) . The classification trees were also used to estimate generalized errors that should be expected when using these qPCR assays for leprosy diagnosis in unforeseen samples , not used in tree fitting . These generalized errors were estimated by the 10-fold cross-validation prediction accuracy ( 10-fAcc . ) , where data is partitioned in 10 parts according to the original class distribution and at each run 9 parts are used for training and one part is used for the estimation of the test accuracy , leading to a mean value after the end of the 10 independent runs . Besides the 10-fAcc . , we also report specificity , clinical sensitivity and the AUC for each of the four qPCR assays ( Table 3 ) . Based on the standard curves for the four assays , using Ct values obtained from 62 skin biopsy samples using the same fluorescence thresholds ( Tables 2 and 4 ) , we estimated the chromosome counts for each sample . Patients and control groups were classified according to clinical , bacteriological and histopathological criteria by experienced dermatologists and pathologists . Patients' names from other dermatological diseases were searched at disease surveillance and control database of Brazilian publicly-funded health care system , SUS ( Portuguese for Unified Health System ) . Indeed , three out of seven patients initially classified as controls had a confirmation of leprosy after databank search ( 5–10 years after biopsy collection ) . Therefore , those patients were reanalyzed histologically and reclassified according to R&J and then , both chromosome counts and diagnostic labels were used in the evaluation of four different qPCR assays for leprosy diagnosis . We found the estimated chromosome counts for each assay to be in agreement with Ridley and Jopling scale for MB leprosy forms ( Figure S1 ) . As a result of the evaluation , similar specificity and sensitivity were found for all four assays with RLEP assay being more sensitive ( Table 3 ) , with optimum chromosome counts cutoffs for leprosy diagnosis estimated as greater than or equal to 0 . 01 , 14 . 36 , 23 . 79 and 0 . 49 for RLEP , 16S rRNA , sodA and Ag 85B , respectively . The fact that the expected mean classification accuracy in distinguishing leprosy patients from non-leprosy with different qPCR assays ranges from 59 . 7 to 87 . 1% is not surprising due to the very low number of bacilli expected in I and BT ( negative BI patients ) cases , which comprised 55 . 31% ( 26/47 ) of leprosy samples in the dataset . As a result , since the highest proportions of the leprosy cases belonged to indeterminate ( 25 . 53%; 12/47 ) , borderline tuberculoid ( 23 . 4%; 11/47 ) , in addition to tuberculoid ( TT ) and pure neural , i . e . PNL , ( 27 . 65%; 13/47 ) forms ( Table 1; Table S1 ) , prediction of patients was expected to be extremely difficult . However , this is more in accordance to the challenging leprosy diagnostics found in day-to-day practice of a typical outpatient unit , which is also in accordance with our aim to validate M . leprae DNA detection toward the situations where PCR could be really useful . These results show that TaqMan® qPCR targeting the multicopy RLEP sequence outperforms other single targeting TaqMan® qPCR assays tested , which in turn have comparable detection , for assessing clinical samples . In addition , the RLEP qPCR assay proved to be more sensitive than others assays and has also a larger approximated area under ROC curve ( Table 3 ) , which shows a better commitment between sensitivity and specificity for this assay . Moreover , the performance of the classifier trained with the chromosome count estimated by all 4 assays did not improve the ability to correctly distinguish leprosy patients with that of the RLEP qPCR assay alone ( Table 3 ) .
This is the first systematic PCR comparative evaluation using different real-time assays for detection of M . leprae DNA in skin biopsies from patients of different clinical forms of leprosy as well as non-leprosy dermatological diseases and healthy individuals . Our previous work [10] indicated that Ag 85B assay was specific as it did not amplify any DNA in healthy skin biopsies . In fact , none of the assays used in this study have shown amplification for healthy individuals . The introduction in this study of patients who had suspicion of leprosy like chronic dermatitis , capillaritis , cutaneous mucinosis , bacterial erythema , leukocytoclastic vasculitis and folliculitis increased the complexity of the differential diagnosis , which justifies the lower estimated sensitivities found as compared to previous studies [10] , [15] , [18] , [19] . Four samples classified as leprosy by RLEP assay presented detectable chromosome counts ranging from 0 . 04 to 3 . 16 . These putative false positive results have to be interpreted very carefully as those patients had a previous suspicion of leprosy . Recently , Goulart and colleagues [20] described that among all nucleic acid markers for leprosy diagnosis in the literature , three presented higher sensitivity and specificity ( RLEP , Ag 85B and 16S rRNA ) . Indeed , our results demonstrated that RLEP qPCR assay could be used to improve patient detection due to its high sensitivity/confidence ( 100/88 . 9% for MB patients and 84 . 6/80 . 5% for PB patients ) , although the specificity of 73 . 3% has to be taken into consideration . As stated before , it is possible that the four patients clinically and histologically classified as non-leprosy had in fact leprosy that was misdiagnosed at the time or even a subclinical state of leprosy , especially because the area in Rio de Janeiro , where those people were diagnosed , is highly endemic . It is common to observe a very long incubation period to leprosy outcome and subclinical stages with dormant M . leprae within granulomas are likely to occur [21] . Nevertheless , those patients were followed up for up to 10 years and did not develop the disease . Thus , PCR positivity might indeed represent carriage of bacilli or subclinical infection , which does not indicate by itself the evolution towards the disease . An opposite speculation is that the repetitive sequence ( RLEP ) is highly conserved and as a result , many homologous sequences may be present in other environmental Mycobacterium species that have not been thoroughly investigated , generating false positive results , as reported for the M . tuberculosis IS6110 marker elsewhere [22] , [23] . If this last hypothesis is true , then the use of a single copy gene such as the Ag 85B is favored and seems to be a more promising candidate for PCR-based diagnosis since it presented the highest confidence ( 55 . 3% ) considering the PB patients as well and compared to all three others qPCR assays and 100% specificity . It is feasible that the two most challenge features when implementing a diagnostic assay based on qPCR by absolute quantification are: the choices of the chromosome count cutoff and its generalization error , or the accuracy of the assay for classifying a new sample . In this study , these challenges were solved by using decision tree classifiers . As result , in different qPCR assays evaluated , namely RLEP , Ag 85B , sodA and 16S rRNA , we have found different optimum chromosome count cutoffs for predicting leprosy , approximately greater than or equal to 0 . 01 , 0 . 49 , 23 . 79 and 14 . 36 , respectively ( Figure 1; Table S1 ) . Not surprisingly , assays with higher chromosome count cutoffs had lower sensitivity than those with lower cutoff , but with a decrease in its specificity ( Table 3 ) , which , in turn , indicates an adequate classification fit to the training data . Also , assays with lower chromosome count cutoffs had lower generalization error ( 10-fAcc . ; Table 3 ) , and so have a higher confidence while predicting leprosy in undetermined samples . The use of any classification assay has limitations , especially those that oversimplify a complex disease such as leprosy . In the absence of commonly accepted reference procedures the choice of data processing is currently at the discretion of the researcher . Also , since there is a shortage of publications discussing the comparison of different DNA-based PCR assays for the detection and enumeration of M . leprae this study provides a comparison of four qPCR assays previously standardized and published in the literature . Notwithstanding , an external quality assurance study on diagnostic proficiency , which includes certifying and publishing the results in a comparative and anonymous manner for leprosy research would be ideal . A multicenter study with blinded samples is essential . Other laboratory tests , such as the ELISA for anti-phenolic glycolipid I ( PGL-I ) IgM antibodies , are non-invasive and useful as an additional aid in diagnosis [24] , [25] . The presence of anti-PGL-I antibodies is known to correlate with the bacterial load [26] , and thus offers a further refinement of the WHO classification into patients with high and low bacterial loads . However , PCR has been proven to be more sensitive than serological tests , especially in paucibacillary patients [25] , [27] . Also , due to the complex and varying immune responses that characterize leprosy spectrum , improved serological tests are hard to achieve and still needed . Hence , even though serological tests may have epidemiological relevance , the higher sensitivity of the PCR technique makes it a more robust tool for leprosy diagnosis . Obviously , that it should be taken into consideration that introduction of qPCR in routine diagnosis of leprosy is not easy since it is an expensive and laborious technique . But , it is likely that qPCR will become cheaper and soon surpass the conventional technique by becoming the gold standard laboratory test for leprosy diagnosis . In tuberculosis , assays based on genexpert technology are currently in use for detection of active disease and resistance [28] . In leprosy , a rapid and early diagnostic tool , possibly based on qPCR , is still needed . The histopathologic and immunologic features of indeterminate cases suggest that it is an early form of the disease . Surprisingly , RLEP PCR assay correctly identified 75% of those patients suggesting that this can be used as a sensitive diagnostic test to detect M . leprae infection before major clinical manifestations . Recently , Banarjee and coworkers [29] presented that the use of PCR positivity in a follow-up of patients' contacts could predict the outcome of leprosy in 20% of the individuals suggesting that a qPCR would help detect and quantify M . leprae in these patients indicating chemoprophylaxis of contacts when needed . Hence , we believe that quantitation of M . leprae bacterial loads using RLEP qPCR will contribute to understanding mechanisms as well as being clinically important in targeting follow-up of high risk individuals and in the development of strategies for early detection and prevention .
|
Leprosy is a chronic infectious disease caused by Mycobacterium leprae an obligate intracellular pathogen that can infect cells in skin and nerves . Leprosy still affects 211 , 903 individuals per year worldwide and lead to permanent nerve injury that is generally associated with late diagnosis . The mechanisms of interaction between pathogen and the human host that leads to active disease are complex and there is no gold standard to detect M . leprae or host response that could early identify patients preventing severe forms of the disease , extensive nerve damage and disabilities . Thus , diagnosis relies mainly on clinical parameters and histopathological and bacteriological sometimes help to ascertain clinical form of patients . But , recently , advances in the genome of the pathogen provided extended information towards new targets to design novel genetic or immunological markers . Also novel molecular biology methods exhibiting higher sensitivity along with easy to handle apparatus based on nucleic acid detection are available . Here , we test and compare different assays for quantitative PCR ( qPCR ) designed to amplify specific M . leprae targets enriching the test sample with difficult-to-diagnose leprosy cases . Our results suggest that qPCR specially the one targeting repetitive element ( RLEP ) could be used to early detection of leprosy cases .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"biotechnology",
"biochemistry",
"genomics",
"mathematics",
"nucleic",
"acids",
"statistics",
"molecular",
"genetics",
"biology",
"computational",
"biology"
] |
2011
|
Evaluation of qPCR-Based Assays for Leprosy Diagnosis Directly in Clinical Specimens
|
Boundary vector cells in entorhinal cortex fire when a rat is in locations at a specific distance from walls of an environment . This firing may originate from memory of the barrier location combined with path integration , or the firing may depend upon the apparent visual input image stream . The modeling work presented here investigates the role of optic flow , the apparent change of patterns of light on the retina , as input for boundary vector cell firing . Analytical spherical flow is used by a template model to segment walls from the ground , to estimate self-motion and the distance and allocentric direction of walls , and to detect drop-offs . Distance estimates of walls in an empty circular or rectangular box have a mean error of less than or equal to two centimeters . Integrating these estimates into a visually driven boundary vector cell model leads to the firing patterns characteristic for boundary vector cells . This suggests that optic flow can influence the firing of boundary vector cells .
Populations of neurons within the entorhinal cortex and subiculum have firing patterns that depend upon the distance and angle of boundaries in the environment , such as barrier walls . Neurons with this pattern of firing are referred to as boundary vector cells ( BVCs ) [1]–[3] or border cells [4] . The definition of BVCs includes that of border cells . Border cells specifically fire at a short distance to the wall whereas BVCs fire at a short or long distance to the wall . More general BVCs have a tuning for different wall distances . Boundary vector cells were initially proposed based on observations of changes in the firing location of hippocampal place cells caused by changes in the location of barrier walls surrounding the environment [1] , [5] . The initial proposal of BVCs was extended in detailed computational models that explicitly predicted the pattern of firing of BVCs that could , in turn , generate the firing pattern of hippocampal place cells [2] , [5] , [6] . The predictions of these BVC models have been supported by recent experimental data clearly showing neural firing patterns similar to proposed BVCs in the subiculum [2] , [3] and the entorhinal cortex [4] , [7] . The firing fields of BVCs at a distance from the walls ( Lever et al . , 2009 ) cannot be explained by proximal cues such as those provided by the whisker system . At least three alternative cues could provide the information for distant firing , and these cues are not mutually exclusive . The first possibility is that distance estimates could be retrieved from memory in combination with sensorimotor path integration . This would require the memorization of the entire environment , especially its boundaries . Information about the spatial location of a boundary would be combined with the current spatial position and head direction to estimate distance and direction of that boundary . The current position and head direction of the rat would be estimated from temporally integrated sensorimotor signals . The second possibility is that multiple visual cues on the wall could be used by rats to estimate the normal of the surface and its distance based on the feature's relative size on the projection , requiring knowledge of the absolute size of the feature . However , typical rat experiments lack the presence of distinct visual features , e . g . wallpapers that could be used to estimate the distance of the wall . Therefore , this possibility seems unlikely . A third possibility is the use of optic flow , the varying patterns of light on the retina while the rat is moving . Optic flow could be used for distance and direction estimation of walls based on the following two assumptions: ( i ) walls are orthogonal to the ground; and ( ii ) these walls have piecewise smooth surfaces . In this article , we test this “flow-influence” hypothesis by simulating a rat's trajectory in a circular or square box while estimating the distance and direction of walls from optic flow and integrating these estimates into a model of BVC firing . A priori it is unclear if distance and direction estimates extracted from optic flow are accurate enough to support the firing of BVCs . We demonstrate that these estimates are sufficiently accurate , even for drop offs that lack an orthogonal wall . Further evidence for our flow-influence hypothesis is provided by the rat brain structures processing visual image motion . For instance , neurons in primary visual cortex are sensitive to visual motion [8] . These neurons are tuned for orientation , spatial frequency , and temporal frequency of gratings [9] . Another example is a hierarchy of visual processing identified in rats based on anatomical differences of brain structure . This hierarchy could have similar functions compared to the hierarchy found in primates [10] which is thought to extract properties of optic flow necessary for estimating self-motion [11]–[14] . An alternative pathway that has been explicitly pointed out in the processing of large-field optic flow could go from the retina to the accessory optic system [15] and from there to the hippocampal formation [16] . The latter connection has been described for pigeons . We test this optic flow processing hypothesis and demonstrate that a template model can interpret optic flow patterns and decompose them into variables of self-motion , distance , and direction estimates of walls . A sketch of our model is shown in Figure 1 . We assume a simulated rat is running in a box , Figure 1a . While the rat is running it samples optic flow patterns from the floor and walls . Sampling is from a wide visual field , as shown in Figure 1a . To model this wide field of view we use a spherical camera model , of which a side-view is shown in Figure 1b . The rat's eyeball is elevated above the ground and is moving in the forward direction , in this example . During this self-motion , sample points of the ground will have an angular displacement in the spherical camera model . The idea of our model is to match all the angular displacements that occur within the visual field by flow templates . These flow templates contain parameters of self-motion , ground , and wall planes , depicted by the three boxes in Figure 1c . Templates of ground and wall are constructed for a specific known head direction and tilt angle of the head , as well as for unknown self-motion parameters . The tilt is the angle between the optical axis and ground . The sensed flow is compared against all of these templates for parameterized self-motion , ground , and wall configurations . In a cascade of steps that detect maximum activity , the model extracts parameters of self-motion and planar surfaces . First , all templates for the ground and wall are compared and a wall-ground segmentation is achieved by selecting the maximum responding template ( no . 1 in Figure 1c ) . Note that the wall and ground template space also contains the parameters of self-motion . Second , the ground flow is used with outputs from the self-motion templates to estimate the self-motion parameters ( no . 2 in Figure 1c ) . Third , the distance and allocentric direction of walls is computed from the wall flow and the parameters of self-motion ( no . 3 in Figure 1c ) . The distance and direction estimates are passed along to the existing BVC model proposed by Burgess [5] , [6] , [17] . A sketch of the BVC model is given in Figure 1d . The BVC model uses the allocentric direction of a wall together with its distance . Model cells construct a tuning for allocentric direction and distance along the normal direction of the wall . In sum , our modeling work suggests that distance and direction estimates are extracted from optic flow and shows that when these estimates are then fed into the previously developed BVC model this can explain the characteristic firing of BVC cells as measured experimentally [3] . We make several assumptions to focus our modeling effort on the estimation of self-motion , distance and direction from optic flow . First , the visual field , across a full range of angles extending 240° horizontally and 120° vertically , is simulated using a spherical camera model that describes the flow of individual features of the visual scene by temporal changes of the azimuth and the elevation angle of these features ( see Figure 1a and 1b ) . Second , the simulation computes the analytical spherical flow of visual features in a virtual environment instead of estimating flow from an image stream . Third , if the rat is in a rectangular or circular box the walls are orthogonal to the ground . Fourth , we assume that the rat leverages different mechanisms to segment walls from the ground versus detecting drop-offs . Fifth , the model builds upon template cells that are tuned to optic flow that is generated by a combination of self-motion and an environment; and the environment is modeled as smooth surfaces for ground and walls . Tuning for self-motion has been found for neurons in macaque monkeys' area MST [11]–[14] . This finding motivated template models of self-motion estimation in macaque monkeys [18]–[21] . Several aspects distinguish our model from previously published template models . In our model , self-motion is restricted to curvilinear motions: These are translational motions along the optical axis combined with rotations around the vertical axis ( yaw-rotations ) . Our template model uses a spherical camera model that helps to account for effects in large visual fields in contrast to a pinhole camera that is restricted to a 180° visual field . Another difference from existing template models is the introduction of templates that are tuned to the combination of self-motion and smooth surfaces modeling walls or ground . This extended tuning allows not only for the estimation of self-motion but also for the estimation of the distance of these surfaces . We make no assumption with respect to the shape of the box , e . g . it could be square , rectangular , or circular . Note that the introduction of multiple models for ground and wall surfaces also requires the segmentation of flow into these separate surfaces . For instance , a rectangular box consists of a ground plane surrounded by planar walls whereas each individual optic flow sample has to be identified as either originating from ground or wall . Given analytical flow for a spherical camera model , the flow that is induced by linear or rotational motion of a wall can be distinguished from flow that is induced by the same motion of the ground . Thus , segmentation in our model is achieved by deciding whether the wall or ground flow template fits better to the sensed flow vector . Our model provides several extensions to existing template models and is motivated by the need to test whether physiological findings of boundary vector cell firing can be explained by using optic flow as a distal cue .
Our aim is to simulate the rat's body movement in an environment similar to the one used in the study of Lever et al . [3] . Therefore , we computed the movement statistics of available rat trajectories in circular [22] and square boxes [23] . Linear velocities are fit by a Rayleigh distribution and rotational velocities by a normal distribution . Values of these fits are reported in Table 1 . For these values we generated rat trajectories that matched these velocity distributions . Values of the match are reported again in Table 1 . For the generation of rat trajectories we combined a deterministic algorithm with a random component . We randomly generate a linear or rotational velocity that follows a Rayleigh or normal distribution , respectively . As the deterministic component we calculate a rotation that turns the rat to continue to walk parallel to the wall . This turn happens only if the rat is closer than 2 cm to the wall and its head direction is smaller than 90° with respect to the normal vector of the wall . Figure 2 contains the pseudo-code for this method . Figure 3 shows characteristics of our simulated rat trajectories . The Panel 3a shows the Rayleigh distribution of linear velocity ( or speed ) and Panel 3b shows the normal distribution of rotational velocity for the data for a rat in a circular box . Panels 3c and 3d show fragments of the first minute and of the first five minutes of the simulated trajectory . The second row , Panels 3e–3h , shows the same properties for simulated trajectories in a square box . Before the distance of walls can be estimated , flow samples of walls have to be segmented from flow samples of the ground . This is accomplished in the first stage of our model , see Figure 1c . Examples of the segmentation are shown in Figure 4c for a circular box and Figure 4g for a square box . In case of drop-offs our model employs a different mechanism by detecting the flow transition from large to small magnitude . Examples of this detection are shown in Figure 4d for a circular box and Figure 4h for a square box . Note that in these examples the drop-off , indicated by the red dots , is not completely detected . The detection shows gaps where the flow differences are not large enough to be picked up by our mechanism . However , these gaps appear for very distant points of the ground-plane and will not directly influence steering for the rat . In contrast , drop-offs that are close to the rat generate large flow differences that are picked up by our model mechanism and which are potential threats for the rat . Instead of modeling specific surface types , like curved and planar , we approximate arbitrary surfaces locally by planes . This allows us to use the same model for curved walls of a circular box or planar walls of a square box . Figure 5 shows examples of distance estimates . For instance , in Figure 5a distances are depicted by the magenta colored arrows that closely match up with the boundary of the box . The Panel 5d shows values of the 2D matching function when comparing the sensed flow to flow templates for walls of a certain allocentric direction and distance . The normalized match value is encoded in gray-values whereas black encodes a low match and white encodes a high match . In the example of Figure 5d ( circular environment ) the maximum is at ≈80° to the right and 20 cm distance . This maximum together with all responses that are within a 70% range of the maximum are displayed in Figure 5a by magenta arrows . Further examples are shown in the 2nd and 3rd column of Figure 5 . Note that wall distances are estimated for both curved and planar walls with the same mechanism , as shown in the examples in Figure 5a–c . Our template model allows for the estimation of distance and direction to multiple walls . In Figure 5b and 5c distances to two walls are estimated . These are represented by their individual matching high intensity regions in Figure 5e and 5f . For instance , for the square box in Figure 5b , high intensity regions appear in Figure 5e at 0° and 90° allocentric direction representing the left and upper wall , respectively . In case of the curved wall in Figure 5a , each segment of the wall is represented by a wall-model . High matching values appear around 80° allocentric direction in Figure 5d . This shows that our model generalizes to non-planar walls . In addition to these examples of single distance estimates , we evaluated the distance error systematically for each sample point of our simulated rat trajectories of approximately 20 min duration that include 60 , 000 sample points for the 50 Hz sampling frequency . We compute the mean distance error for each location , computed for all distance estimates made at that location . Note , that this error measure is , mostly , independent of the actual distance to the wall since all positions provide at least two different distances to walls , excluding the center in the circular box or square box . Here , we assume larger distance estimates for the center and smaller ones for areas close to the wall as our model tends to estimate distance to closer walls rather than farther walls . For the circular box , the mean error is largest in its center; see Figure 5g . For the square box the mean distance error is approximately homogenous and smaller , with a value of about one centimeter; see Figure 5h . For the square box with an intrinsic wall the mean distance error has a maximum of 6 cm , occurring at the inner side of the narrow passages at each end of the intrinsic wall; see Figure 5i . Next , we will integrate these distance estimates for allocentric directions into the boundary vector cell model . Optic flow could be one cue to support firing of boundary vector cells ( BVCs ) that fire for walls being present at a specific distance and allocentric direction . Distant firing distinguishes BVCs from border cells [4] . So far , our template model provides distance and direction estimates of walls , given the allocentric head direction which we assume is available , e . g . , from the head direction cell system . The head direction cell system encodes the head direction in an allocentric representation [24] . In our model simulation we assume the head direction and position given by ground-truth values for every sample point . We use the ground-truth head direction to estimate the wall direction in allocentric angular coordinates . Ground-truth positions are used to spatially register the firing of cells in the model . In the corresponding experiment of rats foraging in a box this ground-truth location is given by tracking the rat's position reconstructed from video recording of a light-emitting diode attached to the rat . Ground-truth position values are not provided to our template model of brain mechanisms for the estimation of self-motion or wall distances . When the model produces inconsistent distance estimates , the plotting of these estimates in relationship to ground-truth position appears as noisy plots of firing . Such firing lacks the consistent tuning properties for allocentric direction and distance toward the wall that is characteristic of data on the firing of boundary vector cells [3] . We compare the data of recordings of BVCs [3] and simulations of the BVC model [5] based on ground-truth input to our visually driven model of BVCs . Figure 6a shows the square box used for this simulation together with the occupancy of the simulated rat in this box . Figure 6b shows the firing of the BVC model when supplied with ground truth input . Figure 6c shows experimental data from recordings of recorded BVCs and Figure 6d shows our visually driven BVC model based on optic flow input . The firing fields of our visually driven BVC model are more restricted in location than the experimental data or the firing of the original BVC model that uses ground-truth input . In the original BVC model only four distance and direction values are used to update the firing of a model cell . For our visually driven BVC model more than four distance and direction estimates are used to update the firing of a model cell , see e . g . , the number of magenta arrows in Figure 5a–c . Because there are more estimates incorporated into the visually driven BVC model its firing fields appear more restricted compared to those of the original BVC model . Simulations and data for a circular box are shown in Figure 6e–g . Again , our simulated firing fields appear more localized than the firing of recorded cells . Our model assumes analytically defined flow . However , in case of flow detected from an image sequence , distance estimates could be more erroneous leading to the firing observed in recorded data . Aside from using a square and circular box we provide additional simulations with a wall inserted inside of the square box and in another simulation we removed all walls to model a platform . Figure 7b shows the BVC firing of our simulation and 7c the corresponding experimental data . The important observation from this simulation is that the BVC firing in the model is not tied to a specific wall of allocentric direction and distance but to any wall of an allocentric direction and distance . In our simulation , firing appears also next to the inserted wall . In the same way our model cells would adapt to wall changes in the environment as shown in another experiment which involved nesting two boxes , a small one in a bigger one . After some time the smaller box is quickly removed in that experiment . Then firing of BVC shifts its absolute position in the larger box to resemble the same distant tuning that it had in the small box [7] . Our model would produce results consistent with this experiment . For a platform , the drop-off is detected as a local discontinuity in flow direction and speed . Once the elevation of the drop-off is determined , it is converted into a distance estimate . All distance estimates are fed into the BVC model with their response values . Figure 7e shows the simulation results and 7f the corresponding experimental data . As in previous cases , the BVC in the model is more clearly restricted in location compared to experimental data . This greater restriction in location might differ if the optic flow signal were detected from visual input instead of analytically defined flow that is used in the simulation . In particular , flow detected from visual input would be noisier , and this would influence the accuracy of detection of flow discontinuities .
This paper presents a template model for scene-segmentation and the estimation of geometric properties of the environment , namely the distance and allocentric direction of walls and drop-offs . Distance estimates of our model in empty boxes are accurate within a two-centimeter-range; for a square box with an inserted intrinsic wall the error is higher at locations at the inner edge of the narrow passages created at either end of the intrinsic wall . When these distance and direction estimates are integrated into the boundary vector cell model [2] , [5] , [6] , the typical firing patterns found in experimental data on boundary vector cells can be observed . Template models for the estimation of ego-motion have been used mainly as a model for self-motion estimation in primates [18]–[21] , [25] . All these models used a pinhole camera model . In contrast , here we used a spherical camera model to simulate the large visual field of rats . Existing template models account for general self-motion sometimes restricted by visual fixation , which allows the translational motion to be compensated by a rotation in order to keep a single point stationary in the visual field [19] . No previously published template model provides a link to estimate environmental variables such as distance toward walls . Thus , our model is novel for defining an extended template space and for combining this with voting that allows for the estimation of multiple walls . An advantage of such a voting technique is the more robust estimation and compact description of the surrounding environment in contrast to reconstructing a depth map with variable depths for every single flow vector as suggested by others , e . g . by Perrone & Stone [19] . Most studies on firing properties of hippocampal structures in rats focus on visual cues in general , e . g . a cue card , but not on optic flow as such . For instance , visual cues influence the orientation and firing location of hippocampal place cells [26]–[28] . In neurophysiological recording data on place and head direction cell firing , landmark cues have been shown to dominate over idiothetic cues ( e . g . path integration of self-motion information ) if the mismatch between cues is smaller than 45° . Above 45° mismatch , the hippocampal representation of place cell firing reorganizes and head direction cell firing is dominated by idiothetic cues [28] . When deprived from vision and audition the majority of place cells ( 11 out of 15 ) lose their spatially consistent firing . Instead their firing pattern rotates with the associated arm of a multi-armed maze [29] . Entorhinal lesions had a similar effect to vision deprivation . Sixteen out of 17 place cells lost their spatially consistent firing [30] . Grid cells rotate their firing with visual landmark cues [22] . Combining results from the lesion and sensory deprivation study suggests a role of visual and auditory sensory signals in spatially consistent firing . However , none of the existing studies focused on optic flow as the only cue for spatially consistent firing . Although visual input provides a rich set of information , other cues might be important for BVC firing , as well . Vestibular information and visual motion influences hippocampal place cell firing [31] . Vestibular inputs are used to find a path back to the home location , especially in the dark [32] . Head direction cells are regulated by the vestibular system [33] . In blind rats place cell firing occurs and in four out of 15 cells the firing is spatially consistent [32] . The consistent firing in four cells provides evidence for the use of idiothetic cues such as path integration in order to maintain a stable representation of the self in the environment model [34; page 466] . Idiothetic cues like path integration and external cues like landmarks interact to regulate place field firing in rats on a running track foraging while cues are brought into mismatch by spatially shifting the goal location [35] . These various examples show that cues other than vision are important to maintain the firing of place cells . Three alternative technical solutions are possible for the segmentation of walls from ground , and subsequently the estimation of self-motion and environment variables . These are: RANSAC [36] , m-functions [37] , or the expectation maximization ( EM ) algorithm [38] . RANSAC could be based on a model for flow of the ground while treating flow samples from walls as outliers assuming that the majority of flow samples originate from the ground . Once the segmentation is achieved all the points identified as outliers can be used to estimate the distance and direction of walls . An integration of Equations ( 3 ) and ( 4 ) into convex m-functions leads to a non-linear optimization problem . An embedding into the EM algorithm with Gaussian mixture models leads again to a non-linear optimization . Overall , the segmentation of walls from ground is a challenging and computationally expensive task . For real-life images the quality of flow based segmentation depends largely on the quality of the detected flow and the dissimilarity between flow templates or flow vectors at the drop-off . Since we do not know the quality of detected flow for real-life images we study simulated noise superimposed on the analytically defined flow . Examples with additive Gaussian noise in each component of the flow with a signal-to-noise ratio of approximately 70 dB leads to larger errors in distance and direction estimates ( see Figure S1 ) . A major source for this error is insufficient segmentation . Since the segmentation is based on local information , a single flow vector , it is strongly influenced by noise . This could be compensated by adding a neighborhood function into the process of segmentation that assumes neighboring points belong to the same planar model , either wall or ground . Another problem is a close similarity between flow templates if matching a noisy input flow . Therefore , the dissimilarity or “distance” between templates should be maximized in the sense of the proposed matching functions in order to match noisy input flow to the correct flow template . For drop-offs the dissimilarity between flows at the drop-off versus everywhere else in the flow field matters . If discontinuities within the flow due to noise become too large false detections happen . This can be only compensated for with context information , e . g . providing extended curve models for the drop-off in the spherical camera model that could be fitted as an entire curve ranging from −120° to +120° azimuth angle for the parameterization of our spherical camera model . So far , these extensions have not been realized in the current model and are the subject of future work . Further properties of our model are the logarithm used in the matching function and the model's capability to incorporate tilt angles . Choosing a logarithmic sampling and the logarithm of motion speeds to compare input flow vectors and template flow vectors makes sense for a first-person perspective from an ecological and behavioral point of view . Typically , objects' distances that are far do not have to be represented with a high sampling , e . g . of centimeter-precision , because they are not reachable or are not potential obstacles . A logarithmic sampling of distance values also has an effect on the comparison between flow vectors of different distance . For optic flow generated by translational self-motion the length of flow vectors is inversely proportional to the distance of a sample point in 3D space . By transforming these distances using a logarithm we put more emphasis on short flow vectors that relate to points that are close to the rat . Figure S2 shows a comparison between a matching function that uses the logarithm of the speed and their difference or only the difference of speeds without the logarithm . In both cases the speeds are computed from the input flow vectors and template flow vectors . The matching that includes the logarithm appears clearer over the entire range of depths compared to directly using the difference of speeds . Note that the speed difference that does not involve the logarithm can be adjusted only to accommodate a small depth range with clear tuning . This concept of using a logarithmic sampling and logarithmic scale to compare speeds could be used even more broadly by mechanisms that afford an ecological solution , e . g . if only a limited small number of samples are available . Another property of our model is the incorporation of non-zero tilt angles . In such configurations the optical axis is not parallel to the ground . The normal vector that describes the wall or ground becomes dependent on the head direction . In our model this head direction is assumed to be given , e . g . by the vestibular cues captured by the head direction cell system , as is the tilt angle ( see also Figure 1c ) . Then our model constructs flow templates for this given tilt and head direction . Simulation results for BVC firing look similar to the ones of Figure 5 and 6 as shown in Figure S3; however , distance errors at large distances are slightly increased . Note that for the positive 30° tilt more flow samples originate from the ground which could give an explanation for the increase in the measured distance error . This is especially the case at large distances to the wall . These two properties of our model , the logarithm of speeds used in the matching function and the non-zero tilt angle that introduces a dependency on head direction , are important for the distance estimation and generalization to other configurations of varying tilt . Our current model has several limitations . So far , our model responds only to visible walls and drop-offs; however , place cells that may be driven by BVCs also respond in the presence of transparent walls [26] . Furthermore , this model does not work in the dark since our model relies on optic flow , the changes of light patterns on the retina . Another limitation of our model is the restriction of self-motion to curvilinear path motion . Such motions exclude pitch and roll rotations and translational motions that are not parallel to the ground . These limitations could be relaxed by modeling more degrees of freedom in the template model . However , such an extension will increase the number of flow templates . Furthermore , it remains unclear if detecting the separation between ground and wall is still possible for such an extended model in the way it is possible for curvilinear motion . Another restriction of our model is the assumption about analytical , noise-free flow . In reality , flow has to be estimated from light changes and flow estimates would contain errors . To address these limitations future work could include other systems , such as distance estimates from binocular vision , a landmark system along with a triangulation strategy , sensorimotor integration and memory to operate in the dark , or the suggested neighborhood function to improve segmentation given noisy , detected flow . Information about self-motion and environment structure that is extracted by our model from optic flow could be useful for other cell types as well . Grid cells can be generated by temporally integrated linear and rotational velocities that are estimated from optic flow [39] . Such integration allows for a reasonable estimate of the rat's position in the environment for a short duration , less than a minute with a temporal sampling frequency of 50 Hz . Optic flow can provide the information about short paths and , thus , has the potential to contribute to the place cell firing , a firing tied to specific allocentric spatial location in the environment . The integration of rotational yaw velocities can provide a head-direction signal , again for the time frame of about a minute . Furthermore , there may be an indirect effect as boundary vector cells might influence the firing of grid cells and place cells . Recent studies suggest that BVCs may function as an independent system from grid cells , as inactivation of the medial septum with muscimol causes a loss of grid cell spatial periodicity with sparing of some cells that look like BVCs , and sparing of the spatial firing response of place cells [40] , [41] . Thus , optic flow may provide input to cell populations in entorhinal cortex , subiculum , and hippocampus . Following our “flow-influence” hypothesis our model would predict cells with sensitivity to large flow fields . However , instead of in hippocampal or related areas , we assume this sensitivity to exist in sensory related areas , such as the primary visual area or higher level visual cortical areas or the accessory optic system . In primates these sensitivities have been found in area MT and MSTd [11]–[14] . The spatially integrative behavior of cells can be tested by using motion stimuli of different retinal size while measuring the response from our hypothetical motion cells . Then there should be an effect on firing rate coupled to retinal stimulus size . Furthermore , the “flow-influence” hypothesis for BVC is supported by our modeling work . An experiment testing this hypothesis would record BVCs from subiculum while the animal is passively watching the visual input of a simulated trajectory . To only provide optic flow cues the displayed stimulus would consist of a random dot texture as used in virtual environment setups for humans and should be compared with performance when viewing a display that consists mainly of object outlines that provide visual cues other than optic flow [42] . This passive watching setup should be compared to the freely moving animal while recording from the same BVC – this might be difficult to achieve but testing of virtual environments with stationary animals has been done [43] . Our modeling work would predict that BVC firing will be observed during the passive watching setup; however , we assume it would be nosier , due to the lack of other cues and the prediction that multimodal sensory cues are usually integrated by BVCs during normal behavior .
The spherical image flow model for instantaneous motion through a rigid stationary environment is [44] , [45]: ( 1 ) where denotes the azimuth angle and the elevation angle . Azimuth is measured from the z-axis pointing forward along the optical axis in the xz-plane . Elevation is measured from z′-axis in the yz′-plane where z′ denotes the z-axis that is rotated by the azimuth angle . This definition uses a left-handed coordinate system . The 3D linear velocity and the 3D rotational velocity cause temporal changes for azimuth and elevation assuming a differential motion model that neglects higher order temporal differences , like accelerations [46] , [47] . The super-index ‘t’ denotes the vector-transpose . The distance is the length toward a 3D sample point in Cartesian coordinates . In the simulations we assume that the rat is moving tangent to the recorded trajectory in the 2D plane . This assumption reduces the six degrees of freedom of the model to two degrees of freedom: The linear velocity along the optical axis ( z-axis ) and the rotational velocity around the y-axis ( yaw-rotation ) . Thus , Equation 1 reduces to a model of visual image motion for curvilinear self-motion: ( 2 ) In this Equation 2 the distance variable is very general and can be different for every image location defined by the azimuth angle and elevation angle . To constrain this variable further , we define a model of a ground plane and planar walls . Figure 8 visualizes this simplified spherical flow model with only two degrees of freedom together with the definition of the camera system . In Hessian normal form a plane is described by its unit normal vector and distance . This distance is measured along the normal . Plugging the plane definition into the projection function for the spherical camera model defined in azimuth angle and elevation angle results in the definition of the 3D point distance: ( 3 ) For a ground-plane with for zero-tilt γ = 0 and distance as eye-height above the ground this ground-plane model simplifies to . For a tilt angle γ≠0 the normal vector is given by which depends now also on the allocentric camera or head direction φ . This normal vector can be computed , e . g . , by using Rodrigues rotation equation and rotating the normal vector around the axis . The depth function for planar walls assumes a wall to be defined by the normal that is rotated according to the allocentric direction φ of the rat's head which results in with the angle α being the allocentric direction of the wall . For a tilt angle γ≠0 the wall's normal vector is described by ( 4 ) For this definition the order of rotations is crucial: First , we rotate for the wall's direction α , second for the tilt angle γ , and third by the allocentric direction of the rat's head φ . The distance function from Equation ( 3 ) with the corresponding normal vectors is plugged into Equation ( 2 ) to define the template flows for curvilinear self-motions defined by and . This results in the constrained flow equation: ( 5 ) For the normal vector the corresponding model for a ground-plane or wall-plane is plugged in . Tuning functions are employed to compare single flow vectors of the template flows against its corresponding vectors of the input flow . These tuning functions are described next . Input flow is defined as and is compared against the template flow for walls or , the template flow for the ground-plane where the latter two parameters of distance and angle are dropped . Our first goal is to segment the flows into samples from ground or wall . To derive a flow constraint that is independent of the rotational velocity ωy but depends on the distances D , we multiply the Equation ( 5 ) by the vector . This provides the following tuning functions for segmentation . First , the tuning function for potential sample points of the ground-plane is: ( 6 ) Second , the tuning function for potential sample points of walls is defined by: ( 7 ) In this tuning function we use the mean velocity that is computed over all m velocity samples . For the wall-ground segmentation we use the following decisions to define the set of wall samples and the set of ground samples . Then we continue with the ground samples to estimate the linear velocity of the rat by using the tuning function: ( 8 ) This function in Equation ( 8 ) defines matches between the input flow and the template flows for the linear velocity samples . Matches are computed over all samples that have been identified to originate from the ground . This provides the overall similarity between the input flow and a template flow . Next , we compute the rotational velocity from ground samples . For this computation we use the following tuning function which computes the Euclidean distance between input flow and template flow: ( 9 ) In this Equation ( 9 ) , is the estimated linear velocity from Equation ( 8 ) , e . g . . In the last step we estimate wall distances for a given allocentric direction and use the already estimated linear and rotational velocity from Equation ( 8 ) and ( 9 ) . For this distance and direction estimation we use the tuning function as defined by Perrone [18] . Note , this function has not been used for any of the previous problems due to optimizing for the rotational velocity in Equations ( 6 ) – ( 8 ) which uses a constraint that is independent of rotational velocities and in Equation ( 9 ) because the rotational velocity is independent of the depth and , thus , a more elaborate log-distance tuning as suggested by Perrone [18] for the length of flow vectors is not necessary . But now , since we estimate the distance of walls this distance tuning is crucial . Perrone's tuning model starts with a transformation of flow vectors from Cartesian into polar coordinates , whereas the radius is associated with the speed of an image location . In this polar representation the matching function is defined as: ( 10 ) The Equation ( 10 ) combines the log-speed tuning , the first factor , with the direction tuning , the second factor , by multiplication . The angular difference in Equation ( 10 ) is denoted by . This assumes that the two tunings for motion speed and direction are independent [18] . The already estimated linear velocity and rotational velocity are used to define self-motion specific flow templates in Equation ( 10 ) . Our extended model can be summarized into the following four steps . First , we compute a wall-ground segmentation by using the tuning functions from Equation ( 6 ) and ( 7 ) . The segmentation is determined by whether a flow vector fits better to a ground template vector from Equation ( 6 ) or a wall template vector from Equation ( 7 ) while sampling all possible linear velocities in Equation ( 6 ) and all possible allocentric directions and possible distances for a wall in Equation ( 7 ) . Therefore , the segmentation is computed without knowing the parameters of self-motion . But once the segmentation into wall-ground is known we use ground samples to estimate linear and rotational velocity in step two and three , respectively . For estimating linear velocity we use the tuning function from Equation ( 8 ) and for rotational velocity the tuning function from Equation ( 9 ) . In the fourth step , we estimate distance and allocentric direction of walls using the known segmentation , linear , and rotational velocity . A pseudo-code of the algorithm is provided in the Figure 9 . So far , we have not described how velocities , distances , and directions are estimated given the activity from evaluating the residual functions in Equation ( 8 ) , ( 9 ) , and ( 10 ) . Such a description follows . The matching functions in Equation ( 8 ) , ( 9 ) , and ( 10 ) depend on different stimulus parameters . For instance , the function of Equation ( 8 ) depends on linear velocity samples , whereas the function of Equation ( 10 ) depends on distance and direction of walls . Our read-out distinguishes between 1D and 2D functions . For a 1D function our read-out method uses a weighted sum with two percent of all argument values that are centered on the maximum . For the 2D match function of Equation ( 10 ) we use a different method . Our read-out mechanism selects all matches with their value being within the 70% range with respect to the maximum match . These match values together with their respective arguments , in the above example the linear velocities , are passed along to the distance error calculation or BVC model . The calculation of distance errors takes the direction arguments and computes the ground-truth distance for this direction . Then this ground-truth distance is subtracted from the estimate . The absolute value is computed for this difference to define the distance error . If the boundary vector cell model is the next stage , arguments about distance and max read-out directions are passed together with their activation . Distance and direction are integrated into the existing BVC model and we weigh each BVC activity by the match value provided by our template model . This is described in more detail next . A pseudo-code of the 1D and 2D readout method is given in Figure 10 . The boundary vector cell ( BVC ) model was described in detail elsewhere [5] , [6] , [17] . Here , we only repeat the main model equation to show how our estimated variables are integrated . The distance with its allocentric direction of a wall leads to the activation: ( 11 ) We assume the i-th BVC is tuned to the distance and the allocentric direction . Normalized match values of the template model are included in the firing of a BVC . These match values are the third factor of the product in Equation ( 11 ) . The indices k and j range over all read out activations from our model that are above 70% of the maximum activity . Parameter values for this Equation ( 11 ) and all other equations are reported in Table 2 . Drop-offs are detected with a center-surround filter applied to the speeds of the flow field . This detection method assumes that the azimuth and elevation angles are arranged on a regular sample grid that is associated with pixels . In our model example we use 400 horizontal samples and 200 vertical samples . To detect the flow discontinuity at the drop-off we apply a center-surround filter kernel to the length of the flow vectors and detect its maximum response . Formally , this is expressed by: ( 12 ) In some cases of small flow discontinuities at the transition from flow at the horizon to the flow of the background this detection does not provide valid values indicated by a small maximum response , see also the pseudo-code in Figure 11 . The detected elevation angle of the drop-off is then converted into a distance estimate assuming the eye-height h , tilt angle γ , and head direction φ are known: ( 13 )
|
Over the past few decades a variety of cells in hippocampal structures have been analyzed and their function has been identified . Head direction cells indicate the world-centered direction of the animals head like a compass . Place cells fire in locations associated with visual , auditory , or olfactory cues . Grid cells fill open space like a carpet with their mosaic of firing . Boundary vector cells fire , if a boundary that cannot be passed by the animal appears at a certain distance and world-centered direction . All these cells are players in the navigation game; however , their interaction and linkage to sensory systems like vision and memory is not fully understood . Our model analyzes a potential link between the visual system and boundary vector cells . As part of the visual system , we model optic flow that is available to rats . Optic flow is defined as change of lightness patterns on the retina and contains information about self-motion and environment . This optic flow is used in our model to estimate the distance and direction of boundaries . Our model simulations suggest a link between optic flow and the firing of boundary vector cells .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Model"
] |
[
"computer",
"science",
"computer",
"modeling",
"mathematics",
"geometry",
"neural",
"networks",
"computational",
"neuroscience",
"synthetic",
"vision",
"systems",
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"differential",
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2012
|
Modeling Boundary Vector Cell Firing Given Optic Flow as a Cue
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Differences in immune activation were identified as the most significant difference between AIDS-susceptible and resistant species . p38 MAPK , activated in HIV infection , is key to induction of interferon-stimulated genes and cytokine-mediated inflammation and is associated with some of the pathology produced by HIV or SIV infection in AIDS-susceptible primates . As small molecule p38 MAPK inhibitors are being tested in human trials for inflammatory diseases , we evaluated the effects of treating SIV-infected macaques with the p38 MAPK inhibitor PH-797804 in conjunction with ART . PH-797804 had no side effects , did not impact negatively the antiviral immune response and , used alone , had no significant effect on levels of immune activation and did not reduced the viremia . When administered with ART , it significantly reduced numerous immune activation markers compared to ART alone . CD38+/HLA-DR+ and Ki-67+ T-cell percentages in blood , lymph node and rectal CD4+ and CD8+ T cells , PD-1 expression in CD8+ T cells and plasma levels of IFNα , IFNγ , TNFα , IL-6 , IP-10 , sCD163 and C-reactive protein were all significantly reduced . Significant preservation of CD4+ , CD4+ central memory , CD4+/IL-22+ and CD4+/IL-17+ T-cell percentages and improvement of Th17/Treg ratio in blood and rectal mucosa were also observed . Importantly , the addition of PH-797804 to ART initiated during chronic SIV infection reduced immune activation and restored immune system parameters to the levels observed when ART was initiated on week 1 after infection . After ART interruption , viremia rebounded in a similar fashion in all groups , regardless of when ART was initiated . We concluded that the inhibitor PH-797804 significantly reduced , even if did not normalized , the immune activation parameters evaluated during ART treatment , improved preservation of critical populations of the immune system targeted by SIV , and increased the efficacy of ART treatment initiated in chronic infection to levels similar to those observed when initiated in acute infection but did not affect positively or negatively viral reservoirs .
Differences in immune activation have been identified as the single most significant difference between AIDS-susceptible and resistant species [1–9] . Immune activation can be induced by a variety of mechanisms , including stimulation of innate and adaptive immune responses , production of a superantigen , and/or production of activating cytokines and chemokines . It is quite likely that more than one mechanism is occurring simultaneously during HIV infection . As immune activation can trigger T-cell apoptosis , the differential level of immune activation induced by HIV and SIV among the species could explain the more drastic depletion of CD4+ T cells that occurs in AIDS susceptible compared to AIDS-resistant species , as apoptosis occurs significantly less in species that do not develop AIDS [7 , 10 , 11] . Apoptosis and immune activation are substantially reduced in HIV-infected individuals that are long-term non-progressors [12 , 13] . Residual chronic immune activation during ART is considered a contributor to the co-morbidity observed during treatment , mainly accelerated aging-related diseases , including renal dysfunction , atherosclerosis and hypertension , diabetes mellitus , respiratory diseases ( e . g . chronic obstructive pulmonary diseases and pneumonia ) , and HIV-associated neurological disorders [14–17] . Inhibition of immune activation has been explored in a few studies that have targeted different molecules and pathways . A COX-2 inhibitor tested in 13 HIV-infected individuals appeared to reduce immune activation as indicated by reduction of PD-1 on CD8+ T cells , increasing numbers of T regulatory ( Treg ) cells , and improved recall responses to a T-cell dependent vaccine [18] . p38 MAPK is also involved in the activation of COX-2 and inhibition of p38 MAPK also resulted in the inhibition of COX-2 [19] . However , when tested in a randomized placebo-controlled trial , no significant immunological effects of the COX-2 inhibitor Etoricoxib were observed in ART-treated patients [20] . PD-1 blockade also reduced immune activation [21] . Interestingly , it is p38 MAPK that stimulates the transcription of PD-1 and induces additional molecules inhibitory of T-cell function [22 , 23] . Anti-TNFα treatment during SIV infection , whose expression is dependent on p38 MAPK , also reduced immune activation [24] . Instead , blocking IFNα in pDC did not reduce immune activation in SIV infected macaques and the administration of an IFNα agonist in SIV-infected sooty mangabeys did not result in immune activation , making it somehow less likely that the direct activity of IFNα is the cause of immune activation in Rhesus macaques ( RM ) [25 , 26] . Reduced inflammation was observed in SIV-infected RM when ART was combined with IL-21 , which also impacted time to rebound , plasma viremia and cell-associated SIV DNA levels after ART interruption but the mechanism of this outcome was not fully understood [27] . Induction of interferon-stimulated genes ( ISG ) during a viral infection is a consequence of Toll-like receptor ( TLR ) activation [28] . This leads to increased transcription of IRF7 and triggering of IFNα production , activation of the kinase cascade , with up-regulation , among others , of p38 MAPK . p38 MAPK triggers a signaling pathway that leads to direct activation of transcription factors implicated in many of cellular process including inflammation , cell cycle , apoptosis , and immune response [29 , 30] . The p38 MAPK pathway is critical for maintaining a sustained response to type I and type II IFNs , leading to the induction of transcription of ISGs via activation of signal transducer and activator of transcription ( STAT ) proteins [31–35] . In addition , p38 MAPK plays an important role in regulating IFN-independent transcription of some ISG after TLR7 triggering [36–39] and production of inflammatory cytokines such as IL-1 and tumor necrosis factor alpha ( TNFα ) . Inhibition of the p38 MAPK pathway may form the basis of a new strategy for treatment of inflammatory diseases . p38 MAPK plays crucial roles in various pathological processes associated with HIV infection , including macrophage activation , neurotoxicity and impairment of neurogenesis , and lymphocyte apoptosis [29 , 30] . Increased , active p38 MAPK has been reported in brains of SIV-infected macaques with encephalitis [40] . Interestingly , p38 MAPK has also been implicated in the production and release of IP-10 in astrocytes exposed to HIV-1 and Tat [41–43] . HIV-1 and Tat were reported to activate p38 MAPK in infected or stimulated monocytes and macrophages [44] . We have shown that HIV and SIV Tat modulates primate antigen presenting cells ( APC ) and that at least a subset of the ISG are not equally affected by SIV infection in APC of AIDS resistant species [45–47] . We found that Tat associated with the MAP2K6 , MAP2K3 and IRF7 promoters and that the association resulted increased activation of p38 MAPK and consequent induction of ISG [45–47] . This mechanism of p38 MAPK activation could further and independently chronically contribute to the activation of ISG that results from TLR activation . Collectively , these data indicate that p38 MAPK activation is an important , additional mediator of HIV-associated pathology . Evaluating in vivo the role played by p38 MAPK in HIV replication and immune activation by inhibiting its activity may provide the rationale for the use of p38 MAPK inhibitors in AIDS therapy , in association with ART or when ART is no longer an option . A series of compounds targeting p38 MAPK were initially discovered and were followed by the development of more potent and specific inhibitors of this protein capable of inhibiting the production of inflammatory cytokines . Different p38 MAPK inhibitors have been shown efficacy in preclinical animal models of a variety of diseases [48–56] . Some of these inhibitors have advanced to clinical studies for rheumatoid arthritis , chronic obstructive pulmonary disease ( COPD ) , post-herpetic neuralgia and neuropathic pain , and osteoarthritis . [54 , 57–59] The diarylpyridinone PH-797804 is a novel , ATP-competitive and reversible potent inhibitor of human p38 MAPK [53] . It specifically inhibits p38α with IC50 value of 26 nM and K ( i ) value of 5 . 8 nM and inhibits LPS induced TNFα and IL-1β production in monocytes in a concentration-dependent manner [50] . PH-797804 blocks RANKL and M-CSF induced osteoclast formation in primary rat bone marrow cells . When given orally , PH-797804 reduces TNFα levels in LPS-induced shock of Lewis rats and of cynomolgus monkeys [50] . In randomized , adaptive design , double-blind , placebo-controlled , parallel-group , multicenter trial demonstrated improvements over placebo in lung function parameters and dyspnea in patients with moderate to severe COPD [58 , 60] . Here we show that inhibiting p38 MAPK in vivo can significantly impact SIV-mediated immune activation and protect immune cell populations that are negatively affected by the infection . However , the reduction of immune activation is not complete , it is unlikely to be fully controlled by acting on any single activation pathway , and possibly requires exploration of different inhibitor doses and intervention on multiple pathways linked to immune activation , including other kinases like JNK that are also affected by HIV and SIV .
The contribution of p38 MAPK in chronic immune activation during lentiviral infection was investigated in the SIV-infected RM animal model , treated with ART over the course of 60 weeks . RM were infected intravenously ( i . v . ) with 10 TCID50 SIVmac251 and divided in groups ( n = 4 , Groups 1 and 2; n = 6 , groups 3–6 ) , with some groups receiving ART alone and others ART combined with p38 MAPK inhibitor ( Fig 1 ) . ART consisted of two reverse transcriptase ( RT ) inhibitors , tenofovir ( PMPA , 20 mg/kg , and emtricitabine ( FTC , 30 mg/kg ) , and the integrase inhibitor dolutegravir ( DTG , 2 . 5mg/kg ) s . i . d , administered i . m . and was initiated in the acute phase of the infection , one week after SIV infection , in groups 5 and 6 , or in the chronic phase , once set point was reached , six weeks post-infection , in Groups 3 and 4 . PH-797804 , 10 mg s . i . d , orally administered , was chosen among other similar compounds for the proposed studies for multiple reasons . It has been tested in humans and cynomolgus monkeys where it could effectively inhibit the acute inflammatory response that follows the administration of lipopolysaccharide ( LPS ) , in particular production of TNFα and IL-6 , and it reduced chronic inflammation and bone loss associated with arthritis in mice and rats [50] . In cynomolgus monkeys exposed to a single dose of LPS , PH-797804 dosed intragastrically at 0 . 001 mg/kg to 1 mg/kg , the dose of 0 . 1 mg/kg reduced TNFα plasma levels to 20% of the levels observed in animals treated with placebo , while the dose of 1 mg/kg reduced it to less than 10% [50] . This reduction was virtually identical to that observed for TNFα and IL-1β in humans after LPS challenge , where a reduction of 50% of the IL-6 levels was also observed [50] . As primary endpoints , we evaluated differences in expression of surface and intracellular molecules linked to immune activation and plasma levels of inflammatory cytokines . As secondary endpoints , we evaluated the effects that treatments had on viral loads , preservation of central memory ( CM ) and other CD4+ T cell subpopulations . After SIVmac251 infection all animals experienced a rapid increase in viremia that peaked before initiation of ART for the groups when ART was initiated on week 6 and was below peak levels in the groups initiating ART one week after infection . ART was effective in suppressing the viral replication in all animals that received it ( Fig 2A ) . The p38 inhibitor PH-797804 was well tolerated and no major side effects were noticed throughout the study . At the dose used in these animals ( 10 mg s . i . d , orally ) , plasma viral loads were comparable between groups receiving PH-797804 and those that did not , indicating that the p38 MAPK inhibitor did not affect virus replication , whether administered alone or in combination with ART , and regardless of when ART was initiated . To obtain a preliminary indication of PH-797804 efficacy in vivo , and considering that p38 MAPK does not directly affect ISG expression but does so via directly increasing the activity of the master transcription regulators of ISG expression IRF7 and pSTAT1 , we evaluated the percentages of PBMC positive for accumulation of IRF7 and pSTAT1 , and the cytokine IP-10 , one of the ISG most significantly upregulated in HIV and SIV infections ( Fig 2B–2D , S1A Fig ) . Using intracellular staining and flow cytometry , we found that the accumulation of these proteins was significantly reduced by the inhibitor when percentages from animals receiving ART alone were compared to those receiving ART and inhibitor for the two paired groups , whether initiating ART at week 1 or 6 ( area under the curve from week 8 to 60 , IRF7: p = 0 . 01 , pSTAT1: p = 0 . 004 , IP-10: p = 0 . 004 for groups initiating ART at week 1 and IRF7: p = 0 . 02 , pSTAT1: p = 0 . 02 , IP-10: p = 0 . 04 , for groups initiating ART at week 6 ) . This was true whether the analysis was done on total PBMC or CD3+ T-cell subpopulations ( S1C Fig ) . Percentages of the CD3+ subpopulations were comparable at individual time points in paired groups ( S1B Fig ) . Results were very similar when the same analyses were carried out in lymph node mononuclear cells ( MNC ) ( S1D Fig ) . This result indicates that the selected PH-797804 dose could reduce expression of ISG transcriptional regulators and of the cytokine IP-10 . To exclude that the inhibitor treatment could reduce the effectiveness of the antiviral immune response , we evaluated the levels of antigen-specific cell mediated responses over the course of the treatment . We found that the number of SIV-specific CD4+ and CD8+ T cells were similar in the group pairs and proportionate to the viral loads present in the animals ( Fig 3A ) , indicating that the p38 inhibitor treatment did not grossly altered the magnitude of the anti-viral immune response . We also evaluated whether inhibition of p38 MAPK could impact the expression of PD-1 , checkpoint known to increase during infection because of persistent immune activation , resulting in inefficient CD8+ T-cell activity [61] . When investigated on week 60 , before removal of ART and inhibitor treatment , we found that the frequency of CD8+ T cells expressing PD-1 was significantly lower in the groups that received the p38 inhibitor combined with ART compared to ART alone , whether ART treatment started on week 1 ( p = 0 . 011 ) or 6 ( p = 0 . 038 ) whereas it was comparable in CD4+ T cells ( Fig 3B and 3C ) . We concluded that PH-797804 did not affect negatively the development of anti-SIV immune responses and reduced the expression of the checkpoint inhibitor PD-1 in CD8+ T cells , most likely indirectly via the overall impact on immune activation . Chronic immune activation has been proposed to be a key determinant of AIDS pathogenesis . A variety of cell surface determinants expressed in the cell membrane are phenotypically associated with T-cell immune activation and provide useful marker to evaluate immune activation levels . In this study , we measured the surface expression of HLA-DR and CD38 and the DNA replication marker Ki-67 , expressed intracellularly in PBMC and tissue MNC and these analyses are reported in Fig 4 and Fig 5 as group averages and in S2 Fig and S3 Fig for individual animals . Percentages of HLA-DR+/CD38+ cells were significantly lower in CD4+ and CD8+ T cells of the groups treated with ART plus p38 MAPK inhibitor compared to those treated with ART alone , whether treatment started at week 1 ( p = 0 . 03 , p = 0 . 009 , for CD4 and CD8 , respectively ) or 6 post-infection ( p = 0 . 002 , p = 0 . 003 , for CD4 and CD8 , respectively ) , when the areas under the curve of the plotted parameters were compared in pair groups for the entire duration of the treatment ( week 8 to week 60 ) ( Fig 4A and 4B ) . The group receiving ART treatment since week 1 post-infection plus PH-797804 achieved the lowest frequency of immune activation markers in CD4+ and CD8+ T cells , although values did not return to baseline and remain approximately 2-fold higher . A similar trend was observed for the Ki-67 marker , which identifies activated cells , undergoing DNA synthesis and cell duplication ( Fig 4C and 4D ) . When PH-797804 was used alone , levels of immune activation were no different than those observed in the control group , suggesting that the level of immune activation in these animals could not be impacted by the PH-797804 dose used here . When the same analysis was carried out in in lymph node MNC ( Fig 5A–5D ) , we found that , when combined with ART , the inhibitor impact was more significant in the animals initiating ART at week 6 and not as much in those initiating ART at week 1 , where only the difference in CD38+/HLA-DR+ CD4 T-cell percentage was statistically significant , possible because the number of biopsy samples available for analysis ( 5 ) was smaller than for PBMC ( Fig 4 ) . The same analyses carried out in rectal MNC revealed that , when combined with ART , the inhibitor impact was significant in three of the four measured parameters in the animals initiating ART at week 1 but not in animals treated since week 6 post-infection , when AUCs were compared ( Fig 5E–5H ) . However , differences in rectal CD38+/HLA-DR+ and Ki67+ CD8+ T cells between Group 3 and 4 were significant at 4 of 5 and 3 of 5 time points , respectively , when time point values were individually analyzed . Interestingly , blood and lymph node immune activation parameters of Group 4 ( ART+ p38 inhibitor initiated in chronic infection , green lines ) were comparable to those observed in Group 5 ( ART only , initiated in acute infection , pink lines ) ( p = ns ) , supporting a significant benefit of this combination treatment when initiated in chronic infection . This result , although limited to phenotypic markers , is important , considering that ART is rarely initiated in the acute infection phase in HIV+ individuals and more commonly initiated during the chronic phase . During lentiviral infection , the production of various inflammatory cytokines and biomarkers is known to be significantly higher than in normal subjects [62–65] . The levels of these cytokines , measured in plasma of SIV-infected RM by ELISA , were highest at peak viremia and were reduced during ART or ART plus PH-797804 treatment . The level of IFNα , IFNγ , TNFα , IL-6 , IP-10 , sCD163 , a molecule shed by monocytes as a consequence of immune activation [66 , 67] , and C-reactive protein ( CRP ) were lower in the animals treated with ART and PH-797804 and the difference was statistically significant when Group 4 was compared to Group 3 ( Fig 6 for group averages and S4 Fig for individual animals ) . Interestingly , even in this analysis , levels of IFNγ , TNFα , IP-10 , sCD163 and CRP in Group 4 became comparable to those of Group 5 , which initiated ART one week post-infection ( p = ns ) . Of note is the fact that IFNα , although impacted by both ART and ART+PH-797804 , remained with IFNγ the most abundant measured cytokine when compared to pre-infection values , despite undetectable viremia in some of the animals , suggesting an ongoing stimulation of innate responses . As a consequence , it is unlikely that activation of the numerous ISG , not covered here , can be fully controlled by simply inhibiting p38 MAPK , as it is highly likely that levels of ISG expression correlate with the levels of IFNs , which , although reduced , were still abnormal in this setting and not only influenced by p38 MAPK . Plasma cytokine reduction was mirrored by reduction of percentages of T cells producing some of these cytokines ( Fig 7 and S5 Fig ) . We found that the percentage of CD4+ T cells producing IFNγ and TNFα were significantly reduced in the groups receiving ART plus PH-797804 compared to ART alone , whether the treatment is started on week 1 ( p = 0 . 005 for TNFα and p = 0 . 02 for IFNγ ) or week 6 post-infection ( p = 0 . 04 for TNFα ) , ( Fig 7A and 7B ) . The percentages of TNFα+/CD8+ T cells in treated animals showed a significant reduction when the PH-797804 was added to ART , regardless of time of ART initiation ( p = 0 . 0001 and p = 0 . 01 for comparisons between Group 5 and 6 and Group 3 and 4 , respectively ) , while instead differences in the percentages of IFNγ+/CD8+ T cells were significant when Group 3 was compared to Group 4 ( p = 0 . 0008 ) ( Fig 7C and 7D ) but not when Group 5 was compared to Group 6 . In addition , the percentage of PBMC expressing IFNα was also significantly reduced when values of individual time points in Group 4 were compared to those in Group 3 ( Fig 7E , asterisks ) but this significance did not extend to the AUC comparative analysis . Taken together these data show that the administration of PH-797804 with ART reduced more significantly than ART alone the production of inflammatory cytokines and that , when added to ART in the chronic phase of the infection , which is the most common occurrence in HIV+ individuals , restored some parameters to the levels observed when ART was initiated in the acute phase , one week after infection . The hypothesis we tested by adding a p38 MAPK inhibitor to ART was that , if immune activation contributes to the immune system deterioration , reduction of immune activation should result in preservation of immune cells . We evaluated the effect of PH-797804 treatment on percentages of total CD4+ T cells and CM CD4+ T cells , which is considered an earlier prognostic marker in the infection , as CM CD4+ T cells decline earlier than total CD4+ T cells [68] . The percentages of CD4+ T cells and CM CD4+ T cells were significantly higher in Group 4 ( ART + PH-797804 since week 6 ) compared to Group 3 ( ART alone since week 6 ) ( p = 0 . 02 for CD4+ T cells and p = 0 . 01 for CM CD4+ T cells ) ( Fig 8A and 8B ) and differences were not significant when Group 4 was compared to Group 5 ( ART since week 1 post-infection ) . The same comparisons for Groups 5 and 6 , receiving ART since week 1 post-infection , with CD4+ T-cell loss not as pronounced as in the groups initiating ART in the chronic phase , were significant for CD4+ T cells but not for CM CD4+ T cells . This result supports the possibility that the addition of PH-797804 to ART permits a more significant recovery of CD4+ T-cell counts than ART alone when the virus damage of the immune system has been more severe and the combined regimen can compensate for a later initiation of ART . Multiple studies have suggested that losses of intestinal Th17 and Th22 cells play a critical role in establishing intestinal mucosal immune dysfunction and are associated with the chronic immune activation typical of pathogenic HIV/SIV infections [69–80] . Several studies have reported that reciprocal changes in Th17 cells and Tregs occur during HIV and SIV infections and that the relative balance of Th17 and Treg subsets , expressed as a ratio of Th17 and Treg percentages , provides a prognostic index of disease progression more significant than each percentage considered individually [81–83] . In addition , Th22 cells play an important role in promoting innate immune defenses against bacterial and fungal infections in mucosal tissues , and in maintaining mucosal barrier integrity via mucus production and repair of damaged mucosal tissue [74–78 , 80] . Therefore , we measured the impact of PH-797804 treatment on levels of the Th17 and Th22 CD4+ T-cell populations by evaluating their percentages in PBMC with intracellular staining in PBMC and in rectal MNC . We found that SIV infection reduced the Th17/Treg ratio but treatment improved it . The improvement was more significant in Groups 4 and 6 , both receiving ART+ PH-797804 , compared to Groups 3 and 5 ( ART alone ) ( p = 0 . 02 for Groups 5 and 6 and p = 0 . 04 for Groups 3 and 4 ) ( Fig 8C ) . We also evaluated Th17/ Treg CD4+ T-cell ratio and IL22+CD4+ T-cell percentage in the intestinal compartment , where loss of Th17+ and Th22+ cells during SIV infection is significant , and confirmed in rectal MNC an improved ratio in the groups receiving ART+ PH-797804 ( p = 0 . 01 for Groups 5 and 6 and p = 0 . 0003 for Groups 3 and 4 ) ( Fig 8E ) . A more significant recovery of PBMC Th22+ cells was observed when the inhibitor was administered ( p = 0 . 04 , Group 6 vs . 5 , p = 0 . 01 Group 4 vs . 3 , Fig 8D ) . Recovery of rectal Th22 CD4+ T cell percentages was significant for Group 6 compared to Group 5 ( p = 0 . 01 ) while differences were not significant between Group 3 and 4 , possibly due to limited samples and higher standard error for the groups , as percentages were higher in the group receiving PH-797804 and similar to those observed in Group 6 ( Fig 8F ) . Taken together , these data indicate that the inhibition of T-cell activation achieved with PH-797804 treatment was significant enough to provide additional benefit to that observe with ART alone and positively impacted preservation or restoration of populations that are affected by chronic SIV infection . Importantly , the addition of the PH-797804 to ART initiated in the chronic phase resulted in immune population recoveries comparable than that observed when initiating ART in the acute phase of infection ( compare data reported in green to those reported in pink ) , an event highly unlikely in most HIV infected individuals . On week 60 after infection , ART and PH-797804 were interrupted . We investigated the viral burden in lymph node cells at the end of ART by evaluating DNA and RNA gag viral copies in MNC extracted from lymph nodes of animals in Group 3–6 . We found that viral loads were significantly lower in Groups 5 and 6 that received ART since week 1 post-infection compared to Groups 3 and 4 , where ART was initiated on week 6 post-infection ( approximately 3 . 5 fold lower , p = 0 . 04 ) , but not significantly different when the groups receiving the inhibitor were compared to the matched group that received ART alone . Similarly , the number of average SIV transcripts/106 cells was lower in Group 5 and 6 . When the total number of SIV RNA copies/ SIV DNA copies was calculated to obtain the average SIV genomic RNA transcripts /SIV infected cells , the number is very similar in all groups , ranging between 0 . 01 and 1 SIV gag RNA copies/ SIV DNA copy , except for one animal in Group 4 , where the average is of 8 . 5 RNA copies/DNA copy ( Fig 9A–9C ) . Averages below one SIV RNA copy / infected cell support the coexistence of SIV DNA+ cells without SIV transcripts , where the infection is latent , and others where number of SIV RNA molecules is higher than the calculated average . Single cell analysis is required to establish the fraction of cells in which transcription is active and quantitative infection assays to evaluate cells producing infectious virus . However , these results indicate that the level of suppression was similar and effective in all groups , compared well to those reported for suppressed HIV+ individuals and suppressed SIV+ macaques [84 , 85] , that the size of the reservoirs was established early on , and that the more prolonged viremia that occurs with later initiation of ART resulted in larger reservoirs . The addition of PH-797804 at week 6 post-infection did not impact the size of reservoirs , measured 54 weeks after inhibitor initiation . Despite the differences in total viral DNA burden in lymph nodes among groups , viremia measured for the first time after 4 weeks from ART interruption , rebounded to similar values in all animals , regardless of when ART was initiated or PH-797804 treatment was administered ( Fig 9D ) . This rebound was comparable to that observed in HIV infection patients treated for a similar length of time , where 136 of 164 patients had significant and fast viral rebound after ART interruption [86 , 87] . Not surprisingly , CD38+/HLA-DR+ percentages , which appears strictly linked to viral replication , rebounded as well and was indistinguishable among groups ( Fig 9E ) . These data support the observation that reservoirs are established early in the infection and that initiating ART in the acute phase reduces but does not eliminate the establishment of reservoirs , possible because it takes time for ART to bring viremia to undetectable levels and reservoirs continue to be seeded for days after ART initiation [88–91] . Decay of reservoirs is time dependent and time to rebound is clearly affected by the duration of ART , which in this trial was restricted to 59 or 54 weeks and it can be significantly longer in ART-treated , HIV infected individuals , evaluated for the same virological parameters .
Immune activation is the differentiating feature between infection is species that progress to AIDS versus species that do not and persistent immune activation remains despite immunosuppressive ART treatment . ART treatment substantially reduces viral loads and , consequently , immune activation . However , CD8+ T-cell activation does not decrease proportionally to the decrease of viral loads and its levels have been inversely linked to the degree of CD4+ T cell reconstitution during ART [92] . HIV-associated pathology and , in particular , HIV associated neurological disorders ( HAND ) , did not decrease after the introduction of ART in the same proportion that one would expect if only dependent on blood viral burden [93 , 94] . Immune activation and/or ART toxicity have been postulated as possible explanations for this outcome . The causes of residual immune activation have been attributed to factors such as residual HIV replication , persistent microbial translocation , and viral co-infections such as CMV [references in [92]] . It seems therefore ideal to conceive a treatment that combines ART and inhibitors of immune activation . Only limited data are available for this approach , with focus on combination of ART with Cyclosporin A during acute/early infection for one short cycle [95–98] . A significant effect on the residual CD8+ T-cell immune activation was observed with this approach [97] . We investigated whether suppression of one of the key player in immune activation , p38 MAPK , can impact SIV-mediated immune activation during ART . We found that this treatment , when combined with ART , does positively impact virus-mediated immune activation and permits preservation of subpopulations that are significantly affected during the infection . However , reduction of immune activation did not appear to impact viral reservoirs , known to be established early on in SIV and HIV infections , even when ART was initiated just a few days after infection [91] . The addition of the p38 MAPK inhibitor to ART significantly suppressed multiple parameters of immune activation . The observed suppression was not complete and residual immune activation was approximately 50–65% of that observed in animals receiving ART alone . Only one inhibitor dose was explored and investigation of additional doses would be preferable . As it is for ART , the combination of multiple inhibitors of immune activation pathways , aimed at different targets linked to immune activation , may ultimately provide a more substantial control of immune activation during ART , considering that redundancy exists in the immune system and that p38 MAPK activity can also , in part , be carried out by other kinases like JNK and ERK . Indeed , when we carried out in vitro experiments , we found that features of immune activation that are observed after HIV infection of APC could most significantly be impacted by treatment with a p38 MAPK inhibitor but also by a JNK inhibitor and to a lesser extent by an ERK inhibitor [45–47] . p38 MAPK inhibition provided diverse benefits with improvement of multiple immune parameters and resulted in a significant preservation or better restauration of cell populations that are critical to the immune system ( Fig 8 ) . Recovery of percentages of total CD4+ , CM and Th22 CD4+ T cells , and of Th17/Treg ratio was more substantial in Group 4 that initiated ART and PH-797804 around the time when viremia reaches the set point ( week 6 ) and when CD4+ T-cell depletion had reached values as low as those in the animals that remained untreated . These results support the possibility that the addition of PH-797804 permits a more significant recovery of CD4+ T-cell populations than ART alone , especially when the damage to the immune system has been more prolonged and substantial . In Group 4 , recovery of affected cell populations reached levels comparable to those observed in Group 5 that initiated ART only one week after infection ( Fig 8 ) . The fact that the addition of PH-797804 provided a more noticeable benefit when ART was initiated later in the infection , when the viral damage to the immune system has been more severe , suggests that this treatment could be significant in HIV+ individuals , where initiation of ART after reaching viremia set-point is the more common occurrence than ART initiated during the acute stage . Lastly , significant reduction of both PD-1 percentages and MFI in CD8+ T-cells may permit a more effective anti-retroviral immune response . As only one PH-797804 dose was tested , the benefit could further increase if the ideal dose was identified . IL-1β inhibition with canakinumab has recently been shown to reduce cardiovascular events in patients with coronary arterial disease and has also been shown to decrease immune activation in treated HIV patients , but there are concerns about its safety , particularly infectious complications [99 , 100] . We did not detect reduced immune responses to SIV while treating the animals with the p38 MAPK inhibitor . The setting in which the p38 MAPK inhibitor was used ( single caged macaques , kept indoor ) significantly reduces the exposure to infectious agents and therefore may not provide a sufficient indicator of lack of impact on infection control . However , this inhibitor could be safer than an IL-1β inhibitor , as it is highly selective for p38 MAPK and does not inhibit the other two members of the family of major mitogen-activated protein kinases , JNK and ERK . These kinases are partially , even if not fully , overlapping with p38 MAPK function and , therefore , the inhibition of some pathways affected by p38 MAPK may not be absolute , avoiding their complete shutdown . This could also be a reason why the observed reduction of immune activation was limited , even if significant . Although a full analysis of ISG expression in blood and tissue populations is beyond the scope of the report , this investigation could reveal in more subtle details whether some ISG are more affected than others and provide additional information on the activity of PH-797804 in vivo . Such analysis will be object of future , larger studies . The expectation is that , if carried out in the setting of this study , a reduction of ISG that could mirror the reduced levels of circulating IFNα and IFNγ would be detected in animals treated with PH-797804 and ART , and that a more significant suppression of IFN pathways could only be achieved by interfering with other mitogen activated kinases that can overlap p38MAPK or their upstream regulators . One expectation of this study was that by reducing immune activation , the availability of activated CD4+ T cells that are a preferred target of infection would also be reduced and therefore reservoir seeding could be impacted . However , we did not find significant differences in reservoir size when Group 3 was compared to Group 4 and Group 5 to Group 6 . It is possible that differences in rebound time could have been observed if earlier sampling had been obtained , when Group 3 and 4 were compared to Group 5 and 6 . As by week 4 all groups treated with ART , with or without PH-797804 , had reached similar levels of viremia , this delay would have been limited and unlikely to impact the course of disease progression . This results also suggests that reducing the immune activation status did not translate in reduced reservoirs and supports the observation that viral reservoirs are set early on in the infection [89 , 91] , before the beginning of ART , are very long-lived [101] , and not necessarily exclusively made of resting , infected cells . However , SIV DNA and RNA viral loads in lymph nodes did not increase because of treatment , suggesting that the antiviral effect of ISG was not impacted . The fact that rebound occurs without administration of latency reactivating agents seems to support the possibility that reservoirs include cells that are not fully resting . Indeed , rebound is observed in HIV+ individuals without treatment of activating agents , although external immune activating stimuli could contribute to the occurrence . It is also possible that in our trial ART was carried out for a period that is relatively short compared to similar studies done in HIV+ individuals , who have received ART for many years , and that the physiological decay of the reservoirs established before the initiation of treatment was not as advanced , opening the possibility that a difference could be observed only if the animals were kept on ART plus PH-797804 for a longer time . An alternative possibility is that the immune activation detected during ART suppression is not fully independent of viral gene expression but stems from continuous , low-level virion production in tissues that maintains TLR activation . As HIV transcription and SIV entry inhibitors were not part of the regimen of this trial , the therapy administered could permit partial rounds of the virus life cycle , with release and cell entry of non-infectious virions , even if productive infection cannot be achieved after entry . However , entry or uptake of non-infectious virions could be sufficient to trigger TLR signaling , even in the absence of reverse transcription and integration , and this activation could support persistent immune activation . If complete suppression of SIV antigen production were achieved and viral genomes were truly latent during ART , one does not explain the fact that CD8+ T-cell depletion leads to viremia rebound while ART is still in place in SIV-infected RM , as CD8+ T-cell activity requires antigen production to be effective . Evaluation of TLR-activated pathways in the context of ART alone and with immune activation suppression is an important goal of future studies . The possibility of persistent , low level antigenemia , which would offer a significant additional source for persistent immune activation , is not sufficiently considered and explored and requires further investigation .
The study received institutional review board approval at the Tulane Primate Research Center , where the macaques used in the study were housed . IACUC approval number of the study is: P0236R . Animal care methods are consistent with the recommendations of the panel on euthanasia of the American Veterinary Medical Association . This study was also carried out in strict accordance with the recommendations in the “Guide for the Care and Use of Laboratory Animals of the National Institutes of Health , National Academy Press , 1996 ) and with the recommendations of the Weatherall report: “The use of non-human primates in research” . The institution also accepts as mandatory the PHS “Policy on Humane care and use of Laboratory Animals by Awardee Institutions” and the NIH “Principles for the Utilization and Care of Vertebrate Animals used in Testing , Research and Training” . Thirty-two male RM ( Macaca mulatta ) , ranging in age between 2 . 40 and 4 . 33 years when the study was initiated , were included in this study and were housed at Tulane Primate Research Center , Tulane University , Covington , Los Angeles . Animals were evaluated for the expression of the following MHC molecules: A*01 , A*02 , A*08 , A*11 , B*01 , B*03 , B*04 , B*08 , B*17 . None of the animals included in the study tested positive for the protective alleles A*01 , B*08 , and B*17 [102 , 103] . Animals were divided in 6 groups and infected intravenously ( i . v . ) with 10 TCID50 SIVmac251 ( day 0 ) . Groups 1 and 2 included four animals , Groups 3 to 6 included six animals . The animals in Group 1 were left untreated as control . Since week 6 after infection , Group 2 received PH-797804 alone , group 3 initiated antiretroviral therapy ( ART ) and group 4 received ART and PH-797804 . Group 5 initiated ART one week post- infection as did Group 6 , who also received PH-797804 starting from week 6 post-infection . ART consisted of two reverse transcriptase ( RT ) inhibitors , tenofovir ( PMPA , 20 mg/kg , and emtricitabine ( FTC , 30 mg/kg ) , and the integrase inhibitor dolutegravir ( DTG , 2 . 5mg/kg s . i . d ) , all administered i . m . [104] . The animals in group 2 , 4 and 6 received 3 cycles of PH-797804 ( 10 mg s . i . d , orally administered ) , each of 12 weeks ( 6–18 , 28–40 and 48–60 weeks ) . ART and PH-797804 treatment were interrupted on week 60 and animals were monitored monthly for virus rebound until week 72 post infection . Blood were collected at various time points , approximately every 4 weeks; rectal and lymph node ( LN ) tissues were biopsied before infection and at the beginning and end of PH-797804 cycles . Briefly , after Telazol anesthesia , seven to eight biopsies/animal/time points were obtained from the rectum and blood was collected in EDTA . PBMC and plasma were separated using Ficoll-Hypaque gradient centrifugation . Rectal and lymph node biopsy-derived MNC were isolated by digestion with 1 mg/ml collagenase for 1 h at 37°C , passed through a 70-mm cell strainer to remove residual tissue fragments and separated using Ficoll-Hypaque gradient centrifugation [105] . Polychromatic flowcytometric analysis was carried out in PBMC , LN and rectal biopsy MNC according to standard procedures for membrane and intracellular staining , using a panel of mAbs ( see below ) shown to be cross reactive with RMs [105] . The percentages of CD4+ T cells and CM CD4+ T cells , immune activated CD4+ and CD8+ cells , FOXP3+ T regulatory cells , IFNγ+ and TNFα+ CD4+ and CD8+ T cells , and IP-10+ , pSTAT1+ and IRF7+ PBMC were evaluated in unstimulated cells by membrane and intracellular staining ( ICS ) [107] and reported as the percentage of CD4+ , CD8+ T cells , or PBMC that express one or more markers . Accumulation of IL-17 and IL-22 in CD4+ T cells was analyzed after phorbol 12-miristate-13 acetate ( PMA , 10 mg/ml ) and Ionomycin ( 1mg/ml ) stimulation , using the same technique . Briefly , aliquots of PBMC , LN and rectal MNC were re-suspended at 106 cells/ml in medium with or without stimulation and containing Golgi stop ( BD Bioscience , San Diego , CA ) and incubated at 37°C for ~ 12 hr . The cells were then washed and stained with the appropriate panel of antibodies for 30 minutes in the dark at room temperature , followed by fixation and permeabilization . After permeabilization , the cells were stained intracellularly with monoclonal antibodies against the cytokines of interest for 1 hour in the dark . Data were acquired on BD LSR II flow cytometer using FACSDIVA software . After acquisition , data were analyzed using the FlowJo software . The following anti-human , macaque cross-reacting , or anti-macaque antibodies were used in this study: anti-CD3-pacific blue/PerCp-Cy5 . 5 ( clone SP34-2 ) , anti-CD4-Amcyan ( clone L200 , anti-CD8-APC-Cy7 ( clone RPA-T8 ) , anti-Ki-67-Alexa Fluor-700 ( clone B56 ) , anti-HLADR-PE-CF594 ( clone G46-6 ) , anti-TNFα- PE ( clone MAb11 ) , anti-IFNγ-Alexa Fluor-700 ( clone B27 ) , anti-IRF7-APC ( clone K47-671 ) , anti- pSTAT1-Pacific blue ( clone 14/ pSTAT1 ) , anti-CD14-Pe-Cy7 ( clone M5E2 ) ( all from BD Pharmigen ) ; anti-FOXP3-FITC ( clone 206D ) , anti-IP-10-PE ( clone J034D6 ) , anti-CD28-Pe-Cy5 ( clone CD28 . 2 ) , anti-CD95-FITC ( clone DX2 ) , anti-PD-1-PerCp-Cy5 . 5 ( clone EH12 . 2H7 ) , anti-IL-2-APC ( clone MQ1-17H12 ) ( all from BioLegend , San Diego , CA ) ; anti-IL-17- PerCp-Cy5 . 5 ( clone- eBio64DEC17 ) , anti-IL-22-APC ( clone IL22JOP ) ( both from eBiosciences , San Diego , CA ) and anti-CD38-APC ( clone OKT10 ) from NHP Reagent Resource , Boston , Massachusetts ) . The levels of IFNγ , TNFα , IL-6 , and IP-10 in plasma were measured using commercially available ELISA kits from U-CyTech , Utrecht , Netherlands , according to manufacturer’s instructions . CRP , sCD163 and IFNα plasma levels were measured using a monkey CRP ELISA kit ( Life Diagnostics Inc . , West Chester , PA ) , a sCD163 ELISA kit ( My Biosource , CA , USA ) and an IFN α ELISA kit ( PBL Assay Science , NJ , USA ) . Calculations and statistical analyses were performed using the GraphPad Prism version 7 software . Normality distribution values were calculated using the D'Agostino-Pearson omnibus test . When values were normally distributed , p values were calculated using unpaired t-test , when non-normal , Wilcoxon-Mann-Whitney ( rank sum ) test was applied . Between-group comparisons at individual time points were carried out with Wilcoxon-Mann-Whitney ( rank sum ) test or unpaired using t-test depending on population normality values . AUC analyses were carried out by calculating an AUC for the time course values of each animal and areas in one group were compared to those is a second group . Results of statistical analyses were considered significant if they produced p values ≤ 0 . 05 .
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The hallmark of Human Immunodeficiency Virus and Simian Immunodeficiency Virus infection in disease-susceptible species is the progressive decline of the CD4+ T cell population and heightened immune activation , which by itself can contribute to CD4+ T-cell death . The cellular pathway regulated by p38 MAPK , which is activated in HIV and SIV infection , can contribute significantly to immune activation . We tested in SIV-infected macaques a p38 MAPK inhibitor in combination with anti-retroviral therapy . This drug is already being evaluated in humans for treatment of immune activation associated with other diseases . We found that , when combined with antiretroviral therapy , the inhibitor PH-797804 significantly reduced a few parameters of SIV-induced immune activation and improved preservation of critical populations of the immune system targeted by SIV , but did not modulate viral reservoirs . Importantly , the addition of the inhibitor to anti-retroviral therapy during the chronic phase of the infection , which is the time when most HIV-infected individuals initiate treatment , permitted a more significant preservation of the immune system compared to antiretroviral therapy alone that was similar to that observed when anti-retroviral therapy was initiated in the acute phase of the infection , which rarely occurs in HIV infection .
|
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"Abstract",
"Introduction",
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"and",
"methods"
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] |
2018
|
Inhibition of p38 MAPK in combination with ART reduces SIV-induced immune activation and provides additional protection from immune system deterioration
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The ability to control lentivirus replication may be determined , in part , by the extent to which individual viral proteins are targeted by the immune system . Consequently , defining the antigens that elicit the most protective immune responses may facilitate the design of effective HIV-1 vaccines . Here we vaccinated four groups of rhesus macaques with a heterologous vector prime/boost/boost/boost ( PBBB ) regimen expressing the following simian immunodeficiency virus ( SIV ) genes: env , gag , vif , rev , tat , and nef ( Group 1 ) ; env , vif , rev , tat , and nef ( Group 2 ) ; gag , vif , rev , tat , and nef ( Group 3 ) ; or vif , rev , tat , and nef ( Group 4 ) . Following repeated intrarectal challenges with a marginal dose of the neutralization-resistant SIVmac239 clone , vaccinees in Groups 1–3 became infected at similar rates compared to control animals . Unexpectedly , vaccinees in Group 4 became infected at a slower pace than the other animals , although this difference was not statistically significant . Group 1 exhibited the best post-acquisition virologic control of SIV infection , with significant reductions in both peak and chronic phase viremia . Indeed , 5/8 Group 1 vaccinees had viral loads of less than 2 , 000 vRNA copies/mL of plasma in the chronic phase . Vaccine regimens that did not contain gag ( Group 2 ) , env ( Group 3 ) , or both of these inserts ( Group 4 ) were largely ineffective at decreasing viremia . Thus , vaccine-induced immune responses against both Gag and Env appeared to maximize control of immunodeficiency virus replication . Collectively , these findings are relevant for HIV-1 vaccine design as they provide additional insights into which of the lentiviral proteins might serve as the best vaccine immunogens .
The development of a prophylactic vaccine against HIV-1 has proven exceedingly difficult . While most successful vaccines rely on the induction of neutralizing antibodies ( nAbs ) to protect against infection , eliciting such responses against HIV-1 has been hampered by several aspects of the lentivirus Env glycoprotein [1] . The env gene of both HIV and simian immunodeficiency virus ( SIV ) encodes a gp160 precursor protein that is post-translationally cleaved into two subunits , gp120 and gp41 . Dimers of these cleavage products assemble into trimers to ultimately form the native Env spike . HIV-1’s resistance to neutralization stems from several factors , including the inaccessibility of neutralizing epitopes in the native trimer , its poorly immunogenic glycan shield , and the enormous env sequence diversity of circulating isolates [1] . Despite these barriers , a fraction of infected individuals develop antibodies capable of potently neutralizing a wide spectrum of HIV-1 isolates [1] , indicating that it is possible to harness the human immune system to mount such responses . The RV144 “Thai trial” remains the only report of vaccine-mediated reduction ( albeit modest ) in HIV-1 infection rates [2] , but this result remains controversial [3 , 4] . A subsequent investigation of immune correlates of protection revealed that vaccine-induced IgG binding antibodies against the Env variable regions 1 and 2 ( V1/V2 ) were associated with reduced HIV-1 acquisition [5] , implying that antibody functions other than neutralization might have been responsible for the apparent protection reported in RV144 . Recent monkey studies have also linked vaccine-elicited binding antibodies directed against V1/V2 to protection against mucosal infection with the biological isolate SIVmac251 [6–9] . However , except for live-attenuated SIV vaccines [10] , no vaccine regimen has been able to prevent mucosal infection with the SIVmac239 clone , perhaps due to the unusual resistance of its Env protein to neutralization [11–15] . Given the difficulty in engendering broadly reactive anti-HIV-1 nAbs by vaccination , considerable efforts have been devoted to the development and optimization of vaccine regimens aimed at eliciting cellular immunity against HIV-1 since T-cell responses have been associated with control of viral replication [16] . Two factors must be considered when designing vaccines for the induction of cellular immunity: the vector platform and which inserts to use . In terms of the former , most immunization protocols have relied on DNA plasmids or replication-defective viral vectors to deliver HIV-1 or SIV genes for eliciting T-cell responses [17–20] . Since these approaches provide only transient Ag production , they favor the induction of central memory T-cell ( TCM ) responses [21 , 22] . Although vaccine-induced TCM have been shown to confer some measure of control of SIV replication [22] , they rely on anamnestic expansion to produce enough effector cells to suppress viral replication [21] . Previous mouse studies have shown that this process can take several days after infection [23] . Alarmingly , however , SIV has been shown to cross the rectal epithelium and reach lymphoid tissues of rectally-challenged rhesus monkeys as early as 4 hr after virus exposure [24] . Thus , the kinetics of a vaccine-induced TCM-based response might be too slow to cope with the dynamism and fast pace of lentivirus infection . In contrast to TCM , effector memory T-cells ( TEM ) are poised for immediate effector function and do not need antigen ( Ag ) restimulation to exert cytotoxic activity [21] . Additionally , TEM recirculate through mucosal tissues where the majority of immunodeficiency virus transmissions take place [21] . These antiviral properties have prompted the development of immunization protocols that provide recurrent Ag exposure since this type of immune stimulation drives CD8+ T-cell differentiation toward the TEM phenotype . One strategy that has shown promise in pre-clinical SIV trials employs a fibroblast-adapted strain ( 68–1 ) of the persistent β-herpesvirus rhesus cytomegalovirus ( RhCMV ) to deliver SIV Ag [25 , 26] . Although RhCMV/SIV vaccination does not protect monkeys from infection with SIVmac239 , 50% of vaccinees manifest early control of viral replication and eventually clear the infection [27] . Of note , the efficacy of this vaccine regimen likely depends on the ability of 68-1-based RhCMV/SIV vectors to engender CD8+ TEM restricted by major histocompatibility complex class ( MHC ) -II and/or non-classical MHC-I molecules [28 , 29] . Experiments conducted in mice have shown that the iterative waves of Ag delivered as part of heterologous prime/boost/boost ( PBB ) vaccine regimens can also generate CD8+ TEM responses [30 , 31] . To explore this approach in nonhuman primates , we designed a new mixed modality immunization protocol comprising an electroporated recombinant DNA ( EP rDNA ) prime followed by sequential vaccinations with recombinant ( r ) adenovirus type-5 ( rAd5 ) and vesicular stomatitis virus ( rVSV ) vectors to elicit SIV-specific immune responses . Since it is unclear if sequential boosting with replication-impaired vectors can maintain high frequency CD8+ TEM for long periods of time , we incorporated a fourth and final boost into this immunization protocol using rhesus monkey rhadinovirus ( RRV ) -based vectors . RRV is a γ2-herpesvirus and , similar to RhCMV , establishes a persistent infection in rhesus macaques [32] . However , in contrast to RhCMV , rRRV/SIV vaccination has been shown to induce classical MHC-I-restricted CD8+ TEM responses [33] . Having decided on an EP rDNA/rAd5/rVSV/rRRV PBBB regimen to elicit SIV-specific immune responses , we set out to determine which of the various lentivirus gene products might be the most efficacious in this immunization protocol . The choice of which viral Ag should serve as the targets of vaccine-induced cellular immunity has been a contentious issue , largely because T-cell responses against different viral proteins have been linked to discordant virologic outcomes in chronically HIV-1-infected individuals [34 , 35] . For instance , broad CD8+ T-cell responses against Env , or accessory and regulatory proteins as a whole , have been associated with higher viral loads ( VLs ) , whereas recognition of multiple epitopes in Gag has correlated with lower viremia [34] . Although these correlations were identified in cross sectional studies and therefore do not necessarily imply causation , they illustrate how the selection of T-cell immunogens for HIV-1 vaccines is not straightforward . Indeed , it is hard to argue against eliciting Env-specific immune responses in light of recent SIV vaccine trials showing that Env is required and sufficient for preventing SIV infection in rectally-challenged monkeys [6 , 36] . Furthermore , while Gag has features of a useful immunogen [16 , 37 , 38] , a Gag-only vaccine is unlikely to afford substantial control of viral replication in the event of HIV-1 infection . Lastly , T-cell responses against accessory and regulatory proteins may not correlate with reduced VLs in HIV-1-infected patients but they can result in significant control of SIV infection in vaccinated rhesus macaques [39 , 40] . Curiously , T-cell responses against the accessory protein Vif have also been linked to lower infection risk in an HIV-1 preexposure prophylaxis trial [41] . Given these uncertainties , additional investigation is needed to define the lentivirus Ag that elicit the most protective immune responses . Here we explored how the selection of SIV immunogens impacts vaccine efficacy . We vaccinated four groups of Indian rhesus macaques with an EP rDNA/rAd5/rVSV/rRRV PBBB regimen encoding different sets of SIV Ag and subsequently challenged them , alongside a group of sham-immunized control animals , intrarectally with SIVmac239 . In comparing vaccine immunogenicity and efficacy among the four groups , we made several observations that might be relevant for the design of HIV-1 vaccine strategies .
A total of 32 Indian rhesus macaques were vaccinated with an EP rDNA/rAd5/rVSV/rRRV vaccine regimen encoding SIVmac239 genes . These animals were subdivided into four groups depending on the SIV antigens delivered by the PBBB regimen ( Fig 1 ) . The vaccinees in Group 1 ( n = 8 ) were immunized with env , gag , vif , rev , tat , and nef; those in Group 2 ( n = 8 ) received env , vif , rev , tat , and nef; macaques in Group 3 ( n = 8 ) were vaccinated with gag , vif , rev , tat , and nef , while those in Group 4 ( n = 8 ) were immunized with a more restricted set of immunogens , comprising vif , rev , tat , and nef . The Group 5 macaques ( n = 8 ) were sham vaccinated with empty constructs or vectors encoding irrelevant inserts and served as the controls for this experiment . To facilitate monitoring of SIV-specific CD8+ T-cells by fluorochrome-labeled MHC-I tetramer staining , each group contained three or four monkeys that were positive for the MHC-I alleles Mamu-A*01 or Mamu-A*02 ( Table 1 ) . None of the animals in this experiment expressed the elite control-associated alleles Mamu-B*08 or Mamu-B*17 . Both the rDNA and rAd5 vectors were delivered intramuscularly . However , in an attempt to elicit systemic immunity and direct vaccine-elicited CD8+ T-cells to relevant sites of lentivirus transmission and amplification , we delivered the rVSV vectors via both the intravenous ( IV ) and intrarectal ( IR ) routes . Curiously , while the rVSV boost increased the frequency of Vif-specific CD8+ T-cells in nearly all animals–especially those in Group 4 ( Fig 2C and 2G ) , it had little effect on the levels of vaccine-elicited CD8+ T-cells targeting Env , Nef , and Tat ( Fig 2B , 2D , 2F and 2H ) . The rVSV boost also augmented the size of the Gag CM9-specific CD8+ T-cell response in the Mamu-A*01+ Group 3 vaccinee r08061 , but it had little effect on the response detected in the Group 1 animal r09046 ( Fig 2A ) . This preferential expansion of CD8+ T-cells directed against Vif epitopes may have been due to the simultaneous administration of two rVSV/vif vectors to the macaques in Groups 1–4 ( see Materials and methods ) . The rRRV vectors were also co-delivered via the IV and IR routes and had a modest effect on the magnitude of SIV-specific CD8+ T-cell responses following vaccination . The Mamu-A*01+ Group 2 vaccinee r04106 was an exception since >30% of its peripheral CD8+ T-cells targeted the Tat SL8 epitope at week ( wk ) 2 post the rRRV boost ( Fig 2D ) . One possible reason for the relatively poor expansion of SIV-specific CD8+ T-cells observed after the rRRV boost is that T-cell immunity engendered by the previous vaccinations may have limited the take of the rRRV vectors . Since these rRRV constructs are live herpesviruses , they need to infect and replicate in host cells in order to produce SIV antigens . Given that we delivered rRRV as the final viral vector boost , CD8+ T-cell responses against vaccine inserts generated by the EP rDNA , rAd5 , and rVSV immunizations could have eliminated rRRV-infected cells in some of the animals before the establishment of a productive infection . Additionally , since several animals in Groups 1–4 were already naturally infected with RRV at the time of the rRRV vaccination ( Table 1 ) , pre-existing immunity to RRV antigens could also have decreased the take of the rRRV vectors in those monkeys . We also analyzed vaccine-induced SIV-specific T-cell responses in peripheral blood from macaques in Groups 1–4 by ICS at the time of the first IR SIV challenge . Except for a few high responders , the vast majority of animals had low or undetectable CD4+ T-cell responses ( Fig 3 ) . Interestingly , while the limited set of antigens delivered to Group 4 resulted in robust but narrowly focused CD8+ T-cell responses in some of the monkeys , increasing the number of immunogens delivered to Groups 1–3 decreased the frequency of CD8+ T-cells recognizing each viral protein ( Fig 3A–3D ) . Despite these differences , the total magnitude of SIV-specific CD8+ T-cell responses elicited in Groups 1–4 was equivalent ( Fig 3E ) , suggesting that there are constraints to the induction of high frequency , broadly targeted T-cell responses by vaccination . Vaccine-induced SIV-specific CD4+ T-cells were also similar among the groups , except for slightly higher levels of these responses in Group 1 compared to Group 2 ( Fig 3E ) . Heterologous PBB regimens in mice have been shown to induce high frequencies of CD8+ TEM that recirculate through extra-lymphoid anatomical sites [30 , 31] . Although we did not determine the frequency of vaccine-elicited CD8+ T-cells in effector tissues in the present study , we characterized the memory phenotype of tetramer+ CD8+ T-cells in blood at the time of the first IR SIV challenge . We delineated tetramer+ CD8+ T-cells as TCM , transitional memory ( TEM1 ) , or fully differentiated TEM ( TEM2 ) based on their expression pattern of CD28 and CCR7 ( Fig 4A ) [42] . Curiously , while the majority of vaccine-induced CD8+ T-cells targeting epitopes in Gag , Tat , and Nef exhibited a TEM2 signature , there was great variability in the proportion of Vif-specific CD8+ T-cells displaying this phenotype ( Fig 4B–4G ) . We monitored the levels of vaccine-induced gp140-binding IgG antibodies in plasma from the Group 1 and Group 2 animals throughout the vaccine phase by semi-quantitative ELISA . Except for r10062 in Group 1 , all animals already had detectable Env-specific antibodies after the third EP rDNA immunization ( Fig 5A & 5B ) . Monkey r10062 was not primed with EP rDNA since it was enrolled in Group 1 shortly before the rAd5 boost as a replacement for a rhesus macaque that died unexpectedly . Anti-Env humoral responses underwent a sharp but transient increase after the rAd5 boost in all animals ( but r10062 ) in Groups 1 and 2 , and subsequently plateaued at levels that remained stable until the time of challenge ( Fig 5A & 5B ) . Neither the rVSV nor the rRRV vaccinations significantly boosted anti-gp140 antibody levels ( Fig 5A & 5B ) . The endpoint titers of vaccine-elicited gp140-binding antibodies in Groups 1 and 2 at the time of the first IR SIV exposure ranged from 400 to 6 , 400 ( Fig 5C ) . As a reference , these levels were nearly two logs lower than those measured in monkeys that had been infected with SIVmac239Δnef for 28 wks as part of a previous experiment conducted by our group [43] . To assess the efficacy of the various combinations of SIV immunogens delivered to Groups 1–4 by the rDNA/rAd5/rVSV/rRRV regimen , all vaccinees and the control animals in Group 5 were subjected to repeated IR challenges with a marginal dose ( 200 TCID50 ) of SIVmac239 . For logistical reasons , the 40 macaques in the present experiment were staggered in two challenge cohorts . Groups 1 , 2 , and half of Group 5 ( cohort #1 ) were challenged first at wk 83 after the first EP rDNA vaccination ( Fig 1 ) . Groups 3 , 4 , and the other half of Group 5 ( cohort #2 ) were challenged at wk 89 post initiation of the vaccine regimen ( Fig 1 ) . Of note , the total magnitude of vaccine-induced SIV-specific T-cell responses was not significantly different between the groups challenged at either wk 83 or 89 after the first EP rDNA vaccination ( Fig 3E ) . In both cohorts , macaques were exposed intrarectally to SIV every other week , and VLs were determined in plasma samples collected on days 7 and 10 after each challenge ( Fig 6A ) . If a monkey was aviremic on both occasions , it was challenged again on day 14 , thereby initiating a new cycle of challenges . However , in case of a positive VL on either day 7 or day 10 , the animal was not re-challenged and its VLs were monitored until wk 20 post infection ( PI ) . This strategy enabled us to identify the infecting exposure for all animals in this experiment , except for r09046 , in which the first positive VL was detected on day 14 after the 10th SIV exposure . As a result , this animal ended up being challenged eleven times ( Fig 6B ) , even though it likely acquired SIV infection after the 10th exposure . Surprisingly , the rate of SIV acquisition in Group 4 appeared delayed compared to the other groups ( Figs 6B & 7 ) . Indeed , while all of the animals in Group 2 and all but one of the monkeys in Groups 1 , 3 , and 5 became infected by the 6th SIV exposure , three vaccinees in Group 4 ( r08031 , r06029 , and rhBF24 ) were still uninfected after six challenges ( Fig 6B ) . These animals remained aviremic after the 7th , 8th , and 9th SIV exposures ( Fig 6B ) . They also had no detectable T-cell responses against SIV Ag that were not included in the vaccine after the 8th IR challenge ( S1 Fig ) . Monkey r08031 eventually acquired infection after the 10th challenge while both r06029 and rhBF24 became infected after the 12th exposure ( Fig 6B ) . Despite the slower kinetics of SIV acquisition in these three vaccinees , neither Group 4 nor any of the other vaccinated groups differed in a statistically significant fashion from the control group in their rates of infection ( Fig 7 ) . Two animals in the present experiment were unusually resistant to SIV infection . The Group 5 control monkey rh2313 resisted 13 IR challenges before becoming infected after the 14th exposure ( Fig 6B ) . Notably , the Group 3 vaccinee r08030 remained uninfected after 22 IR challenges with SIVmac239 , of which the last three exposures delivered a ten-fold higher inoculum ( 2 , 000 TCID50 ) ( Fig 6B ) . Previous studies have reported that expression of certain combinations of TRIM5 alleles , particularly TRIM5TFP/CypA and to a lesser extent TRIM5TFP/TFP , can affect susceptibility to rectal infection with SIVsmE660 [44 , 45] . While monkeys rh2313 and r08030 had moderately restrictive ( TRIM5TFP/Q ) and restrictive ( TRIM5TFP/TFP ) genotypes ( Table 1 ) , respectively , it is hard to conclude that TRIM5 allele combinations influenced the rate of SIV infection in this experiment since SIVmac239 has been shown to be refractory to TRIM5α restriction [46] . Additionally , we have previously shown that expression of restrictive TRIM5 alleles was not associated with delayed SIVmac239 infection in rectally challenged rhesus macaques [45] . Thus , it is not clear why r08030 and rh2313 resisted more challenges than the remaining monkeys in this experiment . Importantly , 5/8 Group 1 vaccinees controlled viral replication to <2 , 000 vRNA copies/mL of plasma in the chronic phase ( Fig 8A & 8H ) . Although the Group 1 monkey r04017 manifested post peak control of viremia until wk 8 PI , SIV replication surged shortly afterwards , perhaps due to viral escape ( Fig 8A ) . Group 1 exhibited significantly lower peak VLs than the control group , and was the only vaccinated group to reduce chronic phase VLs to a statistically significant level ( Fig 8G & 8H ) . Interestingly , the virologic control manifested by the Group 1 vaccinees was largely abrogated by the removal of gag ( Group 2 ) , env ( Group 3 ) , and both gag and env ( Group 4 ) from the set of vaccine-encoded immunogens . Indeed , while Groups 2–4 experienced modest , yet statistically significant , reductions in peak viremia , none of these vaccinated groups significantly decreased chronic phase VLs ( Fig 8G & 8H ) . Of note , one monkey in Group 3 ( r07003 ) and two monkeys in Group 4 ( r09009 and r06029 ) controlled viral replication to <1 , 000 vRNA copies/mL in the chronic phase ( Fig 8C & 8D ) , although it is not clear why these animals fared better after infection than their group counterparts . Together , these results suggest that vaccine-induced immune responses targeting both Gag and Env were crucial for the virologic containment manifested by the Group 1 vaccinees . Lastly , we investigated potential mechanisms for the differential control of viral replication manifested by the vaccinees in Groups 1–4 . This analysis revealed that high titers of vaccine-induced gp140-binding antibodies at the time of challenge correlated with lower peak VLs in Groups 1 and 2 ( Fig 9A ) . However , these antibody responses did not predict control of chronic phase viremia ( Fig 9B ) . Despite the association with peak VLs , none of the animals exhibited serological neutralizing activity against SIVmac239 at the time of challenge ( S2 Fig ) . Since antibody dependent cellular cytotoxicity ( ADCC ) has been linked to the protective efficacy of live-attenuated SIV vaccination [47] , we also measured this parameter in plasma from the Group 1 and Group 2 vaccinees . This analysis revealed little or no ADCC activity against SIVmac239-infected target cells at the time of the first SIV exposure ( Fig 10 ) . We also examined the predictive value of the total magnitude of vaccine-elicited SIV-specific CD4+ or CD8+ T-cell responses in Groups 1–4 and found no correlation between these variables and suppression of SIV replication ( Fig 9C–9F ) . Collectively , these data suggest that virologic control of the highly pathogenic SIVmac239 clone might be achieved by vaccine regimens that elicit high titers of gp140-binding antibodies and T-cells targeting multiple viral proteins ( Env and Gag inclusive ) .
Here we conducted a head-to-head comparison of the immunogenicity and protective efficacy of four different sets of SIV inserts delivered by a novel PBBB regimen . All four sets included the regulatory and accessory proteins Vif , Rev , Tat , and Nef , which were administered by themselves ( Group 4 ) or with the addition of Gag ( Group 3 ) , Env ( Group 2 ) , or both Gag and Env ( Group 1 ) . Interestingly , despite differences in the number and size of vaccine-encoded immunogens , the total magnitude of SIV-specific CD8+ T-cells elicited by vaccination was equivalent in Groups 1–4 . This was explained by some of the Group 4 vaccinees mounting robust CD8+ T-cell responses focused almost entirely on Vif and/or Nef . Although responses against these proteins were also detected in Groups 1–3 , they tended to be lower in frequency , possibly reflecting a diversion of the SIV-specific T-cell response toward the larger Env and Gag proteins . These results are consistent with those reported by Hel et al . in the context of SIV vaccination and suggest that , at least as reflected in peripheral blood , total vaccine-elicited Ag-specific CD8+ T-cells are poised to proliferate until a “ceiling” level is reached , regardless of the number or size of inserts delivered by vaccination [48] . It is not clear how this ceiling of memory CD8+ T-cell expansion is regulated , but host-intrinsic factors such as T-cell competition for Ag-bearing dendritic cells , immunological experience , naïve T-cell precursor frequencies , and CD8+ T-cell immunodominance might be involved . Collectively , these results underscore the difficulty of engendering HIV-1-specific CD8+ T-cell responses by vaccination that are both large in size and broad in epitope recognition . Importantly , increasing the number of immunogens delivered by vaccination appeared to enhance control of SIVmac239 replication . Indeed , Group 1 exhibited the greatest reduction in peak VLs , with 5/8 vaccinees in this group going on to control chronic phase viremia to less than 2 , 000 vRNA copies/mL . In contrast , Groups 2–4 manifested only modest suppression of peak VLs and no reduction in chronic phase VLs . The improved virologic control manifested by the Group 1 vaccinees might have been due to a synergy between vaccine-induced T-cells targeting epitopes in multiple viral proteins and anti-Env humoral responses . The latter possibility is supported by the inverse correlation between titers of vaccine-induced Env-binding antibodies and control of acute phase viremia ( Fig 9 ) , even though these antibodies could not neutralize SIVmac239 in vitro ( S2 Fig ) . ADCC was detectable in several animals but only at high concentrations of plasma ( Fig 10 ) . It is worth mentioning that we did not evaluate antibody functions at the site of virus exposure . Since peripheral blood is an imperfect proxy for the mucosal milieu , additional characterizations of Env-specific antibodies in rectal secretions could have shed light into the mechanisms by which macaques in Groups 1 and 2 suppressed acute phase viremia . Since HIV-1 is transmitted primarily via unprotected intercourse , a successful vaccine may need to induce antiviral immunity at the reproductive and gastrointestinal tracts . Thus , pre-clinical evaluations of HIV-1 vaccine regimens should include mucosal samplings of relevant sites of virus transmission . Our data also suggest that control of lentivirus replication might be facilitated by vaccine-induced immune responses targeting both Gag and Env since the absence of either ( Groups 2 and 3 ) or both of these responses ( Group 4 ) largely abrogated the virologic control afforded by the Group 1 regimen . Of note , since we did not evaluate the protective efficacy of a gag and env-only PBBB regimen , it is formally possible that vaccine-induced immune responses against Gag and Env were sufficient for the superior performance of Group 1 . Indeed , the utility of Gag and Env as vaccine immunogens has been demonstrated by several previous studies [6 , 36 , 49 , 50] . Nevertheless , we favor the interpretation that vaccine-elicited immune responses against Gag and Env acted in synergy with those targeting Vif , Rev , Tat , and Nef to control viral replication in Group 1 . In support of this view , macaques vaccinated with rDNA/rNYVAC encoding SIV gag , pol , env , and a rev-tat-nef fusion insert manifested better control of SIVmac251 replication than did recipients of the same regimen lacking nonstructural SIV genes [48] . Furthermore , the efficacy of rAd5-based immunization protocols against IR SIV challenges appears to increase with the progressive incorporation of inserts encoding viral proteins [49 , 51–55] . Thus , our data and those from others suggest that vaccine-mediated control of lentivirus replication might be improved by inducing immune responses against Gag , Env , and the remaining viral proteins as well . The fact that vaccinees in Groups 1 and 2 became infected at the same rate as the control group contrasts with recent studies reporting that vaccine-induced Env-binding antibodies can affect the rate of SIVmac251 acquisition after IR challenge [6 , 8 , 9 , 56] . While it is difficult to compare these discrepant outcomes–considering the distinct underlying experimental designs , the stringency of SIVmac239 as a challenge virus may explain these different results . Despite being genetically related , SIVmac239 and the SIVmac251 isolates used in the studies cited above differ in important ways . For instance , while SIVmac239 is a molecular clone , resulting in little sequence variability among different stocks , SIVmac251 consists of a swarm of viral quasispecies . Indeed , Del Prete et al . have recently reported considerable sequence diversity among different stocks of SIVmac251 [57] . Although this feature of SIVmac251 might be useful for tracking the number of transmitted/founder viruses in mucosal challenge studies , it can also result in unwanted variability . For example , there are conflicting reports on the susceptibility of SIVmac251 to TRIM5α restriction [58–60] . The passage history of SIVmac251 stocks has also been shown to impact their susceptibility to antibody neutralization in vitro [61] , and SIVmac251 env clones displaying tier 1 and tier 3 neutralization profiles have been isolated [14] . The SIVmac239 Env , on the other hand , is known to be consistently resistant to antibody neutralization [11–13 , 15] . Similar to HIV-1 Env immunogens , vaccination with SIVmac239 Env elicits primarily tier 1 nAbs and , to our knowledge , no vaccine regimen has been able to consistently engender potent nAbs against SIVmac239 [14] . Ultimately , it will be important to determine if these differences have any translational relevance , especially since vaccine efficacy against SIVmac251 has been recently used to justify a phase 2b/3 efficacy trial of an ALVAC-HIV/gp120 vaccine regimen in South Africa [62] . Six animals in the present experiment resisted multiple IR challenges with SIVmac239: one in Group 1 ( r09046 ) , one in Group 3 ( r08030 ) , three in Group 4 ( r08031 , r06029 , and rhBF24 ) , and one in the control group ( rh2313 ) . It is not clear why these monkeys exhibited this phenotype . Of these monkeys , only r09046 expressed a combination of TRIM5 alleles that has been significantly associated with resistance to rectal SIVsmE660 infection ( TRIM5TFP/CypA ) [46] , although this effect was not observed in macaques following IR challenges with SIVmac239 [45] . The remaining animals were positive for either moderately restrictive or susceptible TRIM5 allele combinations ( Table 1 ) , indicating that TRIM5α restriction of SIV infection cannot solely account of these animals’ resistance to SIV acquisition . It is also noteworthy that mucosal transmission of immunodeficiency viruses can be shaped by both selective and stochastic events , and factors such as mucosal integrity , local inflammation , and the amount of intraluminal feces at the time of virus exposure have been proposed to influence susceptibility to rectal lentivirus infection [63–65] . In this regard , we cannot rule out the possibility that the delayed infection rate observed in the aforementioned animals was due to chance . Curiously , however , three of these six macaques were in Group 4 , the most distinctive immunological feature of which was the development of CD8+ T-cell responses focused on Vif and Nef . These results are similar to those observed in another SIV vaccine trial recently conducted by our laboratory . The macaques in this other study expressed the elite control-associated MHC-I allele Mamu-B*08 and were vaccinated with a rAd5/rVSV/rRRV PBB regimen expressing vif , rev , tat , and nef inserts matching the SIVmac239 challenge virus . Similar to the immunization protocol presented here , the rRRV vectors were delivered to these Mamu-B*08+ vaccinees via both the IV and IR routes . These animals also mounted CD8+ T-cell responses predominantly focused on Vif and Nef since Mamu-B*08 restricts immunodominant epitopes in these proteins [66] . Notably , after six IR challenges with the same dose and stock of SIVmac239 utilized here , 4/10 Mamu-B*08+ vaccinees remained uninfected whereas all MHC-I-matched control monkeys became infected . In keeping with these outcomes , Xu et al . have recently assessed the efficacy of a mucosal T-cell-based vaccine encoding SIV accessory proteins in rhesus macaques against repeated IR challenges with SIVmac251 [67] . Tellingly , 3/6 vaccinees versus 1/6 controls remained aviremic after five IR exposures with a marginal dose of SIVmac251 . The small sample sizes of these three independent experiments obviously preclude any definitive conclusions . However , if these similar challenge outcomes are considered together , they suggest that vaccine-induced CD8+ T-cells against accessory proteins may have some capacity to prevent systemic infection in the absence of anti-Env antibodies . How could vaccine-elicited SIV-specific CD8+ T-cells mediate such an effect since CD8+ T-lymphocytes can only eliminate viruses after co-localizing with cells that are already infected ? It is possible that tissue-resident memory T-cells ( TRM ) induced by vaccination intercepted the initial foci of infected cells in the rectum and/or its associated lymphoid structures before the infection became systemic . TRM resemble TEM in their fast acting antiviral properties [21 , 68] , but in contrast to TEM , TRM do not recirculate and remain permanently positioned in effector tissues [68] . TRM have been the focus of intense research lately since these cells participate in the first line of defense against pathogens . Unfortunately , the logistics of conducting a large monkey experiment precluded us from searching for vaccine-induced SIV-specific TRM prior to the challenge phase . Nevertheless , based on results from previous studies [69 , 70] , we speculate that the simultaneous delivery of the rVSV and rRRV vectors via the IV and IR routes may have increased the frequency of SIV-specific CD8+ T-cells at relevant sites of virus transmission and amplification . Importantly , mounting evidence suggests that CD8+ T-cells can suppress immunodeficiency virus replication shortly after mucosal transmission and before a long-lived viral reservoir is established . For example , 50% of RhCMV/SIV vaccinees manifest stringent control of viral replication early after mucosal SIVmac239 infection [26] . This outcome may reflect vaccine-induced T-cell-mediated restriction of viral spread beyond a relatively small and short-lived population of initially infected cells , with clearance or spontaneous decay of this population over time [27] . Furthermore , and as mentioned above , a recent monkey study evaluated the efficacy of a T-cell-based SIV vaccine administered both intramuscularly and intrarectally and reported that a fraction of vaccinees remained aviremic after repeated marginal dose IR challenges with SIVmac251 [67] . Collectively , these results lend support to the hypothesis that vaccine-induced T-cells may be able to prevent systemic infection . Ultimately , however , larger and appropriately powered monkey trials will be needed to validate this hypothesis . Since Gag has largely been the preferred target for the induction of HIV-1-specific cellular immunity by vaccination [16] , the Ag specificity of vaccine-elicited CD8+ T-cells in Group 4 merits discussion since they were focused almost entirely on the accessory proteins Vif and Nef . Although the idea of using the HIV-1 accessory and regulatory proteins as vaccine immunogens has been proposed previously [71] , relatively few monkey studies have explored the protective efficacy of vaccine-induced T-cell responses against these targets in the face of stringent SIV challenges . We have recently shown that high frequency , Nef-specific CD8+ T-cells generated by a PBB regimen did not protect Mamu-B*08+ macaques from the same IR SIVmac239 challenge employed here [72] . This observation raises the possibility that Vif-specific CD8+ T-cells might have been important for the delayed SIV infection kinetics observed in Group 4 and in the aforementioned Mamu-B*08+ vaccinees . Curiously , a recent analysis of immune responses in a large cohort of HIV-1-exposed seronegative individuals revealed that T-cells , especially those targeting Vif , correlated inversely with infection risk [41] . Furthermore , we and others have reported associations between vaccine-elicited T-cell responses against Vif and control of SIV replication in rhesus macaques [39 , 73] . These analyses , however inconclusive , warrant additional investigation into the antiviral role of Vif-specific CD8+ T-cells in vivo . In conclusion , here we show that expanding the number of vaccine-encoded Ag improved control of viral replication in SIVmac239-infected rhesus macaques and that vaccine-induced immune responses against Env and Gag were required for this effect . In this regard , we are currently exploring the efficacy of an enhanced mixed modality immunization regimen encoding the entire SIV proteome against IR challenge with SIVmac239 . The tantalizing hint of delayed SIV acquisition in macaques vaccinated with Vif and Nef has also prompted us to begin to evaluate the protective effects of vaccine-induced CD8+ T-cell responses focused on Vif in a large monkey experiment . Together , these results might be relevant for the design of future HIV-1 vaccine regimens since they provide clues as to the most effective targets of anti-lentivirus immunity .
The details regarding animal welfare described herein are either similar or identical to those published in one of our previous experiments [74] . “The Indian rhesus macaques ( Macaca mulatta ) utilized in this study were housed at the Wisconsin National Primate Research Center ( WNPRC ) . All animals were cared for in accordance with the guidelines of the Weatherall report and the principles described in the National Research Council’s Guide for the Care and Use of Laboratory Animals under a protocol approved by the University of Wisconsin Graduate School Animal Care and Use Committee” ( animal welfare assurance no . A3368-01; protocol no . G00671 and G005145 ) [75] . “Furthermore , the macaques in this study were managed according to the animal husbandry program of the WNPRC , which aims at providing consistent and excellent care to nonhuman primates at the center . This program is employed by the Colony Management Unit and is based on the laws , regulations , and guidelines promulgated by the United States Department of Agriculture ( e . g . , the Animal Welfare Act and its regulations , and the Animal Care Policy Manual ) , Institute for Laboratory Animal Research ( e . g . , Guide for the Care and Use of Laboratory Animals , 8th edition ) , Public Health Service , National Research Council , Centers for Disease Control , and the Association for Assessment and Accreditation of Laboratory Animal Care International . The nutritional plan utilized by the WNPRC is based on recommendations published by the National Research Council . Specifically , macaques were fed twice daily with 2050 Teklad Global 20% Protein Primate Diet and food intake was closely monitored by Animal Research Technicians . This diet was also supplemented with a variety of fruits , vegetables , and other edible objects as part of the environmental enrichment program established by the Behavioral Management Unit . Paired/grouped animals exhibiting stereotypical and/or incompatible behaviors were reported to the Behavioral Management staff and managed accordingly . All primary enclosures ( i . e . , stationary cages , mobile racks , and pens ) and animal rooms were cleaned daily with water and sanitized at least once every two weeks . ” Lights were on a 12:12 diurnal schedule . Vaccinations were performed under anesthesia ( Ketamine administered at 5–12 mg/kg depending on the animal ) and all efforts were made to minimize suffering . Euthanasia was performed at the end of the study or whenever an animal experienced conditions deemed distressful by one of the veterinarians at the WNPRC . All euthanasia were performed in accordance with the recommendations of the Panel on Euthanasia of the American Veterinary Medical Association and consisted of an IV overdose ( greater than or equal to 50 mg/kg or to effect ) of sodium pentobarbital or equivalent , as approved by a clinical veterinarian , preceded by ketamine ( at least 15 mg/kg body weight ) given by the intramuscular ( IM ) route . Additional animal information , including MHC-I and TRIM5 alleles , age at the beginning of study , and sex , is shown in Table 1 . Seven rDNA constructs consisting of different versions of the pCMVkan plasmid were used in this experiment [55] . Six of them expressed one of the following codon-optimized SIVmac239 inserts: env ( full length gp160 ) , gag , vif , rev-tat , and nef . The seventh rDNA construct consisted of “empty” pCMVkan lacking any insert and was administered to the control animals in Group 5 . The macaques in Groups 1–5 were vaccinated intramuscularly with a mixture of 1 . 0 mg of the appropriate rDNA plasmid ( see Fig 1 ) and 0 . 1 mg of the IL-12-expressing AG157 plasmid using the TriGrid in vivo electroporation system ( Ichor Medical Systems , Inc . , San Diego , CA ) [76] . Macaques in Groups 1–5 were primed with EP rDNA three times at 5-wk intervals . Muscles in the thighs and forearms were used for these vaccinations and these anatomical sites were rotated in subsequent immunizations so that each location did not receive vectors encoding the same SIV inserts twice . The rAd5 boost occurred at wk 31 following the first EP rDNA immunization . Five rAd5 vectors were used in this experiment [55 , 77] . Four of these rAd5 vectors expressed one of the following codon-optimized SIVmac239 inserts: env ( full length gp160 ) , gag , a vif minigene encoding Vif amino acids ( aa ) 1–110 , and a nef minigene encoding Nef aa 45–210 . The latter two vectors were produced by Viraquest , Inc , whereas the rest of the rAd5 constructs were produced by the International AIDS Vaccine Initiative . The fifth vector consisted of “empty” rAd5 lacking any insert and was administered to the control animals in Group 5 . The appropriate rAd5 vectors were administered intramuscularly to the monkeys in Groups 1–5 , with 1011 viral particles of each vector delivered to the same sites used for the EP rDNA vaccinations . The rVSV boost occurred at wk 58 following the first EP rDNA immunization . Six rVSV vectors expressing SIVmac239 inserts were used in this experiment . Five were based on a VSV Indiana vector in which the G gene was repositioned to the 5’ terminus of the genome [78] . By placing the G gene in the most distal gene position relative to the promoter ( 6th position ) , its expression was modestly downregulated . The vector was also modified by replacing the VSV Indiana G sequence with that from VSV New Jersey . The five VSV constructs based on this vector included: 1 ) rVSV-EnvΔct4-Gnj6 encoded SIV Env protein with a cytoplasmic tail that was truncated by 159 aa at its carboxyl terminus . This modification increased Env surface expression and genetic stability of rVSV-Env4-Gnj6-infected cells in vivo [78 , 79] . The envΔct4 gene was inserted into the 4th position relative to the 3’ end of the VSV genome . 2 ) rVSV-Gag1-Gnj6 encoded the full-length Gag polyprotein . The gag gene was inserted into position 1 of the VSV genome . 3 ) rVSV-Nef1-Gnj6 encoded a Nef protein lacking its myristoylation signal . This myristoylation-deficient nef gene was inserted into position 1 of the VSV genome . 4 ) rVSV-TatRev1-Gnj6 encoded a fusion of Tat and Rev regulatory proteins . The tatrev fusion gene was inserted into position 1 of the VSV genome . 5 ) rVSV-Vif ( mut4 ) 3-Gnj6 encoded a truncated Vif protein lacking aa 2–41 . This Vif vector was developed after finding that the initial rVSV-Gnj6 constructs expressing full-length vif were genetically unstable . To identify a stable Vif vector , we subsequently screened several new vectors containing vif inserts with or without coding sequence for aa 2–41 , some of which also were modified by shuffling Vif domains . The vif ( mut4 ) 3 gene , which encoded Vif lacking aa 2–41 , was among the modified inserts tested that was genetically stable when inserted into position 3 of the VSV genome . Recombinant VSV-G6 vectors were rescued from DNA using a helper-virus free method described earlier [78] . Vaccine vectors also were amplified and purified as described earlier [78] . Although rVSV-Vif ( mut4 ) 3-Gnj6 was genetically stable , infected Vero cells ( Meridian Life Science ) produced relatively low levels of Vif protein . This caveat prompted us to generate an additional vif-expressing rVSV vector using a different vector design . The SIVmac239 vif gene was amplified by PCR for insertion in the 5th genomic position between the XhoI and NheI sites in the VSV Indiana genomic clone described by Schnell and collaborators [80] . The vif sequence was also modified to include a C-terminal V5 epitope tag for detection by Western blotting . Molecular cloning and rescuing of this rVSV-Vif vector was performed as described before using 293T cell monolayers ( ATCC ) and recombinant vaccinia virus expressing T7 RNA polymerase [81] . Clonal isolates were prepared by plaque purification using baby hamster kidney ( BHK ) cells ( generously provided by M . A . Whitt ) . Vif expression was confirmed by infecting 293T cells and analyzing infected cell lysates by Western blotting . A rVSV-Vif plaque isolate was then amplified by infecting 293T cells and subsequently harvesting virus from medium supernatant . This virus-containing medium was passed through a 0 . 2-μM vacuum filter and then purified by centrifugation ( 27 , 000 RPM/90 min/4°C ) though a low-density cushion of 10% Optiprep ( Sigma ) . The virus pellet was homogenized in PBS and its titer was determined by plaque assay using BHK cells . While generating rVSV-Vif , we did not observe the genetic instability described above for the different VSV-Vif-Gnj6 vectors . We suspect this may be due to full-length Vif expression having an inhibitory effect on VSV replication specifically in Vero cells , which are derived from African Green monkey kidneys [82] . This explanation is based on several observations: 1 ) rVSV-Vif was generated using human 293T cells and BHK cells and not Vero cells; Vif expression by rVSV-Vif was considerably higher in infected BHK or 293T cells compared to Vero cells; and 3 ) rVSV-Vif-Gnj6 vectors were developed by a process based entirely on Vero cells . The appropriate rVSV vectors for each group were simultaneously delivered via the IV and IR routes . The control animals in Group 5 were vaccinated with “empty” rVSV-Gnj6 . A total dose of 108 PFU of each vector was administered per animal; half was delivered intravenously while the other half was given intrarectally . For both routes , the rVSV vector mixture was administered in 1 . 0 mL of PBS . All animals in Groups 1–4 were vaccinated with the two vif-expressing rVSV vectors described above , rVSV-Vif ( mut4 ) 3-Gnj6 and rVSV-Vif . The rRRV boost occurred at wk 69 following the first EP rDNA immunization . The generation of the rRRV constructs employed here has been described elsewhere [33] . Five rRRV vectors expressing SIVmac239 inserts were used in this experiment . 1 ) rRRV-SIV-Gag encoded a codon-optimized full-length gag gene . 2 ) rRRV-SIV-wdo-gp160 encoded an env gene whose codon usage matched that of the RRV gH gene . 3 ) rRRV-SIV-RTN3 encoded a fusion of the rev , tat , and nef genes . 4 ) rRRV-SIV-nef-v5 and 5 ) rRRV-SIV-vif-v5 each encoded the nef or vif genes , respectively . Similar to the rVSV vaccinations , the appropriate rRRV vectors for each group were simultaneously delivered via the IV and IR routes . The vaccine formulation for each route consisted of 1 . 0 mL of PBS containing 7 . 1×107 genome copies of each rRRV vector . All animals in Groups 1–4 were vaccinated with rRRV-SIV-RTN3 , rRRV-SIV-nef-v5 , and rRRV-SIV-vif-v5 . The control animals in Group 5 were vaccinated with rRRV expressing enhanced fluorescent green protein . The challenge stock utilized here was produced by the Virology Services Unit of the WNPRC using SIVmac239 hemi-genome plasmids obtained from the NIH AIDS Research and Reference Reagent Program . These plasmids were transfected into 293T cells and the supernatant was propagated on mitogen-activated PBMC from SIV naïve rhesus macaques for several days . The titer of this stock was 90 , 000 50% tissue culture infective doses ( TCID50 ) /mL . Animals in this study were subjected to the IR challenge regimen described in Fig 6 . The dose of each exposure was 200 TCID50 , which corresponded to 4 . 8×105 viral RNA ( vRNA ) copies . Plasma VLs were assessed seven and ten days after each exposure . Once an animal had a positive VL , it was no longer challenged . VLs were measured using 0 . 5 mL of EDTA-anticoagulated rhesus macaque plasma based on a modification of a previously published [83] . Total RNA was extracted from plasma samples using QIAgen DSP virus/pathogen Midi kits , on a QIASymphonyXP laboratory automation instrument platform . Six replicate two step RT-PCR reactions were performed per sample using a random primed reverse transcription reaction , followed by 45 cycles of PCR using the following primers and probe: forward primer: SGAG21: 5’-GTCTGCGTCAT ( dP ) TGGTGCATTC-3’; reverse primer SGAG22: 5’-CACTAG ( dK ) TGTCTCTGCACTAT ( dP ) TGTTTTG-3’; probe: PSGAG23: 5’-FAM-CTTC ( dP ) TCAGT ( dK ) TGTTTCACTTTCTCTTCTGCG-BHQ1-3’ . The limit of reliable quantitation on an input volume of 0 . 5 mL of plasma was 15 vRNA copies/mL . Rhesus macaque peripheral blood mononuclear cells ( PBMC ) were isolated from EDTA blood as described previously [72] . These cells were stained with fluorochrome-labeled MHC-I tetramers obtained from either the NIH Tetramer Core Facility or MBL International Inc . according to a recently published protocol [84] . Up to 800 , 000 PBMC were incubated with titrated amounts of each tetramer at room temperature ( RT ) for 45 min and then stained with fluorochrome-labeled monoclonal antibodies ( mAbs ) directed against the surface molecules CD3 ( clone SP34-2 ) , CD8α ( clone RPA-T8 ) , CD28 ( clone 28 . 2 ) , CCR7 ( clone 150503 ) , CD14 ( clone M5E2 ) , CD16 ( clone 3G8 ) , and CD20 ( clone 2H7 ) . Amine-reactive dye ( ARD; Live/DEAD Fixable Aqua Dead Cell Stain; Life Technologies ) was also added to this mAb cocktail . After a 25-min incubation at RT , the cells were washed with Wash Buffer ( Dulbecco’s PBS with 0 . 1% bovine serum albumin and 0 . 45 g/L NaN3 ) and then fixed with PBS containing 2% of paraformaldehyde . The configuration of the Special Order Product BD LSR II cytometer used to acquire the samples and the gating strategy employed to analyze the data have been detailed elsewhere [77] . In sum , we used FlowJo 9 . 6 to determine the percentages of live CD14−CD16−CD20−CD3+CD8+tetramer+ lymphocytes shown in Fig 2 and to delineate memory subsets within tetramer+ populations ( Fig 4 ) . PBMC were stimulated with the appropriate pools of SIV peptides in R10 medium ( RPMI 1640 medium supplemented with GlutaMax [Life Technologies] , 10% FBS [VWR] , and 1% antibiotic/antimycotic [VWR] ) containing co-stimulatory mAbs against CD28 and CD49d for 9 h at 37°C in a 5 . 0% CO2 incubator . A phycoerythrin-conjugated mAb specific for CD107a was also included in the assay . To inhibit protein transport , Brefeldin A ( Biolegend , Inc . ) and GolgiStop ( BD Biosciences ) were added to all tubes 1 h into the incubation period . The antigen stimuli consisted of six pools of peptides ( 15mers overlapping by 11 aa ) spanning ( i ) the entire Gag polyprotein ( aa 1–510 ) , ( ii ) Env gp120 ( aa 1–531 ) , ( iii ) Env gp41 ( aa 516–879 ) , ( iv ) the entire Vif protein ( aa 1–214 ) , ( v ) the entire Nef protein ( aa 1–263 ) , and ( vi ) both the Rev ( aa 1–107 ) and Tat ( aa 1–130 ) proteins . The final assay concentration of each 15mer was 1 . 0 μM . We employed the same steps outlined above to stain molecules on the surface of cells and to fix them with 2% of paraformaldehyde . In addition to the same mAbs against CD14 , CD16 , and CD20 and the ARD reagent described above , the surface staining master mix also included mAbs against CD4 ( clone OKT4; Biolegend , Inc . ) and CD8 ( clone RPA-T8; Biolegend , Inc . ) . Cells were permeabilized by resuspending them in “Perm Buffer” ( 1× BD FACS lysing solution 2 [Beckton Dickinson] and 0 . 05% Tween 20 [Sigma-Aldrich] ) for 10 min and subsequently washed with Wash Buffer . Cells were then incubated with mAbs against CD3 ( clone SP34-2; BD Biosciences ) , IFN-γ ( clone 4S . B3; Biolegend , Inc . ) , TNF-α ( clone Mab11; BD Biosciences ) , and CD69 ( clone FN50; Biolegend , Inc . ) for 1 h in the dark at RT . After this incubation was completed , the cells were washed and subsequently stored at 4°C until acquisition . We analyzed the data by gating first on live CD14–CD16–CD20–CD3+ lymphocytes and then on cells expressing either CD4 or CD8 but not both markers . We then conducted functional analyses within these two compartments . Cells were considered positive for IFN-γ , TNF-α , or CD107a only if they co-expressed these molecules with CD69 , a marker of recent activation . Once the appropriate gates were created , we employed the Boolean gate platform to generate a full array of possible combinations , equating to 8 response patterns when testing three functions ( 23 = 8 ) . Leukocyte activation cocktail ( LAC; BD Pharmingen ) -stimulated cells stained with fluorochrome-labeled mAbs of the same isotypes as those against IFN-γ , TNF-α , and CD107a guided the identification of positive populations . We used two criteria to determine if responses were positive . First , the frequency of events in each Boolean gate had to be at least 2-fold higher than their corresponding values in background-subtracted negative-control tests . Second , the Boolean gates for each response had to contain ≥10 events . The magnitude of responding CD4+ or CD8+ T-cells shown in Figs 3 and 9 was calculated by adding the frequencies of positive responses producing any combination of IFN-γ , TNF-α , and CD107a . Background subtraction and calculation of the frequencies of responding cells were performed with Microsoft Excel . Vaccine induced anti-Env responses were measured by ELISA . To begin , the ELISA plate was coated with 100 μL of purified SIVmac239 gp140 protein ( Immune Technology Corp . #IT-001-140p ) at a concentration of 0 . 5 μg/mL and incubated overnight at RT . On the following day , the plate was washed with 1× PBS-Tween20 and wells were blocked with 300 μL of 5% powdered milk in PBS for 1 hr at 37°C . Subsequently , the plate was washed and 100 μL of diluted plasma samples were added to the corresponding wells . After a 1-hr incubation at RT , the plate was washed and 100 μL of a 1:2 , 000 dilution of Goat Anti-Monkey IgG-HRP antibody ( Santa Cruz Biotechnology , sc-2458 ) were added to all wells for 1 hr at 37°C . Finally , the plate was washed before being developed with 100 μL of 3 , 3' , 5 , 5'-Tetramethylbenzidine ( EMD Millipore , 613544-100ML ) . After a short incubation , the reaction was stopped with TMB Stop Solution ( Southern Biotech , 0412–01 ) and the plate was read ( Biotek Synergy 2 ) at 450 nm . The endpoint antibody titers of vaccine-induced anti-Env antibody responses were measured in serum collected at the time of SIV challenge . These titers were determined as the greatest dilution at which the absorbance in experimental wells was at least two-fold higher than that measured in pooled pre-vaccination serum from all animals in the experiment . The SIVmac239 and SHIVAD8-EO stocks used in ADCC assays were produced by transfection of infectious molecular clones into HEK293T cells using GenJet transfection reagent ( SignaGen ) . Virus-containing supernatants were collected 48 and 72 hours ( h ) post-transfection and stored at -80°C . The SHIVAD8-EO clone was provided by Dr . Malcom Martin ( NIAID , Bethesda , MD ) . After heat inactivation for 30 minutes at 56°C , rhesus macaque plasma samples were tested for non-specific ADCC due to the presence of antibodies to human cellular antigens by co-incubating uninfected CEM . NKR-CCR5-sLTR-Luc target cells with an NK cell line ( KHYG-1 cells ) expressing rhesus macaque CD16 at a 10:1 effector-to-target ratio in the presence of serial dilutions of plasma [85] . Non-specific lysis was detected as a reduction in background luciferase activity ( % RLU ) for target cells incubated with NK cells in the presence compared to the absence of plasma . Plasma samples that directed ADCC against uninfected cells were depleted of anti-human antibodies by repeated cycles of incubation with CEM . NKR-CCR5-sLTR-Luc cells , followed by centrifugation and plasma transfer , until ADCC responses to uninfected cells were no longer detectable . To measure ADCC activity in plasma of vaccinated animals , CEM . NKR-CCR5-sLTR-Luc target cells were infected with SIVmac239 or SHIVAD8-EO ( internal negative control ) by spinoculation for 3 h at 1200 × g in the presence of 40 μg/ml polybrene ( EMD Millipore ) . Four days post-infection , target cells were incubated with the NK cell line KHYG-1 at a 10:1 effector-to-target ratio in the presence of serial plasma dilutions . Luciferase activity was measured after 8 h using the britelite plus luciferase assay system ( PerkinElmer ) . Triplicate wells were tested at each plasma dilution , and wells containing effector cells incubated with uninfected or infected target cells in the absence of plasma were used to determine background and maximal luciferase activity , respectively . ADCC responses were calculated from the dose-dependent loss of luciferase activity in the presence of plasma relative to background and maximal luciferase control wells . Replication incompetent SIVmac239 pseudovirus was produced by co-transfecting env plasmids with an env-deficient backbone plasmid ( pSG3Δenv ) in HEK293T cells in a 1:2 ratio , using the X-tremeGENE 9 transfection reagent ( Roche ) . Pseudovirus was harvested after 72 h by sterile-filtration ( 0 . 22 μm ) of cell culture supernatants , and neutralization was tested by incubating pseudovirus and serum for 1 h at 37°C before transferring them onto TZM-bl cells as previously described [86] . Neutralization was measured in duplicate wells within each experiment . Neutralization was tested starting at 1:10 serum dilutions followed by nine serial 3-fold dilutions to ensure highest sensitivity and range of detection . Neutralization IC50 titers were calculated using the ‘One site—Fit logIC50’ regression in Graphpad Prism v7 . 0 . We could not detect vaccine-induced nAb titers against SIVmac239 pseudovirus in any of the monkeys in Groups 1 and 2 at the time of the first SIV challenge . The non-parametric Kruskal-Wallis test was used to compare the total magnitude of vaccine-induced SIV-specific T-cell responses among the four vaccinated groups . In instances of significant Kruskal-Wallis tests , pairwise Mann-Whitney U tests were used to identify the difference between any two groups . The Kaplan-Meier method and log-rank test were used to determine if any of the four vaccine regimens employed here affected acquisition of SIV infection . For this analysis , the time-to-productive infection was analyzed using the Kaplan-Meier method and the differences between each of Groups 1–4 and the control Group 5 were evaluated using log-rank tests . The Mann-Whitney U test was also used to determine the efficacy of each vaccine regimen in reducing viral replication . Peak and setpoint viral loads were compared between each of Groups 1–4 and the control Group 5 . Setpoint VL were calculated as the geometric mean of VLs measured within wks 8–20 PI . Lastly , the Spearman rank correlation was used to indicate immune correlates of protection .
|
There is still some uncertainty as to which HIV-1 proteins should be targeted by vaccine-induced immune responses . Indeed , studies of primary HIV-1 and SIV infections have reported that T-cell responses against different viral proteins can influence viral replication levels . To understand which antigens elicit the antiviral responses best able to control viral replication , we vaccinated rhesus macaques with different combinations of SIV antigens and then challenged them intrarectally with a pathogenic SIV clone using a regimen intended to mimic physiologically relevant human exposures to HIV-1 . Vaccination with Env , Gag , Vif , Rev , Tat , and Nef did not prevent infection but resulted in substantial control of viremia in 5/8 infected vaccinees . Importantly , vaccine-induced immune responses against Env and Gag were required for this outcome . Curiously , macaques vaccinated with Rev , Tat , Nef , and Vif acquired infection at a slower rate than did the control group , although this difference was not statistically significant . Together , these results suggest that expanding the number of vaccine-encoded antigens beyond Env and Gag might improve control of viral replication .
|
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2017
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Vaccine-induced immune responses against both Gag and Env improve control of simian immunodeficiency virus replication in rectally challenged rhesus macaques
|
Convergent adaptation occurs at the genome scale when independently evolving lineages use the same genes to respond to similar selection pressures . These patterns of genetic repeatability provide insights into the factors that facilitate or constrain the diversity of genetic responses that contribute to adaptive evolution . A first step in studying such factors is to quantify the observed amount of repeatability relative to expectations under a null hypothesis . Here , we formulate a novel index to quantify the constraints driving the observed amount of repeated adaptation in pairwise contrasts based on the hypergeometric distribution , and then generalize this for simultaneous analysis of multiple lineages . This index is explicitly based on the probability of observing a given amount of repeatability by chance under a given null hypothesis and is readily compared among different species and types of trait . We also formulate an index to quantify the effective proportion of genes in the genome that have the potential to contribute to adaptation . As an example of how these indices can be used to draw inferences , we assess the amount of repeatability observed in existing datasets on adaptation to stress in yeast and climate in conifers . This approach provides a method to test a wide range of hypotheses about how different kinds of factors can facilitate or constrain the diversity of genetic responses observed during adaptive evolution .
If different species encounter the same selection pressure , will adaptive responses occur via homologous genes or follow distinct genetic routes to the same phenotype ? What factors limit the diversity of viable genetic routes to adaptation and how does variation translate into evolution ? Empirical studies have identified different amounts of convergent adaptation at the genome scale across a range of species , traits , timescales , and levels of developmental-genetic hierarchy [1–3] . When evolution uses the same genes repeatedly to generate a given trait value , is this because of constraints acting on the genetic and developmental pathways limiting the production of variation ( i . e . , there is only a limited number of ways to generate a given trait value ) , or because of fitness constraints acting on genotypes that yield the same trait value ( i . e . , only some genotypes are selectively optimal ) ? Note that “constraint” in the evolutionary literature is commonly invoked to refer to factors that limit an adaptive phenotypic response in general ( e . g . , [4 , 5] ) . Here , we use it to refer to the factors that limit the diversity of genes used in independent bouts of adaptation and use the term “diversity constraint” hereafter for clarity . As a case study to examine the differing types of diversity constraint , Mc1r provides perhaps the most well-known example of convergent local adaptation at the gene scale , and has been implicated in driving colour pattern variation in mice , lizards , mammoths , fish , and a range of other organisms [6–10] . Extensive studies in mice have revealed that over 50 genes can be mutated to give rise to variation in colour pattern [11] , yet Mc1r consistently tends be one of the main contributors to locally adapted colour polymorphisms . Mc1r has minimal pleiotropic side effects [8 , 11] and it can mutate to a similar trait value through numerous different changes in its protein sequence [10 , 11] and therefore may have a higher rate of mutation to beneficial alleles than other genes . As such , it seems to be driven by a combination of both types of constraint: more ways to mutate via Mc1r implies that developmental-genetic constraints limit the contribution of other genes , while limited pleiotropy in Mc1r implies that fitness costs constrain which genes can yield mutations that provide a viable route to adaptation . Are the diversity constraints acting on melanism representative of the kinds of constraints that shape patterns of genome-scale convergence and non-convergence across the tree of life ? To answer this question , it is necessary to quantify the extent of genome-scale convergence in a wide variety of organisms and traits and ascertain what kind of diversity constraints are operating , which requires the development of an appropriate statistical framework . To this end , it is helpful to frame the above questions based on the flexibility of the mapping from genotype to trait to fitness: does repeatability occur because of low redundancy in the mapping of genotype to trait ( hereafter low GT-redundancy [4]: only a few ways to make the same trait value; Fig 1A ) , or because of low redundancy in the mapping of genotype to fitness ? ( hereafter low GF-redundancy: only a subset of the genotypes yielding the same trait value are optimal; Fig 1B ) . GT-redundancy is determined by two factors: 1 ) the difference between the number of genes that need to mutate to yield a given trait value and the number of genes that could mutate to give rise to variation in the trait , and 2 ) the extent to which different genes have interchangeable vs . uniquely important effects on the phenotype . High GT-redundancy means that many different combinations of alleles can yield the same trait value , so if all else is equal , then independent bouts of adaptation are likely to occur via different sets of mutations and repeatability will be low [12 , 13] . The standard quantitative genetic model implicitly assumes complete GT-redundancy with fully interchangeable allelic effects , while the recently proposed omnigenic model assumes high but incomplete redundancy , with “core” vs . “peripheral” genes having different potential to affect variation [14] . GF-redundancy is determined by differences in fitness among genotypes that produce the same trait value and can increase the diversity constraints driving repeatability above the level incurred by GT-redundancy . Such differences in fitness can occur when mutations cause correlated effects on other traits that also affect fitness , such that not all mutations that are equally suitable for adaptation ( i . e . , pleiotropy ) , or when interactions among particular mutations have negative fitness effects , such that only particular combinations of mutations tend to contribute to adaptation ( i . e . , epistasis ) . It is also possible for effects on fitness to arise independent of a phenotypic effect , because architectures with different allele effect sizes and linkage relationships can have different fitness depending on the interaction between migration , selection , and drift . For example , if a given phenotype is coded by many small unlinked alleles , this architecture would be less fit than a similar phenotype coded by a few large or tightly linked alleles , in the context of migration-selection balance [15] or negative frequency dependence [16 , 17] . Similarly , the increased drift that occurs in small populations may prevent alleles of small effect from responding to natural selection [18 , 19] , resulting in such genotypes being effectively neutral and therefore lower in realized fitness than those made up of large-effect alleles . For example , polygenic models of directional selection ( e . g . , [20] ) assume no GT- and GF-redundancy , while traditional quantitative genetic models of Gaussian stabilizing selection assume high GT- and GF-redundancy ( e . g . , [21] ) . In addition to GT- and GF-redundancy , other factors also impact signatures of convergence , such as differences among genes in recombination rate or propensity to retain standing variation . There has been considerable discussion in the literature about the effects of these and other factors on convergence [3 , 23–30] , and various indices have been previously used to quantify repeatability in empirical contexts ( e . g . Jaccard index , Proportional Similarity; [1 , 2] ) . These existing indices provide a useful description of how often the same gene is used in adaptation , but as we will show below , they are not well-suited for testing of hypotheses to discriminate between these different kinds of constraint . They do not incorporate information about the genes that could contribute to adaptation but don’t , which is necessary to evaluate what kinds of diversity constraints are operating , and they are not explicitly tied to the probability of repeatability occurring under a null model . Here , we develop novel statistical approaches for quantifying the diversity constraints that drive repeatability in genomic data from studies of local adaptation and experimental evolution . To study these constraints , we formulate an explicit probability-based representation of the deviation of observed repeatability from expectations under different null hypotheses . This approach can be used after standard tests have been applied to identify the putative genes driving adaptation and uses as input either binary categorization of genes as “adapted” or “non-adapted” or any continuous index representing the relative amount of evidence for a given gene being involved in adaptation ( e . g . FST , p-values , Bayes factors ) . We begin by formulating an analytical model for a contrast of two lineages with binary data , and then generalize this model for contrasts of multiple lineages using either binary or continuous data . We also propose a novel index estimating the proportion of genes in the genome that can potentially give rise to adaptation . In all cases , these models can be used to successively test null hypotheses that incorporate different amounts of information about the constraints that could shape repeatability . The simplest null hypothesis is that there are no constraints and all genes have equal probability of contributing to adaptation . If more repeatability is observed than expected under this null model , then two inferences can be made: natural selection is driving patterns of convergence ( and that observed signatures are not all false positives ) , and some diversity constraints are operating to increase the repeatability of adaptation . We then consider how other null hypotheses can be formulated to represent the various kinds of constraints discussed above . We focus mainly on the effect of low GT-redundancy , where the number of genes that could potentially contribute to adaptation is much smaller than the total number of genes in the genome , but also discuss how constraints arising from GF-redundancy , standing variation , or mutation rate could be modeled . Because this method quantifies repeatability in terms of probability-scaled deviations from expectations , it can be applied across any trait or species of interest , allowing contrasts to be made on the same scale of measurement .
Suppose there are two lineages , x and y , that have recently undergone adaptation to a given selection pressure , resulting in convergent evolution of the same trait value within each lineage . This adaptation could be global , with new mutations fixed within lineages ( e . g . , in experimental evolution studies with multiple replicate populations ) , or local , with mutations contributing to divergence among populations within each lineage ( e . g . , in observational studies of natural adaptation to environmental gradients ) . In either case , we assume that adaptation can be reduced to a binary categorization of genes as “adapted” or “non-adapted” to represent which genes contribute to fitness differences ( either relative to an ancestor or a differently-adapted population ) . We use the following notation to represent different properties of the genomic basis of trait variation: the number of loci in the genome of each species is nx , and ny , with the number of orthologous loci shared by both species being ns; the adaptive trait is controlled by gx and gy loci in each species , with gs shared loci ( i . e . the loci in which mutations will give rise to phenotypic variation in the trait , hereafter the “mutational target” ) ; of the g loci that give rise to variation , only a subset have the potential to contribute to adaptation due to the combined effect of all constraints , represented by gax and gay , with gas shared loci ( the “effective adaptive target” ) ; in a given bout of adaptation , the number of loci that contribute to adaptation in each lineage is ax and ay , with as orthologous loci contributing in both lineages . For simplicity , we assume that there is complete overlap in the genomes ( ns = nx = ny ) , mutational targets ( gs = gx = gy ) , and loci potentially contributing to adaptation ( gas = gax = gay ) in both species ( see supplementary materials and S1 Fig for set notation ) . These assumptions are most appropriate for lineages that are relatively recently diverged , where most orthologous genes are retained at the same copy number and the developmental-genetic program is relatively conserved , so that the same genes potentially give rise to variation in both lineages . Lineages separated by greater amounts of time would be expected to have reduced ns due to gene deletion , duplication , and pseudogenization in either lineage , and reduced gs and gas due to evolution and divergence of the developmental-genetic program , through sub- and neo-functionalization , and divergence in regulatory networks . Under the assumption that all gas genes have equal probability of contributing to adaptation ( i . e . , no diversity constraints are operating ) , the amount of overlap in the complement of genes that are adapted in both lineages ( as ) is described by a hypergeometric distribution where the expected amount of overlap is ās = axay/gas ( e . g . [31] ) . In practice , we typically have little prior knowledge about which genes have the potential to contribute to either adaptation ( gas ) or standing variation in the trait ( gs ) , but we can draw inferences about how these parameters constrain the diversity of adaptive responses by testing hypotheses and comparing the observed amount of overlap ( as ) to the amount expected under a given null hypothesis ( ās ) . To test different hypotheses about how diversity constraints give rise to repeated adaptation , we represent the total number of genes included in the test set as g0 . The simplest null hypothesis is that there are no diversity constraints and all genes potentially give rise to variation and contribute to adaptation ( g0 = gas = gs = ns ) , so by rejecting this null , we can infer that gas < ns , and calculate an effect size that represents the magnitude by which all types of constraints contribute to repeatability ( see Eq 1 , below; note that it is also possible that the null hypothesis could be falsified in the opposite direction , with less overlap in the loci contributing than expected under the null , which might occur if evolution had occurred towards a different optimum in each lineage ) . Without independent lines of evidence about which genes potentially contribute to variation in the trait ( gs ) , it is not possible to evaluate the relative importance of GT- vs . GF-redundancy using the framework here . In model systems where independent information is available for the magnitude of gs ( based on mutation accumulation or GWAS; see Discussion ) , then a more refined null hypothesis can be tested , where g0 = gs , allowing some inferences to be made about the relative importance of GT- and GF-redundancy ( Table 1 ) . By rejecting this null , we can infer that gas < gs , which could occur due to low GF-redundancy or differences among genes in mutation rate or standing variation . Alternatively , if we fail to reject this null hypothesis , then it suggests that gs ≅ gas , which would imply that GF-redundancy doesn’t make any additional contribution to repeatability beyond the contribution of GT-redundancy . We can also reverse the direction of inquiry and estimate gas directly from the data by calculating ga^s=axay/as , such that an index representing the effective proportion of the genome that can potentially contribute to adaptation can be calculated as P^a , hyper=axay/ ( asns ) . For any value of g0 , an effect size representing the excess in overlap due to convergence relative to the null hypothesis can be expressed by standardizing the observed overlap by subtracting the mean ( ās = axay/g0 ) and dividing by the standard deviation of the hypergeometric distribution: Chyper= ( as− ( axayg0 ) ) / ( axay ) ( g0−ax ) ( g0−ay ) / ( g02 ( g0−1 ) ) . ( 1 ) This index provides a quantitative representation of how much more overlap occurs than expected under the null hypothesis , scaled according to how much a given bout of evolution would deviate from this expectation if the null hypothesis were true . Similarly , the exact probability of observing as or more shared loci contributing to adaptation can also be calculated using the hypergeometric probability ( see Supplementary Information for sample R-script ) , which provides a p-value . While pairwise contrasts are most straightforward statistically , they have considerably lower power than comparisons among multiple lineages . If one gene ( such as Mc1r ) tends to drive adaptation repeatedly in a large number of lineages , this may go undetected in an approach using multiple pairwise comparisons but would be readily detected in a simultaneous comparison of multiple lineages . Unfortunately , while the hypergeometric distribution provides an exact analytical prediction for the amount of overlap in a pairwise comparison , which can be used to calculate a p-value and the probability-based effect size ( Chyper ) , it cannot be easily generalized to simultaneously analyze multiple lineages . While it is possible to conduct pairwise analysis and average the results across multiple comparisons , p-values from this approach might fail to detect cases where a single gene contributes repeatedly to adaptation in more than two lineages , as information does not transfer among the pairwise comparisons . We now develop an alternate , approximate approach to assess repeatability in multiple lineages by calculating Pearson’s χ2 goodness of fit statistic and comparing this to a null distribution of χ2 statistics simulated under the null hypothesis to calculate a p-value as the proportion of replicates in the null that exceed the observed test statistic . The p-value obtained by this approach represents the probability of observing a test statistic as extreme or more extreme under the null hypothesis , considering all lineages simultaneously . While the p-value is calculated from simultaneous analysis of all lineages , the effect size is instead calculated as an average across all pairwise comparisons among the k replicate lineages , because this represents the increase in repeatability relative to expectations under the null for a given bout of adaptation in any single lineage . This difference is important because the effect size should not depend on sampling effort in terms of the number of lineages , while the p-value should reflect the statistical power gained from multiple lineages . Consider the case where g0 genes can potentially contribute to adaptation in the given trait and each lineage has some complement of genes that have mutated to drive adaptation , with αi , j representing the binary score for gene i in lineage j ( 1 = adapted , 0 = non-adapted ) . The summation for gene i across all lineages provides the observed counts ( oi = Σjαi , j ) while the expected counts ( ei ) can be set based on the null hypothesis being tested . Under null hypotheses where all genes in g0 have equal probability of contributing to adaptation , the expected counts are equal to the mean of the observed counts ( e = Σioi/g0 ) , and Pearson’s χ2 statistic can be calculated by the usual approach: χ2 = Σ ( o − e ) 2/e . Under ideal conditions , Pearson’s χ2 would approximate the analytical χ2 distribution with its mean and standard deviation equal to the degrees of freedom ( df ) and 2df , respectively . While this could be used to make an analytical hypothesis test ( as above ) , in practice there will often be large deviations between Pearson’s χ2 and the analytical distribution , due to violation of the assumptions when expected counts are low ( See Supplementary Materials , S2 Fig ) . Instead , we simulate a null distribution of χsim2 values under the null hypothesis by using permutation within each lineage and recalculating χsim2 for each replicate . The p-value is then equal to the proportion of the χsim2 values that exceed the observed χ2 ( using all lineages simultaneously ) , while the effect size is calculated as the mean C-score across all pairwise contrasts ( simulating χsim2 for each pairwise contrast ) : Cchisq=χ2−mean ( χsim2 ) sd ( χsim2 ) . ( 2 ) The magnitude of Cchisq therefore represents deviation between the observed amount of repeatability and that expected under the null hypothesis , which will vary as a function of the diversity constraints affecting the trait evolution , but not the number of lineages being compared . While Cchisq relies upon simulation of a null distribution , it can be calculated relatively quickly . Importantly , the magnitude of Cchisq varies linearly with Chyper ( Fig 2A & 2B ) , showing that it represents the extent of diversity constraints in the same way as the analytically precise Chyper . While this approach provides a more accurate p-value for comparisons of multiple lineages , there is no particular reason to use Cchisq rather than Chyper for binary input data , as both effect sizes are calculated on a pairwise basis . The main reason that we develop this approach is to extend it to continuously distributed data , which can allow greater sensitivity and avoid arbitrary choices necessary to categorize the commonly used indices of local adaptation ( e . g . FST or p-values ) into “adapted” or “non-adapted” . In many empirical contexts , genome scans for selection yield continuously distributed scores representing the strength of evidence for each locus contributing to adaptation ( e . g . , FST , p-values , Bayes factors ) . Using the same notation as above , but with αi , j representing the continuous score for the ith gene in the jth lineage , the total score for each gene can be calculated as a sum across lineages , αi¯=∑jkαi , j , while the mean score over all genes and lineages is α¯¯=∑ig0α¯i/g0 . A statistic analogous to the above χ2 can then be calculated as χ2=∑ ( α¯i−α¯¯ ) 2/α¯¯ , and the same approach for calculating the null distribution of this statistic can then be used to calculate Cchisq according to Eq 2 . With continuous data , there are additional complexities that arise depending on the distribution of the particular dataset being used and how its magnitude represents evidence for a gene’s involvement adaptation . One approach , which we used in all examples here , is to transform data so that values scale positively and approximately linearly with the weight of evidence for adaptation , by standardizing data within each lineage by subtracting their observed within-lineage minimum and dividing by their observed within-lineage maximum , such that the values within each lineage are bounded from 0 to 1 . This reduces differences among lineages in the absolute magnitude of indices representing adaptation , which can be desirable when they vary across many orders of magnitude ( e . g . p-values from GWAS of 10−10 and 10−20 both provide strong evidence of adaptation ) . However , if some lineages actually have stronger signatures of adaptation at more loci , then this kind of standardization should not be used , as it would obscure these true differences among lineages . In this case , it would be preferable to use the same standardization across all lineages by subtracting the minimum and dividing by the maximum values observed across all lineages . While Pearson’s χ2 statistic was designed for discrete data , the above approach using continuous data represents the variability among lineages in the same way , as a variance among genes in the sum of their scores representing putative adaptation . The Cchisq statistic on continuous data behaves similarly to the Chyper statistic across wide ranges of parameter space , as both are formulated in terms of deviations from the null distribution ( see below ) . While the number of genes that potentially contribute to adaptation ( gas ) can be estimated using the hypergeometric equation , ga^s=axay/as , it is difficult to apply this to comparisons of multiple lineages , as some pairwise contrasts may have no overlap in the genes contributing to adaptation ( as = 0 ) , making the equation undefined . To estimate ga^s from all lineages simultaneously , we can instead formulate a likelihood-based approach where the probability that we observe locus i adapted in oi lineages is: ζi=Pa*Bin ( k , o¯ , oi ) + ( 1−Pa ) Bin ( k , 0 , oi ) , ( 3 ) where Bin ( n , y , x ) is the probability under the binomial distribution of getting x successes in n trials , each with probability y . As above , oi is the number of adapted genes in k lineages ( with oi = Σjαi , j ) , Pa is the proportion of g0 that can actually contribute to adaptation ( Pa = gas/ns ) , and ō is the probability of each gene contributing to adaptation ō = Σoi/ ( gas k ) . The estimated value of ga^s is then the value at which the log-likelihood function: L ( gas ) =∑logζi ( 4 ) is maximized . Once the maximum-likelihood value of ga^s is estimated , this can be expressed either as an absolute number representing the effective number of genes that can contribute to adaptation or as a proportion of the total number of shared genes in the genome: P^a , lik=ga^s/ns . This approach implicitly assumes that all genes that have the potential to contribute to adaptation ( gas ) have approximately equal probabilities of actually contributing to adaptation . In very extreme cases , such where one gene is very highly repeatable while other genes only contribute to adaptation in a single lineage , ga^s will tend to represent the contribution of the repeatable genes and discount the contribution of the idiosyncratic genes ( see Supplementary Materials ) . Multi-class models could be developed to estimate gas for different classes of genes in such scenarios by accounting for their different probabilities of contributing to adaptation ( See https://github . com/samyeaman/dgconstraint for scripts containing functions for the above calculations ) .
The Chyper , Cchisq , and P^a , lik estimators capture different aspects of the biology underlying convergence than other previously used estimators of repeatability . To estimate the repeatability of evolution , Conte et al . [1] used the additive and multiplicative Proportional Similarity ( PSadd and PSmult ) indices of [32] in a meta-analysis of QTL and candidate gene studies , while Bailey et al . [2] used the Jaccard Index to quantify patterns in bacterial evolution experiments . The PS indices are defined as PSadd = Σ min ( αix , αiy ) and PSmult=∑ ( αixαiy ) /∑ ( αix ) 2 ( αiy ) 2 , where αix and αiy are the relative contribution of gene i to adaptation in lineages x and y [33] , while the Jaccard index is defined as J = ( Ax ∩ Ay ) / ( Ax ∪ Ay ) , where Ax and Ay are the sets of adapted genes in each lineage [2] . Both of these indices are based on standardizing the number of overlapping adapted loci by the total number of adapted loci , and neither includes information about non-adapted genes that potentially could have contributed to adaptation . To illustrate the differences between these various indices of convergence , we generated four example datasets showing either randomly drawn complements of genes with adapted mutations ( Fig 3A ) or highly convergent datasets drawn from a smaller ( Fig 3B ) or larger ( Fig 3C & 3D ) pool of genes that potentially contribute to trait variation ( gs ) , with differing numbers of loci contributing to adaptation . Scenario C is the most constrained , as it exhibits the same amount of overlap as B , but this overlap is drawn from a larger pool of genes so it is less likely to occur by chance . While neither the Jaccard index nor the PS indices distinguish between the B , C , and D scenarios ( as the same proportions of genes are being used for adaptation , so repeatability is the same ) , both the Cchisq and Chyper indices show the highest scores for scenario C , because it has the smallest probability of occurring by chance if all genes had equal probabilities of contributing to adaptation . The P^a , lik index also identifies scenario C as most constrained in terms of the smallest proportion genes potentially contributing to adaptation . The P^a , lik index also shows that this proportion is equal for scenarios B & D , despite differences in the probability of the observed repeatabilities occurring by chance ( as per the C-scores ) . More generally , while P^a , lik tends to decrease with increasing C-score , these indices differ in magnitude ( Fig 2C & 2D ) , as they represent different aspects of diversity constraints . In summary , the Jaccard and PS indices quantify the proportion of genes used for adaptation that are used repeatedly , the C-score indices are inversely proportional to the probability of the observed repeatability occurring if there were no constraints , and P^a , lik represents the proportion of genes in the genome that are available for adaptation , given the existing diversity constraints ( also see S3 Fig for further comparisons ) . To further explore the effect of population genetic parameters on the behaviour of the above indices of repeatability and constraint , we used Nemo ( v2 . 3 . 45; [34] ) to simulate two scenarios of two-patches under migration-selection balance: ( i ) constant size of mutational target with variable proportions of small- and large-effect loci; and ( ii ) constant number of large-effect loci and variable number of small effect loci , resulting in a variable size of mutational target . For scenario ( i ) , simulations had n = gs = 100 loci , of which u loci had alleles of size +/- 0 . 1 , while ( 100 − u ) loci had alleles of size +/- 0 . 01 ( with subsequent mutations causing the allele sign to flip from positive to negative or the reverse ) . For scenario ( ii ) , simulations had 10 large-effect loci with alleles of size +/- 0 . 1 and v small-effect loci with alleles of size +/- 0 . 01 , resulting in a variable size of mutation target . In all simulations , migration rate was set to 0 . 005 and the strength of quadratic phenotypic selection was 0 . 5 , so that an individual perfectly adapted to one patch would suffer a fitness cost of 0 . 5 in the other patch ( patch optima were +/- 1; similar to [13] ) . Simulations were run for 50 , 000 generations and censused every 100 generations . For binary categorization of the input data , loci were considered to be “adapted” if FST > 0 . 1 for >80% of the last 25 census points ( these cut-offs are somewhat arbitrary , but qualitative patterns were comparable under different cut-offs ) ; for continuous input data , raw FST values were used . Results are averaged across 20 runs , each with 20 replicates , with Cchisq calculated across the 20 replicates within each run . These scenarios further illustrate the difference between the Jaccard and PSadd indices of repeatability and the C-score and P^a , lik indices of constraint . In both scenarios , the small effect loci do not tend to contribute much to adaptation because large effect loci are more strongly favoured under migration-selection balance [35] , which results in low GF-redundancy . In scenario ( i ) , all indices show qualitatively similar patterns , with decreasing repeatability occurring as a result of the decreasing constraints that occur as the number of large-effect loci increases , increasing the GT- and GF-redundancy ( Fig 4A ) . By contrast , in scenario ( ii ) , the Jaccard and PSadd indices indicate that roughly the same amount of repeatability is occurring regardless of the number of small effect loci and total size of mutational target ( Fig 4B ) . However , over this same range of parameter space , the C -score indices show that constraint increases as the total mutational target is increasing . This occurs because while a larger number of potential routes to an adaptive phenotype are available with increasing number of small effect loci , only the same small number of loci are actually being involved in adaptation ( i . e . the large effect loci ) , which is illustrated by the decrease in the P^a , lik index . While there are many potential genetic routes to adaptation that could involve these small effect loci ( high GT-redundancy ) , the large effect loci tend to be favoured and repeatedly involved in adaptation ( low GF-redundancy ) . Thus , when the size of the mutational target increases in scenario ( ii ) , the repeatability tends to stay about the same ( Jaccard and PSadd ) but the amount of constraint is higher ( C-scores ) , because a smaller proportion of the available routes to adaptation are being used ( P^a , lik ) . The continuous and binary Cchisq indices are broadly similar across these parameters because there is very little variation in FST among loci within the same size class ( see Supplementary Materials for additional simulations under varying allele effect sizes ) . The amount of constraint quantified by the C-score will depend upon the proportion of the mutational target ( gs ) that is sampled by the sequencing approach , which should be proportional to the sampling of the total number of genes in the genome ( ns ) . Some approaches , such as targeted sequence capture , will sample only a subset of the total number of genes in the genome , which will therefore cause a bias in the estimation of constraint due to incomplete sampling , even if the genes included are a random subset of gs . This can be most clearly seen in the calculation of Chyper , where multiplying all the variables in Eq 1 by a given factor will cause a change in the magnitude of the effect size . By contrast , the Jaccard and PS measures of repeatability are not affected by incomplete sampling . If binary input data are being used and the proportion of gs that has been sampled can be accurately estimated ( q ) , then the calculation of Chyper can be corrected by dividing all input variables by q prior to calculation , yielding a corrected score Chyper-adj . If continuously distributed input data are being used , then the dataset can be adjusted by adding g0 ( 1 − q ) new entries to the dataset by randomly sampling genes with replacement from the existing dataset , and then applying Eq 2 to this extended set . To explore the effect of incomplete sampling of the genome on the calculation of C-scores and the impact of these types of correction , we constructed a test dataset by concatenating 5 replicates from the simulations in Fig 4A with 10 large effect loci , yielding a dataset with 500 loci in total and a high amount of repeatability . We then sampled a proportion q of this total dataset to simulate incomplete representation of the genome and used the above approach calculate uncorrected and corrected C-scores . While incomplete sampling can cause considerable bias in C-scores , as long as q is not too small , these approaches yield relatively accurate corrections of these estimates ( Fig 5 ) . At very low values of q , the variance in estimation among replicate subsets increases as a result of sampling effects when only a small number of adapted loci are included , but on average the magnitude of the corrected C-score is independent of q . Experimental evolution studies provide a controlled framework to test theories on the genetic basis of adaptation under a diversity of scenarios . Gerstein et al . ( 2012 ) previously conducted an experiment to examine the diversity of first-step adaptive mutations that arose in different lines initiated with the same genotypes in response to the antifungal drug nystatin [36] and in response to copper [37] . The design allowed them to directly test how many different first-step solutions were accessible to evolution when the same genetic background adapted to the same environmental stressor . In the nystatin-evolved lines they identified 20 unique and independently evolved mutations in only four different genes that act in the nystatin biosynthesis pathway: 11 unique mutations in ERG3 , seven unique mutations in ERG6 , and one unique mutation in each of ERG5 and ERG7 [36] . The genotypic basis of copper adaptation was broader , and there were both genomic ( SNPs , small indels ) and karyotypic ( aneuploidy ) mutations identified . If we consider just the genomic mutations , mutations were found in 28 different genes , with multiple mutations identified in four genes ( 12 unique mutations in VTC4 , four unique mutations in PMA1 , and three unique mutations in MAM3 and VTC1 ) . If we assume that all genes in the genome could potentially contribute to adaptation ( i . e . g0 = 6604 ) , then Chyper-nystatin = 32 . 5 , while Chyper-copper = 12 . 3 , and p < 0 . 00001 in both cases . If we assume much lower GT-redundancy and that only the observed genes could possibly contribute to the trait ( i . e . g0-nystatin = 4 , g0-copper = 28 ) , we can test whether the mutations are still more clustered than expected within these sets . Using the methods outlined above , we find Chyper-nystatin = 0 . 35 , p = 0 . 002 , and Chyper-copper = 0 . 43 , p < 0 . 0001 , indicating that even under the severe developmental-genetic constraints to diversity represented by this model , these data are slightly more overlapping than expected at random , likely due low GF-redundancy and potentially gene-specific differences in mutation rate ( because these experiments were initiated using isogenic strains , standing variation was precluded ) . Experimental evolution studies lend themselves nicely to future hypothesis testing about the impact of constraint on the genetic basis of adaptation and provide us with hypotheses about differences between the genes that were and were not observed in the screen . For example , we parsed the Saccharomyces Genome Database ( http://www . yeastgenome . org ) for genes that have been annotated as “resistance to nystatin: increased” , where this phenotype is conferred by the null mutation . This should be a conservative dataset , as we also expect there could be mutations in additional genes that do not result in a loss-of-function phenotype that could also confer tolerance to nystatin ( although we expect that the mutations we recovered in ERG3 , ERG5 and ERG6 are all similar to loss of function mutations , ERG7 is inviable when null [36] ) . This identified an additional five genes ( KES1 , OSH2 , SLK19 , VHR2 , YEH2 ) . We can test whether the five genes without an observed mutation have a negative pleiotropic effect when null or are in areas of the genome with a lower mutation rate compared to the ERG genes ( particularly compared to ERG3 and ERG6 ) . Similar experiments could also be conducted with different Saccharomyces cerevisiae genetic backgrounds , with closely related species , or under slightly different environmental conditions ( e . g . , increased or decreased concentration of stress ) to directly examine how different aspects of the genomic and ecological environments influence the observed level of constraints acting on adaptation . Lodgepole pine and interior spruce both inhabit large ranges of western North America and display extensive local adaptation , with large differences in cold tolerance between northern and southern populations in each species . Recent work studied the strength of correlations between population allele frequencies and a number of environmental variables and phenotypes in each species [38] . Taking one representative environmental variable as an example , a total of 50 and 121 single-copy orthologs showed strong signatures of association to Mean Coldest Month Temperature ( MCMT ) in pine and spruce , respectively , with 5 of these genes overlapping ( based on binary categorization using the binomial cutoff “top candidate” method , as per [38] ) . This study included a total of 9891 one-to-one orthologs with sufficient data in both species ( i . e . at least 5 SNPs per gene ) , so observing 5 genes overlapping corresponds to Chyper = 5 . 6 and p = 0 . 00034 under the null hypothesis that all genes had equal potential to contribute to adaptation . Alternatively , it is also possible to estimate Cchisq on continuously distributed data by calculating top candidate scores for each gene using the binomial probability of seeing u outliers when there are v SNPs in a given gene , with an overall rate of w outliers per SNP ( as per [38] , this yields an index rather than an exact probability , due to linkage among SNPs ) . This approach is more sensitive to weak signatures of adaptation that occur below the binary categorization cutoff , yielding Cchisq = 5 . 1 and p < 0 . 00001 . Assuming that the 9891 studied genes represent a random sample from approximately 23 , 000 genes in the whole genome and ignoring divergence in gene content between species ( ns = nx = ny ) , the adjusted C-scores are Chyper-adj = 8 . 6 and Cchisq-adj = 7 . 8 ( with resampling of 50 replicates and 10 , 000 permutations per replicate ) , providing a very rough estimate of the total diversity constraints driving repeatability . As it is possible that some factors such as conservation of the genomic landscape of cold- and hot-spots of recombination could spuriously drive signatures of convergence ( see Discussion ) , it is possible to perform a basic control by comparing the above results for pine-MCMT vs . spruce-MCMT to the overlap between top candidates for different environments in each species , where convergence would not be expected . Examining the variable least strongly correlated to MCMT ( annual heat-moisture index; AHM ) , we find 23 top candidates in spruce with one overlap with pine-MCMT top candidates and 25 in pine with no overlaps with spruce-MCMT , which correspond to p = 0 . 11 and p = 1 , respectively . Thus , there was no significant increase in overlap among the top-candidates for different variables , where signatures of convergence are unexpected but could have been generated spuriously by some combination of demography and low recombination in some regions of the genome . However , as this is a negative control , the lack of a significant result does not prove that such effects are absent , so caution is necessary when drawing inferences from these data . These diversity constraints correspond to an effective adaptive target of gas = 1462 genes that could potentially contribute to adaptation in these species ( out of 9891 ) , which yields P^a , lik=0 . 15 . However , a large number of the 50 and 121 genes identified using their “top candidate test” were likely false positives , because there were no controls for population structure during the association test , as this was subsequently accounted for by the among-species comparison . Thus , if we assume a 50% false positive rate for ax and ay , then gas declines to 370 genes , with P^a , lik=0 . 037 . In their analysis , Yeaman et al . [38] used another more sensitive test ( null-W ) to identify loci with signatures of convergence that were not detected based on overlap in the top candidates lists , which suggests the true amount of repeatability may be higher than inferred here . This example illustrates how these kinds of statistics may be used to make inferences about constraints , but also highlights the sensitivity of the results to small changes in parameters .
Under the simplest null hypothesis that there are no diversity constraints , all genes can give rise to potentially adaptive variation in the trait ( g0 = gs = gas = ns ) . While simplistic , this approach provides an intuitive method to assess whether the amount of convergence observed is more than expected due to pure randomness . But what do we learn if we reject such a simple null hypothesis ? Two inferences can be drawn in this case: many of the genes flagged by our tests for selection are likely evolving by natural selection ( i . e . , they are not all false positives ) and some kind of constraint is involved in shaping this adaptation . The former inference means that analyzing comparative data for convergence can provide a powerful tool for identifying the genes involved in local adaptation , as this is often a significant methodological hurdle in evolutionary biology ( e . g . , [38] ) . The latter inference may seem a straw-man , as few molecular biologists would advocate a model where every gene can mutate to give rise to adaptively useful variation in a given trait . However , different forms of the “universal pleiotropy” model have been assumed in theoretical quantitative genetics [39] , and the recently proposed “omnigenic model” advocates extensive pleiotropy [14] . Regardless of the true number of genes involved , this null hypothesis provides a benchmark against which we can quantify how all factors constraining the diversity of forms combine to drive repeatability , which is useful for interpreting patterns of repeatability among species and traits . In order to make inferences about the potential importance of different kinds of diversity constraints driving repeatability , it is necessary to specify more realistic models for the evolution of local adaptation that incorporate different assumptions about size of the mutational target of the trait , extent of shared standing variation , differences in mutation rate among genes , distribution of mutation effect sizes , and species demography . The simplest modification to the above null model is to represent the extent of GT-redundancy by specifying the number of loci that potentially contribute to trait variation as a subset of the total number of loci in the genome ( g0 = gs < ns ) . In the context of the Chyper index ( Eq 1 ) , reducing g0 increases both the mean and standard deviation of the hypergeometric distribution and therefore decreases Chyper and the inferred level of residual ( unexplained ) constraints . If empirical estimates of gs result in Chyper ~ 0 , then it is reasonable to conclude that low GT-redundancy is mainly responsible for the observed amount of convergent adaptation . This would not discount the importance of natural selection overall , as selection on the phenotype is still responsible for adaptation but would suggest that gs individual loci are more or less interchangeable and GF-redundancy contributes no additional constraints above those imposed by GT-redundancy ( Table 1 ) . However , as we have few ( if any ) conclusive estimates of gs in highly polygenic traits [40 , 41] , the extent of constraint arising through low GT-redundancy will be difficult to assess without further directed study . Although they are by no means simple experiments to conduct , it should be possible to estimate gs from QTLs identified in multiple mutation accumulation experiments , as the number of loci detected across all experiments should asymptote towards gs , and rarefaction designs could be used to estimate gs based on the overlap between QTLs detected in two experiments ( although this would likely still be biased by failing to detect loci of small effect ) . A similar approach to the study of repeatability in adaptive loci taken here could be applied to multiple GWAS results on standing variation for a given trait conducted independently in different species to assess the proportion of shared loci . However , it should be noted that in this case , the loci that contribute to standing variation could be shaped by previous selection and might therefore be more convergent than those identified using mutation accumulation , especially if long-term balancing selection is operating ( e . g . [42] ) . In order to draw inferences about the importance of these types of redundancy , it is critical to account for other factors unrelated to GT- and GF-redundancy that might drive repeatability , mainly through differences among genes in mutation rate or standing variation . The simplest approach to control these factors is to design studies that preclude shared standing variation , either through experiments founded from isogenic strains ( e . g . , [2 , 36] ) or comparisons of distantly related lineages ( divergence time >> 4Ne ) where lineage sorting has been completed ( as per [38] ) . While repeatability could still be driven by differences among genes in mutation rate , this can be seen as a component of GT-redundancy and therefore as a factor that can also constrain diversity . By contrast , the existence of shared standing variation occurs mainly due to historical contingency and is therefore a bias affecting estimation of C-scores , rather than a constraint . As such , parsing the contribution of mutation rate to C-scores and P^a is less critical than parsing the contribution of standing variation when using these as overall indices of constraint . Unfortunately , in studies of recently diverged natural populations , it is not possible to preclude shared standing variation , so C-scores and P^a could be strongly driven by this factor and therefore not particularly representative of diversity constraints . The recently developed likelihood-based method for discriminating between convergence via de novo mutation , migration , or shared standing variation ( [24] ) may provide a means to parse these contributions to repeatability and refine the inference of constraint . While testing the null hypothesis of no constraints is relatively straightforward , discriminating among other potential factors constraining diversity is much more complicated . Although it is possible to make very intricate models with variable mutation rates , selection coefficients , indices of pleiotropy , shared standing variation , and/or other factors determining the likelihood of each gene contributing to adaptation [3 , 25 , 28 , 43] , it may be very difficult to actually confidently discriminate between such models . The accuracy of the indices developed here will critically depend on the correct identification of the genes contributing to adaptation . Studies of local adaptation are particularly prone to false positives when population structure is oriented on the same axis as adaptive divergence , and it is unclear how extensively methods that correct for population structure induce false negatives or fail to accurately control for false positives [44 , 45] . Assuming false positives are distributed randomly throughout the genome in each lineage , failure to remove them will cause the C-scores derived here to be biased downwards . Failure to identify true positives ( i . e . false negatives ) will impair the accuracy of Cchisq , with the direction dependent upon the underlying biology . Assuming false negatives are randomly distributed in the genome , they could also reduce the magnitude of C-scores due to lower information content . On the other hand , if large-effect loci are more likely than small-effect loci to be both detected and convergent , false negatives will tend to bias C-scores upwards . As it is typically necessary to set arbitrary cutoffs for statistical significance to identify putatively adapted loci , we might expect Cchisq to increase with increasing stringency of these cutoffs , as this would be expected to reduce false positives ( but also increase false negatives ) . However , as there are many potential contingencies and interactions between the factors that affect these two types of error , there is a clear need for both theoretical studies on how the repeatability of local adaptation is affected by the interplay between demography and selection ( e . g . [28] ) , and refinement of these methods to derive confidence intervals taking into account likely error rates . A particularly important problem to address in implementing this method is that false positives may be non-randomly distributed throughout the genome in a similar way in different lineages . As local variations in the rate of mutation or recombination can drive genome-wide patterns in some indices used to identify selection and adaptation [46–48] , this could lead to signatures of convergence among distantly-related species if such patterns are conserved over long periods of evolutionary time . For example , genome-wide patterns of variation in nucleotide diversity , FST , and dxy were all significantly correlated across three distantly related bird species , likely driven in part by conservation of local recombination rate coupled with linked selection [49] . The extent of convergence of local recombination rates appears to vary considerably among species [50–53] , so it will be important to consider this factor as a potential driver of similarity in the genomic signatures used to identify selection . Methods for identifying signatures of adaptation that are explicitly linked to a phenotype or environment of interest across multiple pairs of populations may be less likely to be affected by such factors , as recombination and linked selection are unlikely to drive a pattern of repeated correlation between allele frequency and phenotype/environment . However , such methods are still vulnerable to potential biases that arise from the complex interplay between genomic landscape , selection , and recombination , and further study in both theoretical and empirical contexts will be important to test the robustness of different methods to this important source of bias . One potential approach to estimate the contribution of such confounding factors would be to compare signatures of the repeatability for adaptation in two different traits ( which are not phenotypically convergent ) to those for a phenotypically convergent trait . While studying adaptation across multiple pairs of populations can greatly increase the power to detect signatures of selection when all populations are adapting via the same loci , such methods are inherently unable to detect idiosyncratic patterns where different populations of a given species are adapting via different loci . By its very nature , it may be very difficult , if not impossible to detect local adaptation in traits with high GT- or GF-redundancy , as each pair of populations may be differentiated via a different set of loci [13] . If local adaptation is much more readily detected when it arises repeatedly within a lineage , then it will be difficult to identify conclusive cases with low C-scores , causing an overestimation of the prevalence of highly repeated adaptation . If patterns of genomic convergence are compared among multiple differentially-related lineages , it is important to consider their phylogeny when testing the importance of phylogenetic sharing of different factors affecting the propensity for gene reuse [54] . The ability to resolve orthology relationships also decreases with increasing phylogenetic distance , which can affect the estimation of ns . Similarly , the set of genes in a trait’s mutational target ( gi ) is expected to evolve over time , so the set of shared genes should decrease with phylogenetic distance ( so that gi − gs increases with divergence time ) , leading to decreased repeatability over time [33] . When studies include multiple differentially-related lineages , it is probably useful to estimate C-scores on both a pairwise and mean-across-all-lineages basis to more clearly describe cases where convergence is high within pairs of closely related lineages but low among more distantly related lineages . Finally , physical linkage is a factor that could critically affect the measurement of repeatability , as neutral alleles in other genes linked to a causal allele will tend to respond to indirect selection , causing spurious signatures of selection/local adaptation . If the same causal gene is driving adaptation in two lineages , this will tend to overestimate repeatability on a gene-by-gene basis , whereas the opposite will occur if different causal genes are driving adaptation . Yeaman et al . [38] found significantly elevated levels of linkage disequilibrium ( LD ) among candidate genes for local adaptation , which may have arisen due to physical linkage ( with or without selection on multiple causal loci ) or statistical associations driven by selection among physically unlinked loci . In this case , the fragmented genome and lack of suitable genetic map precluded a comprehensive analysis of the impact of LD . If genome/genetic map resources permit , it may be possible to analyse repeatability on haplotype blocks rather than individual genes , which could minimize the biases due to physical linkage . A large number of indices have been developed to characterize similarity among ecological communities , which can be broadly grouped based on binary vs . quantitative input data and whether they account for joint absence of a given type ( reviewed in [55] ) . In most cases , these indices are not derived from a probability-based representation of expectations , though Raup and Crick [56] quantified an index of similarity based on the p-value of a hypergeometric test ( see also [57] ) . The Chyper index that we have developed here uses the same underlying logic as the Raup-Crick index but quantifies the effect size as a deviation from the expectation under the null hypothesis in units of the standard deviation of the null distribution . The C-score and P^a indices developed here provide a complement to indices of repeatability that have been used in previous studies of convergence at the genome scale ( e . g . [2 , 33] ) . Whereas the Jaccard , PSadd , and other similar indices represent how commonly a given gene tends to be used in adaptation , the C-score indices quantify how much constraint is involved in driving this observed repeatability , whereas P^a quantifies the proportion of the genome that is effectively available for adaptation . In some cases , these indices will be qualitatively similar in quantifying patterns of convergence ( e . g . Fig 4A ) , but in other cases they will diverge considerably , because the C-scores are explicitly aimed at representing the importance of genes that could contribute to adaptation but do not . The repeated observation of convergent adaptation at the genome scale violates a fundamental assumption of the infinitesimal model of quantitative genetics: that the mutations responsible for adaptation have small effects and are essentially interchangeable [58] . If there are infinitely many interchangeable loci that could contribute to adaptation , the chance of the same gene playing a causal role in independent bouts should be vanishingly small . Molecular-genetic studies show that some traits are causally generated by only a few genes in a specific pathway , presumably limiting the mutational target and increasing the potential for convergence . For example , only the small number of genes that are directly involved in terpene production [59] would likely contribute to large variations in the amount of terpene produced by a plant . However , a second category of mutations in other non-pathway genes could also indirectly contribute to variation in terpene production through perturbations of regulatory networks . The recently proposed “omnigenic model” posits that genes can be categorized into “core” vs . “peripheral” function for a given trait , as a way to distinguish between those with larger direct effects vs . smaller indirect effects [14] , although this model has also been criticized [60] . The majority of evidence that has been considered in the context of the omnigenic model has come from Genome-Wide Association Studies ( GWAS ) of standing variation , but it is unclear whether this represents the “stuff” of long-term adaptation . Indeed , it appears that in humans there are pronounced differences in the distributions of alleles that contribute to standing vs . adaptive genetic variation , as GWAS studies of standing variation find mainly small-effect variants [61 , 62] , whereas studies of local adaptation have found a number of large effect loci ( e . g , for lactase persistence [63] , diving [64] , and high altitude [65] ) . If GT-redundancy is typically high and GF-redundancy commonly low , then there will be little correlation between the loci that can give rise to standing variation and the smaller subset of those responsible for long-term adaptation . Studying whether adaptation is commonly repeatable at the genome scale will therefore make an important complement to GWAS studies of standing variation , providing a window into the factors that constrain the diversity of viable routes to adaptation , and informing our broader understanding of how variation translates into evolution . We present a method to quantify the constraints that drive genomic repeatability of adaptation , to enable testing of hypotheses about the nature of these constraints . Contrasting the repeatability of adaptation with studies of standing variation will deepen our understanding of evolution and the factors that affect how it gives rise to diversity . Comparative approaches examining C-scores and the proportion of adaptation-effective loci ( P^a , lik ) for the same trait across different branches of the phylogeny may allow us to infer rates of evolution in constraints and potential differences between rapidly vs . slowly radiating lineages , and study whether adaptation drives such changes . Comparisons across traits within lineages will illuminate how different kinds of traits are constrained , and whether low GT- and GF-redundancy constitute important constraints at different levels of biological organization . Similarly , this approach could be used to examine whether the types of constraint that predominate depend upon critical population genetic parameters such as effective population size , which affects the long term efficiency of selection on the developmental-genetic program . While we have focused on repeatability at the gene level , this framework could be applied at other levels of organization , such as gene network , protein domain , or individual nucleotide ( reviewed by [3] ) , and could include the contribution of intergenic regulatory regions if it is possible to identify orthology . These methods therefore provide a first step towards comprehensive quantification and understanding of evolutionary constraints and the role that different factors play in the rise of diversity during adaptation .
|
How many ways can evolution solve the same adaptive problem ? While convergent adaptation is evident in many organisms at the phenotypic level , we are only beginning to understand how commonly this convergence extends to the genome scale . Quantifying the repeatability of adaptation at the genome scale is therefore critical for assessing how constraints affect the diversity of viable genetic responses . Here , we develop probability-based indices to quantify the deviation between observed repeatability and expectations under a range of null hypotheses , and an estimator of the proportion of loci in the genome that can contribute to adaptation . We demonstrate the usage of these indices with individual-based simulations and example datasets from yeast and conifers and discuss how they differ from previously developed approaches to studying repeatability . Because these indices are unitless , they provide a general approach to quantifying and comparing how constraints drive convergence at the genome scale across a wide range of traits and taxa .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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"ecological",
"metrics",
"mutation",
"ecology",
"and",
"environmental",
"sciences",
"species",
"diversity",
"quantitative",
"trait",
"loci",
"ecology",
"natural",
"selection",
"genetics",
"biology",
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"life",
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"genetics"
] |
2018
|
Quantifying how constraints limit the diversity of viable routes to adaptation
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Many biological systems perform computations on inputs that have very large dimensionality . Determining the relevant input combinations for a particular computation is often key to understanding its function . A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs . In systems neuroscience , the corresponding method is known as spike-triggered covariance ( STC ) . This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems . So far , most studies used the STC method with weakly correlated Gaussian inputs . However , it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment . In such cases , the stimulus covariance matrix has one ( or more ) outstanding eigenvalues that cannot be easily equalized because of sampling variability . Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs . In many cases , these modes obscure the significant dimensions . We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more . This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode ( s ) . Analyzing the responses of retinal ganglion cells probed with Gaussian noise , we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons .
How do neurons encode sensory stimuli ? One of the primary difficulties in answering this long-standing problem is the fact that sensory stimuli have high dimensionality . For example , responses of many visual neurons are affected by image patterns that require at least a pixel grid for their description as well as a temporal history spanning multiple time bins or basis functions . Determining what input combinations affect the neural responses is a key step in characterizing the neural computation . Broadly speaking , to detect the presence of certain features in the environment over a range of distances and light conditions , one needs to disambiguate the presence of this feature at a weak contrast from the presence of a similar , but different feature presented at a higher contrast . This can only be achieved with nonlinear functions that depend on multiple input components , such as the presence of an edge of correct orientation and the absence of the edge orthogonal to it [1] . In support of these arguments , the responses of neurons in different sensory modalities are found to be sensitive to multiple input combinations . Examples include vision [2]–[7] , audition [8]–[10] , olfaction [11] , somatosensation [12] and mechanosensation [13] . Neurons respond with all-or-none responses termed spikes . The goal of different methods for characterizing neural feature selectivity is to determine how the probability of eliciting a spike from a neuron depends on its inputs . The underlying assumption is that this dependence of spike probability on input parameters will have a low-dimensional structure . Finding either the linear input dimensions that modulate the spike probability ( we will refer to these dimensions as relevant ) or quadratic forms of inputs [14]–[16] is the focus of much of the current research in the field . Much of the analysis of neural selectivity for multiple input combinations has been carried out using uncorrelated ( “white noise” ) or weakly correlated inputs . With such inputs , the relevant input dimensions can be found using a computationally inexpensive method known as spike-triggered covariance ( STC ) [6] , [7] , [17]–[22] . The STC method works by comparing the change in variance along different dimensions in the input space across all stimuli and across stimuli that elicited a spike . The dimensions along which the variance is found to be significantly different represent the relevant input dimensions for the response of a particular neuron . The method is not limited to strictly Gaussian inputs provided that the inputs are still circularly symmetric [23] , which is another example of an input distribution without correlations . In principle the STC method can also be used with correlated Gaussian stimuli [7] , [20] . The case of correlated stimuli - especially with strong correlations , where the second moment of the covariance spectrum may be infinite - is important for neural coding . This is because signals in the sensory environment possess such correlations in both the second and higher orders [24]–[30] . Because the properties of a cell's relevant subspace may change depending on the stimulus statistics as a result of adaptation [31] , [32] , it may not be sufficient to study neural coding using uncorrelated stimuli . Here we show that with strongly correlated inputs , the significance analysis for determining which of the dimensions obtained by the STC method are relevant for neural spiking needs to be modified to take into account a rather complicated covariance structure of randomly selected inputs drawn from such input ensembles . The nonuniform covariance structure , which has properties akin to the graph laplacian in small-world networks [33] , breaks the symmetry in the input space , and therefore may obscure many significant dimensions . The most prominent aspect of the natural scenes covariance structure is the presence of the so-called “coherent” mode [34] . This stimulus dimension approximately corresponds to the zero frequency input component and has a corresponding eigenvalue that is at least times larger than the mean eigenvalue of the input covariance matrix . Even in datasets of fairly large size , the extremely large variance along the coherent mode obscures many of the truly relevant dimensions for neural spiking ( Fig . 1 ) . These effects are also reproduced in our analysis of the responses of ganglion cells from the salamander retina probed with -type naturalistic Gaussian stimuli . We identify a close relationship between the covariance structure derived from natural scenes to that defined by the Spiked-Wishart matrix model [35] , [36] . This allows us to explain the effects in the context of the STC method using results from random matrix theory , and suggest ways to bypass sampling variability along the outstanding modes .
Mathematically , the first step in the STC method is to compute the covariance matrix of stimuli that lead to a spike and the covariance matrix of all stimuli : ( 1 ) ( 2 ) Here , is the number of recorded spikes , is the number of stimulus frames , is the value of the stimulus along the th dimension at time , the hat denotes that this stimulus triggered a spike , the bar denotes the average across the input distribution and is the average across the distribution of inputs that triggered a spike ( the so called “spike-triggered-average” ) . As the second step , one computes the difference between these covariance matrices: ( 3 ) and finds the eigenvalues that are significantly different from zero . The corresponding eigenvectors span the neuron's relevant subspace . To determine statistical significance of the eigenvalues , they need to be compared to the null distribution , which is the distribution of eigenvalues of the matrices . The matrices are formed assuming no association between the stimulus and the neural response , i . e . by using random spike times chosen at the same rate found for real neurons . If the spike train has particular temporal structure ( e . g . bursting , a refractory period ) , the is obtained by random shifts of the spike train with periodic boundary conditions [20] . Significant eigenvalues of can be positive or negative . The procedures for determining statistical significance are detailed in Materials and Methods . The final step of the STC method is to remove stimulus correlations from the estimate of dimensions found to be significant . This can be done by multiplying them with the ( pseudo ) inverse of ( see Materials and Methods ) . The method which we use to find the optimal rank of the pseudoinverse matrix is detailed in [22] , [37] and for completeness described in Materials and Methods . We note that this approach , Eqs . ( 1 ) – ( 3 ) , of finding the relevant stimulus dimensions by diagonalizing is equivalent to seeking eigenvectors of the following matrix [20]: ( 4 ) This matrix describes a change in the second moment between the distributions stimuli that elicit a spike and that of all stimuli , after subtracting the mean stimulus . Despite the fact that , their eigenvectors coincide . In another formulation , instead of subtracting the matrix in Eq . ( 3 ) , the stimulus is decorrelated ( “whitened” ) prior to its spike triggered characterization [7] . For completeness , the details of this method are brought in Materials and Methods . Throughout the manuscript , we will refer to this method as the “one centered” method , because the null distribution is centered around the identity matrix , rather than a matrix of zeros , as in Eq . ( 3 ) . Correspondingly , we will refer to the version of the STC method obtained by diagonalizing Eq . ( 3 ) as the “zero-centered” method . In essence , both the one-centered and the zero-centered versions are similarly affected by inhomogeneous sampling variability . The authors of [7] proposed a slightly different definition of the null distribution and a nested hypothesis technique for significance testing . For the model cell simulations we used both significance analysis methods , in both the “zero-centered” and “one-centered” STC formulations , and obtained similar results . For the rest of this paper we will refer to our significance testing method as the “global” one , and focus mainly on the “zero-centered” formulation of the STC method . Using this combination the important effects of the strong stimulus correlations on the analysis are more easily understood . We begin with an illustration of the problems that arise when the STC method is used to analyze neural responses to strongly correlated Gaussian noise ( Fig . 1 ) . We simulated a model neuron where the neuronal responses were modulated by stimulus projections onto a single dimension ( termed here the relevant feature ) . The stimuli were constructed to match the second-order statistics from the set of images in the van Hateren dataset [38] ( see Materials and Methods ) . In this example obtained for dataset of a moderate size , no eigenvalues fell outside of the % confidence intervals ( % significant bounds for the largest and smallest rank-ordered eigenvalues ) . Yet , the spike train contains enough signal about the cell's input-output function to identify the relevant feature for this level of significance . Specifically , the variance along the relevant dimension in the spike-triggered stimulus ( ) is much smaller than can be explained by random spike times ( Fig . 1E ) . To understand the origin of such masking of the relevant feature ( s ) , we consider the eigenstructure of covariance matrices for stimulus ensembles with strong pairwise correlations . For example , in the case of natural scenes that exhibit long range correlations over a very wide range of spatial scales [27] , [39] , principal component analysis ( PCA ) yields one outstanding eigenvalue ( for example , see eigenvalue marked in Fig . 2A ) . The corresponding eigenvector has all positive components [28] , [30] and is often referred to as the “coherent mode” [34] . To understand why such a coherent mode appears , one can consider the case where the correlations decrease only slightly over the range of image patches used to compute the covariance matrix . In this case , the correlation values in different image patches will be approximately the same . Such a matrix will have one outstanding eigenvalue with a corresponding eigenvector that has equal weights for all stimulus dimensions [40] . Small differences in the amount of covariation for pixel pairs with different spatial separation will lead to deviations in components of the coherent mode from each other , but the basic structure will remain the same as long as the mean of the correlation values exceeds the standard deviation of their fluctuations [40] . In fact , shuffling entries in the sample covariance matrices of natural stimuli yields matrices whose spectra follow the analytical predictions exactly [40] , [41] . These analytical predictions generalize the Wigner semicircle law [42] for matrices whose elements have a non-zero mean: ( 5 ) where and are the mean and variance of matrix elements . The distribution follows the semicircle law with the addition of one outstanding mode that appears once the mean of matrix elements exceeds their standard deviation . The eigenvector corresponding to the outstanding eigenvalue is . The semicircle law appears because matrices are no longer positive-definite after shuffling . However , the outstanding eigenvalue is located at exactly the same value as the outstanding eigenvalue of the natural scenes covariance matrix ( see Fig . 2C ) . In our analysis of the van Hateren database , the largest eigenvalue tends to be at least times larger than the second largest eigenvalue . This shows how strong the coherent mode is compared to other modes . The principal components ranked below the coherent mode form a collection of orthogonal “edge detectors” , some of which correspond to an eigenvalue still much larger than the mean eigenvalue of , a signature of the stimulus' heavy-tailed covariance spectrum . Such large disparities in variance along the different dimensions in the stimulus space make it problematic to directly compare changes in variance induced by the observation of spikes along these different dimensions . The detailed structure of sampling variability in the estimation of eigenvectors and eigenvalues can be understood in terms of the Spiked Wishart ensemble [35] , [36] . In the Spiked Wishart matrix model , the true ( population ) covariance eigenvalues are all equal to one , except for a small number of outstanding modes with eigenvalues larger than one , where is the stimulus dimensionality . The distribution of sample covariance eigenvalues for a finite number of inputs has a positive bias , with the following analytical expressions [36]: ( 6 ) ( 7 ) ( 8 ) where and is the number of samples . The distribution representing the “bulk” of eigenvalues is the so called Marčenko-Pastur distribution given by: ( 9 ) ( 10 ) This distribution corresponds to the sample covariance eigenvalues obtained when the true covariance is the identity matrix . Using numerical simulations we verified that , although the Spiked Wishart ensemble is only an approximation to the covariance matrices derived from natural stimuli , Eqs . ( 7 ) and ( 8 ) accurately describe the scaling of the variance and the mean of sample eigenvalues as increases . In addition to biases in eigenvalue estimates , there are also biases in the estimation of eigenvectors . The dot product between the true ( population ) th eigenvector and the th eigenvector of the sample covariance approaches ( 11 ) In other words , the “mixing” of the outstanding sample eigenvectors seen in Eq . ( 11 ) ( note the dependence of this mixing on through ) as well as the variance and bias in the sample eigenvalues seen in Eq . ( 7 ) means that whitening cannot be exact . In the context of the spike triggered covariance the consequences of such properties of the distribution of sample eigenvalues are twofold . First , Eq . ( 8 ) indicates that the variance of the outstanding eigenvalues around their mean increases with the square of their value and is inversely proportional to the number of samples . Thus , for sample sizes that are not much larger than the stimulus dimensionality ( in the simulation results presented in Fig . 3A ) , the increased variance of the outstanding sample eigenvalue means that and will not cancel each other exactly along that vector . Second , the mean estimate contains a positive bias relative to the population values , cf . Eq . ( 7 ) . The combination of these two effects widens the null-distribution used to test the significance of the resulting eigenvectors , effectively masking features that should otherwise be identified as being relevant . One way to compensate for the symmetry breaking effects caused by strong correlations in the input space is to equalize variances before applying the STC method . This is the essence of the “one-centered” formulation of the STC method [7] . In principle , this “whitening” should work with Gaussian stimuli with any covariance structure . However , as discussed above , in the case of strongly correlated stimuli , the estimation of eigenvalues ( i . e variances along different dimensions in the input space ) possesses strong variability , cf . Eq . ( 7 ) . As a consequence , normalization by a variance estimated from one part of the dataset does not fully remove correlations in a different subset of the data . With increasing dataset size , the estimate of the variance along the coherent mode improves . However , because the absolute value of variance is not relevant in the pre-whitening method , dimensions with smaller variance can cause just as much contamination as the coherent mode . In addition , the estimation of variance along dimensions corresponding to just larger than remains poor for large . If the sample eigenvalue estimation error diverges as , as follows from Eq . ( 8 ) . In other words , as the number of samples and increase , the bulk of the distribution narrows , and new eigenvalues separate from the bulk . It is these eigenvalues with intermediate values that are poorly determined and make it problematic to equalize variance along different dimensions . Another signature of this phenomenon is that for these dimensions , as follows from Eq . ( 11 ) . Thus , these dimensions are poorly estimated from the sample covariance and , as a consequence , the variance along one stimulus dimension in the training set will be inappropriately used to normalize variance along a different stimulus dimension in the test set . Altogether , we observed that pre-whitening stimuli did not improve the estimation of relevant stimulus features compared to the zero-centered method , compare panels A and B in Fig . 3 . Intuitively , in the zero-centered method the dimensions with the largest variance provide the largest uncertainty in variance estimation , whereas in the one-centered version the problematic dimensions change depending on the dataset size , and are not easily identified a priori . We have also explored the possibility of using a pseudoinverse of the covariance matrix instead of the full inverse to normalize variance along different dimensions ( see Materials and Methods for details ) . When using the pseudoinverse ( instead of the inverse ) , stimulus dimensions with small variance in the stimulus ensemble are removed to avoid noise amplification along these dimensions ( see Materials and Methods for details ) . However , an immediate consequence of choosing a small pseudoinverse order is that the stimulus dimensionality is reduced to . This implies that the effective of the problem is now , i . e . times larger than . This could work well in some cases as illustrated in Fig . 3I . Here , in simulations based on a small number of spikes , the use of pseudoinverse can help recover one or two significant features while the standard zero-centered method fails to find any . However , the use of pseudoinverse only helps within a very narrow band of small pseudoinverse orders . This band may be difficult to determine when analyzing real neural data . In addition , this procedure limits the reconstruction to a linear combination of only a few leading stimulus dimensions . In many cases , the relevant features do include components along stimulus dimensions with smaller variance , and in those cases , the effective increase in will not improve the performance of the STC method . Indeed , one observes that in cases where two significant dimensions are obtained by using substantial reduction in dimensionality of the pseudoinverse , the resulting dimensions have the subspace projection onto the model features of whereas this value is when using the full inverse and a larger number of spikes to obtain for a comparable effective ( Fig . 3I ) . Finally , in the regime where ( i . e . “almost full” inverse ) , the prewhitening approach works just as well as the “zero-centered” formulation , and a relatively high value of the signal-to-noise ratio parameter is required for recovery of the full relevant subspace . As another way to compensate for the symmetry breaking effects caused by strong correlations in the input space , we propose to modify the “zero-centered” formulation of the STC method in the following way . Because the largest drop in variance is between the coherent mode and other dimensions , we propose here to test the significance of changes in variance separately along the coherent mode and in the subspace orthogonal to it . Explicitly , to do the analysis in the dimensional subspace , the coherent mode is projected out of all stimuli . If is a stimulus vector and normalized to length , one can perform the STC analysis using instead of where: ( 12 ) In this approach the correct number of relevant dimensions is determined by evaluating significance in the subspace orthogonal to the coherent mode and then adding back their projections on the coherent mode from the corresponding eigenvectors evaluated in the full input space ( see below ) . We find that considering the coherent mode separately from the rest of stimulus dimensions reduces the value of for which the full relevant subspace is found to be significant by a factor of ( Fig . 3C ) . This improvement can be approximated from Eqs . ( 7 ) and ( 8 ) . Assuming the cell's relevant subspace is exactly orthogonal to the coherent mode , the extremal values of the null distribution are distributed as . The variance of is: ( 13 ) This implies that the number of stimuli sufficient for identifying the relevant features as significant increases with as: ( 14 ) Upon removal of the coherent mode , the minimum value of for which the signal to noise ratio will be high enough to identify the relevant dimensions scales as corresponding to the stimulus' second principal component . Therefore the improvement is proportional to . In our simulations ( Fig . 3A , C ) this corresponds to a predicted fold improvement . Given that our model features were not exactly orthogonal to the coherent mode , and that the spectrum obtained from the van Hateren dataset has a heavy tail and does not conform exactly to the Spiked Wishart ensemble , an approximate fold improvement represents a good agreement with the prediction . It is noteworthy that the minimum requirement on the dataset size for obtaining the correct number of relevant dimensions is actually smaller with correlated stimuli than it is for white noise stimuli for the same neuron ( compare Fig . 3 panels A–D ) when the model parameters were matched such that the firing rate remains constant across different stimuli statistics . Another important point is that considering the coherent mode separately is different from simply discarding a “DC-like” component that could be found to be significant by the STC . This is because when is small , no dimensions are found to be significant with the coherent mode as part of the stimulus ensemble ( Fig . 1 ) . An important consideration is that the final analysis can include the components of the relevant dimensions onto the coherent mode . This is possible for two reasons . First , the coherent mode does not represent an arbitrary dimension in the input space but is one of the eigenvectors of the sample covariance matrix . Second , the significant eigenvectors of have a form , where is the th eigenvalue corresponding to the th eigenvector of the sample covariance matrix , and describes one of the relevant features [20] . Because of these two properties , eigenvectors evaluated in the full input space and in the subspace orthogonal to the coherent mode differ only in their components along the coherent mode ( see Materials and Methods for the details of the derivation ) . This makes it possible to analyze cells with features that have nonzero components along the coherent mode . We have verified that this approach also works in a large number of cases where the relevant stimulus dimensions have a large projection on the coherent mode ( Fig . 4 ) . One concern is that when such neurons are probed with a relatively small number of stimuli , then projecting the coherent mode out may “push” the relevant feature into the null eigenvalue distribution . This does not appear to be a problem in our simulations for ( Fig . 4B ) . If this does happen , the relevant subspace should be the one spanned by both the eigenvectors found to be significant in the full stimulus space and those found to be significant in the subspace orthogonal to the coherent mode . We now demonstrate the importance of this correction scheme by analyzing recordings of 22 salamander retinal ganglion cells ( RGCs ) . These neurons were probed with a correlated noise stimulus whose covariance matrix was matched to that of natural visual stimuli . Without correcting for the presence of the coherent mode , the STC analysis yielded no significant dimensions for a third of the cells , and very few for the rest ( Fig . 5 ) . This happens because the eigenvalue corresponding to the coherent mode injects large eigenvalues into the null eigenvalue distribution ( as seen in Eq . ( 8 ) ) , thus masking the cell's true relevant features . Following the correction , the number of significant dimensions per cell increased from to ( see Fig . 5A for the full population values ) . The dimensionality of the relevant subspace increased for 21 out of 22 cells . For one cell , we were unable to find a significant dimension either before or after the correction of the method . The distributions of null eigenvalues used to determine which of the eigenvectors of are significant ( Fig . 5B , C ) became much more narrow when evaluated in the subspace orthogonal to the coherent mode .
The goal of this work was to extend the range of applicability of a computationally simple method of spike-triggered covariance to strongly correlated stimuli . While the STC method in principle can be used with strongly correlated Gaussian stimuli , our results show that the inhomogeneous sampling variability can in practice make it difficult to recover the correct relevant subspace . We have characterized the effects generated by strong Gaussian correlations using simulations of two model neurons in a wide range of dataset sizes ( which could also be viewed as an inverse measure of the neuron's level of internal noise ) . Results from random matrix theory , and specifically the Wigner and Spiked Wishart ensembles , suggest that the origin of these issues can be traced to the estimation bias and variance of covariance matrices with vastly different eigenvalues . We demonstrate that by considering the coherent mode , which corresponds to the largest eigenvalue , separately from the rest of stimulus dimensions , one can improve the method's sensitivity by . One qualitative lesson offered by these analyses is that while the bulk of the eigenvalues of is a good proxy for the width of the null distribution in the case of white noise inputs , but not in the case of strongly correlated inputs . Furthermore , our analysis suggests that sampling variability along the secondary outstanding modes corresponding to the next few principal components may have similar masking effects to the ones reported here for the coherent mode . Possible solutions to the full problem may include performing a sequence of analyses in subspaces of decreasing dimensionality , orthogonal to several leading principal components . However , the payoff from this procedure is ( at most ) of order which in our case is . At the same time , one runs the risk of losing the ability to resolve the remaining dimensions because of the reduced signal to noise ratio . Another potential solution is to correct for the estimation bias and variance in eigenvalues and eigenvectors , described by Eqs . ( 7 ) and ( 8 ) . However , this procedure is difficult computationally and in most cases can only be done for simple eigenvalue distributions [43] . The treatment of the artifacts caused by a large coherent mode present in the data has been previously discussed in analyses of stock-markets [44] , [45] , evolution of proteins [46] , and Human Immunodeficiency Virus ( HIV ) mutations [34] . In these cases , the extra dimension was removed and the resulting covariance structure was compared against the Marčenko-Pastur eigenvalue distribution that assumes no correlation between the variables and uniform variable variances . The case of reverse correlation experiments discussed here is different from these analyses because the spike triggered ensemble is compared to the full stimulus distribution . In addition , our analyses provide two important novel contributions . First , we show there is a crucial difference between discarding the coherent mode and projecting it out . This is because of the way the coherent mode injects noise into the null distribution . Second , the approach described here also permits the inclusion of the components of the relevant dimensions along the coherent mode in the final results . We hope that the ideas for treating the coherent mode presented here will also be relevant in other areas of computational biology .
Experimental data were collected using procedures approved by the Institutional Animal Care and Use Committee of Princeton University , and in accordance with National Institutes of Health guidelines . Experimental and surgical procedures have been described previously [47] . Each stimulus frame was randomly drawn from a multivariate Gaussian distribution with zero mean and covariance matrix , In the correlated stimulus case , the population covariance was computed from the covariance of pixels patches from the van Hateren image database [38] ( with no downsampling ) . In the uncorrelated ( “white” ) case , was the identity matrix . We describe two approaches for determining significance of candidate features that were previously described in the literature: global and nested . When applied to our datasets , both of the approaches yielded similar results . Within the STC method , stimulus correlations need to be removed from the estimates of eigenvectors obtained by diagonalizing matrix . This correction is needed , because the eigenvectors of have a form , where describe components of one of the relevant features [20] . As described above , one may wish to use a pseudoinverse , instead of the full inverse of the matrix to minimize noise amplification at higher spatial frequencies . Assuming that the eigenvalues are ordered to be monotonically decreasing , the pseudoinverse of order is given by ( 18 ) In the analysis of data from retinal ganglion cells , the optimal order of the pseudoinverse was determined in the following way . The dataset was divided into the training and test sets . The features were computed by diagonalizing the matrix , cf . Eq . ( 3 ) , in either the full input space or in the space orthogonal to the coherent mode using the training set . Following that , the optimal pseudoinverse order was selected as the one that yielded decorrelated features that convey the most information about , or give the largest predictive power for , the neural response . Explicitly , ( 19 ) ( 20 ) where is the probability distribution of the projections of stimuli onto the significant eigenvectors ( ) , decorrelated by . are the decorrelated significant features , and: ( 21 ) ( 22 ) As an alternative to removing stimulus correlations from the eigenvectors of , one can remove stimulus correlations from each of the stimulus vectors , prior to the diagonalization of , a procedure that is known as pre-whitening [7] . The sample stimulus covariance matrix from Eq . ( 2 ) can be written in terms of eigenvalues and eigenvectors as ( 23 ) We can now define a matrix . Then , the analogue of in the “one-centered” formulation is given by: ( 24 ) This procedure is equivalent to whitening each of the stimulus frames independently ( by multiplying it with ) and then computing the spike-triggered covariance . In the limit of infinite data , the null hypothesis corresponds to . In this case . For a dataset of finite size , the null distribution is computed from many realizations of the matrix ( 25 ) where is defined by Eq . ( 16 ) . The eigenvalues of ( most of which are close to ) can then be compared to the null eigenvalue distribution , using either the nested or global comparison tests described above . In Fig . 3 we analyzed the simulated spike trains using every pseudoinverse order of . The prewhitening is then done using this matrix Eq . ( 18 ) instead of the full rank matrix . Performing the pre-whitened STC analysis using all pseudoinverse orders is equivalent to testing models . Therefore , the confidence interval of the null distribution should be adjusted from the percentile range to , where is the Dunn-Šidák correction: ( 26 ) We recall that according to Ref . [20] , the significant eigenvectors of can be written as ( 27 ) Thus , the eigenvectors of represent a sum of projection operators onto the principal components of the stimulus ensemble . When we perform the STC method in the subspace orthogonal to the first principal component of the stimulus , the eigenvectors of can be written as ( 28 ) ( the coherent mode is exactly the vector ) . Comparing expressions for the eigenvectors of and , one observes that there is a one-to-one correspondence between them . This correspondence can be identified based on proportionality in components along second , third , and other principal components: ( 29 ) for any . In sum , once the eigenvector is found to be significant in the subspace orthogonal to , the eigenvector that should be identified as significant in the full stimulus space is that satisfies the condition of Eq . ( 29 ) . The nonlinearity was chosen to be a logistic function because such functions maximize the cell's noise entropy and thus minimize the assumptions imposed on the cell's response [48] . Using the models , we generated simulated spike trains in response to either a white or a correlated noise stimulus . The model used in Fig . 3 ( model “” ) had a two dimensional relevant subspace with features orthogonal to the coherent mode . The probability of spiking was modeled to increase when the projection of the stimulus on either of the preferred features was large in absolute value ( representing a logical OR function ) . If are the preferred model features and is the stimulus presented at time ( here , the 's and are dimensional vectors ) then the probability of a spike at time is: ( 30 ) where and are parameters that determine the width and ( soft ) thresholds of the sigmoid nonlinearities for the model . We have also considered the case where the projection of the stimulus on the features was not taken in absolute value , corresponding to a monotonic nonlinearity . In that case ( model “” , used in Fig . 1 ) the model was one dimensional , so the probability of a spike is ( 31 ) The effects described above were observed for both symmetric ( Fig . 3 ) and monotonic ( Fig . 1 ) nonlinearities . The second model had one relevant input feature with a large component along the coherent mode . In this case , the probability of a spike was modeled as: ( 32 ) where and are the width and the threshold of the sigmoid nonlinearity of this model . In units of the standard deviation of the projection of the stimulus on the model features ( , ) the model parameters were chosen to be: ( 33 ) ( 34 ) ( 35 ) The overlap measure we use when the dimensionality of the relevant subspace is greater than one is given by [49]: ( 36 ) where and are matrices that hold the model and computed features , respectively , is the input dimensionality , and is the number of relevant features in the model .
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In many areas of computational biology , including the analyses of genetic mutations , protein stability and neural coding , as well as in economics , one of the most basic and important steps of data analysis is to find the relevant input dimensions for a particular task . In neural coding problems , the spike-triggered covariance ( STC ) method identifies relevant input dimensions by comparing the variance of the input distribution along different dimensions to the variance of inputs that elicited a neural response . While in theory the method can be applied to Gaussian stimuli with or without correlations , it has so far been used in studies with only weakly correlated stimuli . Here we show that to use STC with strongly correlated , -type inputs , one has to take into account that the covariance matrix of random samples from this distribution has a complex structure , with one or more outstanding modes . We use simulations on model neurons as well as an analysis of the responses of retinal neurons to demonstrate that taking the presence of these outstanding modes into account improves the sensitivity of the STC method by more than an order of magnitude .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2013
|
Spike Triggered Covariance in Strongly Correlated Gaussian Stimuli
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Traumatic brain injury often leads to epileptic seizures . Among other factors , homeostatic synaptic plasticity ( HSP ) mediates posttraumatic epileptogenesis through unbalanced synaptic scaling , partially compensating for the trauma-incurred loss of neural excitability . HSP is mediated in part by tumor necrosis factor alpha ( TNFα ) , which is released locally from reactive astrocytes early after trauma in response to chronic neuronal inactivity . During this early period , TNFα is likely to be constrained to its glial sources; however , the contribution of glia-mediated spatially localized HSP to post-traumatic epileptogenesis remains poorly understood . We used computational model to investigate the reorganization of collective neural activity early after trauma . Trauma and synaptic scaling transformed asynchronous spiking into paroxysmal discharges . The rate of paroxysms could be reduced by functional segregation of synaptic input into astrocytic microdomains . Thus , we propose that trauma-triggered reactive gliosis could exert both beneficial and deleterious effects on neural activity .
Post-traumatic epilepsy develops in some but not all head injury cases , depending on the severity of injury and the time elapsed since trauma . Often there is a latent period between the traumatic event and onset of paroxysmal activity [1] . Identification of neurological mechanisms underlying this latency to seizures can offer a possibility for therapeutic intervention . Experimental and modeling studies suggest that this slow transition from normal to paroxysmal activity might depend on homeostatic adjustment of synaptic conductances , connectivity and intrinsic excitability properties [2] , [3] . Homeostatic synaptic plasticity ( HSP ) likely operates on several spatial and temporal scales [4] . Chronic synaptic and neuronal inactivity , such as the one that often occurs following trauma , engages glial cells to release tumor necrosis factor alpha ( TNFα ) [5] , [6] , [7] . This relatively slow process ( global effects in culture are measurable after ∼48 hours of inactivity [6] ) may represent a global “network response” to prolonged inactivity [8] . The strengthening of inputs from the open eye during monocular deprivation is another slow process that is mediated by TNFα [7] , [8] , [9] . Early after trauma elevated levels of TNFα are likely to be spatially localized to their glial sources , implying spatial localization of homeostatic synaptic plasticity . Earlier studies showed that TNFα causes a rapid , p55 receptor mediated insertion of neuronal AMPA receptors [10] , and endocytosis of GABA receptors [6] . Thus , TNFα could promote epileptogenesis by shifting the excitation-inhibition balance in favor of excitation . Consistent with this , systemic administration of TNFα [11] and constitutive over-expression of TNFα [12] had pro-epileptic effects . Seizure incidence was dramatically reduced in knockout mice lacking p55 TNFα receptors [13] , [14]; susceptibility to seizures was reduced following systemic pre-injection of TNFα antibodies [15] . These data suggest that TNFα can promote epileptogenesis [16] . Given the role of TNFα in HSP [7] , [8] , [9] , the implication is that homeostatic synaptic plasticity can drive the traumatized network toward epileptic activity [3] , [17] , [18] , [19] . In our previous studies [3] , [18] we showed that trauma-triggered HSP can transform cortical activity from asynchronous spiking ( ∼5 Hz for pyramidal neurons , ∼10 Hz for inhibitory neurons ) to paroxysmal bursting , and we further showed that the pattern of trauma changes the threshold for epileptogenesis [20] . In those studies we implicitly assumed that HSP represents the action of TNFα which is released in response to chronically low levels of neuronal activity incurred by the traumatic injury . We also assumed that HSP adjusted synaptic conductances in a manner that depended on the network-global averaging of neuronal activity . The assumption of global network averaging of neuronal activity is likely to be valid at sufficiently long time after trauma , when levels of TNFα had equilibrated throughout the network . However , at a short time ( several hours ) after trauma , elevated levels of TNFα are likely to be localized around their glial sources [21] , thus implying spatial localization of HSP and spatially heterogeneous disruption of excitation-inhibition balance that may strongly favor the transition to seizures . Given the extensive evidence for the dramatic involvement of TNFα in post-traumatic epilepsy [16] , high levels of localized TNFα a short time after brain injury [21] are not consistent with the relatively low incidence of paroxysmal spikes and seizures during that period . In the present study , we addressed this question by studying the early effects of TNFα mediated HSP hours after trauma . Homeostatic synaptic plasticity restored the average network firing rate to its pre-traumatic level but transformed asynchronous spiking to paroxysmal bursts . Thus , we adopted the rate of paroxysmal burst generation ( rather than the network-averaged firing rate ) as a measure of network's propensity to exhibit the transition to seizures . Paroxysmal bursts of highly correlated population activity in our model resembled interictal epileptiform discharges ( IEDs ) , which are often considered an important diagnostic feature of epileptic seizures [22] , [23] , [24] . Thus , a higher rate of population bursting in a post-traumatic model network was considered an indicator of stronger propensity to seizures . With spatially constrained HSP ( “local HSP” ) , representing local synaptic scaling by TNFα , paroxysmal bursts occurred in post-traumatic network at a high rate , with little dependence on the fraction of deafferented neurons ( trauma volume ) . This was in striking contrast to the gradual dependence of burst rate on trauma volume that characterized the later stage of “global HSP” . Properties of paroxysmal discharges could be modulated by functional segregation of synaptic inputs into reactive astrocytic microdomains [25] , [26] . Thus , our modeling studies suggest that some aspects of reactive astrogliosis might alleviate paroxysmal activity early after trauma .
Homeostatic regulation is likely to operate on a localized spatial scale during the early phase of response to trauma , reflecting the local response of glial cells to nearby synaptic activity . Such a change of scale could in principle affect our earlier conclusions regarding the role of trauma pattern in post-traumatic epileptogenesis [20] . In particular , in our earlier studies [20] we found that the trauma threshold for the emergence of paroxysmal events in post-traumatic network depended on the pattern of trauma itself . In those studies , the extent of trauma was parameterized by the fraction of deafferented model neurons , , which we will refer to as the “volume of trauma” . When burst rate was plotted vs . the trauma volume parameter , focal trauma ( spatially contiguous set of deafferented neurons ) caused lower burst threshold as compared to diffuse trauma ( spatially randomly distributed set of deafferented neurons ) . Thus , it was important to validate the conclusions of our earlier studies regarding the role of trauma spatial organization in generation of post-traumatic paroxysmal activity . Here , we assumed that the downregulation of excitatory synaptic conductances in a computational model of a hyperactive pyramidal ( PY ) neuron was determined by the time-averaged firing rate of the postsynaptic neuron , consistent with postsynaptic synaptic scaling [4] . On the other hand , upregulation of excitatory synaptic input in response to reduced levels of synaptic activity was determined in our model by the time-averaged firing rate of all PY neurons that projected their synapses to a PY neuron under consideration , corresponding to glial scaling of synaptic conductances by TNFα [8] . Thus , the baseline model is described by “local UP” regulation and “local DOWN” regulation of synaptic conductance . This model is referred to below as a local HSP model . To compare with our previous results [20] we also used a global HSP model , in which both pre- and postsynaptic components of homeostatic synaptic scaling were determined by the global , network-averaged , firing rate of model PY neurons . Thus , the “global HSP” model that was used in our previous studies [20] is described by “global UP” regulation and “global DOWN” regulation of synaptic conductance . A shift in the spatial scale of HSP rule in the present model would correspond to the transition from the early phase of post-traumatic reorganization ( during which upregulation of synaptic conductance is constrained to glial sources of TNFα ) to the later phase ( of equilibrated levels of TNFα ) . In some simulations ( e . g . , Figure 1C ) we only changed the spatial scale of presynaptic , upregulating , HSP component from local ( averaged only over those PY neurons that project their synapses to a given neuron , as in “local HSP” or baseline model ) to global ( averaged over all PY neurons in the network , “global UP” model in Figure 1C ) . Note that the “global UP” model differs from “global HSP” model in that in the former the downregulating postsynaptic HSP component is local ( i . e . , based on the activity of the specific postsynaptic neuron , similar to the baseline model ) . In other simulations , the downregulating postsynaptic HSP component was removed altogether from the model network , to assess the impact that homeostatic downregulation of synaptic conductance might have on collective activity; this model is referred to as “global UP no DOWN” . Note again that the “global UP no DOWN” model differs from the “global HSP” model in that in the latter the downregulating component of HSP is present . In yet other simulations , the set of synaptic inputs in the local HSP scheme was further randomly and evenly partitioned into several groups , for each of which we applied equations that described presynaptic component of HSP ( Materials and Methods ) . Such partitioning into sub-groups of synaptic inputs was taken to mimic partition of the cortex into astrocytic microdomains [25] , [27] . Finally , we compared two different patterns of trauma: focal trauma ( in which a spatially contiguous subpopulation of neurons was deafferented , ( e . g . , Figure 1A1 ) ) , and diffuse trauma ( in which deafferentation affected fraction of neurons randomly selected from the entire network ( e . g . , Figure 1A2 ) ) . In what follows , the “baseline” model network configuration is defined as a network with one microdomain per neuron , local HSP rule , and subject to focal trauma . Within the “early response” scheme of the HSP based on the activity of presynaptic neurons ( local HSP , see above and Materials and Methods ) , the rate of paroxysmal bursts was significantly higher for focal trauma ( Figure 1A1 ) compared to the spatially diffuse trauma ( Figure 1A2 ) , and this distinction was observed over a wide range of trauma volume parameter values , . This was generally consistent with earlier studies in which we showed that the spatial pattern of trauma could critically affect the threshold for post-traumatic paroxysmal activity [20] . In Figures 1A1 , 1A2 , we also plotted the results obtained with the global HSP model ( in which both up and down regulation of synaptic conductance was determined based on the global network-wide average over activities of pyramidal neurons ) , to compare them with the present model , which made use of local HSP . Although the two models produced the same result qualitatively ( both showed an increase in the rate of paroxysmal activity above some critical threshold of trauma volume parameter , and in both cases the threshold was higher for the diffuse trauma ) , the threshold for paroxysmal activity appeared to be much lower in the case of local HSP rule . The difference between the two HSP models was also reflected in the dynamics of the network-averaged firing rate of the PY neurons , shown in Figure 1B1 for the case of focal trauma . In the local HSP model of the focal trauma , and for relatively small trauma volumes ( ) , the network-averaged firing rate of the pyramidal neurons showed a much steeper transition to its post-traumatic target value compared to the more gradual change observed within the global HSP model ( Figure 1B1 , compare solid red lines for local HSP model and dashed red lines for global HSP model ) . In contrast , after more severe trauma ( ) the approach of the network-averaged firing rate of the model PY neurons toward its post-traumatic target value was more similar for both the local and global HSP scenarios ( Figure 1B1 , black solid and black dashed lines for local and global HSP , respectively ) . The quantitative differences between the two HSP models , as reflected in the dynamics of the network-averaged firing rate of model pyramidal neurons , were discernible also within the scenario of diffuse trauma ( Figure 1B2 ) . However , in the diffuse trauma scenario , there was no qualitative difference between the firing rate reorganization dynamics in different HSP models; both local and global HSP models caused gradual recovery of firing rate for relatively small trauma volume ( Figure 1B2 , solid red and dashed red for local and global HSP models , ) and steeper transition in the case of more severe trauma ( Figure 1B2 , solid black and dashed black for local and global HSP models , ) . Thus , qualitatively , the strongest effect of HSP localization on the post-traumatic reorganization of electrical activity was observed for relatively small volumes of focal trauma . This is consistent with the results in Figures 1A1 , 1A2 , which show that the primary effect of local HSP is to lower the trauma volume threshold for burst generation and that this effect is more pronounced in the focal trauma scenario . We next explored the intriguing independence of the paroxysmal burst rate on trauma volume in a model with a local HSP rule . Several mechanisms in the new model of homeostatic plasticity could have been responsible for this observation . It could have been a consequence of normalizing the neuronal firing rates , which was implemented by downregulating postsynaptic component of HSP ( based on the firing rate of postsynaptic neuron , as suggested in [4] ) . Alternatively , the independence of burst rate on the trauma volume could follow from the local scale of the presynaptic component of the HSP , in contrast to the global , network-wide , scale of HSP employed in earlier models of late post-traumatic phase [3] , [18] , [20] . To test this second possibility , we replaced the local scale of the presynaptic HSP ( for which the averaging of firing rates was performed over the set of those model PY neurons that projected synapses to a given neuron ) with the global scale of the presynaptic HSP ( for which the averaging of firing rates was performed over all model PY neurons ) . The postsynaptic component of HSP remained local and was determined by the firing rate of the postsynaptic neuron . As shown in Figure 1C1 , this manipulation on the spatial scale of the presynaptic HSP component did not result in any significant effect on the burst rate – trauma volume relation . We then tested the possibility that the apparent independence of burst rate on trauma volume was dominated by the postsynaptic downregulating component of HSP . When the postsynaptic component of HSP was excluded from the model and the global scale scheme was used for the presynaptic component , the linear relation ( in the supra-threshold regime ) between the burst rate and trauma volume was recovered ( Figure 1C2 , open green diamonds ) . Thus , it appeared that the downregulating postsynaptic component of HSP acted as a permissive factor , either allowing or preventing the burst rate to be modulated by the spatial scale of the presynaptic HSP component . Earlier studies [3] suggested that post-traumatic paroxysmal activity arises because HSP acts to restore the firing rates of pyramidal neurons to their pre-traumatic value . Thus , we reasoned that the above dependence of burst rate on trauma volume during early stages of post-traumatic reorganization might , at least partially , be reflected in the firing rates of PY neurons . Thus , we estimated the dependence of pyramidal firing rate on the neuronal location in the network . For this analysis , neuronal firing rates were sampled from the center-symmetric strip ( cross section was 5 cells from the center of the strip ) of “neural tissue” , and at each point the firing rates of model PY neurons were averaged over the cross-section of the sampled strip . With the postsynaptic downregulating component of HSP present , the firing rate of PY neurons ( either deafferented or intact ) was clamped at ∼5 Hz and did not depend on the spatial scale of presynaptic HSP component ( Figures 1D1 and 1E1 ) . Indeed , the postsynaptic HSP component prevented firing rate of any individual PY neuron to exceed its preset target rate . The firing rate of the intact neurons never increased and the firing rate of the deafferented neurons reached the target regardless of the presynaptic HSP model . Therefore the model with global presynaptic scaling was virtually indistinguishable from the baseline model ( with focal trauma and local HSP ) and for both models the firing rate was independent on the trauma volume ( Figures 1E1 ) . When the global scale presynaptic scheme was combined with exclusion of the postsynaptic downregulating HSP component , the averaged firing rate of intact PY neurons at the traumatized-intact boundary — defined as a set of PY neurons located within one synaptic footprint from the boundary deafferented neuron ( see Materials and Methods ) — displayed strong dependence on the trauma volume parameter ( Figure 1E2 , open green diamonds ) . In this model , increase of the trauma volume led to an increase in the size of the deafferented ( less active ) PY population and , therefore , required a stronger increase in the firing rate of the intact PY population to keep the overall firing rate constant . This model allowed an increase because the postsynaptic downregulating HSP component was absent . Therefore , for intermediate and high trauma volumes ( Figure 1E2 ) , the firing rates of intact PY neurons were higher than those in the baseline model ( with focal trauma and local HSP ) and the firing rates of deafferented neurons were lower ( Figures 1D2 , black squares vs . green diamonds ) . Surprisingly , for intermediate trauma volumes ( Figure 1C2 , black squares vs . green diamonds ) the relation between the corresponding rates of paroxysmal bursts was opposite to the one observed for neuronal firing rates ( i . e . , for intermediate values of the trauma volume parameter the burst rate in the “global UP no DOWN” model was lower than the burst rate in the baseline model with focal trauma and local HSP ) . This suggests that the burst rate was limited by the firing rates of deafferented neurons; even when intact neurons fired at higher rate , they only occasionally triggered bursts in the deafferented population . Thus , although the “firing rate–burst rate” relation hypothesis could qualitatively account for the dependence of burst rate on trauma volume , it failed to explain the quantitative differences between the two HSP scenarios ( local vs . global models ) . In our previous studies we showed that , in the deafferentation model of cortical trauma , paroxysmal activity is generated by the intact pyramidal neurons located at the boundary between intact and deafferented regions [20] . Because our previous studies utilized “global HSP” model , it was important to test whether or not the same conclusions would hold as well for networks with “local HSP” scenario . Figures 2A1 , 2B1 show snapshots of spatial activity in deafferented regions of model networks ( trauma volume parameter ) , for “local HSP” ( Figure 2A1 ) and “global HSP” ( Figure 2B1 ) , and in both scenarios it is seen that paroxysmal activity propagates in a wave-like manner , from intact and into the deafferented part of the network ( in Figures 2A1 , 2B1 image boundaries correspond to the boundary between the intact and deafferented regions of a network , so that only the dynamics in deafferented regions are shown ) . In Figures 2A2 , 2B2 the spatial spread of activity is further quantified by computing and plotting , for two scenarios , the time-averaged firing rates of the model neurons . In these plots , the axis are the spatial dimensions of the network grid , and color codes the firing rate of individual neurons , averaged over a long time window ( T = 50 s ) after the network had reached its post-traumatic steady state . Destruction of synaptic connectivity between the intact and deafferented parts of the network completely eliminated paroxysmal activity ( Figures 2A3 , 2B3 ) . This confirms that paroxysmal activity in the deafferented part of the network critically depends on the existence of functional synaptic connectivity with the intact part . In our previous studies [28] we showed that the rate of post-traumatic paroxysmal bursts may be set not only by the firing rates of intact PY neurons; other determinants of collective activity include the spatial distribution of intact PY neurons and the strengths of their recurrent synapses [28] . This implies that the spatial scale of synaptic connectivity pattern — the spatial extent to which synaptic connections can be formed , as determined by the size of the synaptic footprint ( see Materials and Methods for details ) — might predispose the traumatized network to become more or less epileptogenic . Indeed , experimental evidence suggests that , following traumatic brain injury , a network is likely to undergo changes in its anatomical connectivity [17] , [19] , [29] , [30] . Further , modeling studies showed that these changes in anatomical connectivity could breach the excitation-inhibition balance and generate epileptic-like seizures [2] . Although reorganization of synaptic connectivity likely occurs on much slower time scales than the ones we study here ( days vs . hours ) , rapid and localized remodeling of synaptic connections was also reported [31] . We addressed the possible interplay of synaptic connectivity and HSP spatial scales by scaling up the size of synaptic footprint in the model . The synaptic footprint is the region from and to which a given model neuron could receive or send synaptic connections , and in the model network it was a 10×10 square centered at the neuron under consideration . As the size of synaptic footprint was scaled ( by scaling the dimensions of the square region from and to which synapses could be received/sent ) , the probability of establishing synaptic contacts inversely depended on the number of potential pre-synaptic partners , as determined by the footprint size , in order to keep the average number of synapses to a given neuron the same , regardless of the footprint size . This allowed us to avoid conflating the effects of footprint size with an increase in synaptic connectivity . As Figure 3A1 shows , the rate of paroxysmal burst generation was smaller for larger synaptic footprint sizes ( parameterized as the half-length of square side ) . This reduction in burst rate was paralleled by an increase in the rate of neuronal firing during the burst , which in turn stemmed from an increase in the number of spikes fired during the burst ( Figures 3B1–3 for sample burst profiles , Figures 3C1 , 2 for quantification of intra-burst spiking activity ) . By contrast , within the global HSP scheme , manipulations of the synaptic footprint size averaging activity over all model PY neurons had a much weaker effect on the burst-rate trauma-volume relation ( Figure 3A2 ) . Because burst nucleation in our model required the activity of a certain fraction of intact neurons to be sufficiently correlated ( in order to be able to “ignite” their deafferented postsynaptic partners ) [28] , a reduction in the rate of paroxysmal discharge could signal reduced correlation between burst-triggering intact neurons . However , correlation between activities of intact neurons on the boundary did not exhibit any remarkable dependence on the size of synaptic footprint ( Figure 3D1 ) . The correlation between activities of deafferented neurons did grow up with the increasing size of synaptic footprint ( Figure 3D2 ) . Thus , the reduction in burst rate that was observed for a larger synaptic footprint did not depend on the reduced correlation between burst-igniting neurons . Another possibility is that a reduced rate of burst generation reflects higher heterogeneity in interconnectedness and synaptic weights for synapses formed among neurons on the boundary between intact and deafferented regions . Indeed , distributions of HSP scaling factors at PY-PY synapses in post-traumatic steady state ( Figure 3F ) were characterized by larger standard deviations for scenarios with larger footprint sizes ( Figure 3E ) . These results suggest that heterogeneity of interconnectedness and synaptic conductances at the intact-deafferented boundary could help to alleviate the onset of paroxysmal bursting activity , but this comes at the expense of more intense spiking activity during the burst . Assuming that the heterogeneity of synaptic organization at the boundary between traumatized and intact regions is likely to be important in post-traumatic epileptogenesis , we sought to identify the physiological mechanisms that might mediate this effect . Experimental evidence suggests that homeostatic scaling of synaptic conductances might be at least in part mediated by the soluble tumor necrosis factor alpha ( TNFα ) that is believed to be released from astrocytes to compensate for low levels of glutamatergic synaptic activity [8] . It is well established that astrocytes can sense glutamatergic synaptic activity and respond to it with diverse spatio-temporal patterns of free cytosolic calcium [32] , [33] . Although a typical astrocyte contacts ∼100 , 000 synapses [34] , in a recent study , the calcium-mediated detection and modulation of synaptic release by astrocytes under physiological conditions was local , with regulation occurring independently along astrocytic processes ( branches ) in groups of 10 s of adjacent synapses [27] . These findings are consistent with the notion of astrocytic microdomains , with each microdomain responsible for the autonomous regulation of a small cluster of spatially proximal synapses [25] . Note that microdomains are morphological feature of astrocytes , and thus astrocytic microdomain should not necessarily contact synapses for regulation; however , any synapse that is regulated by an astrocyte belongs , by definition , to unique astrocytic microdomain . Spatial localization of astrocytic signaling may translate into autonomous regulation of groups of synapses . Since we consider here the early stage of post-traumatic response ( when a relatively high glial TNFα concentration is likely to be spatially constrained to its release sites ) such autonomous regulation could increase the heterogeneity of synaptic conductances scaled by glia-mediated HSP . Thus , we hypothesized that functional segregation of synaptic inputs into astrocytic microdomains could help alleviate the rate of paroxysmal discharges in our model networks . To test this hypothesis , for each model PY neuron the set of all collateral synapses to it ( from PY and IN neurons ) was randomly partitioned into groups ( microdomains ) , such that on average a group of synapses constituted a microdomain ) . Homeostatic scaling of synaptic conductances ( both glutamatergic and GABAergic ) for each astrocytic microdomain was determined independently by the time-averaged activity of glutamatergic synapses in it ( according to Equations 11 , 12 ) . Several computational models were developed to describe interactions between astrocytes and synapses [35] , [36] , [37]; however , these models linked increased levels of synaptic activity to calcium elevations in astrocytes , and thus cannot explain how low levels of synaptic activity could culminate in astrocytic release of TNFα . Rather than attempting to develop a detailed mathematical model to describe this process , we assumed here that the ultimate effect of astrocytic microdomain activation is to scale synaptic conductances according to Equations 11 , 12 . This approximation allowed us to avoid introducing additional complexity associated with biochemical cascades of activation in astrocytes [37] and to focus on the long-term network effects of interactions between neurons and astrocytes . Figure 4A shows the dependence of paroxysmal discharge rate on the trauma volume , for several scenarios in which synaptic input to each model PY neuron was partitioned into several microdomains . We considered here scenarios of focal trauma . For values of trauma volume above a critical threshold , the burst rate still did not depend on the volume of trauma but the plateau value of paroxysmal burst rate now depended on the number of microdomains into which synaptic input set was partitioned . When plotted vs . the number of microdomains ( for the same trauma volume ) , the burst rate monotonically decreased for larger numbers of microdomains ( Figure 4B ) , and reached an asymptotic level of ∼0 . 3 Hz for microdomains , corresponding to a situation in which each synapse to a PY neuron was associated with an unique microdomain ( each model PY neuron received , on average , 55 synapses from its fellow PY model neurons , and the maximal number of glutamatergic synapses per PY neuron was 75 ) . For values , some microdomains had zero “synaptic occupancy” ( i . e . , they had no synapses to regulate ) and thus did not take part in homeostatic synaptic plasticity . Notably , for the same trauma volume , the burst rate that emerged as a result of diffuse trauma also depended on the number of microdomains , but this dependence was much weaker compared to that of the corresponding focal trauma ( Figure 4B , compare closed squares and open circles ) . Thus , even though diffuse trauma resulted in a lower rate of bursts in the model with one microdomain , for strongly segregated set of synaptic input it resulted in more frequent bursting than did the focal trauma . The averaged intra-burst firing rates of PY and IN model neurons were higher for stronger segregation of synaptic input into microdomains ( Figure 4C1 ) , as were the average numbers of spikes fired by model neurons during the burst ( Figure 4C2 ) . Because the firing rates of model PY neurons in our model could influence the outgoing synaptic conductances through the presynaptic part of HSP rule , we also computed the mean HSP scaling factor separately for the set of PY-PY synapses arriving from deafferented model PY neurons and the set of PY-PY synapses arriving from intact model PY neurons . The value of the HSP scaling factor is directly proportional to the value of synaptic conductance after scaling , and thus could be taken as a measure of how much the outgoing synaptic conductance of the deafferented vs . intact model PY neurons changes as a function of the number of microdomains and the pattern of trauma . Figure 4C3 shows that the mean HSP scaling factor shows increasing trend as a function of for excitatory input from deafferented neurons , but decreases with larger for excitatory input from intact neurons . This effect is qualitatively the same for either diffuse or focal trauma scenarios ( Figure 4C3 , closed vs . open symbols ) . The effect of microdomain partitioning in reducing the rate of paroxysmal bursts was further seen by visual inspection of network activity raster plots ( Figures 4D1 , 2 , 3 ) . This suggested that the underlying effect of stronger input segregation on paroxysmal burst rate could be similar to that of altered synaptic footprint size ( Figure 3A1 ) – namely , that increased heterogeneity of synaptic input would lead to the decreased burst rate . Indeed , as Figure 4E1 shows , increasing the synaptic footprint size resulted in the downward offset of burst rate , consistent with the results shown in Figure 3A1 . Both the mean and the standard deviation of the HSP scaling factor at PY-PY synapses were in general higher for larger synaptic footprint size , for all values of microdomains considered ( Figures 4E2 , 3 ) . The mean value of HSP scaling factor at PY-PY synapses was nearly independent of , while its standard deviation was generally higher for larger ( Figures 4E2 , 3 ) . Segregation of synaptic input into microdomains allows a more independent scaling of the inputs from deafferented and intact neurons and thus enhances the correspondence between the firing rate of a given presynaptic neuron and the resulting homeostatic scaling of its downstream synaptic conductance . As a result , in segregated inputs scenario , synaptic conductance from intact neurons is weaker than synaptic conductance from deafferented neurons ( Figure 4C3 ) . On the other hand , the postsynaptic component of HSP scales all of synaptic conductances ( from both deafferented and intact neurons ) by the same amount . Thus , the role of intact neurons in burst generation is weaker ( by virtue of their weaker synaptic conductance ) , but intra-burst firing becomes more intense ( partially because of the stronger synaptic scaling in deafferented neurons ) . Thus , random segregation of synaptic input into microdomains acted to reduce the rate of paroxysmal discharges via a HSP-mediated increase in the variance of the synaptic scaling distribution . Results reported in the previous section suggest that functional segregation of homeostatic synaptic scaling by astrocytes has the potential to alleviate the rate of paroxysmal burst discharges in post-traumatic network albeit the reduction in burst rate is relatively small when only a small number of microdomains is considered . Remarkably however , astrocytes in injured cortex also undergo significant rapid morphological remodeling [26] . Specifically , in the ferrous chloride model of trauma-induced epilepsy , astrocytes that were located relatively close ( 200 microns ) to the boundary between intact and injured cortical regions lost their trademark star shape and elongated in the direction perpendicular to the trauma boundary [26] . Accordingly , the astrocytes at the boundary between intact and injured regions were termed “palisading astrocytes” , to distinguish from “hypertrophic astrocytes” that were located in intact part of the network and still retained their “star shaped” morphology to some extent ( Figure 5A ) . Similar reorganization of astrocytes has also been observed in the kainate-induced epilepsy model [26] , suggesting that it may represent a generic response of astrocytes to the trauma-induced alterations in neuronal activity . Because astrocytic morphology critically determines its ability to sense synaptic activity ( and inactivity ) such trauma-induced reorganization might have important implications for post-traumatic epileptogenesis . To model the role of astrocytic morphological reorganization in trauma induced epileptic like activity , we used the microdomains scheme ( as described in Materials and Methods and above ) to model the presynaptic component of HSP and further assumed that synaptic input arriving to a specific model PY neuron was subdivided into two microdomains . One microdomain included the synapses exclusively from intact presynaptic neurons , and the other microdomain included synapses exclusively from deafferented presynaptic neurons ( Figure 5B for schematic ) . This was a critical assumption and it derived from the observation that in the experimental model of trauma the “palisading astrocytes” were aligned perpendicular to the boundary separating the intact and traumatized parts of cortical tissue ( Figure 5A ) . We further assumed that this orientation allows for a better segregation of synaptic input into distinct groups ( inputs arriving from traumatized neurons vs . inputs arriving from relatively intact neurons ) . The postsynaptic component of HSP was modeled according to Equations 11 , 12 . In the focal trauma scenario , the rate of paroxysmal bursts was significantly lower for the scenario of “segregated inputs” ( compared to the model with one microdomain ) , and this difference was observed for a wide range of trauma volumes considered ( Figure 5C1 ) . For comparison , in diffuse trauma model , the segregation of synaptic input did not have any significant effect on the burst rate trauma volume relation ( Figure 5C2 ) . Firing rates of PY neurons varied depending on the neuronal location in the network ( Figure 5D1 , variation of firing rate along X location ) . The mean ( Figure 5D2 ) and the standard deviation ( Figure 5D3 ) of the PY-PY HSP scaling factor ( computed individually for each model PY neuron ) also showed strong dependence on neuronal location , with neurons on the intact-traumatized boundary having zero mean HSP and strong variability in synaptic conductances ( Figures 5D2 , 3 ) . The average over the population of model PY neurons of the mean HSP scaling factor was positively correlated with the trauma volume , and its value in the segregated inputs scenario was somewhat higher than that obtained for the model with one microdomain ( Figure 5E1 ) . The average ( computed over the population of model PY neurons ) standard deviation of the HSP scaling factor was also positively correlated with the trauma volume , and its value in the segregated inputs scenario was significantly higher than that obtained for the model with one microdomain ( Figure 5E2 ) . As expected , the reduction in burst rate was paralleled by an increase in the average number of spikes fired per burst ( Figure 5F1 ) , as well as by an increase in intra-burst spiking rate ( Figure 5F2 ) of model PY and IN neurons .
In our previous studies we showed that the pattern of trauma can itself determine the threshold for post-traumatic paroxysmal activity [20] . These observations were also qualitatively reproduced in the present study of early post-traumatic reorganization driven by spatially local HSP rule . In particular , in focal trauma scenarios paroxysmal activity emerged for lower values of trauma volume parameter as compared to the diffuse trauma scenarios ( Figure 1 ) . In addition , in focal trauma scenario the rate of paroxysmal discharges did not depend on the trauma volume , but showed strong dependence on it in diffuse trauma cases ( Figure 1 ) . A simple explanation of these simulation results would be as follows: In focal trauma and spatially local HSP rule , neurons at the boundary between intact and deafferented regions get ∼50% of their synaptic input from other intact neurons and another ∼50% from deafferented neurons . Because this breakdown does not depend on the trauma volume , and because paroxysmal bursts are generated at the boundary between intact and deafferented regions [20] , the burst rate is not expected to depend on the trauma volume . Conversely , for diffuse trauma and local HSP , the breakdown of synaptic input from intact/deafferented neurons monotonically increases ( in favor of deafferented neurons ) with trauma volume , thus contributing to the increase in burst rate . We showed earlier [20] that the propagation of paroxysmal events is undermined in diffuse trauma , where asynchronous activity of intact neurons helps to “dissipate” the correlated firing associated with the network burst . Together with the present results , this suggests that the relative role of trauma volume vs . functional segregation of synaptic input depends on the pattern of trauma , with focal trauma allowing for a more efficient “containment” of paroxysmal activity by functional input segregation . We suggest that functional segregation can be achieved by the morphological reorganization of astrocytes , similar to what was observed in some recent experiments [26] . It is widely recognized that astrocytes assume a critical role in different kinds of epilepsies [38] . Computational modeling suggested that glutamate signaling from astrocytes to neurons may drive spontaneous neuronal oscillations [35] and give rise to paroxysmal depolarization shifts as often seen in epilepsy [39] . Recent experimental study confirmed these earlier modeling results by directly demonstrating that a positive feedback loop between neurons and astrocytes can drive neurons to seizure threshold [40] . In our own models of post-traumatic epileptogenesis [3] , [18] , [20] , paroxysmal activity is a consequence of homeostatic synaptic plasticity , which is mediated in part by TNFα that is released by astrocytes in response to neuronal inactivity [8] . All of the above mechanisms of astrocytic involvement in epileptogenesis are based on abnormal variations in neurotransmitter/cytokine signaling . By contrast , we showed here that structural reorganization of synaptic input regulation by astrocytes could constitute a contra-convulsive mechanism . It is tempting to speculate that such a seizure-suppressing program is switched on a short time after the traumatic event to compensate for pro-seizure influences of neuroinflammation; however , to fully address this issue , more refined clinical data ( showing , for example , the relative timing of TNFα release vs . post-traumatic morphological reorganization of astrocytes ) is needed . The main clinically relevant prediction of our model is that a local homeostatic regulation of synaptic activity by astrocytes can lead to distinct network behavior ( compared to the global homeostatic regulatory process ) . This prediction can be tested by targeting glial fibrillary acidic protein ( GFAP ) , which is a common biological marker of trauma-induced morphological transformation of astrocytes and is dramatically increased during reactive gliosis . GFAP helps astrocytes to maintain mechanical strength and thus is instrumental in determining the cell shape and spatial distribution of finer astrocytic processes ( microdomains ) for synaptic regulation . Thus , our model would predict a higher incidence of seizures in trauma models of GFAP knockout animals . A higher incidence of seizures should occur following failure of astrocytic microdomains to reorganize after trauma . Consistent with this prediction , one experimental study reported that hippocampi of GFAP knockout mice exhibited higher sensitivity to kainate-induced seizures [41] . We predict that this GFAP deficiency affects seizure susceptibility via failed regulation of synaptic conductance by astrocytic microdomains . The pathological action of homeostatic synaptic plasticity studied here is only one of the several known mechanisms of epileptogenesis . A common , long-recognized , cause of epileptic seizures is impaired clearance of extra-cellular potassium ions [42] , [43] , [44] . During intense bouts of neuronal activity extracellular potassium may rise to relatively high levels ( 10–12 mM ) thus further depolarizing the neurons and contributing to the onset of seizure [44] , [45] . The predominant mechanism of extracellular potassium clearance is through its reuptake and spatial buffering by astrocytic inward rectifying potassium channels [46] . In fluid percussion model of traumatic brain injury , glial contribution to extra-cellular potassium homeostasis is controversial . Some studies ( e . g . [47] , [48] ) reported alteration in glial uptake of potassium; results of another study suggest that glial contribution to potassium uptake is not altered immediately after trauma [49] . Because the relative apposition of glial potassium channels and neurons is likely to depend on the spatial orientation and cell shape of astrocytes , it is plausible that the spatial pattern of extracellular potassium is further affected as a result of astrocytic reorganization . However , whether reactive astrocytes become more efficient in potassium clearance remain to be shown explicitly . Trauma-induced morphological reorganization of astrocytes , as well as their release of cytokines and gliotransmitters , is part of “reactive gliosis” , a complex set of processes whereby astrocytes undergo various molecular and morphological changes [50] . Because of its role in the formation of glial scar that prevents axon regeneration , reactive gliosis has been associated with the detrimental effects of trauma-induced reorganization of neural circuitry . However , emerging evidence ( reviewed in [50] ) indicates that reactive astrocytes can have both beneficial and detrimental effects on post-traumatic reorganization . Management of post-traumatic epilepsy and related convulsive disorders is often done with a variety of anti-epileptic drugs [51] . In particular , phenytoin and/or sodium valproate therapy can prevent early posttraumatic seizures [52] , [53] . It was shown that sodium valproate inhibits production of TNFα through inhibition of NF-κB [54] . Extensive experimental data implicating the role of TNFα in seizure generation ( reviewed in [16] ) and results of our modeling studies thus provide an explanation with regard to the mechanistic action of valproate in early post-traumatic seizure suppression . Interestingly , valproate was found to be less efficient in suppression of late post-traumatic seizures [52] . This may imply that the trauma-induced astrocyte-mediated TNFα signaling possibly represents one out of several pathways of post-traumatic homeostatic regulation that tends to reorganize the network in response to chronic changes in electrical activity . Indeed , other mechanisms , such as trauma-induced changes in anatomical connectivity , have been implicated in post-traumatic epileptogenesis [2] , [17] , [19] , [30] , [55] . These mechanisms are likely to operate on much slower time scale than regulation by glial TNFα . The multiple temporal scales of post-traumatic HSP could thus explain the fact that anti-epileptic drugs are more efficient during early post-traumatic period ( when they target specific pathway ) as opposed to their relative inefficiency during late post-traumatic period ( when other HSP pathways are activated ) . Synaptic activity can be increased or decreased by molecules released from astrocytes and vice versa . In particular , accumulating evidence indicates that endocannabinoids ( eCB ) might be involved in compensatory mechanisms to offset the effects of trauma [56] . Endocannabinoids are released from neurons following intense neuronal activity . Recently it was shown that endocannabinoids released from hippocampal neurons can cause phospholipase C dependent calcium elevation in adjacent astrocytes through activation of astrocytic CB1 receptors [57] . The endocannabinoid-mediated activation of astrocytes stimulated the release of glutamate from astrocytes that further promoted the excitability of postsynaptic neurons . On the other hand , application of endogenous cannabinoid was shown to suppress TNFα formation through inhibition of nuclear factor kappa beta ( NF-kB ) after traumatic brain injury in a CB1-dependent manner [58]; signaling through this pathway is likely to decrease neuronal excitability . Thus , astrocyte-endocannabinoid interaction can contribute to post-traumatic reorganization in a complex manner . How this interaction contributes to the regulation of paroxysmal activity remains to be investigated [59] . Consistent with this emerging evidence , and based on our modeling results , we propose two opposing roles for reactive astrocytes in early post-traumatic epileptogenesis . Specifically , we propose that the release of TNFα promotes the generation of paroxysmal bursts , and that a post-traumatic morphological reorganization of astrocytes acts to suppress bursting activity at the expense of less frequent , but more intense , paroxysmal bursts . In this conceptual model the reorganization of astrocytes might be an adaptive step aimed at reducing the pro-convulsive effects of TNFα . Interestingly , in the ferrous chloride model of epilepsy , seizure suppressing drugs led to a significant reduction in the extent of seizure-related morphological transformation of astrocytes [26] . Thus , seizure itself appears to be a causative factor behind astrocytic reorganization . It is conceivable then that different components of reactive gliosis are coordinated in a way that aims to maintain minimal risk of seizures incurred by the activation of astrocytes . Biochemical dissection of these components and relations between them may help in understanding the causes of post-traumatic epileptogenesis .
A cortical network was modeled as a 2D network on square lattice ( 80×80 neurons ) in which each neuron could establish synapses with its peers with probability within its local footprint ( a square 10×10 neuron region from and to which a neuron could receive or send synaptic connections ) . Model pyramidal neurons received , on average , 55 synapses from other model PY neurons and 12 synapses from model IN neurons . The distribution of synaptic inputs to model PY neurons is shown in Figure 6 . The synaptic footprint of each neuron was centered on the neuron , and the size of the footprint was given by dimensions of the corresponding square region . Pyramidal neurons accounted for 80% of network population ( 5120 out of 6400 neurons ) , and inhibitory neurons constituted the remaining 20% ( 1280 out of 6400 neurons ) . Inhibitory neurons were distributed regularly on the lattice , such that every 5th neuron was inhibitory . Our goal was to understand the general responses of a cortical network to traumatic perturbation and therefore specific features pertaining to specific cortical layers were not included in the model . The dynamics of neurons were modeled with the one compartmental Morris-Lecar model [60] , as described in detail elsewhere [20] , [28] . Briefly , the equations that governed the neuronal dynamics were: ( 1 ) ( 2 ) ( 3 ) ( 4 ) Phenomenological spike frequency adaptation current was added to model PY neurons to account for the experimentally observed spike frequency adaptation: ( 5 ) ( 6 ) Synaptic currents at PY-PY synapses had both AMPA and NMDA components , with both AMPA and NMDA conductance attenuated by synaptic depression as described below . Inhibitory synaptic currents did not incorporate synaptic depression . Synaptic transmission was modeled as a deterministic process , during which synaptic conductance rose instantaneously following the spike and relaxed , with the characteristics time , to zero: ( 7 ) The value of maximal synaptic conductance , , depended on the pre- and postsynaptic neurons . Thus , ( maximal synaptic conductance from pyramidal neuron to pyramidal neuron ) was different from ( maximal synaptic conductance from pyramidal neuron to inhibitory interneuron ) . Values of synaptic conductance are given in Table 1 . The temporal dynamics of the NMDA conductance was modeled as a difference of fast ( ) and slow ( ) exponentially decaying components: ( 8 ) ( 9 ) The parameter accounted for the efficacy of synaptic transmission . For GABAergic synapses , this parameter was held fixed ( D = 1 ) . For excitatory AMPA and NMDA synapses , it evolved according to the following equation , with representing the strength of synaptic short-term depression: ( 10 ) Values of parameters are given in Table 1 . In the intact network with no deafferentation model pyramidal ( PY ) and inhibitory ( IN ) neurons fired with average rates of 5 and 10 Hz , respectively . In addition to network current , each model neuron received an excitatory current from “the rest” of the cortex ( afferent excitation ) . Synaptic conductance of this current evolved according to: , with . This synaptic conductance was stimulated randomly at times at the baseline Poisson rate of . Trauma was modeled as cortical deafferentation , following which the frequency of external ( afferent ) excitation to a fraction of model neurons ( both PY and IN ) was reduced to 10% of its value in the intact model ( from 100 Hz in intact model to 10 Hz in the deafferented state ) . The parameter represents the fraction of deafferented ( injured ) neurons and can be thought of as being proportional to the relative volume of deafferented neurons; thus , we refer to this as the “volume of trauma” parameter . As in our previous studies , we considered scenarios of focal and diffuse trauma . In focal trauma , the deafferented neurons were organized in a contiguous block ( Figure 1A1 , right ) . In diffuse trauma , the deafferented neurons were picked up at random from the entire model network ( Figure 1A2 , right ) . Recent experimental evidence indicates that TNFα is a permissive , rather than instructive , mechanism that allows the synapses to express homeostatic synaptic plasticity [61] . Thus , our present implementation of HSP aimed to account for both the possible differential nature of up- vs . down- regulation of synaptic conductance and for the permissive ( rather than instructive ) nature of TNFα signaling . Specifically , we assumed the following mathematical form for the HSP at AMPA synapses of PY-PY pairs: ( 11 ) In Equation 11 , is the convergence rate of the homeostatic update and is a preset “target rate” of pyramidal neuron firing ( our HSP equation was only applied to model pyramidal neurons ) , typically set at . Upregulation of excitatory synaptic conductance on model PY neuron could occur if the average firing rate in the set of presynaptic partners ( collateral pyramidal neurons that project synapses to a given neuron ) was below the preset target rate . This regime corresponds to the release of TNFα from glial cells , which is believed to be determined by the levels of synaptic activity in the proximity of these cells ( our implicit assumption is that synaptic activity scales with the firing rate of neurons that generate this synaptic activity ) . By contrast , downregulation of excitatory synaptic conductance on model PY neuron could occur if the firing rate of a neuron under consideration was above the preset target rate . This modeling assumption stems from the fact that TNFα can only upregulate excitatory synaptic conductance; thus , down regulation of synaptic conductance likely depends on the firing rate of postsynaptic neuron [5] . It is also consistent with earlier findings regarding the role of neuronal activity in downregulation of synaptic conductances onto it [62] . The update scheme for GABA synapses on model pyramidal neurons is the opposite of that of the AMPA synapses on model pyramidal neurons ( the average over the presynaptic set was still taken over the presynaptic set of PY model neurons ) ( 12 ) Schematic presentation of homeostatic plasticity rules for up- and down regulation of synaptic conductances is given in Figure 7A . The extent of per synapse homeostatic adjustment was computed as percentage of change in synaptic conductance relative to its value in the corresponding intact model . Taking PY-PY synapse as an example , where T is the time after the network had reached its new post-traumatic steady state . In some simulations , we investigated the effect that functional segregation of synaptic input into microdomains might have on the post-traumatic reorganization of electrical activity in cortical network . For each model PY neuron , the entire set of synapses to it was randomly and equally partitioned into groups , each group on average consisting of synapses . Cortical neurons receive ∼8 , 000 synapses [63] . In the model network , each neuron received on average ∼80 synapses . Thus , each model synapse can be thought of as representing a group of ∼100 synchronously activated biological synapses , consistent with small ( ∼1% ) amount of synchrony present at any time in cortical input [64] . The number of microdomains , , was varied from ( corresponding to the case when all synaptic input is lumped into single astrocytic microdomain ) to ( corresponding to the case when each microdomain is associated with at most 1 model synapse ) . It was shown that in the cortex , each astrocytic domain can cover up to 80 microns of dendritic length [65]; taking linear spine density 1 . 0–1 . 5 spines/micron [66] , it follows that each domain can be associated with up to ∼120 synapses . Thus , the case ( 1 model synapse per microdomain , 1 model synapse = ∼100 biological synapses ) yields values consistent with the experimental findings ( up to ∼120 biological synapses per microdomain ) . A schematic diagram for the case is shown in Figure 7B . The presynaptic component of HSP was computed for each one of these microdomain groups separately , as in Equations 11 , 12 , with being the firing rate averaged over all model PY neurons that belonged to that same microdomain . Downregulating component of HSP was computed as in Equations 11 , 12 , based on the firing rate of postsynaptic neuron . Several models of astrocyte-synapse interaction [35] , [36] , [37] have linked increased levels of synaptic activity to astrocyte calcium elevation . Here , we focused on astrocytic responses to synaptic inactivity . Thus , existing models cannot explain post-traumatic activation of astrocytes . Rather than attempting to develop a detailed mathematical model to describe the response of astrocytes to synaptic inactivity , we assumed here that the ultimate effect of astrocytic microdomain activation was to scale synaptic conductances according to Equations 11 , 12 . This assumption allowed us to avoid introducing additional complexity associated with biochemical cascades of astrocyte activation [37] and to focus on the long-term network effects of neuron-astrocyte interaction . In a separate set of simulations we modeled correlated segregated inputs , whereby the entire set of synapses to each model PY neuron was partitioned into two groups ( two microdomains , ) with synapses in one microdomain associated with the inputs from deafferented neurons , and synapses in another microdomain associated with the inputs from intact neurons . Following deafferentation , homeostatic synaptic plasticity transformed asynchronous spiking to paroxysmal bursts . Thus , we adopted the rate of paroxysmal burst generation as a measure of network's propensity to exhibit the transition to seizures . Paroxysmal bursts of highly correlated population activity in our model resembled interictal epileptiform discharges ( IEDs ) , which are often considered as an important diagnostic feature of epileptic seizures [22] , [23] , [24] . Thus , a higher rate of population bursting in a post-traumatic network model was considered as an indicator of stronger propensity to seizures . Paroxysmal bursting events were detected as previously described in [20] . First , the entire simulation time period was partitioned into non-overlapping bins of 100 milliseconds each . Based on this binning , the spike count per bin for each model neuron was obtained . A paroxysmal bursting event was registered in time bin if at least of recorded model neurons ( both pyramidal neurons and interneurons ) fired action potentials during this time bin , with an average rate of firing greater than the threshold rate . This operational definition was constrained by the minimal fraction of active neurons , , that defined the paroxysmal burst , and by the minimal intra-burst firing rate , , of these active neurons . We set and . The large size of our model network ( 6 , 400 neurons ) made analysis of the entire network computationally intractable; thus , we sampled the activity of a subset of neurons ( both pyramidal neurons and interneurons , from both deafferented and intact regions ) , using this sample to estimate the rate of paroxysmal bursts in the network . In the case of a diffusely traumatized network ( spatially random deafferentation ) , the sampling region was a square block ( usually 20×20 model neurons ) co-centered with the center of the 2D network because spatially random deafferentation resulted in activity roughly symmetric with respect to the center of the lattice . In the case of a focally traumatized network ( spatially structured deafferentation ) , the sampling region was composed of 5 parallel adjacent lines ( resulting in a total of 400 model neurons ) because the activity generally propagated from intact regions into deafferented regions . In our earlier studies we showed that , in the deafferentation model of post-traumatic epileptic activity , the paroxysmal activity is generated by model pyramidal neurons with partially intact connectivity that are located at the boundary between intact and deafferented regions [20] . Consequently , activity generated at the boundary by intact neurons takes the shape of paroxysmal bursts ( waves ) that propagate into the deafferented part of a network . In the present study , we quantified some characteristics of network organization ( e . g . , mean and standard deviation of HSP scaling factors ) and neural activity ( e . g . , cross-covariance between activities of different neurons ) at the network boundary . The boundary was operationally defined as a set of intact neurons located within one synaptic footprint from the boundary deafferented neuron .
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Homeostatic plasticity refers to the ability of neurons and neuronal circuitry to adjust their properties in order to maintain physiologically relevant electrical activity notwithstanding perturbations in synaptic input . Synaptic input is often chronically reduced immediately following brain trauma , and previous studies had suggested that homeostatic synaptic plasticity can aid in the dynamical transition of the traumatized network toward epileptic seizures , a condition known as “post-traumatic epilepsy” . This form of homeostatic plasticity is mediated by glial cells which release regulatory molecules shortly after trauma . In this study we used computational modeling to investigate the mechanisms and the implications of glial mediated plasticity early after trauma . We show that astrocytes ( a subtype of glial cells ) exert both beneficial and deleterious effects on post-traumatic reorganization of neural activity . This suggests that , in the dysfunctional neuronal network , some aspects of glial-neuronal signaling could alleviate the dynamical transition to pathological activity .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"biochemistry",
"theoretical",
"biology",
"neurological",
"disorders",
"neurology",
"biology",
"computational",
"biology",
"neuroscience"
] |
2013
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Divide and Conquer: Functional Segregation of Synaptic Inputs by Astrocytic Microdomains Could Alleviate Paroxysmal Activity Following Brain Trauma
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Acute Epstein-Barr virus ( EBV ) infection is the most common cause of Infectious Mononucleosis . Nearly all adult humans harbor life-long , persistent EBV infection which can lead to development of cancers including Hodgkin Lymphoma , Burkitt Lymphoma , nasopharyngeal carcinoma , gastric carcinoma , and lymphomas in immunosuppressed patients . BARF1 is an EBV replication-associated , secreted protein that blocks Colony Stimulating Factor 1 ( CSF-1 ) signaling , an innate immunity pathway not targeted by any other virus species . To evaluate effects of BARF1 in acute and persistent infection , we mutated the BARF1 homologue in the EBV-related herpesvirus , or lymphocryptovirus ( LCV ) , naturally infecting rhesus macaques to create a recombinant rhLCV incapable of blocking CSF-1 ( ΔrhBARF1 ) . Rhesus macaques orally challenged with ΔrhBARF1 had decreased viral load indicating that CSF-1 is important for acute virus infection . Surprisingly , ΔrhBARF1 was also associated with dramatically lower virus setpoints during persistent infection . Normal acute viral load and normal viral setpoints during persistent rhLCV infection could be restored by Simian/Human Immunodeficiency Virus-induced immunosuppression prior to oral inoculation with ΔrhBARF1 or infection of immunocompetent animals with a recombinant rhLCV where the rhBARF1 was repaired . These results indicate that BARF1 blockade of CSF-1 signaling is an important immune evasion strategy for efficient acute EBV infection and a significant determinant for virus setpoint during persistent EBV infection .
Acute Epstein-Barr virus ( EBV ) infection is the most common cause of Infectious Mononucleosis ( IM ) . Once infected , EBV persists in rare peripheral blood lymphocytes for the life of the host [1] . Almost all humans are persistently EBV infected by adulthood , and persistent EBV infection is almost always asymptomatic as long as host immunity is intact . The number of virus-infected peripheral blood lymphocytes , or virus setpoint , during persistent EBV infection is stable over time [2] . However , in rare instances , persistent infection leads to EBV-associated cancers such as Hodgkin lymphoma , Burkitt lymphoma , nasopharyngeal carcinoma , gastric carcinoma , and B cell lymphomas in immunocompromised people [1] . How virus setpoints are established , how cancer develops from persistent EBV infection , and how virus setpoints affect cancer development remain important unanswered questions . EBV infection of peripheral blood lymphocytes in tissue culture has provided detailed knowledge for the molecular events associated with B cell growth transformation and virus replication [1] . Less well understood are the dynamics of virus infection in humans where EBV must penetrate the oral mucosa and amplify itself during acute infection to gain access and establish persistent , latent infection in the peripheral blood B cell compartment . The lack of small animal models that can accurately reproduce the biology of acute and persistent EBV infection has limited investigation of the relationship between acute and persistent phases of infection , as well as identification of determinants for EBV infection outcomes . Most non-human primates are infected with a herpesvirus that is closely related to EBV and shares the biologic features of EBV infection [3] . Infection of rhesus macaques with their EBV-related herpesvirus , or lymphocryptovirus ( LCV ) , provides a unique opportunity for experimental studies of EBV pathogenesis [4] . The rhLCV genome is colinearly homologous to EBV [5] , and the biology of natural rhLCV infection is similar , if not identical , to EBV infection of humans , eg oral transmission , acute viral load with establishment of life-long persistent infection , and development of virus-induced malignancies after immunosuppression [3] . Additionally , the rhesus macaque cellular and humoral immune responses to rhLCV infection closely mirror those of EBV-infected humans [6]–[9] . rhLCV-naive macaques can be experimentally infected by oral inoculation , reproducing the natural route of transmission followed by acute , persistent , as well as malignant LCV infection in association with Simian Immunodeficiency Virus ( SIV ) infection that appears indistinguishable from EBV infection of healthy and Human Immunodeficiency Virus ( HIV ) -infected humans [4] , [10] . Experimental animal models are important for dissecting the consequences of host-pathogen interactions , especially viral proteins that modify innate or adaptive immune responses . EBV encodes at least five proteins capable of modifying host immunity to EBV infection . All five viral proteins are expressed during replicative , but not latent , infection indicative of their importance for disruption of host immune responses to viral replication . Three EBV proteins interfere with Major Histocompatibility Complex ( MHC ) class I mediated antigen presentation ( BNLF2a , BILF1 , and BGLF5; [11]–[13] ) , whereas a fourth EBV protein , BCRF1 , is an IL-10 homologue [14] . A fifth protein , BARF1 , is secreted from infected cells and acts as a soluble Colony Stimulating Factor-1 ( CSF-1 ) receptor to block CSF-1 mediated signaling , a pathway of innate immunity not known to be targeted by other viruses [15] . CSF-1 is a cytokine important for macrophage production , differentiation , and function , as well as for bone and placental development [16] . BARF1 is a 29 kda monomer which forms a novel hexameric ring to bind CSF-1 [17] and interferes with CSF-1 signaling by multiple pathways including sequestration of cytokine , interference with the receptor-binding surface , and induction of a conformational change preventing interaction with its native receptor [18] . BARF1 functionally blocks CSF-1-induced macrophage proliferation [15] and interferon alpha production from mononuclear cells in vitro [19] . Tissue culture studies with EBV and rhLCV mutants have established that BARF1 is not essential for viral replication or B cell immortalization [19] , [20] . The evolution of BARF1 homologues in Old World non-human primate LCV [5] , but non-essential role for BARF1 in vitro indicates that BARF1 has an important role in natural host infection . To better understand the role of BARF1 in EBV infection , we mutated the BARF1 homologue in rhLCV to study the effect on rhesus macaque infection .
In order to test the importance of rhBARF1-mediated CSF-1 blockade in acute and persistent rhLCV infection , three rhLCV-naïve rhesus macaques were orally inoculated with 106 transforming units ( TU ) of a recombinant rhLCV ( ΔrhBARF1 ) carrying a truncated rhBARF1 previously shown to be incapable of blocking CSF-1-mediated signaling [20] . Successful penetration of the oral mucosa and invasion of the peripheral blood was evaluated by reverse-transcriptase-mediated PCR ( RT-PCR ) amplification for the rhLCV homologue of the small EBV-encoded RNAs ( rhEBER ) in peripheral blood mononuclear cells ( PBMC ) . EBER are abundantly expressed in LCV-infected B cells , with approximately 100 , 000 copies per cell [21] , making rhEBER RT-PCR an extremely sensitive assay for the detection of rare rhLCV-infected cells in the peripheral blood [22] . PBMC were isolated from weekly peripheral blood samples and distributed into multiple aliquots , with the number of cells per aliquot dependent on total PBMC yield per blood draw ( eg , 3 , 5 , or 10×106 PBMC/aliquot ) . RNA was extracted from individual aliquots , and rhEBER and GAPDH RT-PCRs were performed . Aliquots were scored as positive or negative after gel electrophoresis and Southern blot hybridization of PCR products with radiolabelled gene-specific oligonucleotide probes . Representative RT-PCR assays after ΔrhBARF1 rhLCV oral inoculation of a naïve rhesus macaque ( Mm263-05 ) are shown in Figure 1A . Single PBMC aliquots from weeks 0–6 tested negative for rhEBER ( Figure 1A , left panel ) , but repeat testing of a second week 6 aliquot tested positive along with aliquots from week 7 and 8 ( Figure 1A , middle panel ) . rhEBER RT-PCR testing of PBMC aliquots from later time points were occasionally positive , eg week 30 , 48 , 54 , and 70 as shown in Figure 1A ( right panel ) . The results of rhEBER RT-PCR assays for all Mm263-05 PBMC aliquots tested are summarized in Figure 1B ( open symbols = negative results , closed symbols = positive results ) . In the acute phase ( defined as weeks 0–16 ) , 4 of 31 aliquots ( 12 . 9% ) were positive , and viral RNA was detectable between 6 to 8 weeks post-oral inoculation , a time frame similar to the acute viral load ( weeks 3–10 ) reported previously by DNA PCR after experimental inoculation with wild type ( WT ) rhLCV [10] . Oral inoculation of two other rhLCV-naïve rhesus macaques with ΔrhBARF1 rhLCV ( Mm78-05 and Mm98-96 ( 1st ) ) also resulted in intermittently positive PBMC aliquots by rhEBER RT-PCR testing during the acute phase ( 31 . 3% and 58 . 3% positive respectively ) . These results were compared to inoculation with WT rhLCV by using archived PBMC aliquots from rhesus macaques orally inoculated with 106 TU of WT rhLCV ( Mm141-97 and Mm144-97 [10] ) . As shown in Figure 1C , rhEBER RT-PCR assays became positive from 1–3 weeks after oral WT rhLCV inoculation , and then stayed almost uniformly positive for months to years after oral inoculation . Thus , an intact rhBARF1 was not essential for successful penetration of the oral mucosa and entry into peripheral blood , but the ΔrhBARF1 rhLCV-infected animals had a lower level of viral load during the acute phase compared to infection with WT rhLCV . To determine whether ΔrhBARF1 rhLCV could establish persistent infection , PBMC samples from multiple time points >16 weeks post-oral inoculation were tested by rhEBER RT-PCR . In all three ΔrhBARF1 rhLCV-inoculated animals , rhEBER was detectable in intermittent PBMC aliquots ( Figure 1B ) . 11 of 33 PBMC aliquots tested positive ( 33 . 3% ) in the persistent phase for Mm263-05 , 6 of 22 PBMC aliquots tested positive ( 27 . 3% ) for Mm78-05 , and 1 of 21 positive PBMC aliquots tested positive ( 4 . 8% ) for Mm98-06 . Mm98-96 was also orally rechallenged with ΔrhBARF1 rhLCV at 40 weeks post-inoculation . There was an increase in PBMC aliquots testing positive by rhEBER RT-PCR during the acute ( 40 . 7% ) and persistent ( 37 . 5% ) periods following re-inoculation . Overall , the rate of positive rhEBER RT-PCR testing during the persistent phase of ΔrhBARF1 rhLCV infection ( 4 . 8%–37 . 5% ) was much lower than the nearly universal rhEBER RT-PCR positive results during persistent infection with WT rhLCV ( 93 . 8%–100% ) . Of note , the PBMC aliquots tested from Mm141-97 and Mm144-97 contained 3–5×106 cells ( Figure 1C , circles ) , whereas many of the PBMC aliquots from ΔrhBARF1 rhLCV-infected animals contained 10×106 PBMC ( Figure 1B , diamonds ) . Thus , the rhBARF1-defective rhLCV was capable of establishing persistent infection , but the intermittent detection , even when using aliquots with larger numbers of cells , indicated a lower frequency of virus-infected cells in the peripheral blood of ΔrhBARF1 rhLCV-infected animals during persistent infection . To more precisely quantitate the frequency of virus-infected cells in the peripheral blood , or virus setpoint , during persistent rhLCV infection , limiting dilution analysis with rhEBER RT-PCR was performed on PBMC collected from a single time point . PBMC were aliquoted to provide multiple replicates with decreasing numbers of cells , eg 5 replicates with 106 cells , 5 replicates with 0 . 5×106 cells , etc . A representative experiment using PBMC obtained from a rhesus macaque in the conventional colony , ie naturally infected with rhLCV , is shown in Figure 2A . All replicates with 125000 , 62500 , and 31250 PBMC/replicate tested positive , whereas 4/5 , 2/4 , 1/5 , and 0/4 tested positive from replicates with 15600 , 7800 , 3900 , and 1950 PBMC/replicate respectively . By Poisson distribution and application of extreme limiting dilution analysis ( ELDA ) to account for the small number of replicates [23] , a frequency of 1 infected cell per 11 , 240 PBMC ( with a 95% confidence interval between 5 , 976 and 21 , 143 ) was estimated ( Figure 2B ) . Results from 9 random , naturally infected rhesus macaques showed an average frequency of 1 infected cell per 115 , 943 PBMC with a range of 1 in 8 , 342–570 , 565 during persistent infection ( Figure 2C; natural infection ) . To determine whether experimental infection with WT rhLCV could establish persistent infection at levels similar to natural infection , limiting dilution assays were performed using PBMC from Mm141-97 and Mm144-97 obtained years after experimental oral inoculation with WT rhLCV . These assays showed a virus setpoint of 1 infected cell per 558 , 765 and 377 , 815 PBMC respectively ( Figure 2C; WT ) , only slightly lower than the virus setpoints established in natural infection . Thus , experimental rhLCV infection can reproduce virus setpoints comparable to that seen in naturally infected animals . Differences between experimental and natural infections , eg different viral strains , viral titer of the oral challenge , and potential for multiple challenge/reinfections , may contribute to the slight differences in virus setpoints . PBMC from ΔrhBARF1 rhLCV-infected animals were tested by limiting dilution and rhEBER RT-PCR to determine virus setpoints during persistent infection . Few replicates tested positive for rhEBER expression ( 1/25 for Mm263-05 , 2/33 for Mm98-96 , and 0/12 for Mm78-05 ) even though the highest numbers of PBMC/replicate were increased to 2×106 , 1 . 5×106 , and 2×106 PBMC/replicate respectively . Poisson distribution using ELDA indicated that the frequencies of rhLCV-infected cells in Mm263-05 and Mm98-96 were on the order of 1 in 24 . 5 million and 1 in 12 . 8 million PBMC respectively ( Figure 2C , ΔrhBARF1 ) . No reliable estimate can be made for Mm78-05 in the absence of a positive replicate , but the number of replicates and PBMC/replicate used indicated the actual frequency of rhLCV-infected cells was less than 1 in 3 . 8 million PBMC . The precision of these analyses could theoretically be improved by using larger numbers of PBMC/replicate , but this could not be done given the limit of blood allowed per single phlebotomy . The analysis indicated that the virus setpoint during persistent infection was approximately 100 fold lower with ΔrhBARF1 rhLCV ( mean of 1 in 15 . 3 million PBMC for Mm263-05 and Mm98-96 ) compared to animals with natural rhLCV infection ( mean of 1 in 115 , 943 PBMC ) . To support the hypothesis that oral inoculation with ΔrhBARF1 rhLCV resulted in persistent infection at a very low frequency , we purified CD20+ B cells from PBMC to test whether rhEBER could be more easily detected if we increased the number of target cells in a single sample . Affinity purification of B cells should increase the sensitivity of detection by enriching for rhLCV-infected cells and by eliminating dilution of rhEBER RNA by nucleic acids from non-B cells . In Figure 3A , rhEBER RT-PCR testing was performed with RNA isolated from BJAB cells ( a LCV-negative B lymphoma cell line ) , 0 . 9×106 B cells from Mm141-97 , and 1 . 8×106 B cells from Mm263-05 . rhEBER were strongly detected in RNA from Mm141-97 , an animal experimentally infected with WT rhLCV , and not in RNA from the negative control BJAB . A weaker , but positive , rhEBER signal was obtained using the RNA from Mm263-05 , experimentally infected with ΔrhBARF1 rhLCV . A similar experiment is shown in Figure 3B where rhEBER were readily detected in RNA from 0 . 2×106 B cells of a naturally rhLCV-infected animal , not detected in RNA from 2 . 2×106 B cells of a rhLCV-naïve animal , and detected in RNA from 1×106 B cells of Mm98-96 , experimentally infected with ΔrhBARF1 rhLCV . The ability to detect rhLCV infection using larger numbers of B cells confirmed the presence of persistent infection in ΔrhBARF1 rhLCV-infected animals . The results were also consistent with both the limiting dilution studies and intermittent rhEBER positivity in PBMC aliquots over time , indicating a low virus setpoint after oral inoculation with ΔrhBARF1 rhLCV . We asked whether the low virus setpoints in ΔrhBARF1 rhLCV-infected animals were associated with strong immune responses that could drive virus setpoints lower than usual . Surprisingly , ΔrhBARF1 rhLCV infection was associated with delayed or undetectable adaptive humoral and cellular immune responses . Serum antibody responses against the small viral capsid antigen ( rhsVCA; rhBFRF3 ) were undetectable from Mm98-96 and 78-05 for the entire study period , even though rhsVCA serum antibody responses are ubiquitous in macaques with natural rhLCV infection , as they are in EBV-infected humans [22] . In addition , no serum antibody responses from Mm98-96 and 78-05 were detected against recombinant rhLCV lytic infection proteins rhBRLF1 , rhBZLF1 , rhBMRF1 , rhBILF2 , rhBALF4 , and rhBALF2 even though we previously described that serum antibody responses against these antigens can be detected in 61% , 83% , 90% , 95% , 100% , and 100% of naturally infected animals respectively [8] . rhLCV-specific T cell responses could not be detected from Mm78-05 at weeks 23 and 125 post-inoculation nor from Mm98-96 at weeks 63 and 177 post-inoculation by in vitro expansion using autologous rhLCV-immortalized B cell lines , as previously described [6] . Thus , any rhLCV-specific adaptive immune response to ΔrhBARF1 rhLCV infection in these animals was below the level of detection by these assays and much lower than the level of adaptive responses typically present in naturally infected animals . rhLCV-specific serologic responses were detected after ΔrhBARF1 rhLCV inoculation in Mm263-05 , but they were delayed compared to infection with WT rhLCV . As shown in Figure 4 , serum antibodies to rhsVCA in Mm263-05 were detected beginning at week 42 , whereas rhsVCA-specific antibodies are typically detected by week 7 after experimental inoculation with WT rhLCV [10] . rhsVCA-specific antibodies in Mm263-05 rose over time and remained positive during the study through week 142 , consistent with persistent rhLCV infection . Serologic responses were also detected against rhBMRF1 and rhBALF4 at week 18 , both responses appearing delayed compared to weeks 6 and 8 after infection with WT rhLCV [8] . Mm263-05 also developed serologic responses to rhBILF2 at week 30 , but rhBILF2 serologic responses to WT rhLCV are variable and less predictable [8] . rhLCV-specific T cells were not detected in Mm263-05 at week 137 post-inoculation after stimulation with autologous rhLCV-immortalized B cells . Thus , even though some serologic responses were detected in Mm263-05 , they were still abnormal relative to that expected for WT rhLCV infection , they developed after the low ΔrhBARF1 rhLCV setpoint had been established , and T cell responses were not detected . These results indicated that the low virus setpoints established during ΔrhBARF1 rhLCV persistent infection were more likely due to a defect in establishing persistent infection , as opposed to ongoing suppression of virus setpoints by a strong immune response . If rhBARF1 were required for immune evasion in vivo , we predicted that the blunted acute viral load and low virus setpoint in persistent infection after ΔrhBARF1 rhLCV inoculation could be normalized by immunosuppressing the host . A rhLCV-naïve macaque ( Mm278-98 ) was first immunosuppressed by Simian/Human Immunodeficiency Virus ( SHIV ) infection followed by oral inoculation with 106 TU of ΔrhBARF1 rhLCV . As shown in Figure 5 , rhEBER expression was detected in PBMC beginning at week 2 post-inoculation and in the vast majority of PBMC aliquots tested from the acute phase ( 17/20; 85% ) . Similarly , rhEBER expression was detected in the vast majority of PBMC aliquots tested from the persistent phase of infection ( 24/28; 85 . 7% ) . The high frequency of PBMC aliquots testing positive for rhEBER expression during acute and persistent phases after ΔrhBARF1 rhLCV inoculation of an immunosuppressed host was more similar to experimental infection with WT rhLCV ( Mm141-97 and Mm144-97 ) than to ΔrhBARF1 rhLCV infection of immunocompetent hosts ( Mm263-05 , Mm98-96 , and Mm78-05 ) . Limiting dilution analysis of Mm278-98 PBMC taken at week 159 post-inoculation showed that approximately 1 in 195 , 725 PBMC were infected , a level more comparable to animals experimentally infected with WT rhLCV ( 1 in 115 , 943; Figure 2C ) than immunocompetent animals infected with ΔrhBARF1 rhLCV ( 1 in 15 . 3 million; Figure 2C ) . These results indicated that SHIV-induced immunosuppression can rescue the phenotype of ΔrhBARF1 rhLCV infection and that ΔrhBARF1 rhLCV was capable of establishing normal rhLCV setpoints under certain conditions . rhLCV-specific adaptive immune responses were detected in Mm278-98 . Serum antibodies to the rhsVCA were detected beginning at week 41 post-oral inoculation , and serum antibodies to , rhBALF2 ( ≥ week 6 ) , rhBMRF1 ( ≥ week25 ) , and rhBALF4 ( ≥ week 25 ) , but not rhBZLF1 , rhBRLF1 , and rhBILF2 , were detected . CD8+ T cell responses specific for rhEBNA-2 , rhEBNA-3C , rhBRLF1 , rhBLLF2 , and rhBZLF1 were also detected in T cell lines derived from PBMC drawn at weeks 77 , 81 , 88 , 97 , and 102 weeks post-oral inoculation . Thus , ΔrhBARF1 rhLCV could readily induce adaptive immune responses in immunosuppressed hosts where it achieved higher viral loads during acute infection and higher virus setpoints during persistent infection . To determine whether virus in the infected host retained the same molecular genotype of the inoculating virus , we cultured PBMC in vitro for spontaneous outgrowth of virus-immortalized B cells . No spontaneously growing B cell lines could be derived from immunocompetent animals infected with ΔrhBARF1 rhLCV ( Mm263-05 , Mm98-96 , and Mm78-05 ) , likely due to the very low frequency of infected cells . A spontaneously growing B cell line was derived from PBMC collected at week 3 post-inoculation in the immunosuppressed host ( Mm278-98 ) . The rhLCV strain isolated from the peripheral blood of Mm278-98 was identified by PCR amplification of rhBARF1 viral DNA from the spontaneous B cell line . ΔrhBARF1 rhLCV DNA has a unique loxP scar sequence in the rhBARF1 coding sequence where the Bacterial Artificial Chromosome ( BAC ) vector sequences were initially inserted and later excised [20] . Cre-mediated excision of the BAC vector sequences from the recombinant virus leaves 89 nucleotides from the loxP scar sequence in rhBARF1 resulting in a frame shift and premature termination of the rhBARF1 coding sequence . Thus , the 89 additional nucleotides and loxP scar sequence at the rhBARF1 locus provide a unique molecular signature for ΔrhBARF1 rhLCV . PCR amplification across the BAC vector insertion site distinguishes ΔrhBARF1 rhLCV from WT rhLCV , as shown in Figure 5B . A 358 bp PCR fragment could be amplified from a cell line infected with WT rhLCV , and it hybridized with an internal , radiolabelled rhBARF1 probe ( Figure 5B , top panel , WT ) . PCR amplification from ΔrhBARF1 rhLCV-immortalized cell lines derived in tissue culture resulted in a slightly larger , 447 bp DNA fragment that not only hybridized with the rhBARF1 probe ( Figure 5B , upper panel , ΔrhBARF1 1 & 2 ) , but also a loxP probe ( Figure 5B , lower panel ) . Similarly , PCR amplification from the spontaneous Mm278-98 B cell line ( Mm278-98sp ) resulted only in the larger 447 bp PCR product and contained the loxP scar sequence . These studies provide formal proof that the same molecular clone used to orally inoculate Mm278-98 was capable of penetrating the oral mucosa and infecting cells in the peripheral blood where it could be recovered as a spontaneous B cell line in vitro . To demonstrate that the rhBARF1 mutation was responsible for the ΔrhBARF1 rhLCV phenotype , the rhBARF1 ORF in the ΔrhBARF1 rhLCV BAC was restored [20] , and the wild type repaired virus ( WTr ) was used to orally inoculate immunocompetent rhLCV-naïve rhesus macaques , Mm364-98 and Mm151-97 . As shown in Figure 6 , rhEBER were detected at weeks 1-3 post-inoculation with positive results in 15/16 ( 93 . 8% ) and 12/14 ( 85 . 7% ) of aliquots containing 3–5×106 PBMC during acute infection . 12/14 ( 85 . 7% ) and 13/15 ( 86 . 7% ) PBMC aliquots were positive during persistent infection . The kinetics of rhEBER expression in PBMC after oral inoculation with WTr was comparable to experimental infection with WT rhLCV ( Figure 1C; Mm141-97 and Mm144-97 ) from which the BAC was originally derived . Limiting dilution analysis showed virus setpoints of 1 in 43 , 317 and 1 in 1 , 404 , 968 PBMC for Mm364-98 and Mm151-97 at weeks 19 and 29 respectively , levels comparable to both natural rhLCV infection and experimental WT rhLCV infection ( Figure 2C ) . Repeat testing at weeks 24 and 32 post-inoculation showed frequencies of 1 in 62 , 589 and 1 , 105 , 494 PBMC for Mm364-98 and Mm151-97 respectively indicating that the virus setpoint was relatively stable during persistent infection in experimentally infected rhesus macaques and that persistent infection was achieved by 19 weeks post-oral inoculation . Reversal of the abnormal phenotype by repair of the rhBARF1 ORF indicated that the loss of CSF-1 blocking ability was linked to the lower viral load during acute infection and lower virus setpoints during persistent infection with ΔrhBARF1 rhLCV .
These experiments break new ground in two major areas by taking studies of EBV gene function into the context of a natural host and by exploring viral blockade of CSF-1 signaling , an immune evasion strategy not previously described for any other virus . Our studies indicate that viral amplification during acute EBV infection is susceptible to CSF-1-induced immune responses since mutating rhBARF1 resulted in blunting of acute viral load during the first 16 weeks after oral inoculation . In addition , we found a dramatic lowering of the virus setpoint during persistent infection when the virus was incapable of blocking CSF-1-induced immune responses . This anti-viral effect could be reversed by either immunosuppressing the host via SHIV infection or by restoring CSF-1 blocking ability to the rhBARF1 ORF . An important role for BARF1 during acute EBV infection might be predicted since it is expressed during lytic replication [24] and lytic replication is assumed to be an important mechanism for viral amplification during acute infection . However , there is little published evidence to support this assumption . Anti-viral drugs , such as acyclovir , that can block EBV replication have shown no significant efficacy in clinical trials with IM patients [25] , [26] . One interpretation could be that lytic replication is not important in acute EBV infection . Another interpretation may be that anti-viral therapy is initiated too late in IM patients to be effective , since viral amplification through lytic replication may have already occurred by the time patients present with symptoms and are recruited into a clinical trial . Human epidemiologic studies indicate that viral inoculation occurs approximately 6 weeks before IM symptoms develop [27] , and our animal studies show that virus usually becomes detectable in the peripheral blood within 3 weeks after oral inoculation . Similarly , the failure to find robust viral replication in tonsillar epithelial cells of IM patients may be due to the timing of the studies [28] , as opposed to evidence against an important role for lytic viral replication in acute infection . Our results provide the first experimental evidence linking lytic EBV replication to viral amplification during acute EBV infection . The mechanisms by which CSF-1 enhances immune control of acute EBV infection remain to be identified . CSF-1 induces differentiation and maturation of monocytes into active phagocytes in tissue culture [16] , and CSF-1 administration in vivo can increase blood monocytes and tissue resident macrophages [29] . Thus , EBV-infected cells during acute infection may be particularly sensitive to CSF-1-activated phagocytic cells and tissue macrophages . CSF-1 also acts on other components of the immune system that may contribute to its anti-viral effect . CSF-1 increases conventional and plasmacytoid dendritic cells that produce interferon alpha and activate NK cells [30] , [31] , and CSF-1 has been reported to mobilize and enhance NK cytolytic activity [32] . Thus , it is tempting to speculate that BARF1 may have been acquired as a unique EBV strategy to evade NK cells . There are multiple lines of evidence linking EBV susceptibility to NK cells . Patients with X-Linked Lymphoproliferative Syndrome ( XLP ) suffer from fatal IM or lymphomas upon primary EBV infection , but do not have unusual susceptibility to other microbial pathogens [33] . In XLP , mutations in the signaling lymphocytic activation molecule ( SLAM ) -associated protein ( SAP ) prevent activation of NK cell cytotoxicity against EBV-infected B cells [34] . Severe combined immunodeficiency ( SCID ) mice engrafted with human PBMC depleted of NK cells are more susceptible to fatal lymphoproliferation of infused EBV-infected B cells than non-depleted controls , indicating a role for NK cells in preventing outgrowth of infected B cells [35] . B cell immortalization by EBV infection in tissue culture is also sensitive to NK cells [36] , and in particular to tonsil-derived NK cells that may be most proximal to early viral events during acute EBV infection in humans [37] . Interestingly , HIV and SHIV infection have been associated with decreases in circulating NK cells and NK cell function [38] , [39] , and this may explain why SHIV-induced immunosuppression was associated with rescue of a normal viral phenotype after ΔrhBARF1 rhLCV inoculation . The markedly decreased virus setpoint during persistent infection with ΔrhBARF1 rhLCV was surprising . Viral set points during persistent EBV infection are believed to be independent of lytic viral replication since they remain largely unchanged in patients on chronic acyclovir therapy [2] , although recent data has challenged this paradigm [40] . A potential model to explain our findings with ΔrhBARF1 rhLCV may be that the virus setpoint during persistent infection is determined in part by the level of viral load during acute infection , ie the effect on virus setpoint in persistent infection is a consequence of , or dependent upon , the rhBARF1 effect in acute infection . This is similar to Herpes Simplex Virus where multiple factors during acute infection , including viral replication , multiplicity of infection , and location of replication , can contribute to the level of persistent , latent infection established in neurons [41] . Alternatively , rhBARF1 may have an additional and independent effect on persistent infection . Although BARF1 is typically expressed during lytic replication [24] , BARF1 mRNA can be detected in nasopharyngeal carcinoma cells [42] , [43] and EBV-immortalized B cells [44] in the absence of lytic replication opening up the theoretic possibility that BARF1 may be promiscuously expressed during persistent infection in latently infected peripheral blood B cells . Further studies will be required to understand the mechanistic basis for the low virus setpoints established by ΔrhBARF1 rhLCV , but this is the first experimental demonstration that the natural history of persistent LCV infection can be attenuated . The failure to generate robust adaptive immune responses in hosts persistently infected with ΔrhBARF1 rhLCV was also surprising since control of latently EBV-infected B cells in humans is tightly linked to adaptive , and in particular , T cell immune responses [1] . This indicated that adaptive immune responses were not the principle driver for the low virus setpoint during persistent ΔrhBARF1 rhLCV infection . It may be more likely that ΔrhBARF1 rhLCV is a conditionally attenuated virus , ie in a healthy , immunocompetent host , it is incapable of establishing a normal virus setpoint in the face of intact CSF-1-induced immune responses , and the lower virus setpoint provides insufficient antigen expression to stimulate robust adaptive immune responses . When hosts are immunosuppressed or CSF-1 is blocked , the virus can achieve higher setpoints associated with more antigenic stimulation and easily detectable adaptive immune responses . This unusual state of persistent infection with very low virus setpoints and difficult to detect adaptive immune responses may need to be considered when evaluating vaccine studies , ie to differentiate sterilizing immunity from an altered natural history of persistent EBV infection with a very low virus setpoint . Altering the natural history of persistent EBV infection is likely to be an important component for an effective EBV vaccine for IM and for EBV-associated malignancies . Blunting the acute viral load , either in terms of kinetics or absolute magnitude , may be an important strategy for preventing the excessive immune activation that causes IM . Phase II clinical testing in humans has demonstrated proof-of-principle that a gp350 subunit vaccine can prevent IM , but the mechanism by which the vaccine prevents disease remains unclear [45] . Gp350 is the major membrane glycoprotein on the virus and a major target for serum neutralizing antibodies [46] . Serum neutralizing antibodies may protect from IM by providing sterilizing immunity or by altering the speed or magnitude of viral amplification during acute EBV infection . Our studies provide evidence that targeting lytic replication can blunt viral amplification during acute infection and that lytic EBV replication may be especially susceptible to CSF-1-mediated immune responses . For an effective EBV cancer vaccine , lower virus setpoints may translate into a decreased number of EBV-infected cells at risk for malignant transformation and a stochastic reduction in the development of EBV-associated malignancies over time . If the virus setpoint during persistent infection is linked to viral load during acute infection , then an EBV vaccine targeting lytic replication and reducing viral amplification in acute infection may be effective against both IM and EBV-associated cancers . Our studies indicate that tipping the balance in favor of host immunity against acute viral replication can alter the natural history of both acute and persistent phases of LCV infection , providing a potential vaccine strategy for protection against a spectrum of EBV-associated diseases .
Animal experiments were reviewed and approved by the Institutional Animal Care and Use Committee for Harvard Medical School . Animals were cared for in compliance with National Institutes of Health , US Department of Agriculture , and Harvard Medical School guidelines for animal research . Animal well-being was monitored multiple times throughout the day by animal care staff , veterinary technicians , and veterinarians , and appropriate veterinary care was provided as needed . Sedation and analgesia were administered as indicated to minimize stress and pain associated with any veterinary procedures . rhLCV-infected cell lines were grown in RPMI 1640 supplemented with 10% fetal bovine serum at 37°C and 5% CO2 . Virus stocks were derived from cell-free supernatants , and transformation titers were assayed [20] . The rhLCV strain LCL8664 [47] from which the rhLCV BAC was derived , is referred to as WT rhLCV and was obtained from the American Type Culture Collection . ΔrhBARF1 rhLCV refers to the recombinant , BAC-derived virus that has a mutated rhBARF1 open reading frame with the carboxy terminal 70 AA truncated by insertion of a premature stop codon after amino acid 150 ( clone 16 rhLCV [20] ) . WTr rhLCV is the recombinant , BAC-derived virus with a repaired rhBARF1 open reading frame [20] . rhLCV-naïve rhesus macaques were obtained from an extended specific pathogen-free ( spf ) colony at the New England Primate Research Center ( NEPRC ) . This self-sustaining breeding colony undergoes regular serologic screening to ensure that animals are free of infection from several simian viruses including herpes B , rhesus cytomegalovirus , rhesus rhadinovirus , and rhLCV . The NEPRC extended spf colony has been free of rhLCV infection for over a decade . Animals were inoculated with 106 transforming units ( TU ) of cell-free virus applied non-traumatically throughout the oral cavity . Infection with Simian/Human Immunodeficiency Virus ( SHIV ) was as described [10] . Serum antibodies against the rhLCV small viral capsid antigen ( rhBFRF3 ) were detected by peptide immunoassays [22] . Serum antibodies against rhBZLF1 , rhBRLF1 , rhBMRF1 , rhBALF2 , rhBALF4 , or rhBILF2 protein were detected by enzyme immunoassays using recombinant viral antigens [8] . Total RNA was extracted using RNA-Bee reagent ( Tel-Test Inc . ) on peripheral blood mononuclear cells ( PBMC ) or B cells affinity purified with CD20 antibody ( clone 2H7 , Biolegend ) and CELLection Pan Mouse IgG kit ( Invitrogen ) . Extracted RNA was reverse-transcribed using Super Script II reverse transcriptase ( Invitrogen ) and rhEBER173R ( aaaacaggcggaccaccag ) and GAPDH-R1 ( gttcacacccatgacgaacatgg ) primers . Real-time PCR was performed using SYBR green ( Applied Biosystem ) . 18 ul or 0 . 02 ul of cDNA were amplified for 40 cycles ( 15 seconds at 95°C , 30 seconds at 60°C , and 30 seconds at 72°C ) for rhEBER ( rhEBER32F; ggaggagatgagtgtgacttaaatca and rhEBER148R; tgaaccgaagagagcagaaacc ) or GAPDH ( GAPDH-F; gcgagatccctccaaaatca and GAPDH-R2; ccagtggactccacgacgta ) , respectively . Plasmids containing rhEBER ( 6652–7137 nt ) or GAPDH ( 113–510 nt , gi83641890 ) DNA were quantified by spectrophotometry and diluted from 106 to 101 copies for use as standards . PCR products were detected by gel electrophoresis , southern blot transfer , and hybridization with a 32P end-labeled rhEBER116R ( ccaaacttttagcagcaccag ) or GAPDH internal ( gtggggcgatgctggcgct ) oligonucleotide probe . PBMC were isolated by Ficoll-Hypaque density centrifugation and cell numbers were determined using Count Bright absolute counting beads ( Invitrogen ) in flow cytometry . PBMC were 2-fold serially diluted , typically at starting concentrations of 1 or 2×106 , and 3–5 replicates were prepared at each cell concentration . rhEBER RT-PCR was performed using the Super Script III one-step RT-PCR system ( Invitrogen ) , rhEBER32 and rhEBER148R primers , and amplification for 35 cycles ( 15 seconds at 95°C , 30 seconds at 60°C , and 30 seconds at 68°C ) . PCR products were detected by gel electrophoresis , southern blot transfer , and hybridization with a 32P end-labeled rhEBER116R oligonucleotide probe . The frequency of rhLCV-infected cells in PBMC was calculated from the results of limiting dilution replicate testing using the method described by Hu , et . al . ( Extreme Limiting Dilution Analysis; http://bioinf . wehi . edu . au/software/elda/ ) [23] . In all analyses , the single-hit hypothesis was not rejected .
|
Epstein-Barr virus ( EBV ) is a herpesvirus that persistently infects nearly all humans by adulthood . Acute and persistent phases of EBV infection are associated with a variety of human diseases , including infectious mononucleosis and cancer . To investigate how EBV interacts with the host to successfully establish acute and persistent infection , we combined the power of the rhesus macaque animal model for EBV infection with genetic engineering of the EBV-related herpesvirus , or lymphocryptovirus ( LCV ) , that naturally infects rhesus macaques . We created a recombinant rhLCV carrying a mutated EBV BARF1 homologue , a replication-associated viral protein that is secreted and blocks Colony Stimulating Factor-1 ( CSF-1 ) signaling , a cytokine important for innate immunity . Oral inoculation of rhesus macaques showed that the virus' ability to block CSF-1 was important for achieving the normally high viral loads during acute infection , and surprisingly , was also needed to establish normal levels of virus infection , or viral setpoint , during persistent infection . These studies show that virus-mediated interruption of innate immunity is critical for both acute and persistent phases of EBV infection . Understanding how EBV successfully infects humans and how the natural history of EBV infection can be disrupted will aid in development of vaccines to prevent EBV-associated diseases .
|
[
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2012
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An Epstein-Barr Virus Encoded Inhibitor of Colony Stimulating Factor-1 Signaling Is an Important Determinant for Acute and Persistent EBV Infection
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Melanin protects the skin and eyes from the harmful effects of UV irradiation , protects neural cells from toxic insults , and is required for sound conduction in the inner ear . Aberrant regulation of melanogenesis underlies skin disorders ( melasma and vitiligo ) , neurologic disorders ( Parkinson's disease ) , auditory disorders ( Waardenburg's syndrome ) , and opthalmologic disorders ( age related macular degeneration ) . Much of the core synthetic machinery driving melanin production has been identified; however , the spectrum of gene products participating in melanogenesis in different physiological niches is poorly understood . Functional genomics based on RNA-mediated interference ( RNAi ) provides the opportunity to derive unbiased comprehensive collections of pharmaceutically tractable single gene targets supporting melanin production . In this study , we have combined a high-throughput , cell-based , one-well/one-gene screening platform with a genome-wide arrayed synthetic library of chemically synthesized , small interfering RNAs to identify novel biological pathways that govern melanin biogenesis in human melanocytes . Ninety-two novel genes that support pigment production were identified with a low false discovery rate . Secondary validation and preliminary mechanistic studies identified a large panel of targets that converge on tyrosinase expression and stability . Small molecule inhibition of a family of gene products in this class was sufficient to impair chronic tyrosinase expression in pigmented melanoma cells and UV-induced tyrosinase expression in primary melanocytes . Isolation of molecular machinery known to support autophagosome biosynthesis from this screen , together with in vitro and in vivo validation , exposed a close functional relationship between melanogenesis and autophagy . In summary , these studies illustrate the power of RNAi-based functional genomics to identify novel genes , pathways , and pharmacologic agents that impact a biological phenotype and operate outside of preconceived mechanistic relationships .
Significant effort has been focused on identifying the molecular etiology for pigment variation in skin [1] . 127 mouse coat color genes have been identified [2] , 68 of these genes have human homologues , and 29 of these homologues impact pigmentation in humans . Genetic mapping studies have identified a limited set of genes responsible for skin and eye color variability [3] . Pigment production involves the concerted actions of transcriptional , translational , and intracellular trafficking machinery [4] . MITF , the master regulator of melanogenesis in the mouse hair follicle [5] , activates the transcription of tyrosinase , the rate limiting step in melanogenesis [5] . Tyrosinase is translated in the endoplasmic reticulum and is glycosylated in the Golgi apparatus [6] . Tyrosinase activity is restricted to the melanosome , a melanin specific organelle of poorly defined origin [7] , [8] . While the subtle variation in human skin color is thought to be the result of the complex interaction of multiple genes , the majority of mouse mutants described have segmental or complete absence of pigment [9] . Recent studies have identified partial loss of function mutations that impact the shade of melanin in zebrafish and human skin [10] , but the spectrum of gene targets that regulate pigment shade is unknown . Melanin is expressed in different end organs conferring different functions . Melanin protects the skin , eyes [1] , and brain from toxic insults [11] . Melanin in the inner ear impacts sound conduction [12] . Loss of melanin is thought to play a role in the etiology of age related macular degeneration [13] and Parkinson's disease [14] . Additionally , melanin is aberrantly regulated in human skin disorders such as vitiligo and melasma . Harnessing the molecular mechanisms that regulate melanogenesis to selectively modulate melanin production in the skin , eye , or brain could lead to novel treatments for multiple human pathologies . Pharmacologic modulation of melanin production has primarily focused on identifying inhibitors of tyrosinase , the rate limiting step in pigment production [15] . Currently utilized tyrosinase inhibitors are clinically effective , but are carcinogenic in animal studies [16] . Pharmacologic agonists that stimulate pigmentation in human tissues remain to be identified . A better understanding of the molecular network governing pigment production in the human epidermis is indicated to aid design of agents that inhibit or stimulate pigmentation in human skin .
Studies to determine the key molecular regulators of melanogenesis in human melanocytes have been hampered by the innate fragility of these cells and the fact that they produce scant amounts of pigment in culture [17] , [18] . To identify novel regulators of melanogenesis in human cells , we utilized MNT-1 melanoma cells to screen a genome-wide synthetic siRNA library for single-gene loci that support melanocyte pigmentation . MNT-1 cells produce substantial amounts of melanin in culture , have a gene expression profile that is most similar to normal melanocytes [19] , and have been used by others to identify pigment regulatory mechanisms that govern normal melanogenesis [20]–[23] . We employed a previously described [24] Dharmacon siRNA library of 84 , 508 siRNAs corresponding to four unique siRNA duplexes , targeting each of the 21 , 127 unique human genes arrayed in a one-gene/one-well format on 96 well microtiter plates . A spectrophotometric melanin quantitation assay was coupled with an ATP-dependent luminescence cell viability assay ( CellTiter-Glo ) to eliminate siRNAs that decrease melanin production as a consequence of impacts on either cell proliferation or cell survival . Using tyrosinase depletion as a positive control , we determined that a 5-day post-transfection incubation period was optimal for quantitative detection of impaired melanin production ( Figure S1 ) . Other studies demonstrated that the cell titer glo assay did not interfere with the spectrophotometric quantitation of melanin ( data not shown ) . In order to identify genes that impact both pheomelanin and eumelanin production , we measured melanin content at 405 nm [25] , a wavelength at which both pheomelanin and eumelanin absorb light . Raw A405nm absorbance values were normalized to internal reference samples on each plate to permit plate-to-plate comparisons . This analysis was followed by normalization to the experimental mean for each well location calculated from the full data set in order to control for variations in pigment due to plate position effects . Similarly adjusted luminescence values from the multiplexed viability assay were used to generate “normalized absorbance ratios” for each well ( Table S1 ) . The distribution of the means of these values from duplicate analyses is shown in Figure S1B . Previous studies have identified 68 genes that regulate pigment production in human cells . Initial examination of our dataset determined that siRNAs directed towards 13 of these 68 genes impaired melanin accumulation without impacting melanocyte survival or proliferation when depleted in these assays , with tyrosinase itself scoring with one of the lowest ratios ( 2 . 5 standard deviations below the mean; Table S2 ) . Our current siRNA screening protocol relies on siRNA design algorithms to identify effective siRNA sequences and utilizes a single endpoint assay to identify siRNAs that impact pigment production . Genes whose function is not inhibited by selected siRNAs either secondary to the long half-life of the corresponding protein or secondary to poor siRNA sequence selection would not be identified in our screening approach . Identification of several known regulators of melanogenesis by our screening protocol does give confidence that our approach is sufficiently robust to identify novel regulators of pigment production . To facilitate the identification of novel genes that significantly impact melanogenesis , a cutoff of 2 standard deviations below the mean was used to select a candidate hit list . 98 genes were identified as regulators of melanogenesis by our screening approach . Of these 98 genes identified in the primary screen , only 6/98 genes ( marked in red , Table 1 ) exhibited aberrant expression in MNT-1 cells as compared to normal melanocytes [19] , indicating that the screen identified a large number of genes that likely impacted melanogenesis in both primary melanocytes and MNT-1 cells . Two of the genes identified in our screening approach were more recently eliminated from the Refseq database , and were not subject to detailed further evaluation . Individually synthesized , pooled siRNAs directed against 35 of the 96 remaining genes selected from the primary screen , as described above , were retested to determine the false-positive rate ( Table S4 ) . These genes were randomly selected from the putative target list . To more precisely control for the efficacy of siRNA transfection and to correct for the background absorbance of MNT-1 cells , the ability of each target siRNA to inhibit pigment production was compared to the ability of tyrosinase siRNA to inhibit pigment production using a normalized percent inhibition calculation [26] , and relative pigmentation was assessed visually prior to cell lysis ( Figure 1A , B ) . A Keratin 7 siRNA pool that did not impact pigment production was utilized as a negative control . Four siRNA pools failed to significantly impact pigment production upon retesting and were eliminated from further analysis ( Figure 1A , Table S4 ) , giving an estimated false discovery rate of 12 . 1% . To validate that our candidate siRNAs inhibit the expression of the gene of interest , we utilized quantitative RT PCR to examine if a random selection of candidate siRNA pools inhibited the expression of the appropriate target gene ( Figure S2 ) . These results validate that the siRNAs selectively impact the expression of the cognate target gene , although this may not conceivably hold true for all of the siRNAs used in our screen . To eliminate siRNA pools with off-target effects on melanogenesis [24] , the four siRNAs comprising each siRNA pool were retested individually . We found that at least two independent siRNAs against each target gene significantly inhibited pigment production ( Figure 1C , Table S4 ) , suggesting that pigmentation phenotypes are not a common consequence of siRNA off-target phenomena . Together , these studies demonstrate that the genome wide siRNA screening platform accurately identified gene targets that specifically impact pigment production . Initial examination of existing GO annotation data for our pigment regulators exposed a wide variety of cellular processes represented by the validated and candidate hits ( Table 1 ) . Therefore , we employed a focused unbiased approach to identify regulators of tyrosinase , the rate limiting enzyme specifying melanogenesis [15] among novel validated genes supporting MNT-1 pigmentation . Relative accumulation of tyrosinase , the melanogenesis transcription factor MITF , and the melanosomal marker protein Melan-A were examined 96 hours post siRNA transfection . Remarkably , over half of the validated pigment genes appear to be required for tyrosinase protein accumulation ( Figure 2A , Figure S3 ) . This defect did not appear to be a gross inhibition of cell fate specification , as Melan-A expression was mostly unaffected . In addition , the sub cellular morphology of PMEL17 , a melanosome structural protein [27] , was normal at the level of immunofluorescence detection ( Figure S4 ) . Of those pigment genes impacting tyrosinase accumulation , approximately half appear to act at the level of tyrosinase mRNA accumulation ( Table 2 ) , and most of these also impaired MITF mRNA accumulation . Given that tyrosinase is an MITF target gene , the pigmentation genes in this later class may represent action at the level of MITF mRNA . A caveat to this interpretation is our observation that siRNA-mediated turnover of tyrosinase mRNA can also lead to inhibition of MITF gene expression ( Figure 2A ) through a relationship that remains to be defined . Preliminary studies indicated that this phenotype was not a consequence of siRNA off-target phenomenon ( Figure S3 ) . While pigmentation in humans is a complex multigenic trait , the degree of genetic variation that contributes to melanocyte autonomous pigment production is unknown . To examine the phenotypic penetrance of novel pigmentation genes , identified in MNT-1 cells , in diverse genetic backgrounds , we employed primary human melanocyte cultures isolated from two different individuals . Remarkably , the majority of targets that regulated tyrosinase expression in MNT-1 cells also impacted tyrosinase expression when depleted from darkly pigmented primary melanocytes ( Figure 2C , Figure S5A ) . Approximately half of these targets also inhibited tyrosinase expression when depleted from moderately pigmented melanocytes ( Figure 2C , Figure S5B ) . These results indicate that the primary screen identified a number of genes that impact pigment production in several different genetic backgrounds . Selective activity of some of these targets in different genetic backgrounds suggests that some of these novel regulators of melanogenesis may play a role in human phenotypic variation . Future large scale studies are required to determine if these genes are differentially expressed in different pigment backgrounds . For further analyses , we focused on those novel pigmentation genes that impacted tyrosinase expression in all three genetic backgrounds . Among these were two isoforms of aldehyde dehydrogenase , ALDH1A1 and ALDH9A1 , well characterized enzymes that regulate ethanol detoxification [28] . A number of chemical inhibitors of these enzymes have been identified [29] , and several of these agents are clinically utilized to induce alcohol intolerance during detoxification interventions; presenting an opportunity for pharmacological validation of the contribution of Aldh activity to melanocyte pigmentation . Disulfiram is an Aldh inhibitor that is toxic to melanoma cells via a mechanism that is independent of Aldh inhibition [30] . However , two non-toxic Aldh inhibitors , cyanamide and Angeli's salt [29] , inhibited pigmentation and tyrosinase protein accumulation in MNT-1 cells at doses that are equivalent to those required for inhibition of Aldh activity in culture ( Figure 2D ) . For quantifying the impact of compound treatment on pigment accumulation , we used our spectrophotometric-based melanin quantitation assay that couples a CellTiter-Glo assay with a melanin quantitation assay to effectively eliminate compounds that impact cell survival or proliferation . Cyanamide did not appear to impact the viability of MNT-1 cells or primary melanocytes in culture . In addition , these compounds impaired UV-induced tyrosinase expression when tested in primary melanocytes ( Figure 2D , E ) . Melanosomes are distinct lysosome-related organelles dependent upon appropriate post-golgi sorting events for delivery of functionalizing ‘cargo’ including tyrosinase [31] . Therefore , impaired accumulation of tyrosinase can be a consequence of misrouting to lysosomes and subsequent hydrolysis in that organelle . To define target genes that may participate in this sorting event , lysosome acidification was inhibited by bafilomycin A1 exposure subsequent to target gene depletion [32] . As shown in Figure 3A , a 24 hour inhibition of lysosome acidification rescued tyrosinase accumulation upon depletion of the small G-protein RAB4A , and the small G-protein palmitoyltransferase ZDHHC9 . By contrast , bafilomycin did not restore tyrosinase accumulation upon depletion of MSRA , a protein that can protect against oxidative damage through reduction of methionine sulfoxide . These studies offered preliminary evidence that our screening approach did identify novel genes that impact melanosome trafficking/sorting of melanosome protein cargo . Gene annotation data was utilized to identify other genes that may regulate melanosome intracellular trafficking/sorting of melanosome protein cargo . Among the panel of validated pigment regulatory genes with phenotypic penetrance in multiple genetic backgrounds was WIPI1 ( Figure 2 ) . Wipi1 has been implicated as a human homolog of the yeast autophagy protein ATG18 , and is localized to starvation-induced autophagosomes in human cell culture [33] . Two additional autophagy-related proteins , LC3-C and GPSM1/AGS3 were isolated in the primary screen ( Table 1 ) . Autophagy , or cellular self-degradation , is a highly conserved cellular pathway that has been associated with cancer formation , neurodegeneration , and aging [34]–[36] . This pathway functions to transport vesicle cargo ( autophagosomes ) to the lysosome for degradation [35] . Scant evidence currently exists linking autophagy to melanogenesis . Previous studies have documented an abundance of autophagosomes in cells obtained from patients with a disorder of pigmentation ( HPS-1 ) but have hypothesized that their presence is a consequence of the degradation of immature melanosomes within these cells [37] . Other studies have determined that autophagosome components are present in the stage II melanosome , suggesting that parts of the melanosome originate from the autophagosome [38] . Our genome wide siRNA screen directly identified autophagy components as novel regulators of melanogenesis . Validation of these targets by siRNA pool deconvolution supported a functional relationship between autophagosome and melanosome biogenesis ( Figure 3B ) . Furthermore , we found that depletion of two additional components required to trigger autophagosome formation , BECN1 or LC3-A , severely impaired pigment accumulation ( Figure 3B ) . Failure to recover these genes in the primary screen is indicative of the false negative rate inevitably associated with high throughput investigations and illustrates the point that our approach is unlikely to identify all known regulators of melanogenesis . Nonetheless , the validation that both Beclin1 and Lc3 impact pigment accumulation is supporting evidence that autophagy impacts melanogenesis . Consistent with this relationship , heterozygous deletion of the autophagy protein Beclin 1 [39] results in a dramatic coat color defect in mice ( Figure 3C , Figure S6 ) . Homozygous null mutations are embryonic lethal , however haploinsufficient animals show an interesting chimeric phenotype with normal and hypopigmented hair follicles . The hypopigmented follicles in these mice contain less pigment in the hair follicle bulb as observed on horizontal sections of the hair follicle . Previous studies have determined that only melanoblasts within the hair follicle unit express S100b protein [40] . To determine if the phenotype observed in beclin1 haploinsuffiicient mice is secondary to an impact of beclin1 depletion on melanoblast survival , we attempted to identify S100+ melanoblasts within the hair follicle in horizontally sectioned skin specimens of wild type and Beclin1 haploinsufficient mice . Consistent with published studies , it was difficult to identify S100 positive cells within the hair follicle of wild type mice secondary to interfering melanin [40] . However , in Beclin1 haploinsufficient mice , we determined that S100+ cells were present in the hair follicle ( Figure 3D ) . Data from our siRNA screen indicated that beclin1 depletion does not impact melanocyte survival . Taken together , our siRNA data and histologic analysis suggests that the phenotype observed in the Beclin1 haploinsuficient mice is not a consequence of impacts of Beclin1 on melanocyte survival but is more likely secondary to the impact of beclin1 on melanosome number or melanin content within the hair follicle . As melanosomes are thought to be lysosome related organelles , autophagic machinery may be required for the functional sorting of melanin synthetic machinery . At the cell autonomous level , we found co-localization of the autophagy proteins LC3 and APG5 and the melanosome markers PMEL17 in mature melanosomes ( Figure 3E ) . Thus molecular components required for autophagosome formation are directly implicated in the biogenesis of melanin , either at the level of melanosome formation or melanosome maturation . When coupled with previous data demonstrating that autophagosomes accumulate in cells defective in melanosome maturation , these results indicate that the autophagy pathway is intimately involved in the process of melanosome maturation [37] . We have utilized an unbiased , high-throughput functional genomics screening platform to identify critical single gene loci that regulate the notoriously complex , highly regulated process of melanogenesis in human cells . Using this approach , we have identified 92 novel genes that impact pigment production in human cells . The convergence of several of these loci directly on the critical rate-limiting enzyme in melanogenesis , tyrosinase , underscores the power of this approach to identify unrecognized genes that are components of even well characterized enzymatic pathways . The complexity of the network controlling tyrosinase expression uniquely parallels the variation in skin color seen in human skin , underscored by the fact that these mechanisms are differentially active in moderately and darkly pigmented melanocytes . The direct identification of novel pigment modulatory agents highlights the utility of genome wide siRNA screening as a translational approach for deriving novel molecular based treatment strategies .
MNT-1 cells were a gift of M . Marks ( University of Pennylvania ) . These cells were cultured in DMEM ( Invitrogen ) with 15% fetal bovine serum ( Hyclone ) , 10% AIM-V medium ( Invitrogen ) , 1xMEM ( Invitrogen ) and 1× antibiotic/antimycotic ( Invitrogen ) . Darkly pigmented and moderately pigmented melanocytes were purchased from Cascade Biologics . These cells were cultured in Medium 254 with the melanocyte specific HMGS supplement ( Cascade Biologics ) . Beclin 1 heterozygous mice were obtained from Beth Levine . Angeli's salt was a gift from Pat Farmer . Cyanamide was purchased from Sigma . Bafilomycin A1 was purchased from Tocris Biosciences . The genome wide siRNA library used in these studies was previously described [24] . RPMI 1640 ( Invitrogen ) was media used for creating lipid oligonucleotide mixtures . All transfections utilized Dharmafect-2 transfection reagent ( Dharmacon ) . For western blotting we utilized the following antibodies: tyrosinase ( Santa Cruz Biotechnology , cat # sc-7833 ) , MITF ( Santa Cruz Biotechnology , sc-56725 ) , Erk1 ( Santa Cruz Biotechnology , sc-94 ) , and Melan-A ( Santa Cruz Biotechnology , sc28871 ) . Primary antibody dilutions used in these studies ranged form 1∶200 to 1∶1000 and anti mouse or anti rabbit HRP antibodies ( Santa Cruz Biotechnology ) were used in the immunoblot analysis . Antibodies used for immunofluorescence are described below . S100B antibody was purchased from DakoCytomation . High throughput transfection was performed essentially as described [24] with slight modifications . 0 . 28 pmoles of each siRNA pool in a volume of 30 ul of RPMI was delivered to each of 6 assay plates/master plate using a Biomek FX robotic liquid handler ( Beckman Coulter ) . 0 . 1 ul of Dharmafect 2 ( Dharmacon ) in 9 . 9 ul of RPMI was then delivered to each well using a TiterTek Multidrop . Following a 20–30 minute incubation , 1×104 MNT-1 cells from a trypsin-mediated single-cell suspension were delivered to the siRNA/liposome complexes in a total volume of 200 ul . Plates were incubated for 120 hours at 37°C/5% CO2 after which a Hydra 96 ( Robbins-Scientific ) was used to removed 100 ul of the medium . 15 ul of CellTiter-Glo Reagent ( CTG ) ( Promega ) was delivered to each well and incubated according to manufacturer protocol . Luminescence and absorbance values for each well was recorded using an Envision Plate Reader ( Perkin Elmer ) . Each transfection was performed in duplicate . Raw luminescence values collected from the high throughput screen were normalized to internal reference control samples ( cells with no siRNA in wells A1–A8 ) on each plate to allow for plate-to-plate comparisons . These values were used to normalize absorbance values for each well in the plate , effectively controlling for the impact of each siRNA on cell viability . To normalize for positional variation in the plates secondary to prolonged culture times in the humidified incubator , each well in the plate was normalized to the mean value from all wells in the same location . Mean and standard deviation for each data point and the mean and standard deviation of the entire distribution was calculated . siRNAs that produced absorbance/CellTiter-Glo ratios two standard deviations below the mean were subjected to further analysis . 4×103 MNT-1 cells were transfected in 96 well plates with 50 nM candidate siRNA using 0 . 2 ul dharmafect 2 reagent . 48 hours after transfection , cDNA was prepared from transfected cells utilizing a Cells to Ct kit ( Ambion ) per the manufacterer's protocol . Primers targeting each candidate gene , tyrosinase , actin and MITF were purchased from Applied Biosystems . An aliquot of each cDNA reaction was then added to each Taqman master mix reaction along with the appropriate primer per the manufacturer's protocol ( Applied Biosystems ) . A 7900HT Fast Real-Time PCR System ( Applied Biosystems ) was utilized to determine Ct values . Values were normalized using actin and analyzed using the relative quantification mathematical model ( Pfaffl ) . 1×104 MNT-1 cells were plated in a 96 well microtiter plate . 24 hours after plating , cells were incubated with vehicle , hydroquinone Angeli's salt , or cyanamide . 48 hours after drug treatment , cell lysates were prepared and subjected to immunoblotting with a tyrosinase and ERK antibody . Similar protocols were utilized in primary melanocytes . Melanocytes were plated in 96 well microtiter plates in the presence of drug or vehicle . 24 hours after drug treatment , melanocytes were treated with UV . Cell lysates were prepared 24 hours after UV treatment and subjected to immunoblotting . In order to measure an impact of cyanamide on pigment production in melanocytes , primary melanocytes were incubated in the presence of vehicle , phenylthiourea , or increasing concentrations of cyanamide . Cells were incubated for an additional 7 days , with one media change on day 4 , prior to collection of absorbance and viability values . For bafilomycin experiments , MNT-1 cells were transfected with 75 nM siRNA in 12 well plates . 80 hours after transfection , 25nM bafilomycin was added . 96 hours after transfection cell lysates were prepared and subjected to immunoblotting . For immunoflourescence detection of melanosome and autophagy markers , cells were fixed in 2% paraformaldehyde for 1 hour . Coverslips were washed in PBS , cells were permeabilized with 0 . 1% Triton-X-100 ( MNT-1 cells ) or 0 . 4% saponin ( primary melanocytes ) , and blocked in 1% BSA with 0 . 1% Tween 20 . Cells were incubated with the following primary antibodies: Pmel17 ( HMB50 , Lab Vision Corporation , 1∶100 dilution ) , Apg5 ( Santa Cruz Biotechnology , sc-33210 , 1∶50 dilution ) , and LC3b ( Santa Cruz Biotechnology , sc-28266 , 1∶50 dilution ) , for 1 hour . The secondary antibodies used in this study were Alexa Fluor 514 and 594 purchased from Invitrogen . Coverslips were incubated in a 1∶1000 dilution of the corresponding secondary antibody for 1 hour . Confocal images were acquired using a LSM-510 meta confocal multiphoton microscope . Beclin1 haploinsufficient mice were generated as described . [39] All studies involving beclin1 +/+ and beclin1 +/− mice utilized animals that had been backcrossed with C57BL/6J for a minimum of six generations . Representative pictures and figures contained in the manuscript were generated from littermates . Mouse skin sections from four wild type and four beclin 1 haploinsufficient mice were fixed in formalin and paraffin embedded . Haematoxylin and eosin staining were performed following standard protocols . Melanin was stained using the Masson-Fontana technique with a neutral red counterstain [41] . S100 staining was performed as described using an eosin counterstain [42] .
|
Aberrant pigment regulation correlates with skin disorders , opthalmologic disorders , and neurologic disorders . While extensive studies have identified regulators of mouse coat color , the regulation of human skin phenotypic variation is less well understood . To give a broader picture of the molecular regulators of melanogenesis in human cells , we used a genome-wide siRNA functional genomics approach to identify 92 novel regulators of melanin production in heavily pigmented MNT-1 melanoma cells . Our screen identified several genes that converge to regulate tyrosinase , the rate-limiting step in pigment production , in both MNT-1 cells and primary melanocytes . Some of the identified genes were selectively active in different genetic backgrounds , suggesting that they may regulate human phenotypic variation . Small molecule inhibition of a family of novel pigment regulators was sufficient to impair pigment production in melanocytes . Additionally , our screen identified molecular machinery known to support autophagosome biosynthesis as putative regulators of melanogenesis . In vitro co-localization studies and autophagy-deficient mice provided evidence that normal melanogenesis requires the same molecular machinery used by the autophagy pathway . Taken together , these results illustrate the utility of genome wide siRNA screening approaches for identifying genes , novel pharmacologic agents , and pathways that regulate differentiated cellular phenotypes .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] |
[
"genetics",
"and",
"genomics/functional",
"genomics",
"pharmacology/drug",
"development",
"cell",
"biology/membranes",
"and",
"sorting",
"dermatology/pigmentary",
"disorders",
"cell",
"biology/gene",
"expression"
] |
2008
|
Genome-Wide siRNA-Based Functional Genomics of Pigmentation Identifies Novel Genes and Pathways That Impact Melanogenesis in Human Cells
|
Human schistosomiasis is a highly prevalent neglected tropical disease ( NTD ) caused by Schistosoma species . Research on the molecular mechanisms influencing the outcomes of bladder infection by Schistosoma haematobium is urgently needed to develop new diagnostics , therapeutics and infection prevention strategies . The objective of the research study was to determine the microbiome features and changes in urine during urogenital schistosomiasis and induced bladder pathologies . Seventy participants from Eggua , southwestern Nigeria provided morning urine samples and were screened for urogenital schistosomiasis infection and bladder pathologies in a cross-sectional study . Highthroughput NGS sequencing was carried out , targeting the 16S V3 region . Filtered reads were processed and analyzed in a bioinformatics pipeline . The study participants ( 36 males and 34 females , between ages 15 and 65 ) were categorized into four groups according to status of schistosomiasis infection and bladder pathology . Data analytics of the next-generation sequencing reads revealed that Proteobacteria and Firmicutes dominated and had influence on microbiome structure of both non-infected persons and persons with urogenital schistosomiasis . Furthermore , gender and age influenced taxa abundance independent of infection or bladder pathology . Several taxa distinguished urogenital schistosomiasis induced bladder pathologies from urogenital schistosomiasis infection alone and from healthy persons , including known immune-stimulatory taxa such as Fusobacterium , Sphingobacterium and Enterococcus . Some of these significant taxa , especially Sphingobacterium were projected as markers of infection , while several genera including potentially beneficial taxa such as Trabulsiella and Weissella , were markers of the non-infected . Finally , expected changes in protein functional categories were observed to relate to cellular maintenance and lipid metabolism . The urinary microbiome is a factor to be considered in developing biomarkers , diagnostic tools , and new treatment for urogenital schistosomiasis and induced bladder pathologies .
Human schistosomiasis is a devastating and highly prevalent neglected tropical disease ( NTD ) caused by Schistosoma species , a genus of parasitic flatworms with life cycle forms found in freshwater , freshwater snails and human organ systems [1] . Cercarial forms of the parasite are released from infected water snails and penetrate human skin . Eventually , the adult forms inhabit and produce eggs in the intestinal or bladder tissues . The cercariae , schistosomulum and adult stages are all capable of inducing host immune response [1–3] . The eggs of Schistosoma haematobium in the human bladder can cause a spectrum of urogenital clinical presentations including granulomatous inflammation , fibrosis , urinary tract infections and bladder cancer [2 , 3] . Seventy-eight countries and a quarter of a billion persons are at risk of schistosomiasis [4] . After considering the disease along with other NTDs , Nigeria was described as ‘ground zero’ of schistosomiasis due to the high endemicity in the country [5] . Few studies have reported on the immune response to urogenital schistosomiasis in Nigeria [6] , with several studies in different parts of the country reporting prevalence rates between 15–57%[7 , 8] . The occurrence and different forms of bladder tumors and bladder pathologies have been associated with urogenital schistosomiasis in Nigeria[9]and in other parts of Africa[2 , 10] . Research on molecular pathology influencing the outcomes of bladder infection by Schistosoma haematobium is urgently needed to develop new diagnostics , therapeutics and infection prevention strategies[3] . Earlier studies have suggested that the mechanism of formation of bladder tumours will be due to formation of nitrosamines , polyaromatic hydrocarbons , free radicals , and presence of microbes [11] . More recently , studies have highlighted the role of estrogen-related molecules from the parasite in disease progression [12] , based on the discovery that they could be oxidized to form adducts [13] , induce infertility in females [14] , and could probably induce error-prone DNA repair [15] . Molecules related to estrogen were recently detected in urine samples of persons infected with schistosomiasis [16] . Our collaboration with communities in Nigeria at risk of schistosomiasis bladder-related pathologies presents opportunities to conduct basic and translational research projects[6 , 9 , 17] . We are interested in understanding the influences of microbial taxa on human health and disease [18] including the induction of bladder pathologies in urogenital schistosomiasis . Genomic sequencing technologies can determine the membership of , and functions performed by microbial communities ( microbiome ) in the urine [19–21] . The human microbiome is the community of microbes that is estimated to encode up to several million genes with the capacity to influence human health and disease[22] . The microbiome mediates the effectiveness of drugs , xenobiotics and vaccines[23] , and influences disease or health status [24] . The microbiome along the urinary tract structure can have adverse or beneficial effects on human health [19–21] . Therefore , the goal of the research study reported in this article was to understand the microbiome features ( taxa membership and functions of encoded microbial proteins ) in the urine samples from healthy persons and persons infected with urogenital schistosomiasis and related pathologies . The availability of volunteers with asymptomatic schistosomiasis in Eggua , in southwestern Nigeria allowed us to accomplish the research goal . Seventy volunteers were categorized into groups based on the presence of infection and induced bladder pathologies . The objectives of the study were to ( 1 ) determine the microbiome changes in urine samples during urogenital schistosomiasis and induced pathologies; and ( 2 ) identify functional biological processes that could be altered by such changes .
The approach of the research study consisted of recruiting study participants; screening for schistosomiasis infection and bladder pathologies; microbiome sequencing; pre-processing of microbiome sequences; and data analytics of microbiome sequence data collection . Study participants were adults recruited from Eggua , in Ogun State , southwestern Nigeria ( 07° 01 . 592 N; 002° 55 . 083 E ) in a cross-sectional study . Nearby communities have previous history of urogenital schistosomiasis and it was shown recently that the bladder pathologies occurrence in these localities is essentially driven by prevalence of urogenital schistosomiasis infection [7] . Ethical approval was obtained from University of Ibadan/University College Hospital Institutional Review Committee as well as the Ogun State Ministry of Health . Participants were duly informed about the study before sampling and informed consent obtained from all participants , with language translation as required . Exclusion criteria included recent use of antibiotics , painful bladder , urine discharge problems , common urinary tract infection . This was determined by interviews . While some of these criteria may indeed be due to urogenital schistosomiasis , it was necessary to prevent confounders and ambiguity . Samples suspected of urinary tract infection ( positive nitrites , positive leukocyte esterase and ≥ 5wbc/high power field ) were removed from further analysis . Seventy samples meeting the exclusion criteria were eventually processed for high throughput sequencing . Medical history , routine diet and demographic factors were obtained via structured questionnaire , and participants provided midstream urine samples . All samples were collected in the morning hours and immediately anonymized upon collection . The presence of analytes in the urine samples was immediately determined with Urinalysis Reagent Strips ( Rapid Labs , UK ) , and urine microscopy was done on a 10 ml aliquot to detect S . haematobium eggs after sedimentation; and the rest was immediately frozen until further use and transported under dry ice conditions when required . Egg shedding may be infrequent in chronic infection , hence if a sample was negative for S . haematobium eggs , it was subjected to PCR detection using published Dra1 primers [25] . Briefly , 25ul PCR reaction mix containing 100ng isolated urine DNA was prepared . Cycling conditions were: initial denaturation at 95°C for 5mins , 30 cycles of 95°C for 30 secs , 55°C for 30 secs and 72°C for 1min , and final extension at 72°C for 10mins . Bladder scans were carried out with Titan UltraSystem ( Sonosite , WA , USA ) by a trained radiologist , and all images scored according to WHO recommendations [26] and also anonymized . One ml of urine was pelleted and DNA was isolated using Qiagen Blood and Tissue kit ( Qiagen , Hilden , Germany ) , with the modification of adding 20mg/ml of lysozyme at the lysis stage . Isolated DNA was quantified with NanoDrop spectrophotometer ( Thermo Fisher Scientific , MA , USA ) , with quality assessed as 260/280 absorbance ratio >1 . 8 . Library preparation and sequencing were done as previously described [24] . Briefly , quality control of sequencing library ( size and quantity ) was done on 2100 BioAnalyzer ( Agilent Technologies , CA , USA ) following manufacturer’s protocol . Highthroughput sequencing targeting the V3 region of the 16S rRNA gene was carried out on IonTorrent PGM platform . Sequencing and barcoding were done using Ion PGM Sequencing 200 kit v2 and Ion Xpress Barcodes Adapters ( Thermo Fisher Scientific , MA , USA ) using manufacturer's protocol . Barcoded libraries purified with Agencourt AMPURE beads ( Beckman Coulter , CA , USA ) , and equimolar amplicons were pooled prior to sequencing . V3 primers used were 343F- 5’TACGGRAGGCAGCAG3’and 533R- 5’TTACCGCGGCTGCTGGCAC 3’ . Processing and quality filtering of sequence data was done using QIIME 1 . 9 . 1 [27] . Operational Taxonomic Units ( OTUs ) were defined based on 97% sequence similarity and taxonomic classifications were assigned using the Greengenes g_13_8 [28] . Where reference to the Greengenes database did not identify OTUs up to genus level , we used BLASTn to assign taxonomy based on 100% coverage and >98% identity , though this was possible for only two OTUs . Sequence data was examined for possible contamination from kits using the correlation between OTUs and amplicon concentration ( purified individual library ) [29 , 30] . Sequencing was evaluated with Good’s coverage and rarefaction plots . Data was screened for missing values , normality and excessive outliers before applying statistical tools . After rarefaction to 2952 reads , biostatistical analyses were performed using STAMP [31] , R packages Vegan [32] and Biom [33] . Public server at http://huttenhower . sph . harvard . edu/galaxy/ was used for LEfSe [34] . All tests were two-tailed; significant results were indicated by a p value < 0 . 05 and effect size estimated with Eta-squared . Mann-Whitney test ( or non-parametric White's test [35] in STAMP ) was used to test for significant differences between two groups . Comparison of multiple groups was done using non-parametric Kruskal-Wallis test and Tukey-Kramer post hoc test . Benjamini-Hochberg test/FDR was used for multitest correction . In consideration of the criticisms of normalization using rarefaction [36] , which in this case would leave out 11 samples from analysis , we applied edgeR’s RLE method [37] to normalize samples , for the fold change or differential abundance analysis of microbiome; thus including all 70 samples . Variance threshold was set at 1e-5 and FDR<0 . 05 . Functional profiles were inferred with PICRUst [38] .
One of the key findings of this research was that microbial taxa membership and predicted protein function were uniquely discriminant for persons with urogenital schistosomiasis and those who were not infected . Data and project information are deposited in NCBI’s Sequence Read Archives under accession SRP094688 . A total of 1 . 4 million non-polyclonal , trimmed and filtered reads was obtained after quality control . Good’s coverage was 98% and average conditional uncovered probability estimates was 0 . 05 . The reads formed 2946 OTUs , excluding 1504 singletons which were removed before abundance and multivariate analyses . No OTUs were strongly and negatively correlated with purified amplicon concentration , but ten OTUs had moderate , negative correlation ( rho = -0 . 3 to -0 . 4 ) . This indicated that there was minimal level of probable contaminants from reagents . About 110 OTUs occurred in at least 55% of samples and only 1 OTU in all samples . The seventy samples analysed for urinary microbiome through NGS comprised 36 males and 34 females , between the ages of 15 and 65 years . Interviews revealed that the diet was essentially uniform , with a strong starch base . Bladder pathologies detected included abnormal thickness ( >5mm of a full bladder ) , calcification , bladder mass , hyperplasia and irregular shape . We identified four major groups of participants based on the status of infection and bladder pathology ( Table 1 ) , comprising ( a ) the Advanced group , having infection and bladder pathologies , ( b ) Bladder pathology-only group , ( c ) infection-only ( detected by microscopy or PCR ) , and ( d ) controls ( no infection or pathology ) . For microbiome abundance analysis , we also grouped all samples into two—infected and non-infected . Differences in proportions of some phyla in the urine microbiome in the study population are presented in Figs 1 and 2A–2D . The mean relative abundance of two phyla , Proteobacteria ( 70% ) and Firmicutes ( 26% ) were the largest in the microbiome of the sample population , with Bacteroidetes , Actinobacteria , Fusobacteria , Cyanobacteria and others making up the rest ( Fig 1 , Fig 2A ) . The proportions of Proteobacteria differed among groups , highest in infection-only ( 65% ) and pathology-only ( 80% ) cases , and lowest in advanced cases ( 42% ) . The Proteobacteria proportion was higher in non-infected ( 73% ) compared to infected ( 66% ) , and was unchanged in pathology ( 68% ) compared to pathology-absent cases ( 69% ) . In all three comparisons , the opposite is true for Firmicutes . Virtually all of the Actinobacteria OTUs were found in controls and advanced cases . Having observed increased Firmicutes and decreased Proteobacteria in infected cases , the log of the ratio of the abundance of Firmicutes to Proteobacteria was calculated for each sample and plotted as a dysbiosis index . This index associated negatively with disease progression but the correlation was not statistically significant ( rho = -0 . 29 , p = 0 . 08 ) ( Fig 2B ) . The most dominant genera were Pseudomonas , Staphylococcus , Acinetobacter , Enterococcus , unclassified Enterobacteriaceae and Facklamia ( Fig 1 ) . The first three , made up 60% of the whole community . Of the OTUs formed , the most abundant OTUs were those belonging to Pseudomonas and Staphylococcus ( Fig 1 ) . Facklamia was essentially found only in advanced cases , making up 12% in proportion . Pseudomonas proportions were increased by more than two-fold in infection-only and pathology-only cases ( each at 47% ) compared to advanced cases ( 19% ) or controls ( 15% ) . In terms of diversity of the samples , alpha diversity was estimated using the inverse Simpson’s index ( 1/D ) ; this measure takes both OTU richness and relative abundance into account and the results are presented in Fig 3A–3C . We found a non-significant reduction in mean diversity in infected cases compared to non-infected , in pathology cases compared to no-pathology cases , and in advanced cases compared to others ( p = 0 . 1 ) ( Fig 3A and 3B ) . There was higher number of OTUs detected in infected , pathology and advanced cases , respectively in each case . This indicated that advanced cases had higher number of OTUs but reduced diversity index compared to the other three groups . The same was observed for infected cases compared to non-infected cases . Beta diversity was assessed using Bray-Curtis metrics to estimate dissimilarities based on OTU level , rarefied data . Similar patterns were observed considering infection and pathology . The first two principal coordinates explained 36% of the variation among them , and a plot of the first two axes revealed little level of axes separation among the sample groups ( Fig 4A ) . Of the ten most dominant OTUs , 4 of them , all assigned to the genus Pseudomonas , were prevalent ( and in opposition to other prevalent OTUs ) along the first axis ( Fig 4A ) . They clustered close to several infected or pathology samples . Four other OTUs , all assigned to Staphylococcus were in contrast , driving the axes in the opposite direction , and clustering close to some control samples ( Fig 4A ) . Mean diversity of organisms differed among age groups ( Fig 3C ) , and the middle-aged group contained 33% more OTUs than the young or elderly age groups . Since presence of infection or pathology could be expected to affect taxa differences in different ways among age groups and prevalence rates were different among the age groups , we tested taxa differences among age groups using only controls ( n = 13 ) , There were no significant taxon differences at all levels tested , which was probably due to low sample size for comparison . We therefore used partial canonical correspondence analysis to explain taxa differences with age of participants . This will involve all samples and statistically exclude the influence of being infected or having pathology . To achieve this , the age groups were arranged into smaller ranges i . e . age 10–20 ( teens ) , 20–30 , up to 60 and above . This was to increase the number of age groups to six , which was considered better in this type of analysis than having three groups . Canonical correspondence analysis was then mapped using the age ranges as constraining variables and infection as conditioning variable . This was done in order to parse the effect of being infected or not on each taxon . Only OTUs present in at least 40% of samples were utilized . Four OTUs , all assigned to genus Acinetobacter appear sensitive to age 60 and above , those assigned to Citrobacter , Enterococcus , and Enterobacteriaceae were sensitive to age 30–40 ( Fig 4B ) . Indeed , age group 30–40 could be influenced by many OTUs . Similar results were obtained with pathology as the conditioning variable . There was a difference between sexes in the microbial community at the OTU and genus levels . There was more abundance of Actinobacteria and Bacteroidetes phyla in females than males ( Fig 2C ) . More heterogeneity was observed in females , with 40% more OTUs present compared to males . There was a non-significant reduction in diversity in female samples . Using only control samples , unclassified Enterobacteriaceae and unclassified Pseudomonadaceae were significantly abundant in females ( p = 0 . 035 , p = 0 . 021 , respectively ) . There was a significant difference in the microbial community between infected and non-infected , at all levels tested , genus level ( p = 6 . 55E-10 ) and OTU levels ( p = 2 . 06E-16 ) ( Fig 2D ) . Several features ( taxa ) could distinguish persons infected with urogenital schistosomiasis and non-infected persons . Differences in the abundance of microbiome taxa in the study groups are depicted in Fig 5A–5D , S1 Fig and S2 Fig . At phylum level , the differences in the dominant phyla , Proteobacteria and Firmicutes , was not statistically significant between the infected and the non-infected . Phylum Fusobacteria , was the only significant phylum ( FDR = 0 . 006 ) , to distinguish infected samples from non-infected samples . At family level , twenty-two families showed differential abundance between infected and non-infected . The abundance of Veillonellaceae , Fusobacteriaceae , Lactobacillaceae and Enterococcaceae were among those significantly higher in infected cases , while Oxalobacteraceae , Enterobacteriaceae , Staphylococcaceae among others were significantly abundant for non-infected samples ( FDR<0 . 05 ) ( Fig 5A ) . At the genus level , bacterial genera most significantly abundant in infected samples included Facklamia , Fusobacterium , Veillonella , Bacteroides , Lactobacillus and Enterococcus . On other hand , Bacillus , Staphylococcus , Janthinobacterium , Edwardsiella , unclassified Bacillaceae , unclassified Enterobacteraceae , Trabulsiella , Xenorhabdus , Collimonas and Weissella were significantly associated with non-infected samples ( FDR<0 . 05 ) ( Fig 5B ) . Different Acinetobacter OTUs were associated with both infected and non-infected samples ( Fig 5B ) . Only some of these genera , especially Fusobacterium and Janthinobacterium , were found to be highly abundant in infected or non-infected samples , respectively , if rarefaction was applied before analysis ( S2A Fig ) . Comparing controls to other groups , unclassified Clostridiales ( p = 0 . 047 , η2 = 0 . 11 ) was highest in controls , and lowest in infection-only and pathology-only cases ( S1A Fig ) . Enterobacteriaceae ( 0 . 24≥ η2 ≤0 . 29 , 0 . 022≥ p ≤0 . 039 ) was more abundant in controls ( S1B Fig ) , and Pseudomonadaceae ( 0 . 14≥ η2 ≤0 . 31 , 0 . 025≥ p ≤0 . 048 ) far more abundant in infection-only cases and pathology-only cases ( S1C Fig ) . The correlation of Lactobacillus abundance and healthy status was negative ( rho = -0 . 34 , p = 0 . 039 ) ( S1D Fig ) . Five genera—Facklamia , Veillonella , Fusobacterium , Bacteroides , and Aerococcus—were the most differentially abundant in advanced cases , when compared with infection-only cases , pathology-only or control cases ( Fig 5C and 5D , Fig 6A ) . Aerococcus , Acinetobacter and Staphylococcus were most changed in infection-only cases ( Fig 6B , S2B Fig ) , though other OTUs of Acinetobacter and Staphylococcus were highly associated with control cases . The least changes in taxa between groups were in the pathology-only: control pair and the pathology-only: infection-only pair . Microbiome sequence data was subjected ( at OTU and genus levels ) to discriminant analysis using LEfSe to identify possible biomarkers . Comparing infected and non-infected cases , all taxa that were significantly associated with each group from earlier significance analysis were also identified at the OTU level . At genus levels , only two of the significant taxa , Sphingobacterium and Aerococcus were projected as markers of infection , while several genera including Trabulsiella and Weissella , associated with non-infected ( Fig 7 ) . Using our sequence abundance data , we obtained imputed metagenomes and the associated KEGG Orthology pathways present in the microbiome . Nearest Sequenced Taxon Index ( NSTI ) summary ranged from 0 . 021 to 0 . 053 ( mean = 0 . 039 ) . This indicated that several closely related genomes were available for inference purposes . A total of 328 functional categories from 6908 KOs were identified . Of the features differentiating infected samples , several were significant ( Fig 8 ) between infected and non-infected cases , though the effect sizes were rather small . This may be expected given that large portions of microbiome were shared . Considering all four groups together , 7 features which were statistically different—including lipid metabolism ( reduced in advanced cases ) and alpha-linoleic acid metabolism ( reduced in advanced and infection-only cases ) ( 0 . 1<η2 >0 . 143 ) . In pairwise comparison with other groups , the more abundant features with the best effect sizes in advanced cases were pathways involving DNA maintenance including mismatch repair ( η2 = 0 . 28 ) , DNA recombination/repair , and translation factors ( S3 Fig ) .
The overall microbiome structure from our data is , in part , similar to those of earlier studies [19 , 20 , 39 , 40] . These studies also showed that the two phyla , Proteobacteria and Firmicutes , which form the core of the microbiome in the present study , occur in human urinary microbiome . But , in contrast to the aforementioned studies , low proportions of Firmicutes , very high proportion of Proteobacteria , and very low proportions of Actinobacteria /Bacteroidetes , are the features which clearly differentiate the microbiome data of the present study . The greater abundance of Actinobacteria and Bacteroidetes in females as reported previously [41] , was also observed in the current study . Despite the low occurrence of these two phyla , the number of their OTUs in the sequence data of the present study was at least three times higher in females than males in this study ( Fig 2C ) . In addition , the dominance of the Proteobacteria and Firmicutes was found in all samples ( Fig 1 , Fig 2A ) , unlike in the previous reports mentioned [19 , 20 , 39] where only few samples had such dominance . The study location is probably of importance in these contrasts; the present study involves a wholly rural and African population , while all these aforementioned reports have been European , Australian or North American . This raises the question of whether a large reduction in Firmicutes and consequent increase in Proteobacteria could be characteristic of a rural African urinary microbiome . Also , the higher proportion of Proteobacteria in non-infected cases , and its lower proportion in advanced cases compared to infection-only or pathology-only , indicates that the dominance of Proteobacteria in our population is not linked with disease conditions . Another observation of the microbiome structure is the relatively high number of singleton OTU ( 1504 out of 4451 ) . This may be indicative of considerable level of individual uniqueness in urinary microbiome composition , though it is also possible that a greater depth of sequencing will reduce the number of singletons . Such an indication of individual uniqueness is buttressed by the nature of the principal coordinates plot ( Fig 4A ) . The spread of the coordinates indicates that there was substantial within-group variation , which therefore affected between-group axis separation . With this , our data shows there is individual uniqueness in the urinary tract microbiome composition . In a study [42] , two of the most dominant genera from our data , Pseudomonas and Staphylococcus , were isolated in only 2% and 18% , respectively , of 920 school children infected with urogenital schistosomiasis in Ibadan , southwestern Nigeria [42] . The study , which was entirely culture based , also highlighted that common urinary tract infection dominated by E . coli and Klebsiella may associate with urogenital schistosomiasis infection . In the current study , we systematically removed samples suspected of UTI , in order to focus on urogenital schistosomiasis alone and to reduce the possibility of analyzing co-infected samples . In addition , we used a high throughput DNA sequencing approach . Thus , our study was different and shows that Pseudomonas and Staphylococcus species are widespread in the population of interest and not simply because of infection . There was a trend of reduction in the mean diversity of the microbiome in infection and advanced cases , and previous studies have reported such a reduction in diversity in disease conditions; such as in cystitis [43] and in inflammatory bowel disease [44] . In the current study , the reduction in diversity is most likely due to presence of S haematobium infection because there is increased diversity in pathology-only cases ( n = 10 ) . Hence the reduction in diversity in advanced cases is not likely to be because of the contribution of pathologies , but rather of S haematobium infection . The observation of a reduction in diversity , coupled with increased number of OTUs , may indicate that almost all species in the urine microbiome were covered by the sequence data and an increase in total sequence collection may not substantially increase microbiome diversity . For age groups and gender , higher number of OTUs was observed in middle aged and in females , indicating greater heterogeneity in females and the middle-aged . This heterogeneity is not due to infection or pathology because in terms of gender , males had more infection and pathology than females , and the middle-aged group had similar infection or pathology rates with other groups . Associating specific taxon with disease state is an important goal in microbiome studies . For this purpose , the results of the present study were mainly examined at the family and genus levels . A substantial number of abundant genera are pathobionts , including–Enterococcus , Bacteroides , Facklamia ( increased in infected ) and Enterobacter , Chryseobacterium , Edwardsiella , etc ( increased in controls ) . However , based on literature and our functional analysis , several of the dominant genera are biologically relevant within the environment . Some of them have been previously found in association with a non-healthy status . Enterococcus was associated with neuropathic bladder patients who are at risk of asymptomatic bacteriuria [45] . A previous study [20] identified Pseudomonas ( in males only ) , Staphylococcus ( in both genders ) , Enterococcus and Facklamia ( females only ) in urine samples of study subjects who were ‘partially healthy’ i . e . without any urinary tract disease or symptoms , but having other non-specified ailments . Also , their individual attributes as a result of specialty genes , proteins or pathways could be of importance in the urinary microbiome , as discussed subsequently . Clearly , the dominant genus , Pseudomonas , in the microbial community did not significantly differ among groups and it may then be suspected that the genus had no influence on urogenital schistosomiasis or induced bladder pathologies , especially , since the Pseudomonas genus is a known opportunistic pathogen in common urinary tract infections [46] . However , a point of interest is the ability of some strains , including P . fragi and P . putida ( along with very few Proteobacteria strains ) , to utilize extraneous steroids such as estrogen , due to the presence of specialized genes , in particular , tesD [47] . This is of interest because a recent report indicated the availability of catechol estrogens , steroid-like molecules , in the urinary tract during urogenital schistosomiasis infection [16] . In the present study , apart from being a dominant genus , the proportions of Pseudomonas and P . fragi were higher in infected cases . Some other OTUs assigned to the same genus were also significantly higher ( 0 . 00799> p<0 . 042 ) . We hypothesize that the presence and proportion of some strains of Pseudomonas may be linked to the availability of greater amounts of steroid-related lipids or other lipid metabolites in the urine of infected persons and those with induced pathologies . Such a hypothesis requires further investigation involving gene expression studies , or reporter assays and strain identification for evaluation and confirmation . Still on the dominant genera , the presence of different sets of OTUs of Acinetobacter or Staphylococcus in infected or advanced cases and in non-infected controls indicate a species-specific abundance in the two conditions . It is difficult to delve deeper into such observation , because longer length sequences than those used in this study are needed to confidently identify species-specific difference in the two opposing conditions . Nevertheless , it is known that some Acinetobacter species , for instance , A . johnsonii can destroy worms while others are pathobionts [48] . We found that genera with roles in the inflammatory process of human and other mammalian hosts associated strongly with and were differentially abundant in infected and advanced cases . The genus Fusobacterium ( up to family , order and phylum level ) consistently associated with advanced cases but not infection-only cases . Fusobacterium possesses potent lipopolysaccharides , are known to recruit immune cells [49] and are ubiquitous in colon cancer biopsies [50] . The genus is also known to serve as anchor for biofilm formation [49] . Sphingobacterium , identified as a marker in urogenital schistosomiasis , is known to possess unusual , non-mammalian sphingolipids containing ceramides . Such compounds are immunogenic and can activate macrophages , thereby contributing to the inflammatory process [51] . Human IgE antibody regulation could be affected in allergy or atopy , by Enterococcus [52 , 53] . We found elevated proportions of Enterococcus in infected persons , and increased IgE levels were associated with urogenital schistosomiasis [54] . It raises the question as to whether Enterococcus prevents excessive buildup of IgE in urogenital schistosomiasis infection . Thus , a future research objective would be to determine the influence of Enterococcus species on human IgE antibody production in urogenital schistosomiasis . To add to this , Bacteroides numbers are sometimes correlated with inflammation , and its lipopolysaccharides are potent immune-stimulators , yet its polysaccharide A is also capable of repressing pro-inflammatory cytokine [55 , 56] . The four genera discussed above were differentially abundant in advanced cases , implying that their abundance is infection-related . All these suggest a possible role for these taxa in the maintenance or inducement of bladder pathologies in schistosomiasis , a disease in which inflammation is a known driver of complications . Such a role will complement other possible inducers of inflammation such as egg oviposition by the parasite . In summary , we have identified few microbial taxa that could regulate the maintenance or initiation of bladder pathologies in urogenital schistosomiasis . A translational application of microbes is in the treatment of bladder tumours . BCG vaccine ( attenuated Mycobacterium tuberculosis ) when injected into the bladder reduced recurrence and progression in half of bladder cancer patients under study [57] . Administration of L . casei or L . rhamnosus in rodent models decreased progression of bladder tumour cells [58] . Both studies [57 , 58] were concerned with bladder tumours that were not due to schistosomiasis . We hypothesize that in S . haematobium induced bladder cancer , strategies to deplete these bacteria taxa combined with BCG vaccine might improve efficacy of treatment at least in some individuals . Another taxon consistently associated with infection state in our data is the genus Lactobacillus ( up to family and order level ) . High Lactobacillus proportion has been identified in both urine and vaginal microbiome studies , though it tends to be more prevalent in females [41] . This was far from the case in the present study . Rather , our data suggests that the microbiome in our study population belong to the ‘diverse’ or low Lactobacillus group urinary microbiome . As in the current study in which Lactobacillus is associated with infected samples , another study [19] also reported increased abundance of this genus in interstitial cystitis . Our study supports the emergent theory that rather than view the whole genus as symbiotic , certain species are more frequent in disease state , for instance , L . gasseri [39] , and could probably be considered pathobiont . A proposed mechanism to explain these observations is that Lactobacillus tolerance to common anti-bacterial compounds allows it to multiply easily and invade tissues to cause inflammatory changes [59] . Some of the significant genera found in the present study have been previously discovered to be associated with healthy or disease state in urine microbiome studies . Dialister and Gemella were previously associated with STI [41] . Dialister and Facklamia were more frequent in incontinence , and Enterobacteriaceae and Staphylococcus were more frequent in healthy controls [39] . Enterococcus associated with cystitis [43] , but Dialister and Staphylococcus have been found in healthy female urine [19] . Our data agree with these earlier studies in the sense that urine microbial genera found to be frequent in a disease state by earlier authors—Facklamia and Enterococcus were also associated with urogenital schistosomiasis . The aforementioned studies indicated that Dialister and Gemella may occur frequently in either disease or healthy state , but in the current study they were more frequent in infection . Other genera previously described in urine samples such as Corynebacterium and Atopobium were all observed in our data , but did not associate with disease or healthy state . The current study has helped to confirm earlier studies on the frequency of some urinary microbial genera in disease state . Some of the significant taxa in the microbial community abundant in control samples ( whether non-infected , non-pathology or both ) are a mixture of pathobionts as well as beneficial and protective species . Enterobacteriaceae have abilities in tolerance of inflammation and redox stress; Collimonas ( anti-fungal ) ; Weissella ( probiotic properties , anti-fungal , antibiotic , stress resistance ) ; Janthinobacterium ( antibiotic , anti-fungal , anti-tumour , stress tolerance ) ; Trabulsiella ( type IV secretory system to prevent competition ) and unclassified Lactobacillales ( lactic acid bacteria group ) [60–66] . Thus , even in the absence of high proportions of Lactobacillus sp , there could be beneficial microbes in the urinary tract . Whether this is unique to our study population or not requires further investigation . In summary , it may be said that bacterial genera with high tolerance , antibiotic and anti-fungal properties ( including lactic acid bacteria ) , were significant residents in control samples . As the results show , some other beneficial species may occur even in advanced cases and such may help to reduce the extent of damage caused . Microbial-related KEGG Ontology ( KO ) pathways obtained from the analysis of imputed metagenomes are of biological importance . The biochemical pathways are essentially predicted from our sequence data and the proteins involved may not be translated , yet the links in predictions merit an examination . It appears that pathways to enhance proliferation and rapid multiplication of cells are increased in the infected samples compared to non-infected , and in advanced cases compared to other groups ( S3A Fig , Fig 8 ) . Hence , repair , transcriptional or translational factors and nucleotide metabolism are significantly higher in infected cases , and even higher in advanced cases ( S3A Fig ) . Multiplication of microbes is sure to induce action from the immune system in the human host and this may aggravate infection . Hence , it is of concern that this proliferation ability increases with disease progression ( i . e . from controls to infected to advanced ) , as our results suggest . In addition , our results suggest decreased biosynthesis of some lipids in infected compared to controls , and in advanced cases compared to other groups . Hence , pathways significantly more abundant in non–infected cases are those that involve synthesis of several lipids involving quinones , terpenoids and steroids . An explanation for the decreased representation of lipid metabolism , synthesis , or modification pathways in infected and advanced cases could be the abundance of such molecules in the environment ( since it has been reported that S . haematobium produces steroid-like lipids into the urinary tract ) . The question arises especially because it is known that microbes may switch on/off regulatory mechanisms in the presence of needed materials . Further research is clearly needed to explore this relationship . Some of the significant biochemical pathways from this study have also been highlighted in earlier studies . In a review of empirical studies , Borningen et al . [67] highlighted the involvement of riboflavin metabolism in IBD ( Inflammatory Bowel Disease ) , nucleotide and lipid metabolism in type1 diabetes . In the current study , our analysis suggests reduced riboflavin and lipid metabolism , and like IBD , urogenital schistosomiasis is also inflammation driven , leading to induced pathologies . Hence , while IBD is not a parasitic disease , it appears part of the inflammatory process involving microbes may be shared with urogenital schistosomiasis . Furthermore , there is a noticeable link among the microbial pathways whose gene abundances are reduced in infected samples . Alpha-linolenic acid is known to be produced by lactic acid bacteria , it can inhibit shikimate kinase , a precursor to the formation of chorismate ( KEGG C00251 ) in the shikimate pathway . 4-Hydroxybenzenoate ( KEGG C00156 ) from chorismate is used by bacteria in the biosynthesis of ubiquinone and other-terpenoid-quinone , a process more abundant in non-infected cases . Also , isochorismate ( KEGG C00885 ) from chorismate is essential for biosynthesis of siderophore group non-ribosomal peptides , another process more abundant in non-infected cases . A product of 4-Hydroxybenzenoate , hydroquinone , in its modified form , is a byproduct in riboflavin synthesis . This linkage is probably important and could depend heavily on the shikimate pathway and chorismate . It is known that several downstream products of chorismate are useful as antimicrobials [68] , and that the ubiquinones , terpenoid-quinones and riboflavin play important roles as coenzymes in oxidative phosphorylation and electron-carrier system . Also , the siderophore group non-ribosomal peptides include several catechol-based molecules for import of iron chelation , importation of xenobiotics into the cell among other functions [69 , 70] . This is in addition to the fact that some transporters are also significantly reduced . Thus , the abundance of microbial biological processes is altered in the course of urogenital schistosomiasis and bladder pathologies . An explanation for the altered abundance is that dysbiosis brought about by loss or reduction of protective , beneficial bacteria creates a more stressful and less controlled microbiome during urogenital schistosomiasis infection . The use of midstream urine as a representative of the bladder surface from which it is discharged , is not without disagreement in literature [43 , 71] . The arguments about the methods are fuelled by the possibility of contamination especially in samples from females or the elderly; hence contaminant removal is crucial . In this study , none of the elderly participants had any impairment and with proper instructions to participants , we believe that contamination was minimal . Hence , the samples analyzed in this study comprise the bladder surface microbiome . Also , in this study , virtually all genera reported from studies using transurethral catheterization to sample bladder microbiome [39] were observed . In addition , given that other forms of bladder pathology exist , a vast majority of the pathology cases recorded here are induced by urogenital schistosomiasis infection . In our study locality , bladder pathology was extensively associated with urogenital schistosomiasis [9] . It is also possible the pathology cases with no infection ( determined by urine microscopy only ) , could be due to a chronic urogenital schistosomiasis infection in which egg shedding reduces progressively with occurrence of pathologies . To summarize , while the current study substantially reports differences in the urinary tract microbiome between persons infected with urogenital schistosomiasis and healthy persons , and between persons having bladder pathologies due to urogenital schistosomiasis and persons with urogenital schistosomiasis infection alone , there are a few possible limitations . It remains to be confirmed if there is long-term stability in the microbiome observed , although the infected cases in the present study can be classified as chronic infection . Another limitation may be the small sample size .
In this study , we examined the urinary microbiome in urinary or urogenital schistosomiasis and its induced bladder pathologies . We found that the urinary tract microbiome of the whole study population itself differs from earlier studies elsewhere . We also detected several beneficial and stress tolerant taxa in control cases , and immune-stimulatory taxa in urogenital schistosomiasis infected and urogenital schistosomiasis associated bladder pathology cases . In the microenvironment of the bladder and urinary tract , these changes probably cause lower chorismate production , synthesis of some lipids and promote self-proliferation . The urinary microbiome is a factor to be considered in developing biomarkers , diagnostic tools , and new treatment for urogenital schistosomiasis and induced bladder pathologies .
|
The human microbiome comprises bacteria ( plus viruses , fungi and archeae ) inhabiting different sites of the body . They do not specifically cause diseases , but their presence , absence or population influence body functions . We therefore examined such organisms found along the urinary tract , in persons living in a rural community in Nigeria who considered themselves healthy , were infected with the parasite Schistosoma haematobium or had developed bladder complications along with the parasite infection . We found that these groups shared a large portion of the microbiome , but there were microbial species unique to infected persons and those with bladder complication . Some of these were capable of inducing inflammation and could offer less protection to the host . We also predicted pathways that are affected by the difference in the microbiome .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion",
"Conclusion"
] |
[
"fusobacterium",
"infections",
"medicine",
"and",
"health",
"sciences",
"body",
"fluids",
"microbiome",
"acinetobacter",
"infections",
"enterococcus",
"infections",
"tropical",
"diseases",
"microbiology",
"bladder",
"parasitic",
"diseases",
"urine",
"bacterial",
"diseases",
"pseudomonas",
"infections",
"neglected",
"tropical",
"diseases",
"microbial",
"genomics",
"urogenital",
"schistosomiasis",
"infectious",
"diseases",
"medical",
"microbiology",
"helminth",
"infections",
"schistosomiasis",
"anatomy",
"physiology",
"genetics",
"biology",
"and",
"life",
"sciences",
"renal",
"system",
"genomics"
] |
2017
|
The microbiome in urogenital schistosomiasis and induced bladder pathologies
|
MicroRNAs ( miRNAs ) , a large class of short noncoding RNAs found in many plants and animals , often act to post-transcriptionally inhibit gene expression . We report the generation of deletion mutations in 87 miRNA genes in Caenorhabditis elegans , expanding the number of mutated miRNA genes to 95 , or 83% of known C . elegans miRNAs . We find that the majority of miRNAs are not essential for the viability or development of C . elegans , and mutations in most miRNA genes do not result in grossly abnormal phenotypes . These observations are consistent with the hypothesis that there is significant functional redundancy among miRNAs or among gene pathways regulated by miRNAs . This study represents the first comprehensive genetic analysis of miRNA function in any organism and provides a unique , permanent resource for the systematic study of miRNAs .
MicroRNAs ( miRNAs ) were discovered in C . elegans during studies of the control of developmental timing [1–5] . miRNAs are approximately 22-nucleotide noncoding RNAs that are thought to regulate gene expression through sequence-specific base-pairing with target mRNAs [6] . miRNAs have been identified in organisms as diverse as roundworms , flies , fish , frogs , mammals , flowering plants , mosses , and even viruses , using genetics , molecular cloning , and predictions from bioinformatics [7–16] . In C . elegans about 115 miRNA genes have been confidently identified [10 , 11 , 17–20] . In animals , miRNAs are transcribed as long RNA precursors ( pri-miRNAs ) , which are processed in the nucleus by the RNase III enzyme complex Drosha-Pasha/DGCR8 to form the approximately 70-base pre-miRNAs [21–25] or are derived directly from introns [26 , 27] . Pre-miRNAs are exported from the nucleus by Exportin-5 [28] , processed by the RNase III enzyme Dicer , and incorporated into an Argonaute-containing RNA-induced silencing complex ( RISC ) [29] . Within the silencing complex , metazoan miRNAs pair to the mRNAs of protein-coding genes , usually through imperfect base-pairing with the 3′-UTR , thereby specifying the posttranscriptional repression of these target mRNAs [6 , 30] . Binding of the silencing complex causes translational repression [31–33] and/or mRNA destabilization , which is sometimes through direct mRNA cleavage [34 , 35] , but usually through other mechanisms [36–40] . Because many messages have been under selective pressure to preserve pairing to a 6mer in the 5′ region of the miRNA known as the miRNA seed ( nucleotides 2–7 ) , targets of metazoan miRNAs can be predicted above the background of false-positives by searching for conserved matches to the seed region [41–45] . In nematodes , at least 10% of the protein-coding messages appear to be conserved targets of miRNAs [46] . The in vivo functions of a few miRNAs have been established . In C . elegans , the lin-4 miRNA and the let-7 family of miRNAs control the timing of aspects of larval development . For example , the lin-4 miRNA controls hypodermal cell-fate decisions during early larval development by negatively regulating the lin-14 and lin-28 mRNAs [1–3 , 5 , 47] . The let-7 miRNA controls hypodermal cell-fate decisions during late-larval development by regulating the lin-41 , hbl-1 , daf-12 , and pha-4 mRNAs [48–51] . Three additional C . elegans let-7-like miRNAs , miR-48 , miR-84 , and miR-241 , also act in the control of developmental timing and likely regulate the hbl-1 mRNA , but act earlier in development than the let-7 miRNA [52 , 53] . The C . elegans lsy-6 miRNA acts in the asymmetric differentiation of the left and right ASE chemosensory neurons . Specifically , the lsy-6 miRNA targets the cog-1 mRNA , resulting in a shift of marker gene expression in the left ASE to resemble marker gene expression in the right ASE [20] . The first miRNA studied functionally in Drosophila is encoded by the bantam locus , which had previously been identified in a screen for deregulated tissue growth [54] . The bantam miRNA stimulates cell proliferation and reduces programmed cell death . bantam directly regulates the pro-apoptotic gene hid . A second Drosophila miRNA , miR-14 , also reduces programmed cell death [55] . The muscle-specific Drosophila miRNA miR-1 is required for larval development and cardiac differentiation [56 , 57] . Dmir-7 regulates the transcription factor Yan [58] . Finally , Drosophila miR-9a is required for sensory organ precursor specification [59] , and Drosophila miR-278 is required for energy homeostasis [60] . The first loss-of-function studies of miRNAs in the mouse have been reported demonstrating a role for miR-1 and miR-208 in cardiac growth in response to stress [61 , 62] and miR-155/BIC in normal immune function [63 , 64] . miRNA function has also been inferred from studies in which miRNAs have been misexpressed in worms , flies , frogs , mice , and cultured mammalian cells [65] . In addition , miRNA function has been explored by perturbing the functions of genes in the pathway for miRNA biogenesis and by reducing miRNA levels using antisense oligonucleotides . For example , mutants defective in Dicer , which is essential for miRNA biogenesis , have been studied for C . elegans [66 , 67] , Drosophila [68 , 69] , the zebrafish [70 , 71] , and the mouse [72–75] . In all cases , Dicer was found to be essential for normal development . In addition , members of the AGO subfamily of Argonaute proteins , which act in the miRNA pathway , are essential for normal C . elegans and mouse development [67 , 76] . In Drosophila , 2′ O-methyl antisense oligoribonucleotides have been used in miRNA depletion studies [77] . This technique was initially described for human cells and C . elegans [78 , 79] and appears to offer sequence-specific inhibition of small RNAs for a limited time span . Injection of individual 2′ O-methyl antisense oligoribonucleotides complementary to the 46 miRNAs known to be expressed in the fly embryo resulted in a total of 25 different abnormal phenotypes , including defects in patterning , morphogenesis , and cell survival [77] . Knockdown of miRNAs using modified 2′ O-methyl antisense oligoribonucleotides also has been reported for the mouse [80] . Very recently , a study reported the use of morpholinos to knockdown miRNA function in zebrafish and identified a role for miR-375 in pancreatic islet development [81] . To gain a broader understanding of miRNA function , we generated a collection of deletion mutants of the majority of known miRNA genes in C . elegans . We found that mutations in most miRNA genes do not result in striking abnormalities , and therefore most miRNA genes likely have subtle or redundant roles . This permanent collection provides a resource for detailed studies of miRNA function not possible previously .
The cloning of many miRNAs from C . elegans using molecular biological techniques prompted us to take a genetic approach to study miRNA function in vivo in C . elegans through the generation of loss-of-function mutants . We isolated deletion mutants using established C . elegans techniques [82 , 83] . We made extensive use of the “poison” primer method , which increases the sensitivity of detection of small deletions [84] . Most C . elegans miRNAs were cloned and verified in northern blot experiments [10 , 11 , 17 , 85] . Some miRNAs were predicted based on pre-miRNA folds and verified using northern blotting or PCR with specific primers and cloned miRNA libraries [17 , 18 , 85 , 86] . The public database for miRNAs , miRBase release 9 . 0 , listed 114 C . elegans miRNAs [87 , 88] . Of these 114 , 96 miRNAs are confidently identified , based on expression and the likelihood of being derived from stem-loop precursors , whereas many of the others do not appear to be authentic miRNAs [17–19] . Recently , two studies using high-throughput sequencing methods identified 21 additional miRNAs [19 , 26] bringing the total number of miRNAs identified with high confidence in C . elegans to 115 and the total number of annotated miRNA candidates to 135 . We isolated knockout mutants covering 87 miRNA genes . We previously described our studies of knockouts of three additional miRNA genes [52] , and deletions in two other miRNA genes had been obtained by the C . elegans knockout consortium ( D . Moerman , personal communication ) [84] . Three miRNA genes had been mutated in genetic screens , lin-4 , let-7 , and lsy-6 [2 , 4 , 20] . Thus , 95 C . elegans miRNAs can now be functionally analyzed using mutants ( Table 1 ) . Additional alleles for a subset of these miRNA genes were also isolated by the C . elegans knockout consortium ( D . Moerman , personal communication ) [84] . The median size of the deletions we isolated was 911 bases with a range of 181–6 , 288 bases ( Tables 1 and S1 ) . Some deletions likely affect neighboring genes in the case of intergenic miRNA genes or host genes in the case of miRNA genes found in introns . For example , the lethality linked to mir-50 ( n4099 ) ( Table 2 ) might be a consequence of a loss-of-function of mir-50 or of an effect on the predicted host gene Y71G12B . 11a ( Table 1 ) . We performed a broad phenotypic study of all available miRNA loss-of-function mutants , including mutants that had been reported earlier [2 , 4 , 20 , 52] . We focused on phenotypic assays that are relatively rapid and that examine C . elegans morphology , growth , development , and behavior . The assays we performed are shown in Table 3 and the phenotypes we observed are summarized in Table 2 . Our initial phenotypic analysis revealed a single new abnormality linked to miRNA loss-of-function: deletion of the mir-240 mir-797 miRNA cluster resulted in abnormal defecation cycle lengths . This defecation defect was rescued by the introduction of a transgene carrying the mir-240 mir-797 genomic locus ( Table S2 ) . In addition , we observed other abnormal phenotypes . Mutation of the mir-35–41 miRNA cluster resulted in temperature-sensitive embryonic and larval lethality; this lethality was rescued by the introduction of a transgene carrying the mir-35–41 genomic locus ( unpublished data ) . We were unable to generate homozygotes for alleles of mir-50 and mir-353 . mir-50 and mir-353 are in introns of genes that when inactivated by RNAi result in embryonic lethality and may explain why we could not isolate homozygotes for our new deletions . Indeed , the introduction of a transgene carrying the mir-50 genomic locus failed to rescue the lethality associated with the mir-50 allele ( unpublished data ) . The number of times each of the deletion strains has been outcrossed is shown in Table 2 . It is conceivable that some of the miRNA deletion strains harbor additional mutations that suppress abnormalities conferred by miRNA deletion alleles and that could be revealed by outcrossing . To uncover subtle abnormalities in the miRNA mutant strains will require more detailed analyses , as has been performed for lin-4 , let-7 , lsy-6 , mir-48 , mir-84 , and mir-241 . Nevertheless , we note one striking conclusion: the majority of miRNAs are not essential for C . elegans viability and development .
The overexpression of the miRNAs miR-84 and miR-61 from transgenes in C . elegans affects vulval development [89 , 90] . The overexpression of miR-61 leads to the expression in Pn . p cells that do not normally generate vulval cell fates of reporter genes indicative of vulval cell fates [89] . We examined if miR-61 and the closely related miR-247 were required for the normal induction of primary or secondary vulval cell fates by the Pn . p cells . We found that Pn . p cell induction was normal in mir-61 mutants and in mir-61; mir-247 double mutants ( Table S3 ) , although we did not test the effects of combining these mutants with mutants of mir-44 and mir-45 , which have the same seed and thus are predicted to target the same messages . Similarly , let-60 RAS has been suggested to be a target of miR-84 , based on the observation that overexpression of miR-84 from a transgene suppresses the multivulva phenotype of let-60 RAS activation mutants . If let-60 RAS is a target of miR-84 , loss of mir-84 might result in let-60 RAS overexpression and possibly a multivulva phenotype [91 , 92] . However , as we reported previously , mir-84 single mutants or mir-48 mir-241; mir-84 triple mutants do not have a multivulva phenotype [52] . Thus , for both miR-84 and miR-61 , we were unable to confirm a role in vulval development based on loss-of-function alleles . We conclude that these miRNAs are not required for vulval development and suggest that either they act redundantly with other miRNAs or other pathways in vulval development or they do not normally act in vulval development at all . One difference between most protein-coding genes and most miRNA genes in C . elegans is the number of paralogs . Whereas fewer than 25% of protein-coding genes have a recognizable paralog in the C . elegans genome [93] , about 60% of miRNAs are members of a family of two to eight genes [19] . A higher number of paralogs might be a consequence of smaller gene size , which could allow a greater opportunity for gene duplication . As a consequence , miRNAs might act redundantly with other miRNAs and mutation of all paralogs of a miRNA or a miRNA family might result in synthetic abnormal synthetic phenotypes . Alternatively , some nematode miRNAs might act in parallel with other regulatory pathways that can compensate gene expression when the miRNAs are lost . For example , genetic data indicate that Drosophila mir-7 directly regulates the transcriptional repressor Yan in the fly eye , but that loss of mir-7 does not appreciably alter eye development , probably because of redundant protein turnover mechanisms that can also downregulate Yan [58] . In such a scenario , disruptions in the other mechanisms would be needed to reveal the miRNA function . The discovery that the let-7 miRNA is conserved among bilateria , including such disparate organisms as C . elegans and humans [94] , appears not to have been an exception: for 15 miRNA families , miRNAs with identical seeds have been found in C . elegans , flies , fish , and mammals , and several additional families are predicted to be conserved throughout these diverse lineages [19 , 95–97] . The conservation is not only for primary miRNA sequences , but also , at least in some cases , for patterns of expression . For example , the miRNA miR-1 is expressed in muscles of Drosophila , the zebrafish , and the mouse [11 , 56 , 98] . However , the predicted mRNA targets of miRNAs might not share the same degree of conservation as miRNA expression patterns—the spectrum of predicted mRNA targets varies significantly among metazoans [99] . With several miRNA loss-of-function mutants of Drosophila now available , we can begin to compare miRNA functions between C . elegans and Drosophila . Among the microRNAs for which mutations exist for flies and worms , Dmir-1 and C . elegans miR-1 are the most similar in sequence [56] . Whereas Dmir-1 loss-of-function mutant fly larvae display muscle degeneration and die [56] , we found that C . elegans miR-1 loss-of-function mutant animals are fully viable . Despite these differences , the mir-1 miRNA family could have a conserved role in muscle homeostasis and function . For example , the severity of the muscle defect of C . elegans mir-1 mutants might depend on physiological conditions , as is the case for the Dmir-1 mutant phenotypes of Drosophila [56] . We expect that as additional miRNA mutants become available for flies and other animals there will be future comparative studies of the biological functions of miRNAs using the collection of C . elegans miRNA mutants we have generated . More generally , we believe that the functions of miRNA genes , like the functions of protein-coding genes , will often prove to be conserved among animals , and that the collection of miRNA mutants we have generated will help define , test , and analyze general biological roles of miRNAs .
C . elegans was grown using standard conditions [100] . The wild-type strain was var . Bristol N2 [101] . Nematodes were grown at 25 °C , except where otherwise indicated . Details about the mutant alleles we generated are shown in Table S1 . All strains generated in this study have been submitted to the Caenorhabditis Genetics Center . Deletion allele information can be accessed directly from WormBase ( http://www . wormbase . org ) . Deletion mutants were isolated from a frozen library of worms mutagenized with ethyl methanesulphonate ( EMS ) , 1 , 2 , 3 , 4-diepoxybutane ( DEB ) , or a combination of UV irradiation and thymidine monophosphate ( UV-TMP ) [82 , 83] . In most instances , to enhance the detection of deletions one or two “poison” primers were included in the first round of nested PCR reactions [84] . These poison primers were designed to anneal close to the mature miRNA sequence . In the first round of PCR , the three primers in the reaction ( external forward , external reverse , and poison primers ) generated both a full-length ( from external primers ) and a shorter product ( from external and poison ) from the wild-type allele . The shorter product was amplified more efficiently and thereby out-competed the amplification of full-length product . A deletion allele that removed the miRNA sequence and therefore removed the poison primer-binding site generated a product only from the external primers . In the second round of PCR , two internal primers designed just inside of the external primers amplified the full-length product but not the shorter product from the wild-type allele and a single product from the deletion allele . Mutant strains were outcrossed with the wild-type strain as indicated ( Table S1 ) . The minimum number of individual animals scored in each assay is given as n in parentheses below . ( 1 ) Locomotion: Number of body bends during a 20-s period were counted 4 min after transferring 1-d-old adult animals to fresh plates containing food ( n = 10 ) . ( 2 ) Pharyngeal pumping: Frequency of grinder displacement was counted for 20 s by eye , but otherwise as described previously [102] ( n = 5 ) . ( 3 ) Defecation: The time between defecation cycles marked by posterior body muscle contraction events was measured [103] ( n = 3 , 5 events per animal ) . ( 4 ) Egg laying: 1-d-old adult animals were lysed in bleaching solution for 10 min in the well of a round-bottom 96-well plate , and eggs were counted [100] ( n = 20 ) . ( 5 ) Chemosensory neurons: L2 or L3 larvae were stained with DiO dye ( Invitrogen ) and filling of the neurons ASI , ASJ , ASH , ASK , AWS , ADL , PHA , PHB was scored [104] ( n = 15 ) . ( 6 ) Cell number/nuclear morphology: L1 larvae were fixed and stained with 4′ , 6-diamidino-2-phenylindole , dihydrochloride ( DAPI ) ( Invitrogen ) as described previously [105] . Nuclei of the ventral cord and intestine were counted [106] ( n = 15 ) . ( 7 ) Dauer development: To assay dauer larva entry , three L4 animals were incubated at 25 °C until the F2/F3 progeny had been starved for at least five days . Animals were washed from plates using 1% SDS in de-ionized H2O for 30 min . Dauer larvae were identified by observing their thrashing and re-plated onto plates containing food to assay dauer exit . Constitutive dauer entry was scored by testing animals from plates with food for the presence of dauer larvae isolated after SDS treatment as described above ( n = 50 ) .
The miRNA sequences discussed in this paper can be found in the miRNA Registry ( http://www . sanger . ac . uk/Software/Rfam/mirna/index . shtml ) . The C . elegans miRNA genes , their genomic location and deletion allele information can de accessed directly from WormBase ( http://www . wormbase . org ) [107] .
|
MicroRNAs ( miRNAs ) are tiny endogenous RNAs that regulate gene expression in plants and animals . Individual miRNAs have important roles in development , immunity , and cancer . Although the investigation of miRNA function is of great importance , to date few miRNAs have been studied in the intact organism because of a lack of mutants in which specific miRNAs have been inactivated . Here we describe a collection of loss-of-function mutants representing the majority of all known miRNA genes in the nematode Caenorhabditis elegans . This study identifies a new role for miRNAs in C . elegans and also demonstrates that most miRNAs are not essential for viability or development . Our findings suggest that many miRNAs act redundantly with other miRNAs or other pathways . We expect that this collection of miRNA mutants will become a widely used resource to further our understanding of the biology of miRNAs .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods",
"Supporting",
"Information"
] |
[
"caenorhabditis",
"genetics",
"and",
"genomics",
"developmental",
"biology",
"molecular",
"biology"
] |
2007
|
Most Caenorhabditis elegans microRNAs Are Individually Not Essential for Development or Viability
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HIV-1 envelope glycoprotein ( Env ) mediates virus attachment and entry into the host cells . Like other membrane-bound and secreted proteins , HIV-1 Env contains at its N terminus a signal peptide ( SP ) that directs the nascent Env to the endoplasmic reticulum ( ER ) where Env synthesis and post-translational modifications take place . SP is cleaved during Env biosynthesis but potentially influences the phenotypic traits of the Env protein . The Env SP sequences of HIV-1 isolates display high sequence variability , and the significance of such variability is unclear . We postulate that changes in the Env SP influence Env transport through the ER-Golgi secretory pathway and Env folding and/or glycosylation that impact on Env incorporation into virions , receptor binding and antibody recognition . We first evaluated the consequences of mutating the charged residues in the Env SP in the context of infectious molecular clone HIV-1 REJO . c/2864 . Results show that three different mutations affecting histidine at position 12 affected Env incorporation into virions that correlated with reduction of virus infectivity and DC-SIGN-mediated virus capture and transmission . Mutations at positions 8 , 12 , and 15 also rendered the virus more resistant to neutralization by monoclonal antibodies against the Env V1V2 region . These mutations affected the oligosaccharide composition of N-glycans as shown by changes in Env reactivity with specific lectins and by mass spectrometry . Increased neutralization resistance and N-glycan composition changes were also observed when analogous mutations were introduced to another HIV-1 strain , JRFL . To the best of our knowledge , this is the first study showing that certain residues in the HIV-1 Env SP can affect virus neutralization sensitivity by modulating oligosaccharide moieties on the Env N-glycans . The HIV-1 Env SP sequences thus may be under selective pressure to balance virus infectiousness with virus resistance to the host antibody responses . ( 289 words )
The HIV-1 envelope glycoprotein ( Env ) is synthesized as a gp160 precursor protein that is cleaved into gp120 ( the receptor-binding subunit ) and gp41 ( the transmembrane subunit ) . Three non-covalently linked gp120-gp41 heterodimers assemble to form a functional trimeric Env spike expressed on the virion surface . All membrane-bound and secreted proteins , including HIV-1 Env , contain N-terminal signal peptides ( SP ) that target the nascent polypeptides to the endoplasmic reticulum ( ER ) . During the transport through the ER and subsequently the Golgi apparatus , HIV-1 Env is subjected to extensive glycosylation that adorns ~30 potential N-linked glycans on each gp160 molecule . Disulfide bonds are also formed , enabling the protein to adopt the appropriate conformation and oligomerization . Although SP is clearly a critical element that determines the glycosylation , folding , and trimerization of HIV-1 Env , very little is known about the contribution of its amino acid composition . Like other SPs , the HIV-1 Env SP consists of three segments: a cationic N-terminus , a central hydrophobic region and a C-terminal region . However , SPs are highly diverse in terms of the lengths and the amino acid sequences . For examples , the SP of the vesicular stomatitis virus G protein ( VSV-G ) is only 16 amino acids long [1] , while the SPs of the Env proteins from feline immunodeficiency virus and foamy virus are 87 and 187 amino acids long respectively [2 , 3] . The SP of HIV-1 Env consists of about 30 amino acids with a ~15 amino acids long N-terminus bearing charged residues , a hydrophobic region of ~11 amino acids essential for the translocation of the newly synthesized polypeptide chain to the ER membrane , and a ~3 amino acids long C-terminal region that contains the cleavage site for the signal peptidase [4] ( Fig 1A ) . Among SPs of proteins in general , the highest diversity is found in the N-terminal region , and the charged residues in this region influence the ER translocation function of the neighboring hydrophobic region [5] . The SP of HIV-1 Env is unique; it has an unusually long N-region with a relatively high number of positively charged amino acids [6] . The HIV-1 Env SP is also cleaved post-translationally as opposed to the SPs of many other proteins which are cleaved co-translationally [6–8] . Hence , the HIV-1 gp160 remains N-terminally attached to its SP for some time after the completion of its synthesis [7] . Nonetheless , SP cleavage is required for Env secretion; Env with uncleaved SP is retained in the ER and degraded [9] . It is hypothesized that the SP regulates the HIV-1 Env biogenesis [6–8] not only by controlling the timing of Env binding to the ER chaperones but also by influencing the HIV-1 Env folding and glycosylation [8 , 10] . Furthermore , in view of the fact that a high degree of variability is found among the Env SPs from different HIV-1 isolates , the SP sequence variation is likely to modulate the Env structure and glycosylation to impact on virus interactions with cells and immune system of the host . Comparison of the HIV-1 Env SPs from the different strains and clades reveals remarkable amino acid variability ( S1 Fig ) . The study by da Silva et al . [11] also reported deletions of neutral and basic residues at the amino terminal Env SP in viruses from early stages and insertion of basic residues in the hydrophobic region in late-stage isolates . Comparison of Env between pairs of newly infected individuals and their transmitting partners similarly showed mutations in Env SP [12 , 13] . However , the significance of such variations is yet unclear . Using a computational strategy , Gnanakaran et al . [14] identified several signature amino acids in the HIV-1 Env glycoprotein . Of particular interest was the loss of histidine at position 12 in the Env SP that was associated with the transition from acute to chronic viruses [14 , 15] . Gonzalez et al . also reported a similar signature motif in the Env SPs of SIV [16] . The amino acid changes accumulated in the SP during virus evolution from the acute stage to the chronic stage of infection implicate a potential role of the SP in immune evasion , presumably by controlling the differential Env expression levels , folding , or post-translational modifications . Consistent with this idea , swapping the gp120 SP with a heterologous SP or decreasing the number of positively charged amino acids were found to increase gp120 expression and secretion ( 7–11 ) . However , these past studies were done mainly in the context of recombinant Env proteins and the effects of the Env SP variability on the virus have not been much studied . This study sought to evaluate the importance of the amino acid polymorphism at position 12 and the contribution of charged amino acids in the N-terminal region of the HIV-1 Env SP on the functions of Env expressed by full-length infectious molecular clones ( IMCs ) . The data show that some Env SP mutations altered the level of Env incorporated into virions without drastic effect on virus infectivity . Certain mutations also rendered the virus resistant to neutralization by anti-V1V2 antibodies . Similar changes in neutralization sensitivity were observed when analogous mutations were introduced in the Env SPs of two different HIV-1 isolates ( REJO and JRFL ) . We postulate that the Env SP mutations impact Env glycosylation which in turn masks or exposes the neutralizing epitopes . Lectin-probed Western blot and mass spectrometric analyses demonstrate that indeed these mutations affected the sugar composition of N-glycans that decorate the HIV-1 Env . Thus , the data support the hypothesis that the amino acid variability in HIV-1 Env SP shapes Env glycosylation to affect Env recognition by antibodies . These findings highlight the importance of SP in regulating the N-glycan composition of HIV-1 Env .
We began our exploration to study the effects of mutations in the Env SP by examining the relative levels of Env and Gag incorporated into virions . 293T cells were transfected with the REJO WT and mutant constructs shown in Fig 1A . Forty-eight hrs later viruses released into the supernatants were pelleted and analyzed by Western blot for Env and Gag levels ( Fig 1B ) . We calculated the ratios of Env/Gag to compare Env incorporation among the WT and mutant viruses . The SP mutations altered the ratios of Env/Gag to varying extents . The ratios ranged from 115% to 20% in comparison to WT ( set to 100% ) , ( Fig 1C ) . Interestingly , three mutations affecting H12 residue ( H12Q , H12R , and H12Y ) caused the most reduction in Env incorporation . The mutations affecting basic K or R residues at positions 4 , 8 , 9 , and 15 minimally reduced the ratios of Env/Gag incorporated into virions , while in K2G mutant Env was incorporated into virions at a slightly higher density compared to the WT . The levels of Env expression in the cell lysates were also lower for R15G and H12 mutants ( H12Q , H12R , and H12Y ) ( S2A and S2B Fig ) , similar to those found in the virions , whereas higher amounts of K2G and R9G Env were detected in the cell lysates . Of note , two Env bands ( 120kDA and 140kDa ) , which reacted with anti-gp120 MAbs , were observed in both virus and cell lysates ( Fig 1B and S2 Fig ) . Similar bands were also seen in virus preparation purified using sucrose cushion . The blots were then probed with anti-gp41 MAbs: A cocktail of 7 anti-gp41-specific MAbs did not react with either bands , although it strongly detected gp41 in the same samples ( S3A Fig ) . In contrast , the anti-gp41 MAb 2F5 , specific to the MPER region , weakly recognized the upper and not the lower Env band ( S3B Fig ) , suggesting that these two Env bands are cleaved gp120 and uncleaved gp160 . The 2F5 also detected the gp41 . Subsequently , the relative rate of Env production was measured in cells after transfection using a sandwich ELISA with capturing antibody specific for the C-terminus of gp120 ( C5 ) and probing with MAb EH21 against C1 epitope at the gp120 N-terminus or MAb A32 recognizing a conformational-dependent epitope involving C1 , C2 , and C4 . This assay detects properly-folded gp120 Env with accessible N- and C-termini that result from cleavage of both signal sequence and gp41 . The data demonstrate comparable rates of gp120 production with WT vs mutated SP ( S2C Fig ) , indicating that the SP mutations did not drastically alter Env synthesis and proteolytic cleavage . The infectivity of REJO WT and mutant viruses was evaluated in TZM . bl cells at 48 hours after one round of infection with virus inputs normalized by p24 contents . None of the mutations completely abrogated virus infection . Among mutations affecting basic residues at positions 2 , 4 , 8 , 9 , and 15 , the R15G mutation reduced virus infectivity the most , while the others had minimal effects ( Fig 1D ) . The three H12 mutations also lowered virus infectivity , albeit to different extents and evident only at lower p24 concentrations . A significant correlation ( Spearman r = 0 . 83 , P = 0 . 004 ) was observed between virus infectivity and virus-associated Env/Gag ratio ( Fig 1E ) , indicating that virus infectivity is impacted by reduced Env incorporation into virions as a result of SP mutations . To evaluate whether the SP mutations alter the Env antigenicity , solubilized gp120 proteins from REJO WT and mutant viruses were tested in ELISA with MAbs specific for V2i ( 697 , 1357 , 1361 , 1393 and 2158 ) , V3 ( 2219 , 2557 , 3074 and 3869 ) [17] , the CD4-binding site ( CD4bs: NIH45-46 ) [18] , and a CD4-IgG fusion protein ( CD4-IgG2 , Progenics ) . The V2i MAbs target distinct epitopes that are nearby or overlap with the integrin α4β7 binding site in the V1V2 domain . MAb 1418 specific for human parvovirus B19 was included as a negative control [19] . The same amounts of HIV-1 Env gp120 ( 100 μl/well at 20 ng/ml ) from the different mutant and WT viruses were added to ELISA wells pre-coated with capturing anti-C5 antibody . The S4 Fig show that , except for H12Q , the SP mutations minimally affected Env gp120 recognition by the MAb panel . None of the mutations completely abolished MAb binding with gp120 , although the V2i MAb 1357 reacted weakly with WT and the SP mutants . Notably , the H12Q mutation caused the greatest reduction of Ab binding: the binding of H12Q gp120 by all five V2i MAbs , two V3 MAbs ( 3074 and 3869 ) , and the CD4bs MAb NIH45-46 decreased by >25% relative to WT . However , H12Q did not affect the binding of two other V3 MAbs ( 2219 and 2557 ) . The other mutations only sporadically lowered the strength of gp120-MAb reactivity . In contrast , all mutants interacted less efficiently with CD4-IgG2 . These data revealed structural changes that may be promulgated from SP to affect the MAb epitopes and the CD4 binding site in the Env gp120 subunit . Although most of the SP mutations only minimally altered MAb reactivity with soluble gp120 monomers , we postulated that they might cause more dramatic changes to virus neutralization sensitivity as a result of altered assembly and/or glycosylation of the native Env trimers on HIV-1 virions . To test this idea , we examined neutralization of REJO WT and mutants by a panel of V2i , V3 , and CD4bs MAbs used in ELISA plus bNAbs specific for the quaternary V1V2 ( V2q ) epitopes ( PG9 , PG16 , PGT145 ) and CD4-IgG2 . Our past work demonstrated that increasing the virus-MAb incubation time to 24 hours before addition of TZM . bl target cells allowed the detection of neutralizing activities by V2i and V3 MAbs against the Tier 2 viruses REJO and JRFL , while no neutralization was detected with these MAbs with the standard 1-hour pre-incubation [17] . Hence , we assessed REJO neutralization with 24 hours of virus-MAb pre-incubation for all MAbs , except for bNAbs ( V2q MAbs: PG9 , PGT145; CD4bs MAb: NIH45-46 ) and CD4-IgG2 . Virus input was set to 150 , 000 to 100 , 000 RLU in TZM . bl cells . AUC and IC50 values were calculated from titration curves . Titration curves from two of the mutants , H12R and H12Q , are shown in Fig 2 , whereas AUC and IC50 data from all virus and MAb combinations were tabulated in Figs 3 and 4 . The data showed that the SP mutants displayed varied sensitivity to different MAbs ( Figs 2 , 3 and 4 ) . Notably , many mutations rendered REJO resistant to neutralization by V2i MAbs . In contrast , neutralization by V3 MAbs and the bNAbs against V2q and CD4bs was less affected . The H12R mutant , for example , was more resistant than WT to V2i MAbs 697D , 1357 and 1393 . This mutant also displayed increased resistance to the V2q MAb PG16 , which recognizes a glycopeptidic epitope and interacts specifically with sialic acid on the complex-type glycans [20] . On the other hand , H12R neutralization by all V3 MAbs , PGT145 , NIH45-46 , and CD4-IgG2 was comparable to WT . Similar patterns were observed with K4G , R8G , R15G , and H12Y ( Figs 3 and 4 ) , although K4G , R15G , and H12Y each affected only 1 or 2 V2i MAbs . In contrast , the H12Q mutant became more sensitive than WT to V2i MAb 697 , V3 MAb 2557 , and V2q MAb PG9 . The changes were not drastic for MAbs 2557 and PG9 , but the shifts in the titration curves were consistently observed that affected both AUC and IC50 values . Nonetheless , not all SP mutations altered neutralization sensitivity . K2G mutation did not affect REJO neutralization sensitivity to any V2i or V3 MAbs tested . R8G and R15G mutants showed higher sensitivity to PG9 as compared to WT; however , although their IC50 values differed by >3 fold ( p<0 . 05 ) , their AUC values had only 28–29% difference . Effects on the V3 glycan-specific MAbs such as PGT121 and PGT128 and the mannose-binding MAb 2G12 could not be assessed , because REJO Env does not have the N322 glycan essential for recognition by this class of MAbs . Overall , based on AUC ( Fig 3 ) , 11 of 38 ( 29% ) REJO mutant-V2i MAb combinations tested became more resistant , while only 1 combination of 27 ( 4% ) showed more resistance to V3 mAb . Altered patterns of virus neutralization were similarly observed with WT REJO produced in HEK293S GnTI- ( GnTI- ) or in HEK293T cells with kifunensine . The GnTI- cells are deficient in N-acetylglucosaminyltransferase I , an enzyme required for Man5GlcNAc2 progression into hybrid and complex carbohydrates in the Golgi . Thus , virus produced in GnTi- cells has an increased amount of Man5-9 GlcNAc2 [21] . On the other hand , kifunensine is a glycosidase inhibitor that prevents the trimming of Man9GlcNAc2 by the ER mannosidase I enzyme . Virus grown in the presence of this inhibitor displays mainly Man8-9GlcNAc2 at the utilized N-linked glycosylation sites . Figs 2 , 3 and 4 show that REJO WT produced in GnTI- cells ( WT GnTI- ) or grown with kifunensine ( WT Kif ) were resistant to V2i MAbs , mimicking the phenotypes of many SP mutants . Neutralization by V3 MAbs , on the other hand , was not altered . As expected , neutralization by PG9 of which recognition depends on high-mannose glycans was enhanced , whereas neutralization by PG16 which binds to complex-type glycans was reduced [20] . Neutralization of WT GnTI- virus by the CD4bs MAb NIH45-46 and CD4-IgG2 was also altered , albeit in opposing ways . Because SP mutations conferred significant alterations in HIV-1 sensitivity to neutralizing MAbs that may be associated with Env glycan modifications , we next examined whether the mutations also affect the ability of DC-SIGN to bind and transmit HIV-1 . DC-SIGN is a C-type lectin which recognizes selective arrays of high mannose- and complex-type N-glycans [22] . Expressed on dendritic cells , DC-SIGN participates in mediating HIV-1 capture and transfer from dendritic cells to T cells [23] . The relative efficiencies of DC-SIGN-mediated capture of REJO WT and mutants were assessed using DC-SIGN+ Raji cells and measured by p24 ELISA ( Fig 5A ) [24] . Most mutants showed similar levels of virus capture as WT , except for H12Q and H12Y mutants which were less efficiently captured ( 68% and 50% , respectively ) . Virus capture was undetected with the parental Raji cells lacking DC-SIGN . When we assessed transmission of REJO WT and mutant viruses from DC-SIGN+ Raji cells to TZM . bl cells [24] , all mutants showed decreased transfer relative to WT ( Fig 5B ) . However , only the transfer of K2G , R15G , and all three H12 mutants ( H12R , H12Q , H12Y ) was reduced significantly . In the absence of DC-SIGN , no virus transmission was observed . The efficiencies of DC-SIGN-mediated capture and transmission correlated with Env incorporation to virions ( Spearman r = 0 . 85 , P = 0 . 002 and r = 0 . 64 , P = 0 . 03 , respectively ) ( Fig 5C ) , demonstrating the main contribution of Env expression level in determining virus interaction with DC-SIGN . To determine if the SP mutations indeed alter sugar composition of the Env N-glycans , we sought more direct evidence of changes in N-glycan compositions on Env from 5 mutants displaying different patterns of Ab-mediated neutralization and DC-SIGN-mediated transmission . To this end , first we analyzed mobility shift of WT vs mutant virus-derived Env after digestion with Endo-H and PNGase F under reducing and non-reducing conditions . Endo H cleaves oligomannose residues at the β-1 , 4 linkage connecting two GlcNA residues and thus removes high mannose and hybrid but not complex N-glycans . PNGase F cleaves between asparagine and the first GlcNAc residue , and removes all N-glycans ( high-mannose , hybrid and complex ) . The data show that under reducing condition Endo H digestion lowered the apparent molecular mass of WT and all five mutants to ~90 kDa bands that were reactive with gp120 MAbs ( S5A Fig ) , while PNGase F digestion reduced the molecular mass to 90kD and 60 kDa ( S5B Fig ) , similar to the pattern reported previously [25] . Endo H-digested K2G mutant migrated at a slightly lower rate , but no major differences were apparent between WT and SP mutants . Similar results were observed with Endo H digestion under non-reducing condition ( S5C Fig ) . PNGase F digestion of WT and SP mutants under non-reducing condition also yielded Env products with comparable mobility , except that mutant H12Q exhibited more diffused wide bands as compared to WT and the other mutants ( S5D Fig ) . Overall no dramatic changes were apparent in the proportions of high mannose and complex glycans on Env of SP mutants vs WT to significantly affect in their glycosidase digestion profiles . To allow detection of finer changes in the sugar compositions of Env N-glycans from SP mutants vs WT , lectin-probed Western blot analyses were performed using lectins known to bind distinct sugar moieties: GNA ( specific for terminal α1–3 mannose ) , GRFT ( specific for α1–2 mannose ) and AAL ( specific to α-1 , 6 or a-1 , 3 fucose on complex glycans ) . The Env contents of sucrose-pelleted virus lysates were first quantified by Western blot using the anti-gp120 MAb cocktail similar to that done for Fig 1B , and equal amounts of WT and mutant Env were then used for the lectin-probed blots . The ability of lectins to detect differences in Env glycan compositions was first established by testing Env from REJO WT virus grown in 293T cells as compared to the same virus produced in HEK293S ( GnTI- ) cells and in 293T cells in the presence of 25μM kifunensine . Virus lysates were separated by SDS-PAGE and probed with anti-gp120 MAbs , GNA , GRFT and AAL . The gp120 MAb cocktail detected Env from all three viruses which displayed molecular mass differences consistent with the presence of different glycoforms ( Fig 6A ) . The relative band intensities were quantified ( Fig 6B ) . The GnTI--derived virus expressed Env with mainly Man5GlcNAc2 N-glycans bearing terminal α1–3 mannoses; Env from this virus was well recognized by α1–3 mannose-specific GNA , but not by GRFT or AAL . Env of virus produced in presence of kifunensine , on the other hand , was enriched in Man8-9GlcNAc2 containing terminal α1–2 mannoses and was more reactive with GRFT than GNA or AAL . For comparison , the 293T-produced virus displayed Envs with various N-glycan types recognizable by GNA , GRFT and AAL . The data also revealed that , of the two Env bands present in the 293T-produced virus , the upper band corresponded to Env bearing high mannose-type glycans which reacted better with GNA and GRFT , whereas the lower band reacted more strongly with AAL indicating Env containing complex-type glycans . We subsequently utilized this assay for analyzing Env from REJO WT vs SP mutants produced in 293T cells . The data in Fig 6C and 6D showed that the upper and lower Env bands were detected in all 5 SP mutants and WT , and that comparable reactivity was seen with anti-gp120 MAbs , consistent with equivalent Env inputs . The amounts of gp41 were also similar for all viruses . However , lectin binding showed distinct patterns among the SP mutants . The terminal α1–3 mannose-specific GNA , which detected only the upper band , reacted more strongly to R15G and H12R as compared to WT and the other SP mutants . GRFT , specific for terminal α1–2 mannose , reacted to both upper and lower bands , but showed stronger binding to the upper band of R15G and weaker binding to that of K2G as compared to WT . The fucosylated glycan-binding AAL detected mainly the lower bands for WT , K2G , and H12Q , but had enhanced binding to the upper bands of R8G , R15G and H12R . As summarized in Fig 7 , differences in lectin binding to Env of SP mutants were evident to indicate enrichment of certain oligomannose- and fucosylated complex-types of N-glycans on Env of SP mutants . For examples , R15G and H12R had higher levels of terminal α1–3 mannoses and fucosylated glycans than WT and the other mutants . R15G also had higher levels of terminal α1–2 mannoses . In contrast , R2G had lower levels of terminal α1–3 and α1–2 mannoses . The glycan composition of sucrose-pelleted REJO WT and mutant viruses was also evaluated by liquid chromatography–mass spectrometry ( LC-MS/MS ) . Using SEQUEST with 1% FDR for assignment of spectra to peptides , we were able to identify peptides derived from REJO GAGpr55 , Pol and Env with sequence coverage of 75% , 58% and 29% , respectively ( S2 Table ) . We also detected 2 intact glycopeptides , IIIVHLN290ETVK and CLSN446ITGLILTR , corresponding to REJO Env positions 283–293 ( C2 ) and 445–456 ( C4 ) . These Env fragments displayed 9 and 3 different glycoforms , respectively ( Fig 8 and S3 Table ) . Importantly , the analysis clearly showed alterations in the relative abundance of glycoforms associated with SP mutants vs WT . Thus , the LC-MS/MS data supports the idea that a single change in the SP can indeed alter the sugar composition of the Env N-glycans , which in turn influenced virus interaction with DC-SIGN and virus neutralization by Abs . To assess whether the SP mutations can impart similar effects on another HIV-1 isolate , we mutated charged residues in the SP of JRFL Env , a subtype B chronic isolate . We substituted the R/K residues at positions 8 and 15 to glycine ( R8G , K15G ) ( Fig 9A ) . In addition , we introduced Y12Q and Y12R mutations , because JRFL has a Y residue at position 12 instead of H . Similar to the effect seen on REJO , SP mutations K15G , Y12R and Y12Q reduced JRFL Env incorporation into virions , whereas R8G mutation had no effect ( Fig 9B and 9C ) . The Y12R and Y12Q mutants also showed reduced infectivity detectable at lower p24 inputs , while the infectivity of R8G and K15G was comparable to WT ( Fig 9D ) . Correlation was observed between Env incorporation and virus infectivity ( r = 0 . 9 , P = 0 . 04 by Spearman test ) ( Fig 9E ) . Effect of the SP mutations on antigenicity was assessed by testing solubilized gp120 proteins from JRFL WT and mutant viruses in ELISA . As shown in S6A and S6B Fig , the SP mutations did not abolish gp120 reactivity to MAbs tested . However , gp120 from the K15G , Y12R and Y12Q mutants reacted more weakly with most V2i MAbs , and had reduced binding to CD4-IgG2 . The reactivity with V3 MAbs was minimally affected . Interestingly , the JRFL R8G mutant showed increased binding to many MAbs tested , including V2i MAbs ( 697 , 1357 ) , V3 MAbs ( 3074 , 3869 ) , and to CD4-IgG2 ( S6B Fig ) ; such increase in ELISA reactivity was not seen with REJO R8G and other REJO mutants ( S4B Fig ) . Next , we evaluated the neutralization phenotype of the JRFL Env SP mutants . Except for Y12Q mutation that did not affect JRFL neutralization , the SP mutations increased JRFL resistance to V2i MAbs ( Fig 10 ) . R8G mutant was the most resistant to all 4 V2i MAbs tested ( Fig 10 ) , although the V2i MAb reactivity with R8G gp120 was comparable or even increased ( S6 Fig ) . In contrast , the SP mutations minimally affected JRFL neutralization by V3 and CD4bs MAbs . Overall , 7/16 ( 44% ) mutant-V2i MAb combinations showed increased resistance , while no mutant ( 0/8 ) became more resistant to V3 MAbs . This pattern was similar to that seen with REJO ( Figs 3 and 4 and S7 Fig for side-by-side comparison of REJO and JRFL mutants ) . Moreover , the same 3 SP mutations affecting V2i MAb neutralization ( R8G , K15G and Y12R ) rendered JRFL more resistant to the mannose-binding MAb 2G12 . These data indicate that these SP mutations induce alterations in the N-glycan oligosaccharide composition that influence virus sensitivity to neutralizing Abs [26 , 27] . The glycan composition of JRFL R8G mutant , which showed the most altered neutralization pattern , was further compared to its WT counterpart in lectin-probed Western blots . Terminal α1–3 mannose-specific GNA and terminal α1–2 mannose-specific GRFT detected only the upper band of JRFL Env , while fucose-binding AAL was reactive with both upper and lower bands ( Fig 11 ) . GNA and AAL reacted more strongly with the JRFL R8G mutant as compared to WT , whereas GRFT binding was comparable , demonstrating specific enrichment of N-glycans with terminal α1–3 mannose and fucose moieties on JRFL R8G Env ( Figs 11 and 7 ) . These results provide corroborating evidence that single amino-acid substitutions in the Env SP are sufficient to influence the oligosaccharide composition of the Env N-glycans on different HIV-1 isolates to result in altered virus phenotypes .
This paper evaluated the influence of HIV-1 Env SP in modulating the phenotypic characteristics of HIV-1 viruses in the context of IMCs ( REJO and JRFL ) , in which natural linkages to all regulatory and structural proteins were maintained [28 , 29] . The REJO and JRFL Env SPs carry 6 and 5 positively charged residues , respectively . We sought to understand the importance of these charged residues in determining virus phenotypes and Env functions . The results show that mutating one of these charged residues was sufficient to alter Env incorporation to virions , virus binding and transmission via DC-SIGN , virus neutralization by MAbs , and oligosaccharide compositions of Env glycans . These single substitutions did not completely abrogate virus infectivity , but mutations affecting position 12 ( REJO: H12R , H12Q , H12Y; JRFL: Y12R , Y12Q ) and position 15 ( REJO: R15G; JRFL: K15G ) significantly decreased Env packaging into the virions and also affected virus infectivity . Notably , enrichment of H at position 12 was identified as a signature of acute HIV-1 isolates [14 , 15] . A similar signature site was also reported on the acute SIV Env SP [16] . The presence of H or R at this position was associated with higher Env expression and virion incorporation levels [15] . In contrast to this literature , our results with mutant H12R showed lower Env incorporation and slight decrease in infectivity , relative to WT , which may be due to the differences in the choice of virus strains and the use of IMCs as opposed to pseudoviruses . However , consistent with this past study , lower Env incorporation was observed in virions when non-signature amino acids Q or Y were introduced at this position as compared to amino acids H or R . The molecular basis for these changes remains unclear . During protein targeting , the basic residues in the cationic N-region of the SP are suggested to establish an electrostatic interaction with the phosphate backbone of the signal recognition particle ( SRP ) [6 , 30] that influences the subsequent binding to the Sec61p complex [31] . Hence , a possible explanation for the alterations of Env expression by the SP mutations is that the basic residue removal affects the SP binding to SRP and consequently the rate of Env transport to or processing in the ER and the Env glycosylation . Nonetheless , we found no evidence for delayed rate of gp120 synthesis as a result of SP mutations . No Env accumulation was detected in the cells , either . Moreover , as indicated by the H12R mutation , removal of basic residue alone cannot fully explain the SP mutant phenotypes . Rather , H12Q and H12Y mutations drastically diminished the overall Env expression on the virions and also in the cells . Altogether , these data support the notion that the signature amino acids at position 12 of the Env SPs determine virus infectivity and transmissibility by controlling Env expression and incorporation to virions . Among the REJO and JRFL SP mutations studied , mutations that increased virus resistance to V2i MAbs were located at residues 8 , 12 , and 15 . The upstream REJO K2G mutation led to increased Env being incorporated into the virion , but did not alter REJO neutralization sensitivity to any of the MAbs tested . However , considering that mutations at some of these residues affected DC-SIGN-mediated uptake and transmission , and that viruses with altered N-glycan compositions as a result of glycosidase inhibitor or lack of glycosyltransferase enzyme also displayed increased resistance to V2i MAbs , these SP mutations most likely altered the oligosaccharide profiles of the Env N-glycans; this was also consistent with the lectin-probed Western blot and LC-MS/MS data . The V2i epitopes themselves do not contain N-glycans [32] , but the MAb recognition of V2i epitopes are dependent on N-glycans [26] . The reactivity of the V2i MAb 697 , for example , was abrogated by treating Env with sodium metaperiodate that oxidizes oligosaccharides [26] . The V2i MAb 2158 was sensitive to mutations that removed the N190-glycan , reducing the MAb binding to 20–50% [27] . Single mutations at other PNGs on gp120 also induced global structural changes that better exposed V2i , V3 , and the CD4-binding site to yield more sensitive viruses [33] . To our best knowledge , our study is the first to reveal that a single amino acid change increases HIV-1 resistance to neutralization by MAbs , particularly V2i MAbs . Remarkably , the changes uniquely involve the Env SP , an Env fragment not present in the mature Env displayed on the virions . Our LC-MS/MS analysis did not detect any SP fragments associated with REJO WT or SP mutant virions . Nonetheless , unlike the complete loss of V2i MAb-mediated neutralization instigated by GnTI- cells or kifunensine that inflicts wide-spread and more homogenous effects on all 29 N-glycans potentially present on the REJO Env , the single-point SP mutations studied here cause more subtle changes in the oligosaccharide moieties detectable by differential reactivity with specific lectins and by mass spectrometry . Increased resistance to neutralization by V2i MAbs was also seen when mutations were made in the SP of JRFL Env , indicating that the effects are not isolate-specific . Moreover , increased resistance to MAb 2G12 , which specifically recognizes high-mannose glycans on HIV-1 Env , was observed with JRFL mutants R8G , K15G and Y12R , further strengthening the evidence that these SP mutations affects oligomannose moieties of the Env glycans . The SP has been implicated in governing HIV-1 Env glycosylation [6] . Our data from lectin-probed Western blotting and LC-MS/MS analyses provided direct evidence for altered oligosaccharide contents of Env glycans as a result of SP mutations . Increased binding to fucose-specific AAL was demonstrated by R8G , H12R and R15G , all of which rendered the REJO virus resistant to V2i MAbs ( Fig 7 ) . R15G and H12R , but not R8G , also reacted more strongly with GNA , a lectin specific for terminal α1–3 mannoses present on Man5-8 and hybrid glycans but not on Man9 and complex glycans [34 , 35] . Similarly , the JRFL R8G mutant also showed increased binding to GNA and AAL as compared to its WT counterpart . In contrast , REJO K2G , which display comparable neutralization as WT , had no change in its fucose content as detected by AAL , and had lower reactivity with GNA and GRFT . Taken together , the data demonstrate that increased α1–3 or α1–2 mannoses and fucose contents of HIV-1 Env are associated with increased virus resistance to neutralization by V2i Abs . The REJO H12Q mutant , on the other hand , showed increased neutralization sensitivity to some of the V2 and V3-specific MAbs . The reason for this phenotype is unclear , but this mutant showed no discernable changes in lectin binding , although apparent alterations were noted with its gp120-MAb reactivity and glycosidase digestion under non-reducing condition . The LC-MS/MS results also show similar glycoform profiles for H12Q vs WT , although changes on other glycosylation sites unidentified in this study cannot be ruled out . In conclusion , this study shows that mutations in the Env SP impact Env incorporation into HIV-1 virions , Env binding to lectins , virus transmission via DC-SIGN , and virus susceptibility to neutralization by MAbs . The study also provides evidence that the Env SP serves as a modulator of Env glycosylation to influence Env function and immune recognition .
HEK293T/17 and HEK293S ( GnTI- ) cells were obtained from the American Type Culture Collection ( ATCC ) . The following reagents were obtained through the NIH AIDS Reagent Program , Division of AIDS , NIAID , NIH: TZM-bl from Dr . John C . Kappes , Dr . Xiaoyun Wu and Tranzyme Inc [36]; Raji and Raji/DC-SIGN cells from Drs . Li Wu and Vineet N . KewalRamani [37] and pREJO . c/2864 ( cat# 11746 ) from Dr . John Kappes and Dr . Christina Ochsenbauer . [38] . pNL-JRFL ( NFN-XS-r-HSA ) was constructed by Dr . Jerome Zack ( UCLA ) [39] V2i , V3 , and control MAbs used in this study were produced in our laboratory as described [26 , 40–45] . The following antibody reagents were obtained through the NIH AIDS Reagent Program , Division of AIDS , NIAID , NIH: anti-HIV-1 gp120 Monoclonal ( IgG1 b12 ) from Dr . Dennis Burton and Carlos Barbas [46]; anti-HIV-1 gp120 Monoclonal ( 2G12 ) from Dr . Hermann Katinger [47]; NIH 45–46 from Pamela Bjorkman [18] , anti-HIV-1 gp120 Monoclonal PG16 [48] and anti-HIV-1 gp120 Monoclonal PGT145 [49] . V2q MAb PG9 was purchased from Polymun Scientific . V2i MAbs target V1V2 epitopes that overlap with the integrin α4β7-binding motif , while the V2q MAb PG9 is specific for a quaternary V1V2 epitope preferentially presented on the Env trimer [17 , 27] . Single-point mutations were introduced to the Env SPs of pREJO . c/2864 and pNL-JRFL infectious molecular clones ( Figs 1A and 9A ) by multi-step overlapping PCR mutagenesis strategy using Pfx50™ DNA Polymerase PCR System ( Invitrogen ) . In the first PCR step , mutated fragments were individually generated in two separate reactions using two primer pairs . The list of all primer pairs is shown in S1 Table . For example , the primers AvrIIF/K2GR and K2GF/BstEIIR were used to generate the mutant K2G . The fragments were agarose gel-purified , combined , and added to a second-stage PCR with the flanking primers AvrIIF and BstEIIR . Products of the second-stage PCR were digested by AvrII and BstEII restriction enzymes and inserted into the AvrII- and BstEII-digested fragment of pREJO . c/2864 to yield the mutant K2G . The other mutants were similarly constructed using their respective primers . In case of JRFL the second-stage PCR product was digested with EcoRI and NheI and inserted into the EcoRI- and NheI-digested fragment of pNL-JRFL . All the plasmids were sequenced to confirm the presence of the desired sequence changes without any other mutations . Viruses were produced by transfecting 293T/17 cells with wild type ( WT ) or mutated pREJO . c/2864 and pNL-JRFL plasmids using jetPEI transfection reagent ( Polyplus ) . Glycan-modified viruses were generated in the presence of 25μM kifunensine or by transfecting GnTI- cells . Supernatants were harvested after 48 hrs and clarified by centrifugation and 0 . 45μm filtration . Single-use aliquots were stored at −80°C . Viruses were sucrose pelleted as in [15] . Virus infectivity was assessed on TZM . bl cells as described [50] . An HIV-1 p24 enzyme-linked immunosorbent assay kit ( XpressBio ) was used to quantify the p24 content in supernatants using the manufacturer’s protocols . To quantify the ratios of Env to p24 proteins incorporated into the WT and mutant viruses and to evaluate Env reactivity with different lectins , Western blot analyses were performed . The virus particles pelleted from 200μl supernatant were lysed , resolved by SDS-PAGE on 4–20% tris-glycine gels ( Bio-Rad ) , and blotted onto membranes , which were then probed with antibodies or lectins . A cocktail of anti-human anti-gp120 MAbs ( anti-V3: 391 , 694 , 2219 , 2558; anti-C2: 841 , 1006; anti-C5: 450 , 670 , 722; 1μg/ml each ) , a cocktail of anti-gp41 MAbs ( 181-D , 240-D , 246-D , 167–7 , 1367 , 2295 , 2556; 1μg/ml each ) , and anti-gp41 MPER MAb 2F5 ( 2μg/ml ) were used to detect Env . MAb 91-5D ( 1μg/ml ) was used to detect Gag p24 . His tagged-GRFT ( Griffithsin lectin; NIH AIDS repository ) , biotinylated GNA ( Galanthus nivalis lectin; Vector Laboratories ) , and biotinylated AAL ( Aleuria aurantia lectin; Vector Laboratories ) were each used at 2μg/ml . Lectin binding was detected with HRP-neutravidin ( 1:1500 for 1 hr RT ) . For GRFT , the blots were incubated with anti-mouse His-tag MAb ( 1:1000 for 1hr ) followed by anti-mouse HRP ( 1:1000 for 1hr RT ) . All dilutions were made in Superblock T20 ( SuperBlock T20 ( PBS ) Blocking Buffer; Thermofisher ) . Membranes were developed with SuperSignal West Pico reagents ( Pierce ) and scanned by a ChemiDoc Imaging Systems ( Bio-Rad Laboratories ) . Purified recombinant gp120 and p24 proteins were also loaded at a known concentration as controls and quantification standards . Band intensities were quantified using the Image Lab Software Version 5 . 0 ( Bio-Rad ) . The relative binding of MAbs to gp120 from the WT and mutant viruses was measured by a sandwich ELISA . ELISA plates were coated with the sheep anti-gp120 Abs ( D7324; 2μg/ml , Aalto BioReagents , Dublin , Ireland ) , blocked with 2% bovine serum albumin ( BSA ) in phosphate-buffered saline ( PBS ) , and incubated with Env ( 20 ng/ml as measured by Western blots ) from 1% Triton X-treated virus lysates . Serially diluted MAbs ( 0 . 01–10μg/ml ) were then added for 2hrs , and the bound MAbs were detected with alkaline phosphatase-conjugated goat anti-human IgG and p-nitrophenyl phosphate substrate . The kinetics of Env production in the cells was measured similarly by ELISA . Briefly , HEK293T cells in 6 well-plates were transfected with REJO WT or mutant plasmids . Samples containing cells and supernatants were frozen at -80°C at 2 , 8 , 12 , 24 , 28 , and 36 hrs post-transfection . Samples were clarified by centrifugation , lysed with 1% Triton-X , and tested in the sandwich ELISA . Env were captured by polyclonal sheep anti-C5 antibodies and probed with MAb EH21 ( specific for C1 ) or MAb A32 ( specific for a discontinuous epitope involving residues within the C1 , C2 and C4 regions ) . Virus neutralization was measured with TZM . bl target cells using a β-galactosidase-based assay ( Promega ) [17 , 51] . Because REJO and JRFL neutralization by anti-V3 and anti-V2i MAbs are attained only after >18 hr pre-incubation of the virus-MAb mixture [17] , in this study neutralization assays were performed with 24 hrs of pre-incubation for all MAbs , except for PG9 , PGT145 and CD4-IgG2 which were tested with the standard 1 hr incubation . Each condition was tested in duplicate or triplicate . Percent neutralization was determined based on virus control ( TZM . bl cells with virus alone ) and cell control ( TZM . bl cells only ) under the specific assay condition . Virus inputs corresponding to 150 , 000–200 , 000 RLUs were used . For virus capture assay , parental Raji or DC-SIGN+ Raji cells ( 1x106 each ) were incubated for 2 hrs with WT or mutant REJO viruses ( 15 ng/ml p24 ) . After unbound viruses were removed by washing , the cells were lysed in 1% Empigen detergent for 1 hr at 56°C , and p24 levels were determined by ELISA ( XpressBio ) . For transmission experiments , Raji or DC-SIGN+ Raji cells ( 1x105 ) were incubated for 2 hrs with virus ( 3 ng/ml p24 ) , washed three times and co-cultured with TZM-bl cells for 48 hrs in the presence of DEAE . HIV-1 transmission to TZM . bl cells was quantified by measuring β-galactosidase activity ( Promega ) . The LC-MS/MS was performed as previously [52] . Briefly , sucrose-pelleted virions were added to 8 M urea in 1 M ammonium bicarbonate buffer and reduced with 5 mM DTT at 37°C for 1 h . Proteins were alkylated by iodoacetamide at a final concentration of 10 mM and incubated at RT in the dark for 40 min . Samples were applied to the Microcon-10 kDa centrifugal filter unit and centrifuged until the solution was minimal in the filter unit . The samples were washed six times with 0 . 1 M ammonium bicarbonate buffer , and 5 μg of trypsin was added in the buffer after the final wash . The digestion was incubated at 37°C for overnight . The tryptic peptides were harvested by centrifugation . The solution containing peptides and glycopeptides were acidified to pH = 3 , desalted by C18 cartridge according to manufacturer’s instructions , dried in a speed-vac , and resuspended in 0 . 2% formic acid . The samples ( 1 μg ) were separated through a Dionex Ultimate 3000 RSLC nano system ( Thermo Scientific ) . MS analysis was then performed using a Thermo Q Exactive mass spectrometer ( Thermo Scientific ) . HIV-1 peptides were identified by using SEQUEST in Proteome Discoverer software ( Thermo Fisher Scientific , version 2 . 2 ) . The intact Env glycopeptides were identified using GPQuest [52 , 53] . To quantify the glycosylation in different mutants label-free quantification of Env peptides and glycopeptides was done using Thermo SIEVE software version 2 . 1 ( S3 Table ) . The data was normalized using a non-glycosylated the Env peptide VVQIEPLGIAPTR that showed high confident identification and most reliable quantitative value in the LC-MS/MS data . Normalization was validated using two other Env peptides ( LTPLCVTLK and EATTTLFCASDAK ) . Comparisons of virus neutralization and MAb binding were performed using GraphPad Prism . Statistical analyses were performed on neutralization data that reached ≥50% .
|
HIV-1 envelope glycoprotein ( Env ) is indispensable for virus infection . HIV-1 Env contains at its N terminus a signal peptide ( SP ) that directs the protein to the endoplasmic reticulum . The SP sequences exhibits high variability among HIV-1 isolates , and the significance of such variability is unclear . We hypothesize that changes in the Env SP influence the Env biogenesis , Env folding and/or glycosylation and the phenotypic traits of the virus . This study evaluated the consequences of mutations in the Env SP of infectious molecular clone HIV-1 REJO . c/2864 . Results show that three different mutations affecting histidine at position 12 impacted on the Env incorporation into virions that correlated with virus infectivity and transmission . Additionally , Env SP mutations at positions 8 , 12 , and 15 increased virus resistance to neutralization by Env monoclonal antibodies . These mutations also altered the oligosaccharide composition of N-glycans on Env as shown by changes in the Env reactivity with lectins and by mass spectrometry . Similar phenotypic changes were observed when analogous SP mutations were introduced to another virus strain , JRFL . Thus , the HIV-1 Env SP controls Env expression and glycosylation that affect virus infectivity , transmission , and sensitivity to neutralization by antibodies . ( 191 words )
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2018
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Alterations of HIV-1 envelope phenotype and antibody-mediated neutralization by signal peptide mutations
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In mammals , the circadian clock allows them to anticipate and adapt physiology around the 24 hours . Conversely , metabolism and food consumption regulate the internal clock , pointing the existence of an intricate relationship between nutrient state and circadian homeostasis that is far from being understood . The Sterol Regulatory Element Binding Protein 1 ( SREBP1 ) is a key regulator of lipid homeostasis . Hepatic SREBP1 function is influenced by the nutrient-response cycle , but also by the circadian machinery . To systematically understand how the interplay of circadian clock and nutrient-driven rhythm regulates SREBP1 activity , we evaluated the genome-wide binding of SREBP1 to its targets throughout the day in C57BL/6 mice . The recruitment of SREBP1 to the DNA showed a highly circadian behaviour , with a maximum during the fed status . However , the temporal expression of SREBP1 targets was not always synchronized with its binding pattern . In particular , different expression phases were observed for SREBP1 target genes depending on their function , suggesting the involvement of other transcription factors in their regulation . Binding sites for Hepatocyte Nuclear Factor 4 ( HNF4 ) were specifically enriched in the close proximity of SREBP1 peaks of genes , whose expression was shifted by about 8 hours with respect to SREBP1 binding . Thus , the cross-talk between hepatic HNF4 and SREBP1 may underlie the expression timing of this subgroup of SREBP1 targets . Interestingly , the proper temporal expression profile of these genes was dramatically changed in Bmal1−/− mice upon time-restricted feeding , for which a rhythmic , but slightly delayed , binding of SREBP1 was maintained . Collectively , our results show that besides the nutrient-driven regulation of SREBP1 nuclear translocation , a second layer of modulation of SREBP1 transcriptional activity , strongly dependent from the circadian clock , exists . This system allows us to fine tune the expression timing of SREBP1 target genes , thus helping to temporally separate the different physiological processes in which these genes are involved .
Mammals possess an internal circadian clock which allows them to anticipate and adapt to daily environmental changes [1] . The molecular mechanism underlying the cell-autonomous circadian rhythms relies on a network of feedback loops in which BMAL1 , CLOCK , Neuronal PAS domain ( NPAS ) protein 2 and Retinoic acid receptor-related Orphan Receptor ( ROR ) proteins act as transcriptional activators and period homolog proteins ( PER1 , 2 and 3 ) , cryptochromes ( CRY1 and 2 ) and REV-ERBs function as inhibitors producing the self-sustained oscillating production of their target genes , including themselves . At central level , the expression of clock genes is dictated by a pacemaker localized in the hypothalamic suprachiasmatic nucleus ( SCN ) which synchronizes the phase in nearly all body cells . However , in peripheral organs such as the liver , oscillations are also entrained by the feeding and fasting cycle [2] , [3] , [4] . This sophisticated regulatory system contributes to coordinate many physiological processes , such as sleep-wake cycles , locomotor activity , body temperature , hormone secretion and energy metabolism that all display circadian rhythms . In particular , the importance of the connection between circadian clock and metabolism regulation is emerging . Epidemiological studies have shown an increased incidence of obesity , diabetes , and cardiovascular disease , in addition to certain cancers and inflammatory disorders in night workers [5]–[7] . Accordingly , in genetic mouse models the disruption of the clock alters metabolic homeostasis at different levels ( reviewed in [8] ) , suggesting a still unresolved relationship between nutrient state and circadian homeostasis . The Sterol Regulatory Element Binding Protein 1 ( SREBP1 ) , a basic Helix-Loop-Helix-Leucine Zipper ( bHLH-LZ ) transcription factor , plays a key role in the regulation of lipid biosynthesis , which is one of the most feeding-related function in the liver [9] . SREBP1 is synthesized as an inactive precursor , anchored to the ER-membrane and its N-terminal fragment is released into the nucleus after proteolytic cleavage in response to cholesterol depletion [10] or to activation of the insulin signalling pathway [11] , [12] . Two SREBP1 isoforms , 1a and 1c , are obtained through alternative splicing of the same gene [13] , [14] . The liver expresses mostly the SREBP1c isoform that mediates the insulin-driven lipogenic activity [15] . Besides being under the control of the feeding-fasting cycle , SREBP1 translocation to the nucleus is also influenced by one of the master clock regulators , REV-ERBα [16] . Nevertheless , in absence of a functional clock , such as in cry1−/−;cry2−/− mice , a normal expression pattern of several SREBP1 target genes can be restored by an imposed rhythmic food intake [4] , suggesting a dominant role of the feeding-fasting cycle in the regulation of SREBP1 . To systematically understand how the interplay of circadian clock and nutrient-driven rhythm regulate SREBP1 activity , we evaluated the genome-wide binding of SREBP1 to its targets along the day in wild-type mice . Our results define SREBP1 binding pattern in the physiological context of both rhythmic food absorption and circadian rhythm and they give the first tools to comprehensively explore how SREBP1 activity is connected to circadian-driven regulatory events .
To evaluate the genome-wide dynamics of SREBP1 binding to its target sites in a physiological context , we prepared liver chromatin from C57BL/6 mice , collecting samples each 4 hours during one day ( see Material and Methods ) . ChIP-seq with an antibody that recognizes both SREBP1 isoforms was performed at each time point . The SREBP1 antibody was tested extensively ( Figure S1 ) and has also been used in previous studies [17] . We obtained an average of 38 millions sequence reads by time point by ultra-high-throughput sequencing ( Table S1 ) . The mapping allowed the identification of 448 bona fide SREBP1 binding peaks , above the background . As shown in Figure 1A , the binding of SREBP1 is overall oscillatory , with the maximum for most of the sites at Zeitgeber Times ( ZT ) 14 or 18 ( light is on at ZT0 and is off at ZT12 ) . To systematically evaluate the rhythmicity of SREBP1 recruitment to its targets , a cosine function was fitted to the temporal profile of the binding ( see Material and Methods ) . This allowed to calculate , for each peak , the binding phase and the amplitude of the oscillation together with its associated P-value , as exemplified for the two sites found on the Srebp1 gene itself ( Figure 1B ) . 53% of SREBP1 binding sites were found to be rhythmic ( P<0 . 1 for the amplitude ) . Four clusters of targets were clearly distinguishable based on binding kinetics ( Figure 1A ) , the first with a phase distributed around ZT15–ZT17 , whereas the other ones with the phase peaking around ZT11–ZT12 , as determined by cosine function ( Figure 1C ) . The observed kinetics of SREBP1 binding , especially for cluster A peaks , was consistent with its gene expression and nuclear localization , ( Figure 1D , 1E and 1F ) . Collectively , these results show that the activity of SREBP1 oscillates with a pronounced circadian rhythm , in agreement with the previously reported daily variations of its RNA and protein levels [16] , [18]–[20] . SREBP1 binding sites identified in this study are grouped in four clusters with a slightly shifted phase . To better investigate the features of these sites we calculated the number of nucleotides spanned by each peak and found that sites belonging to cluster A ( 236 out of 448 ) were narrow , with a typical length of about 200 nucleotides ( Figure 2A ) . These peaks were also closer to the nearest annotated transcription start site ( TSS ) than peaks belonging to clusters B , C or D , whose distance to the nearest annotated TSS roughly matches randomly picked genomic locations ( Figure 2B ) . Moreover , the amplitude of the binding oscillation along the 24 hours was greater for cluster A peaks ( Figure 2C ) . These observations suggest that cluster A sites may be more relevant in the regulation of transcription mediated by SREBP1 . In agreement with this hypothesis , a MEME [21] motif search analysis clearly identified the canonical SREBP1 consensus motif in more than 60% of the sites belonging to cluster A ( Figure 2D ) , but only in 6% of the sites assigned to clusters B , C and D . Within cluster A , the MEME analysis also showed that motifs for SP1 and NFY , two transcription factors ( TFs ) known to cooperate with SREBP1 to regulate the transcription of its target genes , were overrepresented [17] . The consensus motif for the Hepatic Nuclear Factor 4 ( HNF4 ) was also identified in 61 out of the 236 cluster A sites . The discovered motifs were enriched in cluster A peaks with an empirical p-value<0 . 001 , as shown in Table S2 . In addition , in the regions belonging to cluster B , C and D , we determined only several highly repetitive sequences as top-scoring motifs ( for example ACACACACA in 73 sites out of 212 ) that could not be associated to any known consensus motif for TFs . This result suggests that SP1 , NFY and HNF4 may participate to SREBP1-mediated transcriptional regulation and further supports the functional importance of SREBP1 binding sites assigned to cluster A . Thus , we opted to focus the following analyses on these regions , although we cannot exclude that the other sites might contribute to mediate SREBP1 activity in mouse liver potentially through genome loops . To explore the cellular processes that are regulated by SREBP1 along the day , we annotated each site with the nearest Ensembl transcript . We used DAVID [22] , [23] to identify clusters of genes enriched with functional annotations . As expected , we identified lipid biosynthetic processes and fatty acid metabolism as the most prominent pathways controlled by SREBP1 ( Table S3 ) . In addition , we found a significant enrichment of genes involved in carbohydrate metabolism , in the response to nutrient levels , in mitochondrial and endoplasmic reticulum functions and in coenzyme metabolism . In a previous genome-wide study performed in human HepG2 cells , it was shown that unique combinations of SREBP1 , SP1 and NFY target distinct functional pathways [17] . Since we found a good enrichment within the SREBP1 binding sites of the consensus motifs for NFY and SP1 , but also HNF4 , we explored whether a network among these three transcription factors could be highlighted in mouse liver . As shown in Table 1 , genes involved in lipid biosynthesis and in the regulation of fatty acid and steroid metabolism were highly represented in all categories . In some cases , however , one biological function was targeted by a unique combination of regulators . For example , the biosynthesis of coenzymes was selectively represented within the genes bearing only the site for SP1 , whereas both SP1 and HNF4 motifs were present in genes involved in apoptosis . Likewise , a combination of HNF4 and NFY motifs marked most of the genes involved in immunological processes . Finally , pathways related to carbohydrate metabolism and mitochondria were particularly enriched in genes without NFY or SP1 motifs , suggesting that SREBP1 may cooperate with other regulators at the promoter of these genes ( the complete functional annotation clustering is reported in Table S4 ) . Our results suggest that in mouse liver , in physiological conditions , the network SREBP1-SP1-NFY-HNF4 may be important in order to determine the functional effect of SREBP1 binding ( Figure 2E ) . In Figure 1 , we showed that SREBP1 binds to target sites belonging to cluster A with a sharp phase between ZT15 and ZT17 . To investigate the functional effects of SREBP1 binding on gene transcription , we checked in our previously reported data set [24] the 24 hours profile of RNA polymerase II ( Pol II ) recruitment in the proximity of SREBP1 target genes . Importantly , most of the SREBP1 binding sites belonging to cluster A were co-occupied by Pol II ( Figure 1A ) , further supporting the functional relevance of these regions . We next evaluated Pol II binding to the promoter and in the gene body of all putative SREBP1 target genes . In parallel , we measured mRNA levels of the same genes by microarray analysis ( Table S5 ) . More than 85% of SREBP1 target genes show an expression level above the median expression level of all the transcripts , suggesting that they are transcribed . Our analyses revealed three clusters of target genes , that we called A1 , A2 and A3 , with distinct temporal profile of transcription and expression ( Figure 3A and Figure S2 ) . In cluster A1 , the peak of Pol II binding was concomitant , or even slightly earlier than SREBP1 binding . In contrast , for genes belonging to cluster A2 , Pol II association to both promoter and gene body strictly followed SREBP1 binding . Lastly , Pol II recruitment to the genes of the A3 group was shifted by about +8 h with respect to SREBP1 . For all clusters , the temporal profile of gene expression was consistent with the dynamics of Pol II association . The distribution of all the expression phases obtained for the genes belonging to the three groups confirmed that SREBP1 target genes are expressed in different moments of the day , in spite of the concomitant binding of the transcription factor ( Figure 3B ) . This observation suggests that other factors participate in the regulation of the various SREBP1 target genes in order to assure their appropriate expression timing . Interestingly , genes that were mainly expressed during the fed state ( clusters A1 and A2 ) were functionally enriched in the regulation of lipid and coenzyme biosynthetic processes , as well as in the response to hormones , such as insulin . In contrast , SREBP1 target genes involved in mitochondrial oxidation and apoptosis were enriched during the fasting period ( Table 2 ) . Thus , the promoter specific events that determine the different temporal expression profile of SREBP1 target genes contribute to define the set of cellular functions that are active at a given time . To understand the molecular mechanism underlying the different temporal expression of SREBP1 target genes , we first explored the possible involvement of the network SREBP1-SP1-NFY-HNF4 in determining the functional effect of the binding of SREBP1 to its targets . To check for the presence of a pattern characterizing the three groups of SREBP1 target genes identified earlier ( see Figure 3 ) , we evaluated the presence of different combinations of SP1 and NFY motifs and their orientation with respect to the SREBP1 binding sites ( data not shown ) . However , we could not establish any significant correlation . In contrast , we found that HNF4 motifs were significantly overrepresented ( P-value<0 . 02 ) in the regions under SREBP1 peaks of the genes expressed during the fasting period ( cluster A3 ) , compared to the other clusters ( Table S6 ) . The actual recruitment of HNF4 to these putative binding sites was assessed by ChIP on randomly selected SREBP1 Responsive Elements ( SREs ) ( Figure 3C ) . Besides HNF4 , other transcription factors , such as the cAMP response element-binding protein ( CREB ) or Forkhead box proteins O ( Foxo ) , are important players in the hepatic metabolic regulation upon fasting [25] , [26] . However , their known consensus motifs were not found in the proximity of cluster A3 SREBP1 peaks . These observations strongly suggest a specific cross-talk between HNF4 and SREBP1 in the regulation of these genes . To further investigate which control processes dictate the distribution of SREBP1 target gene expression along the day , we then considered the possible role of the circadian rhythm in this regulation . To test this hypothesis , it was necessary to uncouple the circadian rhythm from the response to nutrients . Thus , we fed mice lacking BMAL1 ( Bmal1−/− ) only during the darkness period for one week before collecting liver samples every four hours . Upon this experimental conditions , the circadian clock was completely disrupted in Bmal1−/− mice , as demonstrated by the flattened expression of key core and output components of the clock , such as Clock1 , Cry1 , Cry2 , D site albumin promoter binding protein ( Dbp ) , Rev-Erbα and Kruppel-like factor 10 ( Klf10 ) ( Figure 4B ) . Body weight , daily food intake and glycemia were unchanged in Bmal1−/− mice ( Figure S3 ) . Importantly , the imposed rhythmic food intake restored an oscillatory nutrient response , as shown by the levels of circulating insulin that were comparable to the wild type ( Figure 4A ) . Accordingly , in Bmal1−/− mice SREBP1 translocated to the nucleus from ZT18 onwards ( Figure 4D and 4E ) and its expression was still cycling , although the phase was delayed by about 6 h compared to the wild type ( Figure 4C ) . We next checked the dynamics of SREBP1 binding to a panel of the targets previously identified in wild type mice and we found that SREBP1 was recruited to all the tested sites in an oscillatory way , but with an average phase shift of about 4 hours ( figure 4F ) . Finally , to assess the impact of the circadian oscillator impairment on SREBP1-driven transcription , we globally evaluated the expression of SREBP1 target genes in Bmal1−/− mice ( Table S5 ) . Most SREBP1 target genes were still scored as oscillating in Bmal1−/− upon temporal restricted feeding ( 57% have a P<0 . 05 ) . However , the heatmap rendering of their expression patterns ( Figure 5A ) revealed a temporal profile that was perturbed in Bmal1−/− compared to WT mice , as most of the genes now had a maximum expression at ZT18 , coinciding with the binding of the transcription factor ( Figure 5C ) . Accordingly , the expression phases of the genes belonging to the clusters A1 and A3 identified earlier ( Figure 3 ) were now largely concomitant with those of genes belonging to cluster A2 , therefore mostly grouped between ZT14 and ZT24 ( Figure 5B and Figure S4 ) . This phase shift was not due to a selective decrease of the number of cycling genes in clusters A1 and A3 , as the percentage of the significantly oscillating genes was comparable in the three clusters in WT and Bmal1−/− mice ( cluster A1: 84% in WT vs 94% in Bmal1−/−; cluster A2: 71% in WT vs 66% in Bmal1−/−; cluster A3: 62% in WT vs 64% in Bmal1−/− with P<0 . 05 ) . To explore how the core clock components participate to this regulation we checked in published data sets whether key transcription factors such as BMAL1 , CLOCK1 , CRY1 , CRY2 , PER1 , PER2 , NPAS2 and REV-ERBs can differentially bind to the promoters of the three clusters of SREBP1 target genes [27]–[29] . Interestingly , we found that most SREBP1 peaks ( 148 out of 236 , ≈63% ) have an overlapping REV-ERBα and/or REV-ERBβ peak . In addition , a REV-ERBα/β binding site was detected also in another 17% of the promoters of SREBP1 target genes , but in a non-overlapping position . This strong occupancy of SREBP1 targets by REV-ERBs is consistent with the previously reported involvement of REV-ERBα in the regulation of lipid metabolic genes [30] , and suggests the existence , in mouse liver , of a SREBP1-REV-ERBs network in physiological conditions . The frequency of REV-ERBs recruitment was comparable in clusters A1 , A2 and A3 ( data not shown ) , thus arguing against the possible role of these nuclear receptors in determining the distinct phase of expression of these genes . However , due to the presence of REV-ERB binding sites in many SREBP1 target genes , the flattened REV-ERB expression observed in Bmal1−/− may perturb , at least in part , the phase of several SREBP1 target genes . Indeed , in WT mice , the temporal expression profile of SREBP1 and REV-ERBs is very different ( the phases of expression are ZT15 and ZT8 , respectively [16] ) , and these factors are not expected to compete for binding at the same time to the same genes . The other transcription factors tested were recruited to a lesser extent on SREBP1 target gene promoters and for none of them we observed a significant enrichment in clusters A1 , A2 or A3 ( data not shown ) . Taken together , our results confirm that SREBP1 activity is strongly dictated by the rhythmicity of nutrient intake . In addition , our observations indicate that a functional circadian core clock is necessary to assure the correct temporal expression profile of SREBP1 target genes and suggest a role for HNF4 in dictating the phase of expression of genes whose mRNA levels peak when SREBP1 binding is low . Further studies will aim at understanding whether and how the lack of circadian rhythm perturbs HNF4 activity .
SREBP1 is a highly circadian transcription factor whose activity is strongly regulated by nutrient availability through the insulin signaling pathway . In mouse liver SREBP1 expression displays a daily rhythm with a peak in the nocturnal feeding period under standard housing condition of mice [16] , [18]–[20] . In this study we evaluate the dynamics of SREBP1 recruitment to DNA by determining its genome wide cis-acting targets ( cistrome ) in the liver along an entire day . SREBP1 binds to 448 sites with an oscillatory profile that is temporally coherent with the phase of its maximal expression . Within SREBP1 binding sites , four distinct groups are clearly distinguishable . The first set ( cluster A ) contains peaks that are likely the more relevant in the transcriptional regulation mediated by SREBP1 as they are the closest to TSS and they are bound more rhythmically by SREBP1 . Importantly , in more than 60% of these sites we identified the direct repeat 5′-ATCACCCCAC-3′ that was described as the Sterol regulatory proteins Responsive Elements ( SRE ) in several promoters , such as the human LDL receptor promoter [13] , [31]–[33] . This direct repeat variant of the canonical E-box inverted repeats 5′-CAnnTG-3′ was shown to be specifically recognized by SREBP proteins due to the presence of a tyrosine residue in a position that corresponds to an arginine in all the other bHLH-LZ proteins and that is critical for high affinity contacts with the SRE [34] , [35] . Furthermore , our ChIP-seq results highlighted the presence of predicted binding sites for SP1 , NFY and HNF4 in 60% , 30% and 25% of cluster A sites , respectively . Since SREBP1c , the major SREBP1 isoform in the liver , is a weak transcriptional activator , this observation is consistent with earlier studies demonstrating that the transcription factors SP1 , NFY and CREB cooperate to regulate different SREBP1-responsive promoters [36]–[39] . In 2009 , Seo et al have published a list of liver SREBP1 target genes obtained from a genome-wide study of mice subjected to 24 hours fasting followed by 12 hours refeeding with high carbohydrate diet [40] , thus creating a condition where a very high SREBP1c activity is expected . In this study , a functional variant of the direct repeat SRE ( 5′ACTACANNTCCC-3′ ) was identified as a preferred site for SREBP1 binding , and no enrichment of the predicted NFY binding site was identified . The difference between this data set and ours can most likely be attributed to the difference in the specific experimental conditions , acute challenge on the one hand and physiological condition on the other hand ( present study ) . Consistent with our study , both SP1 and NFY proteins were recruited on more than 30% of SREBP1 target genes in a genome-wide analysis of SREBP1 binding in HepG2 cell line [17] . In addition to SP1 and NFY , here we identify HNF4 as an important player of the interconnected regulatory circuit that may assure the specific regulation of SREBP1 target genes with distinct functions . Interestingly , consensus motifs for SP1 , NFY and HNF4 were found to be overrepresented in the promoters of cycling genes in the liver [41] , [42] . Since ≈70% of SREBP1 targets show a circadian gene expression , our results are in line with these bioinformatics predictions , supporting the involvement of these transcription factors in the complex transcriptional regulation of circadian rhythm in liver . The second set of SREBP1 target sites falls in the three clusters B , C and D . These peaks are not enriched in regions proximal to TSSs for mapped genes , nor in predicted motifs for known transcription factors . Furthermore the temporal profile of SREBP1 binding to these sites is flattened compared to the first set of SREBP1 target sites ( cluster A ) . Additional studies are required to understand whether these peaks have a functional role , or whether they are bound in a secondary manner by SREBP1 due to the formation of DNA loops . In the liver the expression of several known SREBP1c target genes is decreased in fasted mice , when the levels of SREBP1 are very low and increased upon refeeding , when both SREBP1 expression and nuclear translocation are induced [40] , [43] . Accordingly , our analysis of Pol II recruitment on SREBP1 putative target genes , coupled with the measurement of their mRNA levels , revealed a maximum of transcription and expression during the fed state , namely between ZT12 and ZT24 , for the majority of these genes . This is consistent with the binding of SREBP1 to DNA , which is higher at this time of the day . Nevertheless , a large set of SREBP1 target genes ( cluster A3 ) displays a temporal expression profile strongly shifted with respect to SREBP1 recruitment . However , the different phase of expression observed in these genes is coherent with the dynamics of Pol II association to their promoter and gene body , thus arguing against a major involvement of post-transcriptional mechanisms in this delay and suggesting the existence of promoter specific events that determine the different temporal expression profile of SREBP1 target genes . In particular , the low level of expression of genes belonging to cluster A3 when SREBP1 is bound raises the question whether SREBP1 itself , or through interaction with coregulatory proteins , can act as transcriptional repressor for these genes . Interestingly , it was proposed that SREBP1 may act as negative regulator of the cytosolic phosphoenolpyruvate carboxykinase ( Pck-1 ) gene by impairing the recruitment of the transcriptional coactivator Peroxisome Proliferator-Activated Receptors γ Coactivator -1 ( PGC-1 ) on HNF4α [44] . To explain the negative effect of SREBP1 on this gene , a second mechanism was put forward by Chakravarty and colleagues , suggesting an interference between the binding of SREBP1 and SP1 , due to the orientation on the opposite DNA strands of the two binding sites [45] . Although we find an enrichment of motifs for NFY and SP1 in the close proximity of SREBP1 peaks from the first set of target sites ( clusters A1 , A2 and A3 ) , we do not observe a different presence and/or orientation of these sites with respect to SREBP1 peaks , among these three groups of target sites . Conversely , the high frequency of the HNF4 motif in the cluster A3 suggests that the cross-talk between HNF4 and SREBP1 may be a general mechanism through which SREBP1 negatively affects the transcription of a sub-set of its target genes . In agreement with this hypothesis , among the targets of SREBP1 expressed upon fasting we detect the Peroxisome Proliferator-Activated Receptor α ( Pparα ) gene , that was shown to be crucially regulated by HNF4 [46] . In recent years , growing evidences have highlighted the impact of circadian gene networks on nutrient balance and , on the other hand , the regulation of the circadian clock by metabolism and food consumption [47] , [48] . Thus , circadian clock and metabolism converge in numerous ways to control the activity of a number of transcription factors that are essential for maintaining metabolic homeostasis , although the exact contribution of each input remains to be deciphered . Several studies demonstrated that upon restricted feeding ( RF ) , namely when time and duration of food availability is limited in time , mice adjust to the feeding period within a few days , they display food anticipatory behavior and consume their daily food intake during that limited time [49]–[52] . This feeding regimen drives rhythms in arrhythmic and clock mutant mice or in animals with SNC ablations , thus uncoupling the circadian clock , synchronized by SCN , from the periphery [3] , [4] . Many physiological activities that are normally dictated by the SCN master clock , such as hepatic P450 activity , body temperature , locomotor activity , and heart rate , are restored by RF . In the liver of cry1−/−;cry2−/− mice , RF restores the oscillatory circadian expression profile of a number of “feeding driven” transcripts , although with a small delay in their phase of expression , showing that the circadian clock anticipates changes in the feeding state and accelerates the transcriptional response to an acute activation or repression by feeding [4] . This is consistent with our observation that in Bmal1−/− mice , rhythmic SREBP1 expression and activity , that are drastically flattened when mice are fed ad libitum ( data not shown ) , are reinstated upon RF , although with a deferred phase . Notably , growth and metabolic defects that were reported in Bmal1−/− mice either at older age or under different feeding regimens [53]–[58] , are negligible in the experimental conditions adopted in our study , suggesting that the role of the circadian clock in the regulation of SREBP1 could be evaluated in the absence of major confounding pathologies . As an example , Bmal1−/− mice at 8–10 month of age have an impaired insulin release due to the absence of a functional clock in pancreatic beta-cells [59] . However , in our case the delayed SREBP1 activation cannot be attributed to a reduced insulin release , since we detect normal glucose and insulin levels in Bmal1−/− mice at 3 month of age upon RF . Conversely , the expression of REV-ERBα , that is directly regulated by BMAL1 , is constantly downregulated . This event leads to the derepression of the Insulin Induced 2 ( Insig2 ) gene , encoding a trans-membrane protein that sequesters SREBP proteins to the endoplasmic reticulum membranes , thus interfering with the proteolytic activation of SREBPs , in agreement to what was shown in REV-ERBα−/− mice [16] . SREBP1 activity in the nucleus reflects also the rate of its proteosomal degradation after DNA binding [60] , [61] , a process that is strongly sensitive to the insulin-mediated inactivation of the glycogen synthase kinase 3 ( Gsk3 ) [62] . In Bmal1−/− mice the phase of SREBP1 recruitment to DNA is shifted , but we do not observe a longer SREBP1 accumulation on its targets , suggesting that the absence of a functional clock is not significantly altering its degradation process . In conclusion , our results show that besides the nutrient-driven regulation of SREBP1 nuclear accumulation , a second layer of modulation of SREBP1 transcriptional activity exists and is strongly dependent from the circadian core clock . This system allows to fine tune the expression timing of SREBP1 target genes , thus helping to temporally separate the different physiological processes in which these genes are involved . Thus , SREBP1 is situated at the interface of the circadian and the metabolic regulation and its study promises to shed light on the emerging association between diabetes , obesity , sleep , and circadian timing .
All animal experiments and procedures were approved by the Swiss Veterinary Office ( authorisation VD-1453 . 4 ) . C57BL/6 male were purchased from Charles River . Bmal1−/− mice were a kind gift from Dr . Frédéric Gachon and were generated as previously described [63] , [64] . 12–14 week old ( at time of sacrifice ) , mice were housed in a 12 h light/12 h dark ( LD ) regimen for 2 weeks with food and water freely available during night and day . They were then phase-entrained to a 12 hr/12 hr LD regimen with food access between ZT12 and ZT24 for 7 days ( ZT = Zeitgeber time; ZT0 is defined as the time when the lights are turned on and ZT12 as the time when lights are turned off ) . At each ZT2 , ZT06 , ZT10 , ZT14 , ZT18 and ZT22 three to five mice were anesthetized with isoflurane and decapitated . Mice were killed under dim red light at ZTs during the dark phase . The livers were perfused with 2 ml of PBS through the spleen and immediately collected . A small piece of liver tissue was snap-frozen in liquid nitrogen . The remaining liver tissue was immediately homogenized in PBS containing 1% formaldehyde for chromatin preparation . Perfused livers were processed for chromatin preparation as previously described [65] . The chromatin samples from the mice of the same ZT were then pooled , frozen in liquid nitrogen and stored at −80°C . The following antibodies were used: anti-RPB2 ( Santa Cruz Biotechnology , H-201 ) , anti-SREBP1 ( Santa Cruz Biotechnology , H-160 ) , anti-HNF4 ( Santa Cruz Biotechnology , C-19 ) . Chromatin was subjected to immunoprecipitation of Pol II as described [24] . For SREBP1 , the samples were diluted ten times in “sonication buffer” containing 50 mM HEPES ( pH 7 . 9 ) , 140 mM NaCl , 1 mM EDTA , 1% Triton X-100 , 0 . 1% Na-deoxycholate , 0 . 1% SDS and proteinase inhibitors ( Roche ) . 1 ml of diluted chromatin was immunoprecipitated with 10 µg of antibody as described [66] . Briefly , the immune complexes were collected by adsorption to ten µl of protein-A-Sepharose ( 25% slurry in sonication buffer ) , pre-blocked with 10 µg/ml of salmon sperm DNA and BSA at 4°C overnight . The beads were washed twice with “sonication buffer” , twice with sonication buffer containing 500 mM NaCl , twice with 20 mM Tris , pH 8 . 0 , 1 mM EDTA , 250 mM LiCl , 0 . 5% NP-40 , 0 . 5% Na-deoxycholate and twice with TE buffer . The immunocomplexes were eluted with 50 mM Tris , pH 8 . 0 , 1 mM EDTA and 1% SDS at 65°C for 10 min . , adjusted to 200 mM NaCl and incubated at 65°C overnight to reverse the cross-links . After successive treatments with 10 µg/ml Rnase A and 20 µg/ml proteinase-K , the samples were extracted with NucleoSpin Kit ( Macherey- Nagel ) . The DNA concentration was determined by fluorometry on the Qubit system ( Invitrogen ) . 10–12 ng DNA were used for the preparation of the library . Libraries for ultra-high throughput sequencing were prepared with the ChIP-Seq DNA sample kit ( Illumina ) as recommended by the manufacturer . About 100 mg of snap-frozen liver tissue were used for RNA preparation with the TRIzol reagent ( Invitrogen ) followed by purification with miRNeasy Mini Kit ( Qiagen ) , according to manufacturer's instructions . For microarray analysis 500 ng of total RNA from each liver sample at the same time point were pooled and analyzed on Mouse Gene 1 . 0ST arrays according to the manufacturer's instructions ( Affymetrix ) . All statistical analyses were performed with the statistical language R and various Bioconductor packages ( http://www . Bioconductor . org ) . Normalized expression signals were calculated from Affymetrix CEL files using RMA normalization method . For quantitative RT-PCR analysis , the retrotranscription has been done using iScript cDNA synthesis kit ( Bio-Rad , Laboratories , Hercules , CA ) and following the manufacturer's instructions . The primers sequences are shown in Tables S7 and S8 . Real-time monitoring of PCR amplification of cDNA was performed using the FastStart Universal SYBR Green Master ( Roche Applied Science , Indianapolis , IN ) in an ABI Prism 7900 Sequence Detection System ( Life Technologies , Carlsbad , CA ) . The PCR arbitrary units of each gene were defined as the mRNA levels normalized to the 36b4 and the Rps9 expression level in each sample using the qBase Software . Nuclear extracts were prepared by the NUN procedure as described previously [67] , and Western blotting was performed according to standard protocols using the antibody for SREBP1 indicated above . U2AF and Lamin A were used as loading control ( anti-U2AF and anti-Lamin A were from Sigma-Aldrich ) . At sacrifice , blood was taken for determination of biochemical parameters and circulating hormones . Insulin levels were determined with ELISA kit from Mercodia , Uppsala , Sweden , following manufacturer's instructions . At each time point , DNA sequenced reads were mapped to the mouse genome ( Mus musculus NCBI m37 genome assembly ( mm9; July 2007 ) ) using Bowtie [68] with three mismatches and at most five hits allowed on the genome . When computing genomic read densities , each alignment contributed 1/ ( total number of hits ) to the local density . If several reads in the same library mapped at the same genomic position and on the same strand ( redundant tags ) , we kept only one read for the rest of the analysis . The total numbers of reads per time point are given in Table S1 . The mapped reads were shifted to account for the length of the inserts based on the average fragment size , namely 190 184 204 199 202 208 and 176 , for each of the seven libraries . The fragment size was divided by two and half of the read length was subtracted resulting in a shift of 55 , 52 , 62 , 60 , 61 , 64 , and 48 nucleotides from ZT02 to ZT26 . We fragmented the genome into 500 nucleotide blocks and collected the counts within each block for SREBP1 as well as for input experiments . We kept all blocks for which we had a signal equivalent to 40 tags in at least one time point of the SREBP1 experiment . We log transformed the data after adding 1 pseudo count and quantile normalized both SREBP1 and input experiments . We selected blocks with a log2 signal SREBP1/input greater than 2 , i . e . at least a four-fold enrichment of the SREBP1 signal in comparison to the input signal in at least one time point . We repeated this procedure by shifting the block definition of half the length of the blocks and merged the overlapping blocks that passed these criteria . To define proper “peaks” in these wide regions , we look for shorter regions accounting for most of the counts . For this , we repeatedly consider the two borders along 50 nucleotides , and discard the one with less read counts if we keep 75% of the total reads in the remaining region . This operation is repeated with shorter borders until no further refinement is possible . We used the MEME suite [21] to identify enriched motifs in the sequences corresponding to the refined peaks . We first performed several motif discovery , on all peaks , and on the subset associated or not with Pol II . We searched for 15 motifs between 6 and 10 nucleotides long . The discovered motifs have been associated to known transcription factors ( from the TRANSFAC database ) with STAMP . To retrieve these motifs in the subsets where they have not been discovered , we searched for them in all sequences ( using FIMO ) . To assess the relevance of the number of observed motifs in our dataset , we counted the occurrence of the same motifs in random sequences . These sequences are selected in the proximity of the TSS of genes expressed in our samples ( among the top 10% in the microarray data ) . Their size and distance to TSS are in the same range as that of our SREBP1 peaks . Before fitting a cosine function to estimate the amplitude and the phase of the oscillation in a 24 hour period , counts in the refined peaks were quantified and normalized according to the total number of non redundant mapped reads for each given library . We used the function x ( t ) = b0+b1*cos ( b3+2π*t/24 ) to perform a least squared fitting of temporal profiles . The parameter b0 represents the mean signal , b1 the amplitude of the oscillation , and b3*24/2π the phase . These parameters were estimated by nonlinear least-squares using the Gauss-Newton algorithm . For the microarray temporal profile analysis we used the function while when we compared WT and Bmal1−/− mice we used the functionwhere b4 and b5 represent the different batch effects , GT is a dummy variable that indicates the mouse genotype ( WT or KO ) and b0gt , b1gt , b3gt the associated coefficients . Illumina sequencing data for the ChIP-seq are available at GEO as the GSE48375 . Additional processed data and visualization tools are provided at http://cyclix . vital-it . ch .
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Circadian rhythmicity is part of our innate behavior and controls many physiological processes , such as sleeping and waking , activity , neurotransmitter production and a number of metabolic pathways . In mammals , the central circadian pacemaker in the hypothalamus is entrained on a daily basis by environmental cues ( i . e . light ) , thus setting the period length and synchronizing the rhythms of all cells in the body . In the last decades , numerous investigations have highlighted the importance of the internal timekeeping mechanism for maintenance of organism health and longevity . Indeed , the reciprocal regulation of circadian clock and metabolism is now commonly accepted , although still poorly understood at the molecular level . Our global analysis of DNA binding along the day of Sterol Regulatory Element Binding Protein 1 ( SREBP1 ) , a key regulator of lipid biosynthesis , represents the first tool to comprehensively explore how its activity is connected to circadian-driven regulatory events . We show that the regulation of SREBP1 action by nutrients relies mainly on the control of its subcellular localization , while the circadian clock influences the promoter specific activity of SREBP1 within the nucleus . Furthermore , we identify the Hepatocyte Nuclear Factor 4 ( HNF4 ) as a putative player in the cross-talk between molecular clock and metabolic regulation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biology"
] |
2014
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Genome-Wide Analysis of SREBP1 Activity around the Clock Reveals Its Combined Dependency on Nutrient and Circadian Signals
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Manipulation of the mosquito gut microbiota can lay the foundations for novel methods for disease transmission control . Mosquito blood feeding triggers a significant , transient increase of the gut microbiota , but little is known about the mechanisms by which the mosquito controls this bacterial growth whilst limiting inflammation of the gut epithelium . Here , we investigate the gut epithelial response to the changing microbiota load upon blood feeding in the malaria vector Anopheles coluzzii . We show that the synthesis and integrity of the peritrophic matrix , which physically separates the gut epithelium from its luminal contents , is microbiota dependent . We reveal that the peritrophic matrix limits the growth and persistence of Enterobacteriaceae within the gut , whilst preventing seeding of a systemic infection . Our results demonstrate that the peritrophic matrix is a key regulator of mosquito gut homeostasis and establish functional analogies between this and the mucus layers of the mammalian gastrointestinal tract .
Mosquitoes of the Anopheles genus are responsible for the transmission of Plasmodium parasites , the causative agents of malaria . The study of the Anopheles gut microbiota has recently emerged as an important field in an effort to characterize mosquito-parasite interactions in greater depth and to develop new methods to stop disease transmission . The microbiota have been shown to trigger a constitutive immune response in the mosquito gut epithelium that enhances resistance to parasite infection [1 , 2] . Furthermore , specific gut bacteria have been found to directly impact parasites , compromising their infectivity [3 , 4] . Finally , a promising transmission-blocking intervention is paratransgenesis , which aims to use vector-associated bacteria as a delivery tool for antimalarial effectors [5] . The success of such an approach would require the persistence of genetically-modified bacteria at sufficient abundance within the gut ecosystem , and potentially their successful dissemination throughout the mosquito body . As such , deeper understanding of mosquito-microbiota interactions may highlight mechanisms by which bacteria can be utilized to block malaria transmission . The balance between immune resistance and tolerance is key to bacterial persistence within the gut environment . Resistance refers to bacterial killing or the prevention of bacterial growth , whilst tolerance encompasses the prevention or repair of host tissue damage caused by pathogens or immune responses [6] . In Drosophila , commensals are controlled largely by the production of reactive oxygen species ( ROS ) by the dual oxidase ( DUOX ) enzyme [7 , 8] , whilst the other main resistance mechanism in the Drosophila gut , the Imd pathway , is under strong negative regulation to prevent its stimulation by commensals [9–11] . In mosquitoes , blood feeding triggers substantial microbiota proliferation [12 , 13] and induces high levels of oxidative stress , potentially precluding further production of ROS for immune control [14] . In A . gambiae , commensals are known to induce the Imd pathway , and suppression of the Imd pathway receptor PGRPLC and its transcription factor REL2 causes microbiota overgrowth [1 , 2] . The transcription factor Caudal , which is specifically expressed in the gut , down-regulates REL2-dependent expression of antimicrobial peptides ( AMPs ) , facilitating microbiota tolerance [15] . Some tolerance mechanisms are based on the strengthening of physical barriers between the microbiota and the host . Notably , an A . gambiae heme peroxidase is induced by blood feeding and , together with DUOX , forms a network of dityrosine bonds that is thought to protect the gut epithelium from immune elicitors , thus mediating bacterial persistence [12] . The peritrophic matrix has also been identified as playing a role in host-bacteria interactions in a number of insects . It is an acellular structure composed of chitin , proteins and glycoproteins located between the gut lumen and the epithelium . The mosquito type I peritrophic matrix is produced by adult female midgut cells during blood feeding and physically surrounds the blood bolus , whilst the type II peritrophic matrix is permanently produced by the cardia in the anterior larval gut . The type II peritrophic matrix of the hematophagous tsetse fly provides infectious Serratia bacteria with a protective niche in which they can proliferate without inducing a gut immune response , increasing susceptibility to infection [16] . In the tick Ixodes scapularis , the gut microbiota induces the formation of a peritrophic matrix whose presence facilitates colonization of the spirochete bacterium Borrelia burgdorferi , possibly by protecting the pathogen from blood meal pro-oxidants and cellular immunity [17] . In Drosophila , oral bacterial infection induces the expression of genes encoding proteins with chitin binding domains ( CBDs ) [18] , and a protein of the type II peritrophic matrix is shown to reduce both local and systemic Imd pathway stimulation and to protect epithelial cells against pore-forming toxins [19 , 20] . The mosquito peritrophic matrix is often considered as a barrier to parasite infection , though one that parasites have evolved to overcome . Secretion of chitinase by Plasmodium effectively facilitates traversal of the peritrophic matrix [21–25] . A constitutive peritrophic matrix protein , fibrinogen-related protein 1 ( FREP1 ) , has recently been proposed to be exploited by invading parasites , serving as an anchor that facilitates P . falciparum invasion [26] . More generally , the Aedes aegypti peritrophic matrix is thought to play a role in blood meal detoxification , sequestering large quantities of heme released during blood bolus digestion [27] . The role of the mosquito peritrophic matrix in bacterial pathogenesis and microbiota homeostasis in the gut has not yet been explored . Here , we use RNA sequencing to explore the microbiota-dependent gene expression in the midgut of the A . coluzzii mosquito ( until recently known as A . gambiae M form ) . We find that the gut microbiota induce the expression of several components of the peritrophic matrix , and that the microbiota are necessary for the synthesis of a structurally complete peritrophic matrix . We also show that the peritrophic matrix plays a role in resistance to the Enterobacteriaceae bacteria present in the gut microbiota , both reducing the extent to which this family of bacteria grows and persists within the gut , and precluding this family of bacteria from seeding a systemic infection .
To explore the transcriptional response to the dynamic changes in microbiota load over the blood feeding cycle , we sequenced RNA extracted from A . coluzzii midguts at five time points: 2–3 day old mosquitoes that had accessed only fructose since emergence ( sugar-fed , ‘SF’ ) , 5h , 24h and 72h after a human blood meal and 24h ( 96h ) after a second human blood meal that was given at the 72h time point . This time course was performed with conventionally-reared mosquitoes that harbored their native microbiota , and a cohort of mosquitoes that were fed an antibiotic cocktail ( 50μg/ml gentamicin , 60μg/ml streptomycin , 60U/ml penicillin ) in both sugar and blood meals . This antibiotic treatment was effective in substantially depleting mosquito guts of bacteria as detected by qRT-PCR against 16S rRNA ( Fig 1A ) . Each sample consisted of a pool of 20 midguts , and four independent replicates were performed using four independent batches of mosquitoes , as there is evidence that the microbiota of laboratory-reared mosquitoes varies between generations [1] . The resulting cDNA libraries were sequenced across four lanes of an Illumina flowcell on an Illumina Hiseq 1500 , resulting in a total of 893 , 247 , 801 pairs of 100bp reads across the forty samples . After quality control , an average of 85 . 6% of input sequences per sample aligned uniquely to the A . gambiae PEST genome ( AgamP4 ) . A total of 6753 genes ( 49 . 9% of all annotated genes ) had non-zero counts in all forty samples . Principal component analysis ( PCA ) indicated that the samples clustered according to their blood feeding status , with no obvious outliers ( Fig 1B ) . Soft clustering analysis indicated that the oral antibiotic treatment had an overall relatively minor effect on the general transcriptional changes occurring over the blood feeding cycle ( S1 Fig ) . Nevertheless , we identified 889 genes that were significantly differentially regulated at one or more time points by antibiotic treatment ( S1 File ) . Gene Ontology ( GO ) and Kyoto Encyclopedia of Genes and Genomes ( KEGG ) enrichment analysis implicated these genes in diverse processes , including carbohydrate , protein and lipid metabolism , folate biosynthesis , oxidation-reduction processes and immunity ( S1 Table ) . Interestingly , the 0h and 72h samples exhibited the greatest number of differentially regulated genes ( Fig 1C ) , despite having the lowest bacterial load in the control samples . We hypothesised that this could be indicative of the microbiota playing a more significant role in midgut physiology at these time points , or of the existence of highly effective tolerance mechanisms in the gut following blood feeding . As observed previously [1] , we noted that several microbiota-regulated genes encoded proteins containing CBDs , a signature of the structural components of the peritrophic matrix . Although the precise structure of the peritrophic matrix remains under-explored , a proteomic analysis has previously identified its most abundant protein components [28] . Of genes encoding 24 of the top candidate proteins identified in that study , 12 were significantly differentially regulated in our dataset , with 11 of these being down regulated following antibiotic treatment ( S2 Table ) . The microbiota-induced genes included AgAPER1 ( AGAP006795; Fig 2A ) , which encodes a chitin-binding A . gambiae peritrophic matrix component [29] and was the most abundant CBD-containing protein identified by mass spectrometry [28] . We also noted the microbiota-dependent expression of ICHIT ( AGAP006432 ) that is known to be transcriptionally induced by both P . berghei and bacterial infections and encodes two CBDs and a proline-rich domain that may be involved in protein-protein aggregation [30] ( Fig 2A ) . Two genes ( AGAP009313 and AGAP006194 ) encoding proteins identified in the peritrophic matrix proteomic study [28] were significantly microbiota regulated at all five time points ( Fig 2A ) ; neither of these genes encode CBD-containing proteins . In addition to the protein components of the peritrophic matrix , the main structural constituent is chitin , a polymer of N-acetylglucosamine . Insects are able to synthesize chitin from glucose in a multistep reaction ( Fig 2B ) ; fructose-6-phosphate , derived from glucose , is converted to glucosamine-6-phosphate in a rate limiting step catalyzed by glucosamine-fructose-6-phosphate aminotransferase ( GFAT ) [31] . Glucosamine-6-phosphate is then metabolized to UDP N-acetylglucosamine , which is subsequently polymerized to chitin fibers by chitin synthase . The A . gambiae genome encodes two chitin synthase enzymes , CHS1 ( AGAP001748 ) and CHS2 ( AGAP001205 ) , of which CHS2 is expressed in the midgut and responsible for the synthesis of peritrophic matrix-associated chitin [32] . Here , we identified GFAT and CHS2 , the enzymes catalyzing two rate-limiting steps of the chitin synthesis pathway , as being microbiota-regulated at the transcript level at one or more of the time points examined ( Fig 2C ) . Following antibiotic treatment the expression of these enzymes is either significantly reduced or temporally delayed . We speculated that this transcriptional response in the production of both chitin and peritrophic matrix proteins could be bacterially induced either directly , through detection of bacterial elicitors , or indirectly as a result of bacteria causing thinning of the peritrophic matrix ( e . g . through chitinases ) that results in compensatory transcription to produce a peritrophic matrix of normal thickness . We used thin abdominal sections 24h post blood meal stained with hematoxylin and eosin ( H&E ) to observe the effect of oral antibiotic treatment on the structure of the gut tissue ( Fig 2D ) . In the control samples , a thick layer of dark pigment was observed surrounding the blood bolus and effectively separating the contents of the lumen from the epithelial cells . We hypothesized that this dark layer is likely an accumulation of heme pigment at the surface of the peritrophic matrix . Indeed , heme released during hemoglobin digestion is shown to bind CBD-containing peritrophic matrix proteins in Aedes aegypti mosquitoes [27 , 33 , 34] . In the antibiotic-treated mosquitoes , several regions exhibited disruption of this layer , suggestive of a similar disruption of the peritophic matrix , resulting in red blood cells ( RBCs ) coming into direct contact with the epithelial cells ( Fig 2D ) . Quantification of such instances confirmed that RBC contact with the epithelium is significantly increased in antibiotic-fed ( 92% , n = 12 ) compared to control guts ( 6% , n = 18; p<0 . 0001 , Chi-square test ) . To confirm the disruption of the peritrophic matrix , we stained abdominal sections with the chitin specific stain calcofluor white ( Fig 2E ) . In both control and antibiotic treated samples , chitin specific staining of the cuticle was observed . In control mosquitoes , we additionally observed a prominent layer of chitin staining surrounding the blood bolus , which corresponds to the peritrophic matrix . In the antibiotic treated group this staining was either absent or fragmented . These observations suggest that , indeed , the presence of the microbiota is required for the synthesis of a structurally complete peritrophic matrix . The RNAseq data indicated that the microbiota play a significant role in regulating antimicrobial peptide ( AMP ) expression in the gut , with seven characterized immune effector-encoding genes being upregulated at one or more time points by the presence of the microbiota ( S3 Table ) . These AMPs include three cecropins ( CEC1 , CEC2 and CEC3 ) , one defensin ( DEF1 ) , gambicin ( GAM1 ) and two C-type lysozymes ( LYSC1 and LYSC7 ) . We therefore sought to explore whether the peritrophic matrix plays a role in mediating the mosquito immune response to the microbiota . We supplemented the blood meal with 100μM polyoxin D , a chitin synthase inhibitor that has previously been demonstrated to abolish synthesis of the A . gambiae type I peritrophic matrix [24] . Staining of abdominal mosquito sections with calcofluor white at 24h post blood meal confirmed the absence or fragmentation of the peritrophic matrix upon treatment with polyoxin D ( S2A Fig ) . In the midguts of polyoxin D-fed mosquitoes , we also observed increased RBC contact with the epithelium ( 47% , n = 17 ) compared to control guts ( 19% , n = 32; p<0 . 05 , Chi-square test; S2B Fig ) . We next investigated whether the peritrophic matrix plays a role in modulating the midgut epithelium response to the microbiota . We selected two AMP reporter genes , CEC1 and GAM1 , which showed strong microbiota-dependent expression at all time points examined ( Fig 3A and S3 Table ) . The midgut expression of the two AMP genes was monitored at 24h after blood meal supplementation with 100μM polyoxin D or an equal volume of water as a control . We observed a significant increase in the expression of GAM1 in the midguts of polyoxin D-treated mosquitoes ( Fig 3B ) , whilst the increase in CEC1 expression between polyoxin D treated and untreated mosquitoes was not statistically significant ( S3A Fig ) . Treatment of mosquitoes with antibiotics revealed that the increase of GAM1 expression was microbiota-dependent ( Fig 3B ) . In order to confirm that the effect of polyoxin D on the immune response in the gut was due to disruption of the peritrophic matrix as opposed to any direct effect of polyoxin D on gut bacteria or the cells of the epithelium , we sought an independent method of peritrophic matrix disruption . To this end , we silenced by RNAi the APER1 gene that encodes an abundant peritrophic matrix component . The results showed an elevated immune response in the midguts of APER1 knock down mosquitoes , corroborating the polyoxin D feeding experiments ( S3B Fig ) ; in this case , CEC1 expression was significantly increased , whilst GAM1 expression also showed non-significant up-regulation . This effect was again microbiota dependent ( S3B Fig ) . These data raised the question whether disruption of the peritrophic matrix affects tolerance or resistance mechanisms . In the former case , the elevated AMP expression in peritrophic matrix-disrupted midguts would reflect increased access of bacteria and immune elicitors to the innate immune receptors found on the epithelial cells , which could consequently result in decreased bacterial growth . In the latter case , disruption of the peritrophic matrix could relieve bacterial growth from biochemical and/or physical constraints , which may result in a higher bacterial load , consequently increasing AMP induction . We quantified the total bacterial load in the polyoxin D-treated compared to control midguts as well as the specific load of three bacterial families commonly found in Anopheles midguts: Enterobacteriaceae , Flavobacteriaceae and Acetobacteraceae [35] . We did not detect a significant difference in total bacterial load nor in the load of bacteria of the Flavobacteriaceae and Acetobacteraceae families between the two groups ( S3C Fig ) . However , a significant increase was detected in the load of the Enterobacteriaceae , which was highly variable between midgut pools ( Fig 3C ) . Corroborating this , we also observed substantial Enterobacteriaceae overgrowth in a subset of the APER1 knock down mosquito cohorts compared with the LACZ controls ( S3D Fig ) . These data point to a role of the peritrophic matrix in resistance to the Enterobacteriaceae . To further characterize the role of the microbiota in AMP regulation , we examined the correlation between the bacterial loads and GAM1 expression in each of the mosquito pools used in the polyoxin D experiments described above . In control mosquitoes , GAM1 expression positively correlated with both the Enterobacteriaceae and Acetobacteraceae loads , but not with the total bacterial load or the Flavobacteriaceae load ( Fig 3D ) . These data suggest that the Enterobacteriaceae and Acetobacteraceae families are primarily responsible for the induction of GAM1 . In the polyoxin D-fed mosquitoes , the positive correlation between Enterobacteriaceae load and GAM1 expression was maintained , but not that between Acetobacteraceae load and GAM1 expression ( Fig 3D ) . These data are consistent with a model whereby formation of the peritrophic matrix serves as a resistance mechanism , limiting the growth of the Enterobacteriaceae after blood feeding and the extent to which this family of bacteria induces a local immune response . By 72h after the blood meal , we observed that gut microbiota load had been restored to pre-blood feeding levels ( Fig 1A ) [36] . We sought to understand the mechanisms underlying this re-establishment of homeostasis following blood feeding , hypothesizing that the excretion of the blood bolus may additionally facilitate the physical removal of bacteria from the gut . To investigate this , we monitored individual mosquitoes 48h after blood feeding , dividing them into two groups according to whether or not they had excreted their blood bolus , and analyzed the gut bacterial load in each group ( Fig 4A ) . We found that , indeed , mosquitoes that had excreted their blood bolus had 98% lower bacterial load than those that still retained their blood bolus at this time point . These results strongly suggested that bacteria are excreted with the blood bolus , thus contributing to the restoration of gut homeostasis . Upon completion of blood digestion , the peritrophic matrix is believed to be excreted with the blood bolus [37] . To investigate whether the peritrophic matrix plays a role in mediating bacterial excretion , we monitored the effect of peritrophic matrix disruption on the bacterial load at 72h post blood feeding , a time point at which all individuals have excreted their blood bolus . The polyoxin D-fed cohort of mosquitoes harbored significantly higher loads of Enterobacteriaceae and Acetobacteraceae than the control cohort ( Fig 4B ) , as well as non-significantly higher loads of Flavobacteriaceae and total 16S rRNA ( S4 Fig ) , suggesting that the peritrophic matrix prevents bacteria from occupying niches within the gut that cannot be cleared upon excretion of the blood bolus . We performed immunohistochemistry against lipopolysaccharide ( LPS ) , a major component of the outer membrane of Gram-negative bacteria , to investigate bacterial localization in the mosquito gut . We observed the majority of staining in the periphery of the gut , suggesting possible co-localization of the gut bacteria with the peritrophic matrix ( Fig 4C ) . We next used Gram staining to investigate this localization further in both control and polyoxin D treated guts . In the control guts , we observed bacteria localizing between the blood bolus and the epithelial cell layer ( Fig 4D ) . In the polyoxin D treated guts , bacterial localization was more diffuse , with bacteria being observed at the periphery of the blood bolus , and indeed proximally to the cells of the epithelium , as well as within the gut lumen , amongst the blood bolus . Together , these data are suggestive of a model whereby the presence of an intact peritrophic matrix facilitates the efficient clearance of bacteria from the gut after blood bolus digestion , while co-localization of the gut bacteria and the peritrophic matrix may be a pre-requisite of this . In Drosophila and other insects , one function of a local gut immune response is to prevent or minimize systemic immune induction arising from an oral infection . We investigated whether the peritrophic matrix plays a role in preventing the induction of a systemic response to microbiota growth within the gut following a blood meal . For each pool of dissected midguts we collected the associated carcass samples , consisting of the abdominal cuticle with the fat body attached , after removal of all other organs , namely the gut , ovaries and malpighian tubules . At 72h post blood feeding , we observed that the gut microbiota induced considerable systemic induction of CEC1 in a subset of the polyoxin D-fed mosquitoes ( Fig 5A ) , with GAM1 expression exhibiting a similar trend ( S5A Fig ) . The same effect was also observed in APER1 knock down mosquitoes compared to the LACZ double stranded RNA-injected control , though in this case at 24h after the blood meal , where a significant increase in the expression of both GAM1 and LYSC1 was observed ( S5B Fig ) . Again , this systemic immune response was fully dependent on the presence of the microbiota ( S5B Fig ) . Mechanistically , we considered that this could occur either via translocation of live bacteria from the gut to the hemocoel , or via bacteria or mosquito-derived molecules signaling from the gut to the hemocoel . We focused our analysis on peritrophic matrix disruption by polyoxin D feeding , as the APER1 knock down cohort had sustained damage to the carcass during the injection process , providing a possible route of entry for exogenous bacteria . To investigate the former scenario , we attempted to amplify 16S rRNA from the carcass samples of the control and polyoxin D fed cohorts ( Fig 5B ) . In the antibiotic-treated mosquitoes , 16S rRNA amplification was insignificant , at the level of the qRT-PCR negative controls , whereas 16S rRNA was amplified above this level in a subset of both the non-antibiotic-treated control and polyoxin D-fed samples . We observed no significant difference in the relative total 16S rRNA that was amplified from the carcasses of the control or polyoxin D-fed mosquito cohorts at 72h post blood feeding ( Fig 5B ) . Given that we observed an increase in the Enterobacteriaceae load in the gut at 24h post blood feeding in the polyoxin D fed cohort , and no difference in the overall bacterial load detected in the control and peritrophic matrix disrupted carcasses , we hypothesized that the systemic immune induction could be due specifically to translocation of this bacterial taxon . Indeed , at 72h post blood feeding we found a significant increase in the Enterobacteriaceae load in the peritophic matrix disrupted cohorts , with this family only being confidently detected in polyoxin D-fed pools of mosquito carcasses and not in the control pools ( Fig 5C ) . No significant difference was observed in the incidence or load of the Flavobacteriaceae or Acetobacteraceae ( S6C Fig ) . Furthermore , in the polyoxin D-fed group , Enterobacteriaceae detection in the carcass correlated significantly with CEC1 induction , which was not the case in the control group ( Fig 5D ) . Flavobacteriaceae and Acetobacteraceae abundance did not correlate with CEC1 expression ( S5C Fig ) . The clear relationship between Enterobacteriaceae load and CEC1 expression , together with the fact that this family of bacteria is detected only in the carcasses of polyoxin D-fed mosquitoes , strongly suggests that this family of bacteria is able to translocate from the gut to the hemocoel upon disruption of the peritrophic matrix , seeding a systemic infection .
The data presented here reveal a complex and dynamic relationship between the midgut microbiota , the type I peritrophic matrix and local and systemic immune responses in adult female mosquitoes . In mammals , the inner and outer mucus layers of the gastrointestinal tract are composed of mucin glycoproteins and form a physical and biochemical barrier between the gut flora and the epithelial cells [38] . The mucus layer is at its thickest in the distal colon , the region of highest bacterial colonization , where it functions as a scaffold for AMPs and immunoglobulin A , and acts to protect against microbiota contact with the epithelium [39 , 40] . The outer mucus layer is known to interact with intestinal microbes [41] , providing a habitat for O-glycan foraging taxa [42] . Thus , the defensive nature of mucus is dependent on the entrapment of microbes in the outer layer , but this equally facilitates microbial colonization in acting as a source of nutrition . The mosquito peritrophic matrix is structurally analogous to the vertebrate mucus layer , containing heavily glycosylated proteins , though in this case cross-linking chitin . Here , we reveal additional functional analogies between these two evolutionarily diverse biological structures in limiting gut microbiota growth and precluding bacterial invasion of the intestinal epithelia . The type I peritrophic matrix is specifically produced by adult female midgut cells upon blood feeding and physically surrounds the blood bolus where blood digestion takes place . We show that synthesis of a structurally complete type I peritrophic matrix is dependent on the presence of the gut bacteria . Similar observations have been reported in other insects . In adult Drosophila , oral infection by Erwinia carotovora carotovora ( Ecc15 ) has been shown to induce the expression of genes encoding proteins with CBDs , with the induction of a proportion of these genes being dependent on the Imd pathway , one of the main immune signalling pathways in the fly gut [18] . Similarly , a protein constituent of the adult Drosophila peritrophic matrix , Drosocrystallin , is induced by oral bacterial infection [19] . The presence of the gut microbiota in the tick I . scapularis has also been shown to be necessary for production of a peritrophic matrix of proper thickness , with this being dependent on STAT signalling [17] . Finally , a proteomic analysis of the type II peritrophic matrix of the tsetse fly identified 27 proteins derived from the secondary endosymbiont Sodalis glossinidius , suggesting similar interaction of this bacterium with the peritrophic matrix [43] . In the mosquito gut , the microbiota is also known to induce the Imd pathway [1 , 2] . The JAK/STAT pathway , which is activated in response to viral infections [44 , 45] , is known to be responsive to bacterial infection [46] but has not yet been characterized as being microbiota responsive . It remains unclear which signalling pathway ( s ) are responsible for the microbiota-dependent induction of the A . coluzzii peritrophic matrix , though it is noteworthy that a number of regulated genes have canonical STAT binding sites in their upstream regions ( S4 Table ) , indicating a potential role for the JAK/STAT pathway . Importantly , we observed significant microbiota-dependent regulation of the FoxO signalling pathway , which has recently been shown to facilitate bacteria-dependent synthesis of AMPs in Drosophila enterocytes [47] and may therefore also be considered a candidate pathway for peritrophic matrix induction . Disruption of peritrophic matrix synthesis resulted in elevated load of the Enterobacteriaceae family of bacteria . Given that we observed bacteria co-locating with the peritrophic matrix , it is likely that the peritrophic matrix has antibacterial properties , whether by direct interaction or by sequestration within a hostile niche . Indeed , there is evidence that peritrophins from other organisms are able to interact directly with bacteria and have antibacterial functions [48 , 49] , while a properly structured peritrophic matrix can also be a scaffold maintaining AMPs and other immune factors in the gut [38 , 50] . Interestingly , we found that AMP expression in the midgut correlated with the load of the Enterobacteriaceae and the Acetobacteraceae families , but not with the Flavobacteriaceae . This could suggest that the Flavobacteriaceae occupy niches within the gut that are not surveyed by the immune system , whilst the Enterobacteriaceae and Acetobacteraceae live more proximally to the epithelium , likely within or upon the peritrophic matrix . It remains unclear why the load of the Enterobacteriaceae but not the Acetobacteraceae is limited by the presence of the peritrophic matrix after blood feeding . This observation is , however , consistent with a previous study that found Asaia , a major constituent of the Acetobacteraceae family in our mosquito colony , to be resistant to the mosquito immune response [51] . Intriguingly , we observed bacteria present throughout the ectoperitrophic space , including proximally to the epithelium . This could suggest that the bacteria that are directly associated with the peritrophic matrix are efficiently excreted with the blood bolus , whilst those located in the ectoperitrophic space remain in the gut , seeding the bacterial population in the next gonotrophic cycle . In addition to local effects in the gut , we observe the induction of a systemic immune response upon disruption of the peritrophic matrix and show that this is associated with the break down in the integrity of the gut barrier and translocation of bacteria of the Enterobacteriaceae family into the body cavity . In humans , bacterial translocation is thought to be a common occurrence in healthy individuals and can present as a complication in the critically ill [52] . It is understood to be a consequence of bacterial overgrowth [53] , disruption of the mucosal barrier [54] and impaired immune defense [55] . In Drosophila , it has recently been demonstrated that the enteric nervous system controls peritrophic matrix permeability , and that when permeability is compromised flies succumb to bacterial dissemination throughout the body following oral bacterial infection [56] . In concurrence with this , our data suggest that the peritrophic matrix is a key barrier to prevent or limit translocation of microbiota-derived Enterobacteriaceae into the mosquito body cavity . In our A . coluzzii colony , abundant genera of the Enterobacteriaceae family include Cedecea , Enterobacter , Ewingella and Serratia [36] . Species of Enterobacter have been demonstrated to invade epithelial cells [57] and Serratia marcescens is a model pathogen in Drosophila that , when introduced orally , is able to traverse the gut epithelium [58] . More generally , Enterobacteriaceae have been associated with the induction of colitis , or inflammation of the colon , in mice [59] . Bacterial translocation has not been formally demonstrated in the mosquito , but certain lines of evidence point to this phenomenon . Importantly , a GFP-tagged Asaia strain is known to be able to colonize both the reproductive organs and salivary glands when fed to adults in a blood or sugar meal [60] . Furthermore , knock down of immune effectors can result in bacterial proliferation in the hemolymph even in the absence of infection , though in both of these cases the cuticle was damaged by RNAi injection , providing a possible route of entry for exogenous bacteria [61 , 62] . Taken with the results presented here , these data suggest that at least some native constituents of the mosquito gut microbiota are able to disseminate throughout the body , and that the peritrophic matrix plays a key role in limiting this dissemination .
The A . coluzzii Ngousso colony was used in all experiments described here . Eggs were hatched in 0 . 1% salt water and larvae fed Tetramin or Nishikoi fish food . All adults were allowed ad libitum access to 5% w/v fructose solution and females were maintained on human blood . The insectary was maintained at 27°C ( ±1°C ) , 70–80% humidity with a 12h light/dark cycle . Human blood for mosquito feeding was acquired from the NHS blood service . During feeding , blood was maintained at 37°C on a membrane-feeding device or in a parafilm-covered Petri dish warmed with a handwarmer . Mosquitoes were allowed to feed for 1h and non-engorged mosquitoes were removed within 24h . Mosquitoes were offered egg dishes for oviposition the night before each subsequent blood meal . Antibiotics ( 60U/ml penicillin , 60μg/ml streptomycin and 50μg/ml gentamicin ) or an equal volume of water were supplemented in the sugar solution offered from emergence , in the blood meal and in the egg dish provided for oviposition . For polyoxin D feeding , 0 . 01M stock solution was prepared from powder in water and added to human blood at a final concentration of 100μM immediately before feeding . An equal volume of water was added to the control blood meal . Double stranded RNA ( dsRNA ) was used for transient in vivo knock down of target genes by RNAi . The target region was amplified from total A . gambiae cDNA using primers flanked with the T7 RNA polymerase promoter sequence ( sequences are listed in S5 Table ) . dsRNA was synthesised from the PCR product by overnight incubation at 37°C with T7 polymerase and dNTPs from the MEGAscript RNAi kit , according to the manufacturer’s instructions . dsRNA was purified using the Qiagen RNeasy kit , adjusted to a concentration of 6000 ng/μl , and stored in aliquots at -20°C . 69 nl of 6000 ng/μl dsRNA ( totalling 414 ng ) was injected into the thorax of CO2- anaesthetised 0–2 day old female mosquitoes using the Nanoject II ( Drummond Scientific ) . dsRNA against a region of the lac operon ( LACZ ) , not present in the A . gambiae genome , was injected as a control for the injection process . Prior to dissection mosquitoes were ‘surface sterilized’ by immersion in 75% ethanol for 3–5 min and washed three times in phosphate buffered saline ( PBS ) to minimize environmental contamination from cuticle bacteria into dissected midgut samples . Midguts were removed under a dissecting microscope , frozen immediately on dry ice in pools of 20 ( for RNA sequencing ) , 3–5 ( for excretion experiment and APER1 experiments ) or 8–10 ( for all other experiments ) , and stored at -20°C until processing . For carcass dissections , the abdominal carcass and attached fat body tissue was dissected , ensuring that all other organs ( ovaries , gut , malpighian tubules ) were removed . Carcasses were frozen immediately on dry ice in pools of 3–5 ( for APER1 experiments ) or 8–10 ( for polyoxin D experiments ) then stored at -20°C until processing . Frozen tissues were homogenized in TRIzol ( Invitrogen ) and chloroform using a Precellys24 tissue homogenizer with bead beating ( Bertin ) . RNA was precipitated from the aqueous phase with isopropanol , washed twice in 70% ethanol and resuspended in water . For RNA sequencing experiments , samples underwent a further column purification using the Qiagen RNeasy kit . For qRT-PCR experiments , cDNA was synthesized from up to 500 ng RNA using the Takara reverse transcriptase kit , according to the manufacturer’s instructions . Libraries for sequencing were prepared in accordance with the Illumina TruSeq RNA sample preparation v2 guide ( Part # 15026495 , rev . D , September 2012 ) for Illumina Paired-End Indexed Sequencing . PolyA mRNA first underwent two rounds of purification using Illumina poly-T oligo-attached magnetic beads . During the second elution , the polyA mRNA was fragmented and primed with random hexamers for cDNA synthesis . After first strand cDNA synthesis , the RNA template was removed and a replacement strand was synthesized to generate double stranded cDNA . Ends were then repaired , dA base added and Illumina indexing adapters ligated . cDNA fragments with adapters on both ends underwent 15 cycles of PCR . Libraries were validated with the Agilent 2100 bioanalyzer to check size distribution . Samples were quantified by qRT-PCR , the concentrations normalized and samples pooled according to biological replicate . Pools were loaded at 10 pM onto four lanes of an Illumina flowcell v3 and sequenced using the Illumina HiSeq 1500 , 2 X 100 bp paired-end run . Sequences are deposited in the NCBI Sequence Read Archive under the BioProject ID PRJNA385903 . Quality control , filtering and alignment were conducted in the Galaxy platform [63–65] . Groomed FASTQ files underwent adapter clipping ( ILLUMINACLIP with Truseq3 adapter sequences ) and were then trimmed by sliding window , averaging a minimum Phred quality score of 20 over 4 bases ( Trimmomatic tool version 0 . 32 . 1 ) . Only reads with both mate pairs being longer than 20 bp were processed further . These were aligned by Bowtie2 ( version 0 . 4 ) to a custom built index to filter out non-mRNA reads , composed of all sequences annotated as A . gambiae in the SILVA rRNA database ( release 119 ) [66] , plus all sequences annotated as A . gambiae tRNAs and mitochondrial rRNAs in the AgamP4 . 2 geneset in Vectorbase . The splice aware aligner Tophat2 v2 . 0 . 9 was used to align paired-end reads to the A . gambiae PEST genome AgamP4 . The mean inner distance between mate pairs was set to -25 with a standard deviation of 60 . Default settings were used for alignment with the following exceptions: the maximum number of mismatches allowed between a read and the reference sequence was 5 to allow for the highly polymorphic nature of the A . gambiae genome , and the minimum intron length was set to 30 bp . The accepted hits were filtered such that only reads that were uniquely mapped were accepted for downstream analysis . Aligned reads were converted to gene count data using HTSeq , specifying the union mode [67] . The input gtf file was AgamP4 . 2 after removal of all features annotated as rRNA . Differential expression analysis was conducted with the DESeq2 package [68] , using HTSeq count tables as input files . For each gene , the DESeq2 package fits a generalized linear model ( GLM ) with a negative binomial distribution . For pairwise comparisons at each time point the input parameters were “replicate” and “treatment” ( i . e . , plus/minus antibiotics ) , and “treatment” was removed in the reduced model . DESeq2 applies the Wald test to assess statistical significance followed by the Benjamini-Hochberg adjustment for multiple testing . Genes with adjusted p-values <0 . 1 were considered significantly differentially expressed . Variance stabilizing transformation of count data was performed in DESeq2 prior to clustering . A median-transformed value of the four replicates was calculated for each condition and soft clustering performed in Mfuzz [69] . Soft clustering does not require a priori gene filtering , is noise robust and allows genes to be placed in more than one cluster , making it ideal for time-course data . The fuzzifier m was chosen with the mestimate function , and the optimal number of 12 clusters was selected based on when the minimum distance between cluster centroids ( Dmin ) declines at a reduced rate . KEGG and GO term enrichment analysis for differentially expressed genes were performed in g:Profiler [70] . Genes were ordered by their fold change for input to the software and a Bonferroni adjustment was made for multiple testing . qRT-PCR was used to quantify A . gambiae mRNA levels , as well as bacterial load by amplification of the 16S rRNA gene , employing primers that anneal to a region of the sequence that is common to all eubacteria or specific to bacterial families examined . Primer sequences are listed in S5 Table . In each case , the A . coluzzii ribosomal protein encoding gene S7 ( AGAP010592 ) was used as an internal control of the quantity of input RNA . Expression ratios were calculated using primer efficiencies that were determined by amplification of serially diluted targets . qRT-PCR amplifications were performed in duplicate using the SYBR premix ex Taq kit ( Takara ) in a total volume of 10μl on a 7500 Fast Real Time PCR machine ( Applied Biosystems ) . For hematoxylin and eosin ( H&E ) staining , whole mosquito abdomens were dissected 24h post blood feeding , fixed overnight at 4°C in Duboscq’s-Brasil fixative ( 0 . 4% w/v picric acid , 53% ethanol , 27% formalin , 7% glacial acetic acid ) and washed in 70% ethanol . Abdomens were then processed to paraffin wax and sections cut to 4μm onto Superfrost Plus slides ( VWR ) . For Gram staining , immunostaining and calcofluor white staining , whole mosquito abdomens were dissected 24h post blood feeding , fixed overnight at 4°C in 4% formalin , washed in Aedes saline ( 150mM sodium chloride , 1 . 4mM calcium chloride , 2mM potassium chloride , 1 . 2mM sodium hydrogen carbonate , pH 7 . 2 ) , and embedded and sectioned as described . For Gram staining , sections were dewaxed and stained according to the Gram/Twort protocol . Slides were observed under a Leica DMR microscope . For immunostaining , sections were stained with E . coli polyclonal antibody at 1:400 ( bs-2351R Bioss Antibodies ) and a goat anti-rabbit antibody bound to Alexa 647 ( Thermofisher A21245 ) was used as secondary ( 1:1000 ) . Slides were mounted in Prolong Gold antipode ( Invitrogen ) and observed under a Zeiss Widefield Axio Observer Microscope . For calcofluor white staining , sections were dewaxed and rinsed in distilled water before being stained for 2h in calcofluor white solution in the dark ( Sigma 18909 ) . Sections were observed under a Zeiss Widefield Axio Observer Microscope . qRT-PCR data ( including gene expression and 16S analyses ) were analyzed by generalized linear mixed models ( GLMMs ) in R ( version 3 . 1 . 2 ) . GLMMs fit both fixed-effect parameters and random effects in a linear predictor via maximum likelihood . Mixed effect models were used to account for the use of multiple sample pools per condition within each independent replicate , avoiding issues of pseudoreplication . Statistical significance was assessed by an ANOVA test on a linear mixed effect regression model ( lmer , in the lme4 package ) . Correlation was analyzed by a Spearman rank-order correlation test .
|
When a female mosquito takes a blood meal from a human , the bacteria residing within its gut grow significantly . Following a blood meal , female mosquitoes produce a barrier within their gut , known as the peritrophic matrix , which physically separates the blood meal from the cells of the epithelium . Here , we show that the presence of bacteria in the gut is required for the synthesis of the peritrophic matrix . By experimentally disrupting this barrier , we find that this structure plays a role in limiting the extent to which bacteria of one particular family are able to grow and persist in the mosquito gut . We also find that the peritrophic matrix ensures that bacteria remain within the gut , preventing them from invading the mosquito body cavity . These results will be useful in designing disease control strategies that depend on the ability of bacteria to colonize and persist in relevant tissues in the mosquito host .
|
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2017
|
Microbiota-induced peritrophic matrix regulates midgut homeostasis and prevents systemic infection of malaria vector mosquitoes
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The pathogenic yeast Cryptococcus neoformans causes cryptococcosis , a life-threatening fungal disease . C . neoformans has multiple virulence mechanisms that are non-host specific , induce damage and interfere with immune clearance . Microarray analysis of C . neoformans strains serially passaged in mice associated a small gene ( CNAG_02591 ) with virulence . This gene , hereafter identified as HVA1 ( hypervirulence-associated protein 1 ) , encodes a protein that has homologs of unknown function in plant and animal fungi , consistent with a conserved mechanism . Expression of HVA1 was negatively correlated with virulence and was reduced in vitro and in vivo in both mouse- and Galleria-passaged strains of C . neoformans . Phenotypic analysis in hva1Δ and hva1Δ+HVA1 strains revealed no significant differences in established virulence factors . Mice infected intravenously with the hva1Δ strain had higher fungal burden in the spleen and brain , but lower fungal burden in the lungs , and died faster than mice infected with H99W or the hva1Δ+HVA1 strain . Metabolomics analysis demonstrated a general increase in all amino acids measured in the disrupted strain and a block in the TCA cycle at isocitrate dehydrogenase , possibly due to alterations in the nicotinamide cofactor pool . Macrophage fungal burden experiments recapitulated the mouse hypervirulent phenotype of the hva1Δ strain only in the presence of exogenous NADPH . The crystal structure of the Hva1 protein was solved , and a comparison of structurally similar proteins correlated with the metabolomics data and potential interactions with NADPH . We report a new gene that modulates virulence through a mechanism associated with changes in fungal metabolism .
Cryptococcus neoformans is an encapsulated yeast that causes fungal meningitis in immunocompromised patients and is the primary cause of secondary infections among AIDS patients . A number of virulence factors have been identified in C . neoformans that contribute to its pathogenesis , such as the capsule [1] , secreted enzymes such as urease [2] , phospholipase [3 , 4] and laccase [5–7] , as well as the pigment melanin . In addition , a few studies have recently shown a correlation between virulence and reduction-oxidation reactions in the cell [8 , 9] , suggesting that virulence of a microbe may also result from alterations in redox homeostasis . However , many parts of the host-pathogen interaction remain undefined . Thus , identification of novel virulence factors can provide insight into the mechanisms used by C . neoformans to infect and survive within their hosts . Additionally , understanding how virulence factors contribute to pathogenesis may lead to new therapeutics to treat disease . There is increasing evidence that proteins/enzymes involved in metabolism ( glycolysis , the tricarboxylic acid cycle , the glyoxylate cycle and various biosynthesis pathways ) are also involved in virulence and pathogenesis of microorganisms . For instance , in C . neoformans , the glycolysis enzyme phosphoglucose isomerase was found to be involved in production of the virulence factors melanin and capsule as well as cell wall integrity and resistance to osmotic stress [10] , the isocitrate lyase gene in the glyoxylate shunt pathway was upregulated in a rabbit meningitis model [11] , the acetyl-CoA synthetase gene involved in acetate metabolism was required for virulence in a mouse model [12] and enzymes in both gluconeogenesis and glycolysis were required for virulence in both a mouse and rabbit model [13] . In human urinary tract infections , enzymes in both glycolysis and the pentose phosphate shunt pathways were found to be required for in vivo growth of the bacterium Proteus mirabilis , while gluconeogenesis was required for in vivo growth of Escherichia coli [14] . In Paracoccidioides species infections , many enzymes in glycolysis , tricarboxylic acid cycle and the glyoxylate cycle aid in adhesion to the host extracellular matrix [15] . In Talaromyces marneffei , the glyoxylate cycle enzyme isocitrate lyase is required for pathogenesis in macrophages and mutants of this enzyme are attenuated for virulence in nude mice [16] . In the malaria parasite Plasmodium falciparum , the TCA cycle enzyme aconitase is required for full development of the parasite while parasites deficient in the TCA cycle enzyme α-ketoglutarate-dehydrogenase failed to develop oocysts in mosquitoes [17] . Thus , these examples illustrate a number of microorganisms where modulation of metabolism is associated with pathogenesis and virulence . To better understand how C . neoformans evolves virulence , a relatively low virulence strain of C . neoformans ( H99W ) was serially passaged in different strains of susceptible B10 MHC-congenic mice [18] . The resulting passaged strains showed various levels of increased virulence as measured by decreased time to death in mice . Microarray analysis between the pre-passage strain ( H99W ) and two post-passaged strains ( b/b and q/q ) identified an unknown gene ( CNAG_02591 , HVA1 ) whose expression was confirmed with real-time PCR and was correlated with virulence . Characterization of the hva1Δ strain using metabolomics analysis , three-dimensional structural analysis of the Hva1 protein and macrophage fungal burden experiments in the presence of NADPH suggest this protein may interact with NADPH . The overall aim of these experiments was to determine how HVA1 affected virulence in C . neoformans . Thus , HVA1 seems to have an influence in the virulence of C . neoformans through NADPH and modulation of fungal metabolism .
Microarray analysis comparing two C . neoformans strains obtained after multiple passages through the livers of mice with the pre-passaged H99W strain identified a gene , CNAG_02591 ( HVA1 ) , that was similarly down-regulated in both passaged strains compared to H99W ( Table 1 ) . Real time qRT-PCR confirmed that the HVA1 gene was also down-regulated in Galleria-passaged strains ( Table 1 ) relative to the pre-passage H99W strain . Expression of HVA1 was down-regulated in vivo for all passaged strains tested in the mouse liver , lungs and brains after intraperitoneal infection relative to the pre-passage strain H99W ( S1A–S1C Fig ) . In addition , HVA1 gene expression levels in the liver were correlated with virulence ( as measured by time to death in mice , p<0 . 021 , Fig 1 ) . In contrast , gene expression of HVA1 in the lungs and brain after infection for all passaged strains was not correlated with virulence ( as measured by linear regression , S2A and S2B Fig ) . The HVA1 gene was disrupted using the nourseothricin antibiotic gene ( hva1Δ ) and reconstituted using neomycin as the antibiotic marker ( hva1Δ+HVA1 ) . Southern blot analysis confirmed the gene was integrated by homologous recombination ( S3 Fig ) and Western blot analysis confirmed Hva1 protein expression in the hva1Δ+HVA1 strain ( S4 Fig ) . Microarray analysis comparing the hva1Δ and hva1Δ+HVA1 strains revealed that only three genes showed expression changes between the two strains: CNAG_02591 ( HVA1 ) , CNAG_00474 ( CNA04560 , hypothetical protein ) and CNAG_05544 ( CNH01920 , expressed protein ) ( Table 2 ) . BLAST analysis of the two other genes showing expression changes revealed that both CNAG_00474 and CNAG_05544 have 90% and 80% homology to hypothetical proteins in both C . neoformans var . neoformans ( serotype D ) and C . gattii , respectively . CNAG_00474 also contains a domain that suggests it could be a membrane protein and may be involved in energy production . Extensive phenotypic analysis of the hva1Δ and hva1Δ+HVA1 strains revealed no differences in virulence factor expression . There was no difference in capsule size , capsular structure , melanin production , glucuronoxylomannan ( GXM ) release , phospholipase or urease production , doubling time , growth in conditions of stress , capsule structure or survival in J774 . 16 mouse macrophages between the hva1Δ and hva1Δ+HVA1 strains ( S1 Table ) . To determine if HVA1 was involved in virulence , the hva1Δ and hva1Δ+HVA1 strains were used to infect BALB/c mice and two invertebrate hosts ( C . elegans and G . mellonella ) . Mice infected intravenously with the hva1Δ strain showed increased fungal burden in the spleen ( p = 0 . 001 , Fig 2A ) and brain ( p = 0 . 007 , Fig 2B ) but decreased fungal burden in the lungs ( p = 0 . 0003 , Fig 2C ) compared to mice infected with the hva1Δ+HVA1 strain . Mice infected intravenously with the hva1Δ strain manifested decreased survival ( p<0 . 04 , Fig 2D ) compared to mice infected with the hva1Δ+HVA1 strain . In contrast to the findings in mice , there was no difference in survival between the hva1Δ and hva1Δ+HVA1 strains in C . elegans , G . mellonella or in BALB/c mice infected intratracheally ( S5A–S5C Fig ) . To understand why mice infected with the hva1Δ strain had a decreased fungal burden in the lungs compared to the spleen and the brain , histology was performed . At day 7 post-infection , lungs from mice infected with the hva1Δ strain showed very few C . neoformans but more dense areas compared to lungs from mice infected with the hva1Δ+HVA1 or H99W strains ( Fig 3A–3C ) . At day 14 post-infection , lungs from mice infected with the hva1Δ strain showed lower fungal burden and greater levels of inflammation than lungs from mice infected with the H99W strain ( S6A–S6C Fig ) . To gain insight into the potential function of HVA1 , the structure of the Hva1 protein was solved by X-ray crystallography and refined to highly acceptable accuracy . The three dimensional architecture of each Hva1 monomer was predominantly β-stranded ( Fig 4A ) . There were seven β-strands of varying lengths with five forming interdigitating antiparallel hydrogen bonds to create a semi-cylindrical barrel-like twisted β-sheet . The lengths of β-strands that form the twisted sheet were not uniform with the ones in the center being much longer than those in the edges . In addition , this small protein also contained one unconnected α-helix . The secondary structural motifs , β-strands and α-helix , were interconnected by a complex topology as illustrated in Fig 4B . As observed in most globular proteins , several hydrophobic and aromatic residues formed the core of Hva1 , which is presumably responsible for its twisted architecture . Overall , the monomeric structure of Hva1 resembled a 6-fingered human palm with the α-helix forming the thumb . This crystal structure clearly revealed that Hva1 is highly ordered with secondary structural features forming a stable three-dimensional architecture . The crystal structure further revealed that the protein crystallized in a P1 space group with two Hva1 monomers that are related by a non-crystallographic two-fold symmetry ( Fig 4A ) . The interface is very extensive as the “thumb” helix of the first monomer is inserted firmly into the “fingers” forming the semi-cylindrical barrel of the second monomer . This arrangement is repeated for the second monomer due to the non-crystallographic two-fold symmetry . The monomers are connected by extensive polar and apolar interactions . Currently , there are no experimental data to suggest Hva1 may form a dimer in solution . Although the observed 2-fold association between the two Hva1 monomers may be a crystallographic artifact , the potential for these interacting surfaces to attract ligands and binding partners cannot be completely ruled out . Therefore , this moiety could be a hotspot for being involved in broader protein-protein associations . We analyzed the tertiary structure of Hva1 to search for clues as to its function . Using the online structural homology search utility PDBeFold [19] , five PDB coordinates were identified for further analysis . Although the lengths of the β-strands and loops vary in comparison to Hva1 , these five PDB structures also exhibited strikingly similar topology ( Fig 5B ) . Most parts of the β-strands superposed within 0 . 5 Å but a few exhibited drastic variation in structural disposition . The amino acid sequences of these five PDB structures were aligned with Hva1 based on the structural homology ( Fig 5A ) . This alignment suggested little or no sequence correlation thereby emphasizing the need for further investigation of the structures . Of the six protein structures analyzed for functional homology based on structure considerations , Type II dihydrofolate reductase ( DHFR ) ( PDB: 2RK1 [20] ) , an enzyme which confers resistance to antifolate drugs using NADP as a cofactor manifested the highest superposition with Hva1 . Each of the five β-strands in the sheet superposed well between these two structures while the fifth strand of the twisted β-sheet , β5 , was placed differently in the remaining four PDB structures compared in this study . The region corresponding to the monomer-monomer interface of Hva1 was occupied by a bound nicotinamide adenine dinucleotide phosphate ( NADP ) ligand in DHFR-NADP complex ( Fig 5F ) . Moreover , the same region was also a topological equivalent for a histone binding site observed in the solution structure of Tudor domain 2 ( 38–95 ) of human PHD finger protein 19 ( PHF19 ) ( PDB: 4BD3 [21] ) ( Fig 5D ) . In the Tudor domain containing protein 3 ( TDRD3 ) , the same interface also served as the FAB recognition site ( PDB: 3PNW [22] ) ( Fig 5E ) . The structural architecture of Hva1 also bears a striking similarity with the unbound dimeric form of Tudor 2 of PHF20 ( PDB: 3P8D [23] and PDB: 3QII [24] ) . Given that the Hva1 structural analysis suggested a potential metabolic role we carried out metabolomics analysis for the hva1Δ and H99W strains . The hva1Δ strain showed a block in the production of 2-ketoglutarate compared to H99W and the hva1Δ+HVA1 strain . The hva1Δ strain also had an increase in other upstream metabolites and many amino acids appeared to be elevated ( Fig 6 ) . Given that the structural analysis and the metabolomics analysis suggested a possible interaction of Hva1 and NADP , fungal burden experiments in RAW264 . 7 macrophages were performed with and without the addition of exogenous NADPH . Macrophages infected with the hva1Δ strain showed increased fungal burden only in the presence of NADPH ( p<0 . 0027 , Fig 7 ) , which was consistent with the hypervirulent phenotype observed in mice .
We have identified a novel gene that is associated with changes in virulence , CNAG_02591 ( hypervirulence-associated protein 1 , HVA1 ) , through gene expression microarray analysis that compared two mouse-passaged strains to the pre-passage H99W strain . The HVA1 gene is predicted to contain 3 exons separated by two introns that encode a 75 amino acid protein . HVA1 is located on chromosome 3 of strain H99W and has protein homologs in a variety of plant , animal , and human fungi . No known protein domains or homologous gene families exist for this gene . Expression of HVA1 was down-regulated in the mouse-passaged strains , both in vitro and in vivo in the mouse liver , which was correlated with virulence . Since the mouse-passaged strains were created using intraperitoneal passages of liver homogenate from the previous mouse [18] , they likely adapted to the liver environment . There are high levels of NADPH in the liver , as it is the primary organ where the pentose phosphate pathway occurs . Thus , the passaged strains are likely to be adapted to an environment with high levels of NADPH . If one function of HVA1 is to regulate cellular levels of NADPH , then in situations of high levels of NADPH ( as seen in the liver ) it may be dispensable , consistent with the observed down-regulation in the passaged strains . For the hva1Δ strain the decreased levels of glucose-6-phosphate , an enzyme that catalyzes the first step in the pentose phosphate pathway , is also suggestive of adaption to high levels of NADPH , which occur in liver tissue . In this regard , there is data to support the hypothesis that C . neoformans can undergo organ-dependent selection during the course of infection [25] . HVA1 gene expression was also down-regulated in all of the mouse-passaged strains in vivo in the mouse lungs and brains , suggesting that the absence of HVA1 contributed to the pathogenic effect in these organs . The question of whether HVA1 affected the expression of other genes was investigated by microarray gene expression analysis comparing hva1Δ and hva1Δ+HVA1 strains . The presence and absence of HVA1 impacted the expression of only two genes , arguing against a major role for this gene in the expression of regulatory cascades associated with virulence . BLAST analysis of the protein sequence of these genes identified homologues in C . neoformans var . neoformans and C . gattii . Furthermore , the two genes affected were each annotated as hypothetical genes with an unknown function , though CNAG_00474 does contain a domain thought to be involved in energy production . Thus , though these genes do not clearly elucidate a functional role for HVA1 , this data in combination with a potential interaction with NADPH suggests HVA1 may affect energy production in the cell . The hva1Δ and hva1Δ+HVA1 strains were used to infect three host model systems with different immune responses: C . elegans , G . mellonella and Balb/c mice . While there was no difference in virulence in C . elegans , G . mellonella and mice infected intratracheally , mice infected intravenously with the hva1Δ strain manifested decreased survival compared to mice infected with the hva1Δ+HVA1 strain , a hypervirulent phenotype . Additionally , mice infected with the hva1Δ strain showed increased fungal burden in the spleen and the brain , but decreased fungal burden in the lungs . Histological examination of infected organ tissue revealed that the decreased fungal burden in the lungs was associated with increased inflammation . Since stronger inflammatory responses result in reduced tissue burden [26] the more robust immune response in the lungs compared to the immune response in the liver , spleen and the brain was likely associated with this finding . The down-regulation of gene expression was correlated with a more virulent phenotype in an intravenous mouse model of infection . In fungal pathogens , a more virulent phenotype due to the removal of a gene has been described in fungi such as: Candida glabrata with the down-regulation of the transcription factor Ace2 [27] , Aspergillus fumigatus with the down-regulation of the cell wall organization gene ECM33 [28] , and Cryptococcus neoformans with the down-regulation of the protein kinase A regulatory subunit , Pkr1 [29] , the copper transporter Ctr4 [30] , the glycosyltransferase Cas1 [31] , the transcription factor Rim101 [32] and the ALL1 gene involved in capsule formation [33] . Thus , the more virulent phenotype seen with the disruption of HVA1 is echoed by other examples in the literature . Sequence and structural comparisons revealed the homology between five different enzymes: ferredoxin thioredoxin reductase ( FTR ) , glutamyl-tRNA amidotransferase , human PHD finger protein 20 ( which has histone acetyltransferase activity ) , dihydrofolate reductase , fungal lipase and Hva1 . It is noteworthy that the closest homology matches were enzymes , but it is unlikely that Hva1 shares their functions . For example , FTR is similar in size but Hva1 does not contain any cysteine residues and thus lacks a similar active site . Similarly , it is unlikely that Hva1 has a similar function to glutamyl-tRNA amidotransferase as this enzyme has a unique Ser-Ser-Lys catalytic triad that is used for amide hydrolysis and Hva1 contains only one serine residue . The possibility that Hva1 had any of the activities of the remaining enzymes was tested using the hva1Δ and hva1Δ+HVA1 strains with negative results . The structural comparison suggested that Hva1 has a binding pocket that may bind other proteins . Intriguingly , all of the proteins used in the structural comparison , even though they are small , play a pivotal role in host-defense mechanisms . This analysis indicates that the three dimensional structure assumed by Hva1 contains a conserved recognition site that is optimal for binding a variety of ligands that may include NADP , histone moieties and FABs . Thus , the deletion of Hva1 from the pathogen might potentially impede the immune response thereby increasing virulence . In this regard , it is noteworthy that we observed differences in virulence in mice but not C . elegans or G . melonella , with the latter two lacking adaptive immunity . Given that we found no significant effect for HVA1 on established virulence factors and that the crystallographic analysis of this small protein suggested that it had an enzymatic activity we explored whether HVA1 had an effect on metabolism . The metabolomics analysis in combination with the structural comparison study provided a key piece of insight in that both implied a potential interaction for HVA1 with NADP . The metabolomics data also showed that the hva1Δ strain has increased levels of phosphoenolpyruvate and decreased levels of 2-ketoglutarate , which is suggestive of a block in the TCA cycle and less production of ATP . Thus , one possibility is that HVA1 regulates levels of NADPH as an electron donor in an alternate pathway to produce ATP . When HVA1 is removed , causing levels of NADPH to increase , it would result in increased energy , proliferation and fungal burden . In support of this hypothesis we observed that addition of exogenous NADPH to macrophages infected with the hva1Δ strain , resulted in increased fungal burden , which recapitulated the hypervirulence observed in mice , possibly due to an increased generation of ATP through an alternate pathway . Hence , one possible explanation for the increase in virulence in the absence of HVA1 is that this protein is involved in NADPH regulation , which could affect virulence through effects on metabolism [34] . There is now a rapidly increasing body of literature in bacteria , fungi and protozoa that alterations in metabolism , and specifically in TCA cycle activity , can translate into differences in fitness during infection that manifest themselves as differences in virulence [35–38] . Given these precedents , one can imagine several scenarios by which a blockage in the TCA cycle could result in increases in NADPH that affect oxidative metabolism and the capacity of C . neoformans to survive in mammalian tissues . In this regard , the observation that addition of exogenous NADPH enhanced virulence for the hva1Δ strain but not the hva1Δ+HVA1 strain is consistent and supportive for the notion that this protein is involved in the regulation of metabolism . However , we caution that a metabolism-related effect in virulence could be the result of protean effects that directly affect both fungal cell fitness in vivo and the intensity of the immune response . Additionally , we note that effects in virulence were observed in mice but not moths or worms , which are ectotherms and lack adaptive immunity . The apparent mammalian specificity for the virulence differences may be a result of the fact that this gene was identified from C . neoformans strains passaged in mice . Furthermore , we note that HVA1 expression was reported to be up-regulated four-fold during amoeba infection [39] raising the additional dimension that this gene is also involved in fungal survival after ingestion by environmental phagocytic predators . In summary , microarray and real-time qRT-PCR experiments comparing two mouse-passaged C . neoformans strains with the pre-passage H99W strain identified a novel gene that was associated with increased virulence . Generation of the hva1Δ and hva1Δ+HVA1 strains allowed us to explore the function of this gene and its role in virulence . The absence of HVA1 on C . neoformans phenotypes known to be associated with virulence suggests that it mediates its effects on the host through a new pathogenic mechanism . We note that although extensive work has identified several phenotypes associated with virulence , over half of the virulence composite that contributes to cryptococcal pathogenesis has not been identified [40] . Although further investigation is needed to determine if Hva1 directly or indirectly interacts with NADPH , this study suggests the possibility that HVA1 modulates virulence through an effect on fungal energy metabolism , thereby introducing a new dimension for future research explorations in C . neoformans-host interactions .
C . neoformans pre-passage strain H99W ( serotype A ) , b/b , d/d , f/f , k/k , Balb/c and q/q mouse-passaged C . neoformans strains have been described [18] , hva1Δ and hva1Δ+HVA1 were grown from frozen stock in Yeast Peptone Dextrose ( YPD ) broth for 36–42 h ( mid-log phase ) at 37°C , washed 3X and resuspended in phosphate buffered saline ( PBS ) . The experimental design and the data for both microarrays have been deposited in NCBI’s Gene Expression Omnibus [41] and are accessible through GEO Series accession numbers GSE59582 and GSE59583 . Strains were grown from frozen stock in Yeast Peptone Dextrose ( YPD ) broth for 36–42 h ( mid-log phase ) at 37°C for all RNA preparations . The cells were washed 3X and resuspended in PBS before RNA was extracted ( RNAeasy Kit , Qiagen , Valencia , CA ) and genomic DNA was removed ( Message Clean Kit , GenHunter , Nashville , TN ) . Two different pools of RNA were analyzed at Washington University ( St . Louis , MO ) , using the C . neoformans JEC21 genomic microarray , which was developed by the Cryptococcus Community Microarray Consortium with financial support from individual researchers and the Burroughs Wellcome Fund . The array included 7775 probes in duplicate . In the original microarray analysis , H99W was compared to both b/b and q/q mouse-passaged strains and b/b and q/q were compared to each other . For the second microarray comparison , the hva1Δ strain was compared to the hva1Δ+HVA1 strain . Each comparison was done with two RNA pools and a Cy3-Cy5 dye swap . The gene expression data was averaged across both RNA pools , analyzed ( GeneSpring 7 . 2 , Agilent , Redwood City , CA ) and the data filtered for genes with > 2-fold change and p<0 . 05 . RNA was made from H99W , b/b and q/q strains , as above . cDNA was made from two pools of RNA ( Quantitech Reverse Transcription kit , Qiagen ) and real-time PCR was done using SYBR Green ( Applied Biosystems ) , cDNA and primer . Each cDNA was done in quadruplicate , normalized with actin or GAPDH and the fold change was determined [42] . The fold change for each transcript was calculated relative to the pre-passage H99W strain . Real-time PCR was repeated twice . The HVA1 5’ untranslated region ( UTR ) gene fragment , the drug resistance gene nourseothricin ( NAT ) and the HVA1 3’ UTR gene fragment were cloned into the pUC19 plasmid such that the NAT gene was in the middle of the HVA1 gene [43] . The entire disrupted gene was removed from the plasmid using restriction enzymes . The DNA was directly transformed into the pre-passage H99W strain using the Biolistic Gene Gun [44 , 45] . Transformants were selected on plates containing NAT and streaked out on YPD without selection 4X ( to ensure that the gene disruption had been stably integrated into the genome ) . Transformant DNA was used in PCR and Southern experiments to show that the insertion was the correct size and in the correct position in the genome . For reconstitution of HVA1 a PCR overlap [46] was used to insert the drug resistance gene neomycin at the 5’ end of the HVA1 gene . The DNA was directly transformed into the hva1Δ strain using the Biolistic Gene Gun [44 , 45] . Transformants were selected on plates containing neomycin and streaked out on YPD without selection 4X ( to ensure that the gene disruption had been stably integrated into the genome ) . Transformant DNA was used in PCR and Southern experiments to show that the insertion was the correct size and in the correct position in the genome . Microarray analysis comparing the hva1Δ and the hva1Δ+HVA1 strain showed that only two other genes showed expression changes in addition to HVA1 . Western analysis showed that Hva1 protein expression was absent in the hva1Δ strain and present in the hva1Δ+HVA1 strain . Approximately 10 mg of genomic DNA from each strain was digested with various restriction endonucleases according to the manufacturer’s recommendations . Restriction fragments were separated on a 0 . 8% agarose gel and transferred to a nylon membrane using 20X SSC as transfer buffer . Southern analysis was performed using the DIG Probe Synthesis kit ( Roche ) as per the manufacturer’s instructions . Polyclonal Abs to Hva1 were generated in rabbits ( Genemed Synthesis , Inc . ) . Strains H99W , hva1Δ and hva1Δ+HVA1 were grown at 37°C to mid-log phase , washed and resuspended in PBS plus proteinase inhibitors ( Roche ) . Cells were homogenized in a bead-beater 10X for 30 sec ( set on ice for 1 min between each homogenization step ) . Cell debris were removed by centrifugation and total protein concentration of the lysate was measured using the BCA protein assay kit ( Pierce ) . Equal amounts of total protein from each strain lysate were loaded onto a 10–20% SDS PAGE gel and transferred to a nylon membrane in 1X TBS transfer buffer on ice . The membrane was blocked overnight at 4°C in TBS + 5% milk . The next day , a 1:100 dilution of purified ( IgG only ) Hva1 rabbit serum was added to the TBS + 5% milk and incubated at room temperature for 1 h , shaking . The membrane was washed 3X with 1X TBS and then incubated with 1:20 , 000 dilution of donkey-anti rabbit IgG-HRP for 1 h at room temperature . The membrane was washed 3X with 1X TBS , then incubated with anti-HRP ECL Western blotting substrate ( Pierce ) per the manufacturer’s instructions and exposed to film . For each of the following phenotyping analysis experiments , H99W , hva1Δ and hva1Δ+HVA1 were grown in YPD from frozen stock at 37°C for 2–3 days and then washed 3x with PBS and counted . Capsule structure experiments were carried out as in [51] . Briefly , the cells were grown in minimal media for 7 days at 30°C and then washed three times with milli-Q water . Capsular polysaccharide was isolated using DMSO extraction as in [52] and the molecular mass and structure of the capsular polysaccharide was determined using light scattering . To determine if HVA1 affected survival in an invertebrate host model , 1 × 105 cells in 5 μl were injected into the last left proleg of 15 larvae of Galleria mellonella for each strain . Additionally , 15 larvae were injected with PBS as a control . Larvae were then incubated at 37°C and monitored daily for death or pupation . To determine if HVA1 affected killing of C . elegans ~1 × 109 cells of each strain were plated in a lawn onto nematode growth medium agar and grown overnight at 30°C . The next day , ~25 wild type ( strain N2 ) C . elegans adult worms were placed on each plate ( 5 plates/C . neoformans strain ) and incubated at 25°C . Worms were monitored every 12 h for 6 days for death . All animal use complied with the standards described in the NIH Guide for the Care and Use of Laboratory Animals , The US Animal Welfare Act , PHS Policy on Humane Care and Use of Laboratory Animals and Albert Einstein College of Medicine Institutional Animal Care and Use Committee guidelines . The protocol was approved by the Committee on the Ethics of Animal Experiments of Albert Einstein College of Medicine ( protocol #20100102 ) . Experiments were not randomized or blinded and were done once . For euthanasia , carbon dioxide overdose was used . For in vivo real-time qRT-PCR , six different mouse-passaged strains of C . neoformans were used to infect adult female Balb/C mice ( 2 of each per infection , 6–8 weeks old obtained from NCI ) . The mice were sacrificed on day 6 post-infection and liver , lungs and brain were collected from each mouse . Total RNA was isolated from each organ ( RNAeasy Kit , Qiagen , Valencia , CA ) and used to make cDNA , which was then used as a template for real-time qRT-PCR using primers specific for C . neoformans HVA1 . To determine fungal burden , adult female BALC/c mice ( 6 of each per infection , 6–8 weeks old obtained from NCI ) were infected via intravenous or intratracheal injection with 1 x 106 CFU of H99W , hva1Δ , hva1Δ+HVA1 or PBS . For intravenous infections , 100 μl of each strain was injected directly into the tail vein . For intratracheal infections , mice were injected intraperitoneally with a 2 . 5:1 mix of ketamine:xylazine to anesthetize them ( 5–10 mg/kg ) prior to surgery . For the procedure , mice were placed on their back , their neck area was cleaned with alcohol and a small incision was made over the thyroid . The skin was gently pulled aside and 50 μl of each strain was injected directly into the trachea using a bent tuberculin needle . The incision was closed using VetBond and the mice were kept warm and observed closely until they regained consciousness . Mice were euthanized using carbon dioxide overdose at day 7 post-infection and the spleen , lungs and brain were removed and homogenized . Homogenates were diluted and plated on YPD plates for 2 days at 37°C and colonies were counted to determine fungal burden . To determine survival , mice were infected as above and observed over the course of infection . Any mouse in a moribund state and/or distress was euthanized using carbon dioxide overdose to avoid unnecessary suffering . Adult female BALB/c mice ( 10 of each per infection , 6–8 weeks old obtained from NCI ) were infected via intravenous or intratracheal injection with 1x106 CFU of H99W , hva1Δ , hva1Δ+HVA1 or PBS . Mice were monitored daily for mortality and morbidity and deaths or dates euthanized were recorded . One mouse infected with H99W was not included in the survival data because it cleared the infection and was euthanized at the end of the experiment with the PBS controls ( day 115 post-infection ) . To examine lung histology during infection , adult female BALB/c mice ( 2 of each per infection , 6–8 weeks old obtained from NCI ) were infected via intravenous injection with 1x106 CFU of H99W , hva1Δ , hva1Δ+HVA1 or PBS . Mice were euthanized using carbon dioxide overdose on days 2 , 7 and 14 , the lungs excised and fixed with 10% buffered formalin ( Fisher , Pittsburgh , PA ) for 48–72 h . Samples were sent to the Albert Einstein Histopathology Facility where they were embedded in paraffin . 5-μm-thick sections were stained by H&E and analyzed under a Zeiss AxioScope II microscope ( Carl Zeiss , Thornwood , NY ) by a board-certified veterinary pathologist . H99W , hva1Δ and hva1Δ+HVA1 cells were grown in YPD to log phase ( 36 h ) , centrifuged to collect the cells and the cell pellets stored at -80°C . Cells were shipped to the Metabolomics Core Facility at the University of Utah where cell pellets were extracted using a modified method derived from Canelas et . al [53] . Five ml of boiling 75% ethanol ( aqueous ) was added to each cell pellet followed by vortexing and incubation at 90°C for five min . Cell debris was removed by centrifugation at 5000 x g for three min . The supernatant was removed to new tubes and dried en vacuo . All GC-MS analysis was performed with a Waters GCT Premier mass spectrometer fitted with an Agilent 6890 gas chromatograph and a Gerstel MPS2 autosampler . Dried samples were suspended in 40 μl of a 40 mg/ml O-methoxylamine hydrochloride ( MOX ) in pyridine and incubated for one h at 30°C . To autosampler vials was added 25 μl of this solution . Ten μl of N-methyl-N-trimethylsilyltrifluoracetamide ( MSTFA ) was added automatically via the autosampler and incubated for 60 min at 37°C with shaking . After incubation , 3 μl of a fatty acid methyl ester standard solution was added via the autosampler then 1 μl of the prepared sample was injected to the gas chromatograph inlet in the split mode with the inlet temperature held at 250°C . A 10:1 split ratio was used for analysis . The gas chromatograph had an initial temperature of 95°C for one min followed by a 40°C/min ramp to 110°C and a hold time of 2 min . This was followed by a second 5°C/min ramp to 250°C , a third ramp to 350°C , then a final hold time of 3 min . A 30 m Phenomex ZB5-5 MSi column with a 5 m long guard column was employed for chromatographic separation . Helium was used as the carrier gas at 1 ml/min . Due to the high amounts of several metabolites including valine , leucine , isoleucine , proline , phosphate and inositol the samples were analyzed once more at a 10 fold dilution . Data was collected using MassLynx 4 . 1 software ( Waters ) . For first pass data analysis the targeted approach for known metabolites was used . Metabolites were identified and their peak area was recorded using QuanLynx . This data was transferred to an Excel spread sheet ( Microsoft , Redmond WA ) . Metabolite identity was established using a combination of an in house metabolite library developed using pure purchased standards and the commercially available NIST library . Not all metabolites are observed using GC-MS . The HVA1 gene was cloned into the pGEX-2T plasmid ( GE Healthcare ) in frame with glutathione S-transferase ( at 3’ end ) and transformed into BL21 cells . The transformant was grown overnight at 37°C in LB + ampicillin ( 50 μg/ml ) . The next morning the overnight culture was diluted 1/100 into LB + ampicillin ( 50 μg/ml ) and grown to OD600 = 0 . 5 at 30°C . At that point , protein expression was induced with 0 . 1 mM IPTG and the culture was allowed to grow overnight at 30°C . The next morning , cells were collected and suspended in PBS + 10 mM DTT + proteinase inhibitors ( Complete Mini; Boehringer Mannheim ) . The cells were sonicated and lysed with 1% Triton X-100 at 4°C for at least 45 min . The cell lysate was centrifuged at 12 , 000 × g for 10 min at 4°C and the supernatant collected . Sepharose beads ( GE Healthcare ) were added to the supernatant to bind the Hva1-GST fusion protein and incubated at 4°C for 45 min . The Hva1-GST fusion protein bound to sepharose beads was then washed and eluted as per the manufacturer’s instructions . The Hva1 protein ( 5 mg/ml in milliQ water ) was crystallized at 4°C by the vapor diffusion method by mixing 1 . 0 μl of protein with 1 . 0 μl of precipitant composed of 0 . 2 M CdSO4 , 2 . 0 M ( NH4 ) 2SO4 and equilibrated over a well containing 50 μl of mother liquor . A single crystal was grown from this condition after a month and was harvested with mother liquor supplemented with 10% glycerol and flash-frozen in liquid nitrogen . Data were collected at the beam line X29A , National Synchrotron Light Source , BNL , USA , integrated , and scaled using the program HKL2000 [54] . The crystal diffracted to ~1 . 5 Å and the diffraction was consistant with the space group P1 ( a = 31 . 78 Å , b = 34 . 69 Å; c = 38 . 25 Å; and α = 83 . 93° , β = 72 . 85° , γ = 79 . 46° ) . A total of 260° ( 1 . 0° /frame ) of data were collected . In the absence of a reliable model coupled with reasonable anomalous signal in the data , the structure solution was carried out using the SAD method . Also , it was assumed that the anomalous signal might be coming from ordered cadmium ions present in the crystallization buffer . Structure solution using SHELXC/D/E [55] as incorporated in the program HKL2MAP , resulted in an electron density where most of the residues could be manually traced . Density modified phases were input into the model building program aRP/wARP [56] . This program was able to build almost 90% of the residues . The model was further improved by alternative cycles of manual revision with the model building program COOT [57] and refinement with REFMAC5 [58] . The final model with two molecules in the asymmetric unit ( chains named A and B ) was refined to 1 . 5 Å resolution , with Rwork and Rfree of 13 . 5% and 17 . 7% , respectively . Electron density was continuous starting from 4Met to 77Gln in both molecules . The final model also contained 1193 protein atoms , 156 water molecules , seven sulphate ions , a glycerol and nine partially occupied Cd2+ ions . The atomic coordinates of this structure were submitted to Protein Data Bank ( PDB ID: 4P5N ) and the specific crystallographic data and refinement statistics are shown in S2 Table . The online 3D comparison server , PDBeFold , [19] , was used to identify proteins that share structural similarity with Hva1 . This multiple comparison and 3D alignment program searches for structural identity in the PDB using several criteria . Five proteins that share a three-dimensional homology with Hva1 with low root mean square deviation ( RMSD ) ( 1 . 75–2 . 25 Å ) and high structural overlap ( over 50% ) were chosen for this comparison . Visual structural comparisons were performed using the interactive graphics package PyMol [59] . Gene expression levels in the liver were tested for statistical significance using linear regression analysis . Differences in mouse organ fungal burden and macrophage fungal burden were tested using a multivariate analysis of variance with simple effects . Differences in survival of mice infected with the hva1Δ or hva1Δ+HVA1 strains were tested using the Wilcoxon rank sums test . p<0 . 05 was considered significant . The PDB accession number for the X-ray crystal structure of Hva1 is 4P5N . The GEO accession numbers for the microarrays are GSE59582 and GSE59583 .
|
C . neoformans is a pathogenic yeast that is the causative agent of cryptococcal meningitis . This fungal pathogen causes disease in immune compromised hosts , primarily AIDS patients in developing countries , though it also afflicts organ transplant patients and patients undergoing chemotherapy . There are >600 , 000 deaths per year and >1 million new infections . Unfortunately , treatment options for C . neoformans are limited and cause high kidney and liver toxicity . Thus , understanding specific steps in pathogenesis may help with design of new therapeutics . We have identified a gene ( HVA1 ) whose absence is associated with a hypervirulent phenotype in mice . Metabolomics analysis suggests that when HVA1 is absent there is a block in the citric acid cycle , while structural analysis of the Hva1 protein suggests a potential interaction with NADPH . Fungal burden experiments in macrophages recapitulate the hypervirulent phenotype in mice only in the presence of exogenous NADPH , suggesting that modulation of NADPH affects virulence . This work adds to the growing list of genes involved in pathogen metabolism that also contribute to virulence and pathogenesis , underscoring the need to better understand the mechanisms of how pathogen metabolism affects virulence .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cryptococcus",
"neoformans",
"medicine",
"and",
"health",
"sciences",
"cryptococcus",
"protein",
"metabolism",
"pathology",
"and",
"laboratory",
"medicine",
"fungal",
"genetics",
"pathogens",
"microbiology",
"fungi",
"bioassays",
"and",
"physiological",
"analysis",
"fungal",
"diseases",
"fungal",
"pathogens",
"research",
"and",
"analysis",
"methods",
"infectious",
"diseases",
"mycology",
"medical",
"microbiology",
"gene",
"expression",
"microbial",
"pathogens",
"microarrays",
"biochemistry",
"virulence",
"factors",
"genetics",
"biology",
"and",
"life",
"sciences",
"metabolism",
"organisms"
] |
2016
|
A Small Protein Associated with Fungal Energy Metabolism Affects the Virulence of Cryptococcus neoformans in Mammals
|
Circadian clocks are biological timekeepers that allow living cells to time their activity in anticipation of predictable daily changes in light and other environmental factors . The complexity of the circadian clock in higher plants makes it difficult to understand the role of individual genes or molecular interactions , and mathematical modelling has been useful in guiding clock research in model organisms such as Arabidopsis thaliana . We present a model of the circadian clock in Arabidopsis , based on a large corpus of published time course data . It appears from experimental evidence in the literature that most interactions in the clock are repressive . Hence , we remove all transcriptional activation found in previous models of this system , and instead extend the system by including two new components , the morning-expressed activator RVE8 and the nightly repressor/activator NOX . Our modelling results demonstrate that the clock does not need a large number of activators in order to reproduce the observed gene expression patterns . For example , the sequential expression of the PRR genes does not require the genes to be connected as a series of activators . In the presented model , transcriptional activation is exclusively the task of RVE8 . Predictions of how strongly RVE8 affects its targets are found to agree with earlier interpretations of the experimental data , but generally we find that the many negative feedbacks in the system should discourage intuitive interpretations of mutant phenotypes . The dynamics of the clock are difficult to predict without mathematical modelling , and the clock is better viewed as a tangled web than as a series of loops .
The task of the circadian clock is to synchronize a multitude of biological processes to the daily rhythms of the environment . In plants , the primary rhythmic input is sunlight , which acts through photoreceptive proteins to reset the phase of the clock to local time . The expression levels of the genes at the core of the circadian clock oscillate due to mutual transcriptional and post-translational feedbacks , and the complexity of the feedbacks makes it difficult to predict and understand the response of the system to mutations and other perturbations without the use of mathematical modelling [1] . Early modelling of the system by Locke et al . demonstrated the feasibility of gaining new biological insights into the clock through the use of model predictions [2] . The earliest model described the system as a negative feedback loop between the two homologous MYB-like transcription factors CIRCADIAN CLOCK ASSOCIATED 1 ( CCA1 ) and LATE ELONGATED HYPOCOTYL ( LHY ) [3] , [4] on one hand and TIMING OF CAB EXPRESSION 1 ( TOC1/PRR1 ) [5] on the other . Over the past decade , models have progressed to describing the system in terms of multiple interacting loops , still centred around LHY/CCA1 ( treated as one component ) and TOC1 . The latest published model by Pokhilko et al . ( 2013 ) describes transcriptional and post-translational interactions between more than dozen components . We refer to that model as P2012 [6] , in keeping with the tradition of naming the Arabidopsis clock models after author and submission year ( cf . L2005 [2] , L2006 [7] , P2010 [8] and P2011 [9] ) . The clock depends on several genes in the PSEUDO RESPONSE REGULATOR ( PRR ) family: PRR9 , PRR7 , PRR5 , PRR3 and TOC1/PRR1 are expressed in a clear temporal pattern , with PRR9 mRNA peaking in the morning , PRR7 and PRR5 before and after noon , respectively , and PRR3 and TOC1 near dusk [10] . PRR9 , PRR7 and PRR5 act to repress expression of CCA1 and LHY during the day [11] , but , until recently , TOC1 was thought to be a nightly activator of CCA1 and LHY , acting through some unknown intermediate . However , TOC1 has firmly been shown to be a repressor of both CCA1 and LHY , and it now takes its place in the models as the final repressor of the “PRR wave” [9] , [12]–[14] . PRR3 has yet to be included in the clock models and the roles of the other PRRs are being reevaluated following the realization that TOC1 acts as a repressor [15] . The GIGANTEA ( GI ) protein has long been thought to form part of the clock [16] , whereas EARLY FLOWERING 3 ( ELF3 ) was known to affect clock function [17] but was only more recently found to be inside the clock , rather than upstream of it [18] , [19] . GI and ELF3 interact with each other and with other clock-related proteins such as the E3 ubiquitin-ligase COP1 [20] . GI plays an important role in regulating the level and activity of ZEITLUPE ( ZTL ) [21] , which in turn affects the degradation of TOC1 [22] and PRR5 [23] but not of the other PRRs [24] . The clock models by Pokhilko et al . include GI and ZTL; GI regulates the level of ZTL by sequestering it in a GI-ZTL complex during the day and releasing it at night [8] . Together with EARLY FLOWERING 4 ( ELF4 ) and LUX ARRHYTHMO ( LUX ) , ELF3 is necessary for maintaining rhythmicity in the clock [25]–[27] . The three proteins are localized to the nucleus , and ELF3 is both necessary and sufficient for binding ELF4 and LUX into a complex termed the evening complex ( EC ) [19] . In recent models , EC is a major repressor; it was introduced in P2011 to repress the transcription of PRR9 , LUX , TOC1 , ELF4 and GI [9] . We here present a model ( F2014 ) of the circadian clock in Arabidopsis , extending and revising the earlier models by Pokhilko et al . ( P2010–P2012 ) . To incorporate as much as possible of the available knowledge about the circadian clock into the framework of a mathematical model , we have compiled a large amount of published data to use for model fitting . These curated data are made available for download as described in Methods . The aim of this work is to clarify the role of transcriptional activation in the Arabidopsis circadian clock . Specifically , we use modelling to test whether the available data are compatible with models with and without activation . There is no direct experimental evidence for any of the activators postulated in earlier models , and as a crucial step in remodelling the system we have removed all transcriptional activation from the equations . Instead , we have added a major clock component missing from earlier models: the transcription factor REVEILLE 8 ( RVE8 ) , which positively regulates the expression of a large fraction of the clock genes [28] , [29] . A further addition is the nightly transcription factor NOX/BROTHER OF LUX ARRHYTHMO ( NOX/BOA ) , which is similar to LUX but may also act as an activator of CCA1 [30] . By examining transcriptional activation within the framework of our model , we have clarified the relative contributions of the activators to their different targets .
Overexpression of ELF3 rescues clock function in the otherwise arrythmic elf4-1 mutant [27] . This suggests that the function of ELF4 is to amplify the effects of ELF3 through the ELF3-ELF4 complex , which led us to consider an evening complex ( EC ) where free ELF3 protein can play the role of ELF3-ELF4 , albeit with highly reduced efficacy . This , together with our aim to add the NOX protein in parallel with LUX , as described in the next section , prompted us to rethink how to model this part of the clock . EC is not given its own variable in the differential equations , unlike in the earlier models . Instead , EC activity is seen as rate-limited by LUX and NOX on one hand and by ELF3-ELF4 and free ELF3 on the other . In either pair , the first component is given higher importance , in accordance with previous knowledge . For details , see the equations in Text S1 . This simplified description requires few parameters , which was desirable because the model had to be constrained using time course data for the individual components of EC , mainly at the mRNA level . The effects of our changes to EC are illustrated in Figure 2 , which shows EC and related model components in the transition from cycles of 12 h light , 12 h dark ( LD 12:12 ) to constant light ( LL ) . ELF3 , which is central to EC in our model , behaved quite differently at the mRNA level compared with the P2011 and P2012 models , and more closely resembled the available experimental data , with a broad nightly peak and a trough in the morning at zeitgeber time ( ZT ) 0–4 ( Figure 2A ) . The differences in the dynamics of the EC components between our eight parameter sets demonstrate an interesting and more general point: The components that are most reliably constrained are not always those that were fitted to measured data . In our case , the model was fitted to data for the amount of ELF3 mRNA ( Figure 2A ) and total ELF3 protein ( not shown ) , but the distribution between free ELF3 and ELF3 bound in the ELF3-ELF4 complex was not directly constrained by any data . As expected , the variation between parameter sets was indeed greater for the levels of free ELF3 protein and the ELF3-ELF4 complex , as shown in Figure 2B–C . However , the predicted level of EC ( Figure 2D ) showed less variation than even the experimentally constrained ELF3 mRNA . This indicates that the shape and timing of EC were of such importance that the EC profile was , in effect , tightly constrained by data for the seven EC repression targets ( PRR9 , PRR7 , PRR5 , TOC1 , GI , LUX and ELF4 ) . NOX is a close homologue of LUX , with a highly similar DNA-binding domain and a similar expression pattern which peaks in the evening . Like LUX , NOX can form a complex with ELF3 and ELF4 , but it is only partially redundant with LUX , which has a stronger clock phenotype [31] . The recruitment of ELF3 to the PRR9 promoter is reduced in the lux-4 mutant and abolished in the LUX/NOX double amiRNA line [32] . To explain these findings , we introduced NOX into the model as a component acting in parallel with LUX; we assumed that NOX and LUX play similar roles as transcriptional repressors in the evening complex . There is evidence that NOX binds to the promoter of CCA1 ( and possibly LHY ) in vivo and activates its transcription . Accordingly , the peak level of CCA1 expression is higher when NOX is overexpressed , and the period of the clock is longer [30] . This possible role of NOX as an activator fits badly with its reported redundancy with LUX as a repressor . In an attempt to resolve this issue , we first modelled the system with NOX only acting as a repressor in EC , and then investigated the effects of adding the activation of CCA1 expression . Figure 3 illustrates the role of NOX in the model in comparison with LUX . The differences in their expression profiles ( Figure 3A–B ) reflect the differences in their transcriptional regulation ( cf . Figure 1 ) . CCA1 expression is decreased only marginally in the nox mutant ( Figure 3C–D ) but more so in lux ( Figure 3E ) . Because of the redundancy between NOX and LUX , the model predicted that the double mutant lux;nox has a stronger impact on circadian rhythms , with CCA1 transcription cut at least in half compared with lux ( Figure S2A ) . According to the model , the loss of LUX and NOX renders the evening complex completely ineffective , which in turn allows the PRR genes ( including TOC1 ) to be expressed at high levels and thereby repress LHY and CCA1 . A comparison with the P2011 and P2012 models , which include LUX but not NOX , is shown in Figure 3B , C and E . Here , the most noticeable improvement in our model was the more accurate peak timing after entry into LL , where in the earlier models the clock phase was delayed during the first subjective night [33] . Period lengthening and increased CCA1 expression was observed in NOX-ox only for some of the parameter sets ( Figure 3F ) . The four parameter sets with increased CCA1 all had a very weakly repressing NOX whose main effect was to counter LUX by taking its place in EC . Removing NOX from EC in the equations and reoptimizing a relevant subset of the parameters worsened the fit to the data ( Figure S3 ) . These results support the idea of NOX acting through EC in manner that makes it only partially redundant with LUX . The possibility that NOX is a transcriptional activator of CCA1 and LHY was probed by adding an activating term to the equations ( see Text S1 ) and reoptimizing the parameters that control transcription of CCA1 and LHY . The resulting activation was very weak in all parameter sets , and had negligible effect on the expression of CCA1 in NOX-ox ( Figure S2B–C ) . Accordingly , the addition of the activation term did not improve the fit to data as measured by the cost function described in Methods ( Figure S3 ) . In earlier models that included the PRR genes , the PRRs were described as a series of activators; during the day , PRR9 activated the transcription of PRR7 , which similarly activated PRR5 . These interactions improved the clock's entrainability to different LD cycles [8] . However , this sequential activation disagrees with experimental data for prr knockout mutants , which indicate that loss of function of one PRR leaves the following PRR virtually unaffected . For instance , experiments have shown that the expression levels of PRR5 and TOC1 ( as well as LHY and CCA1 ) are unaffected in both prr9-1 and prr7-3 knockout mutants [11] , [34] . Instead , direct interactions between the PRRs have been found to be negative and directed from the later PRRs in the sequence to the earlier ones [15] , [35] . A strong case has been made for TOC1 as a repressor of the PRR genes [9] , [14] . As in P2012 , we modelled transcription of PRR9 , PRR7 and PRR5 as repressed by TOC1 , but we also included negative auto-regulation of TOC1 , as suggested by the ChIP-seq data that identified the TOC1 target genes [14] . Likewise , PRR5 directly represses expression of PRR9 and PRR7 [35] , and we have added these interactions to the model . As illustrated in Figure 4A–C , this reformulation of the PRR wave is compatible with correct timing of the expression of the PRRs in the wild type , and the timing and shape of the expression curves were improved compared with the P2012 model . An earlier version of our model gave similar profiles despite missing the repression by PRR5 , which suggests that such repression is not of great importance to the clock . A nightly repressor appears to be acting on the PRR7 promoter , as seen in the rhythmic expression of PRR7 in LD in the cca1-11;lhy-21;toc1-21 mutant [36] . An observed increase in PRR7 expression at ZT 0 in the lux-1 mutant relative to wild type [29] points to EC as a possible candidate . Although Helfer et al . report that LUX does not bind to the LUX binding site motif found in the PRR7 promoter [31] , we included EC among the repressors of PRR7 . This interaction was confirmed by Mizuno et al . while this manuscript was in review [37] , demonstrating the power of modelling and of timely publication of models . We further let EC repress PRR5 . We are not aware of any evidence for such a connection , but the parameter fitting consistently assigned a high value to the connection strength , as was also the case with PRR7 . This result hints that nightly repression of PRR5 is of importance , whether it is caused by EC or some related clock component . The real test of the model came with knocking out members of the PRR wave . Here , the model generally outperformed the P2012 model , as judged by eye , but we are missing data for some important experiments such as PRR7 in prr9 . As an example , Figure 4D shows the level of PRR5 protein in the prr9;prr7 double mutant , where half of our parameter sets predict the correct profile and peak phase . In the earlier models , the only remaining inputs to PRR5 were ( a hypothetical delayed LHY/CCA1 ) , TOC1 ( in P2012 only ) and light ( which stabilized the protein ) , and these were unable to shape the PRR5 profile correctly . The crucial difference in our model was the repression of PRR5 by CCA1 and LHY , as described in the next section . CCA1 and LHY appear to work as transcriptional repressors in most contexts in the clock ( see e . g . [38] ) , but knockdown and overexpression experiments seem to suggest that they act as activators of PRR9 and PRR7 [34] . Accordingly , previous models have used activation by LHY/CCA1 , combined with an acute light response , to accomplish the rapid increase observed in PRR9 mRNA in the morning . However , with the misinterpretation of TOC1 regulation of CCA1 [12] in mind , we were reluctant to assume that the activation is a direct effect . To investigate this issue , we modelled the clock with CCA1 and LHY acting as repressors of all four PRRs . If repression was incompatible with the data for any of the PRRs , parameter fitting should reduce the strength of that repression term to near zero . As is shown in Figure 4E , the model consistently made CCA1 and LHY strongly repress PRR5 and TOC1 . PRR7 was also repressed , but in a narrower time window that acted to modulate the phase of its expression peak . In contrast , PRR9 was virtually unaffected; CCA1 and LHY do not directly repress PRR9 in the model . Even though CCA1 and LHY were not modelled as activators , the model reproduced the reduction in PRR9 expression observed in the cca1-11;lhy-21 double mutant ( Figure 4F and Figure S4 ) . PRR7 behaved similarly to PRR9 in both experiments and model . Conversely , in the P2011 and P2012 models , where LHY/CCA1 was supposed to activate PRR9 , there was no reduction in the peak level of PRR9 mRNA in cca1;lhy compared to wild type ( Figure S5A ) . To explore whether CCA1 and LHY may be activating PRR9 transcription , we temporarily added an activation term to the equations ( see Text S1 ) and reoptimized the relevant model parameters . The activation term came to increase PRR9 expression around ZT 2 at least twofold in two of the eight parameter sets , and by a smaller amount in several ( Figure S5B ) . This would seem to suggest that activation improved the fit between data and model . Surprisingly , there was no improvement as measured by the cost function ( Figure S3 ) . With the added activation , PRR9 was reduced only marginally more in cca1;lhy than in the original model ( Figure S5C ) . A likely explanation is that feedbacks through EC and TOC1 , which repress PRR9 , almost completely negate the removed activation of PRR9 in the cca1;lhy mutant . Thus the model neither requires nor rules out activation of PRR9 by CCA1 and LHY . Like CCA1 and LHY , RVE8 is a morning expressed MYB-domain transcription factor . However , unlike CCA1 and LHY , RVE8 functions as an activator of genes with the evening element motif , and its peak activity in the afternoon is strongly delayed in relation to its expression [28] . Based on experimentally identified targets , we introduced RVE8 into our model as an activator of the five evening expressed clock components PRR5 , TOC1 , GI , LUX and ELF4 , as well as the morning expressed PRR9 [29] . PRR5 binds directly to the promoter of RVE8 to repress its transcription [35] , and it is likely that PRR7 and PRR9 share this function [28] , [29] . Using only these three PRRs as repressors of RVE8 was sufficient to capture the expression profile and timing of RVE8 , both in LL and LD ( Figure 5A ) . RVE8 is partially redundant with RVE4 and RVE6 [28] , which led us to model the rve8 mutant as a 60% reduction in the production of RVE8 . To clearly see the effects of RVE8 in the model , we instead compared with the rve4;rve6;rve8 triple mutant , which we modelled as a total knockout of RVE8 function . The phase of the clock was delayed in LD , and the period lengthened by approximately two hours in LL in the simulated triple mutant , in agreement with with data for LHY ( Figure 5B–C ) , though we note that CAB::LUC showed a greater period lengthening in experiments [29] . To investigate the significance of RVE8 as an activator in the model , we made a version of the model without RVE8 . The model parameters were reoptimized against the time course data ( excluding data for RVE8 and from rve mutants ) . As with NOX , we found that removing the activation had no clear effect on the costs of the parameter sets after refitting ( Figure S3 ) . It appears that activators such as RVE8 are not necessary for clock function . Still , the effects of the rve mutants can only be explained when RVE8 is present in the model , motivating its inclusion . The model used RVE8 as an activator for four of its targets in a majority of the parameter sets ( Figure 5D–F ) . The exceptions were TOC1 and ELF4 . Although TOC1 is a binding target of RVE8 in vivo , TOC1 expression is not strongly affected by RVE8-ox or rve8-1 [28] , [39] . This was confirmed by our model , where the parameter fitting disfavoured the activation of TOC1 in most of the parameter sets ( Figure 5E ) . The eight parameter sets may not represent an exhaustive exploration of the parameter space , but the results nevertheless support the notion that the effect of RVE8 on TOC1 is of marginal importance .
Constraining the many parameters in our model requires a cost function based on a large number of experiments . To this end , we compiled time course data from the published literature , mainly by digitizing data points from figures using the free software package g3data [40] . We extracted more than 11000 data points from 800 time courses in 150 different mutants or light conditions , from 59 different papers published between 1998 and 2013 . The median time resolution was 3 hours . The list of time courses and publications can be found in Text S2 , and the raw time course data and parameter values are available for download from http://cbbp . thep . lu . se/activities/clocksim . Most of the compiled data refer to the mRNA level , from measurements using Northern blots or qPCR , but there are also data at the protein level ( 67 time courses ) and measurements of gene expression using luciferase assays ( 12 time courses ) . About one third of the time courses can be considered as replicates , mainly from wild type plants in the most common light conditions . Many of these data are controls for different mutants . Where wild type and mutant data were plotted with the same normalization , we made note of this , as their relative levels provide crucial information that is lost if the curves are individually normalized . To find suitable values for the model parameters , we constructed a minimalistic cost function based on the mean squared error between simulations and time course data . This approach was chosen to allow the model to capture as many features of the gene expression profiles as possible , with a minimum of human input . The cost function consists of two parts , corresponding to the profiles and levels of the time course data , respectively . For each time course with experimental data points the corresponding simulated data were obtained from the model . The simulations were performed with the mutant background represented in the model equations , with entrainment for up to 50 days in light/dark cycles followed by measurements , all in the experimental light conditions . The cost for the concentration profile was computed as ( 1 ) Since the profile levels are thus normalized , eq . ( 1 ) is independent of the units of measurements . The parameters ( see Text S2 for values ) allowed us to weight time courses to reflect their relative importance , e . g . where less data was available to constrain some part of the model . Where several experimental time courses had the same normalization , e . g . in comparisons between wild type and mutants , the model should reproduce the relative changes in expression levels between the time courses . For each group of time courses , we could minimize the sum ( 2 ) Unlike eq . ( 1 ) , the nominators in this sum are guaranteed to be non-zero , which allows us to operate in log-space where fold changes up or down from the mean will be equally penalized . Replacing with and likewise for we write the final scaling cost for group as ( 3 ) This cost term thus penalizes non-uniform scaling between experiment and data within the group . The total cost to minimize was ( 4 ) where sets the balance between fitting the simulation to the profile or the level of the data . We used A downside to our approach is that period and phase differences between different data sets result in fitting to a mean behaviour that is more damped than any individual data set . To reduce this problem , we removed the most obvious outliers from the fitting procedure . We also considered distorting the time axis ( e . g . dynamic time warping ) to normalize the period of oscillations in constant conditions , in order to better capture the effects of mutants relative to the wild type . This process would be cumbersome and arbitrary , which is why it was deemed outside the scope of our efforts . Compared to previous models by Pokhilko et al . , fewer parameters were manually constrained in our model . In the P2010–P2012 models , roughly 40% of the parameters were constrained based on the experimental data [6] , [8] , [9] , and the remaining free parameters were fitted to mRNA profiles in LD and the free running period in LL and DD ( constant dark ) in wild type and mutants [9] . For the F2014 model , we completely constrained 16 parameters in order to obtain correct dynamics for parts of the system where we lacked sufficient time course data . Specifically , the parameters governing COP1 were taken from P2011 where they were introduced , whereas the parameters for the ZTL and GI proteins ( except the GI production and transport rates ) were fitted by hand to the figures in [41] . All other parameters were fitted to the collected time course data through the cost function . The eight parameter sets presented here were selected from a group of 30 , where each was independently seeded from the best of 1000 random points in parameter space , then optimized using parallel tempering for iterations at four different temperatures which were gradually lowered . The resulting parameter values , which are listed in Text S1 , typically span at least an order of magnitude between the different parameter sets ( Figure S6 ) . The sensitivity of the cost function to parameter perturbations is presented in Figure S7 and further discussed in Text S1 . Plots of the single best parameter set against all experimental data is shown in Figure S8 . To simulate the system and evaluate the cost function rapidly enough for parameter optimization to be feasible , we developed a C++ program that implements ODE integration and parameter optimization using the GNU Scientific Library [42] . Evaluating the cost function for a single point in parameter space , against the full set of experiments and data , took about 10 seconds on a 3 GHz Intel Core i7 processor . Our software is released under the GNU General Public License ( GPL ) [43] and is available from http://cbbp . thep . lu . se/activities/clocksim/ .
Accurately modelling the circadian clock as a network of a dozen or more genes is challenging . Previous modelling work ( e . g . P2010–P2012 ) [6] , [8] , [9] has drawn on existing data and knowledge to constrain the models , but as the amount of data increases it becomes ever more difficult to keep track of the effects of mutations and other perturbations . For a system as large as the plant circadian clock , it is desirable to automate the parameter search as much as possible , but encoding the uncertainties surrounding experimental data in a computer-evaluated cost function is not trivial . Our modelling demonstrates the feasibility of fitting a model of an oscillating system against a large set of data without the construction of a complicated cost function based on qualitative aspects of the model output , such as entrainability , free-running period or amplitude . Instead , we relied on the large amount of compiled time course data to constrain the model , using a direct comparison between simulations and data . This minimalistic cost function had the additional advantage of allowing the use of time courses that span a transition in environmental conditions , e . g . from rhythmic to constant light , where the transient behaviour of the system may contain valuable information . Consequently , our model correctly reproduces the phase of the clock after such transitions ( see e . g . Figure 3C ) . Our approach makes it easy to add new data , at the price of ignoring previous knowledge ( e . g . , clock period ) from reporters that are not represented in the model . Accordingly , our primary modelling goal was not to reproduce the correct periods of different clock mutants , but rather to capture the profiles of mRNA and protein curves , and the changes in amplitude and profile between mutants and different light conditions . Compiling a large amount of data from different sources has allowed us to see patterns in expression profiles that were not apparent without independent replication . For example , the TOC1 mRNA profile shows a secondary peak during the night in many data sets ( see examples in Figure 4B ) . All collected time course data were used in fitting the parameters . To validate the model , we instead used independently obtained period data from clock period mutants . The results are shown in Text S1 . In brief , most predictions in LL are in good agreement with experiments , with the exception of elf4 where the period changes in the wrong direction . To experimentally measure a specific parameter value , such as the nuclear translocation rate of a protein , is exceptionally challenging . Hence , constraining a model with measured parameters can introduce large uncertainties in the model predictions , especially when the understanding of the full system is incomplete . Fitting the model with free parameters can instead give a large spread in individual parameter values , but result in a set of models that make well constrained predictions . For this reason , we have based our results on an ensemble of independently optimized parameter sets , as recommended by Gutenkunst et al . [44] . At the cost of computational time , this approach gives a more accurate picture of the uncertainties in the model and its predictions , rather than focusing on individual parameter values . Based on our experience of curation of time course data , we offer some suggestions for how data can be compiled and treated to be more useful to modellers . These points arose in the context of the circadian clock , but they apply to experiments that are to be used for modelling in a broader context . Two of these suggestions concern the preservation of information about the relative expression levels between experiments . One example of the value of such information comes from the dramatic reduction in PRR9 expression in cca1;lhy ( Figure 4F ) . As implied in the section on PRR9 activation in Results , clock models ought to be able to explain both shape and level of expression curves in such mutant experiments , but this is only possible if that information is present in the data . Based on the current knowledge of the clock , most clock components are exclusively or primarily repressive , and RVE8 sets itself apart by functioning mainly ( or solely ) as an activator . According to our model , RVE8 has only a marginal effect on the expression of TOC1 , but activates PRR5 and other genes more strongly , in agreement with earlier interpretations of the experimental data [29] . We note that all six targets of RVE8 in the model ( PRR9 , PRR5 , TOC1 , GI , LUX and ELF4 ) are also binding targets of TOC1 [14] . This may be a coincidence , because TOC1 is a repressor of a majority of the genes in the model . It is conceivable , however , that activation by RVE8 around noon is gated by TOC1 to confer sensitivity to the timing of RVE8 relative to TOC1 in a controlled fashion . We were surprised by the ease with which we could remove RVE8 from the model . After reoptimization of the parameters , the cost was decreased in three of the eight parameter sets compared with the original model ( Figure S3 ) . Thus , the clock is not dependent on activation for its function ( although it should be noted that the model without RVE8 lost the ability to explain any RVE8-related experiments ) . This result indicates that the model possesses a high degree of flexibility , whereby the remaining components and parameters are able to adjust and restore the behaviour of the system . Such flexibility challenges our ability to test hypotheses about individual interactions in the model , but we argue that predictions can also be made based on entropy . Even if an alteration to the model , such as the addition of RVE8 , does not result in a significant change in the cost function , it may open up new parts of the high-dimensional parameter space . If , following local optimization , most parameter sets indicate that a certain interaction is activating , we may conclude that the activation is likely to be true . The parameter space is sampled in accordance with the prior belief that the model should roughly minimize the cost function , and the same reasoning motivates the use an ensemble of parameter sets to explore the model . The conclusion about activation is indeed strengthened by the use of multiple parameter sets , because we learn whether it is valid in different areas of the parameter space . Our model agrees with a majority of the compiled data sets , but like earlier models it also fails to fit to data for some mutants . This indicates that important clock components or interactions may yet be unknown or misinterpreted . We here give a few examples . NOX expression is rhythmic in the short period double mutant cca1;lhy [30] , but our model predicts a constant high NOX level in constant light ( Figure S4F ) . If NOX is repressed by PRR7 as assumed in the model ( see Text S1 ) , the rhythmicity can only be explained if PRR7 is also rhythmic and drives the NOX oscillations . Unfortunately , the model predicts that PRR7 oscillates only for a single cycle in cca1;lhy , before going to a constant low level ( Figure S4B ) . This is a prediction shared with the P2012 model; we are not aware of any data that invalidate the prediction , but given that PRR7 is only slightly reduced in cca1;lhy in light/dark cycles [36] , we believe that PRR7 may be rhythmic in constant light in this mutant . The addition of NOX as a component partly redundant with LUX leads to an untested prediction regarding CCA1 and LHY . Their peak expression levels are reduced only marginally in nox but roughly by half in lux compated with wt . In the lux;nox double mutant , the model predicts that their expression is cut by at least half again , to nearly zero even in light/dark cycles ( see Figure 3 and Figure S2 ) . The modelling suggests that nightly repression of PRR5 and PRR7 is of importance . The evening complex ( EC ) is thought to repress PRR9 and TOC1 , and our prediction that EC also represses PRR7 was experimentally confirmed while this manuscript was in review [37] . Several known clock components were not included in the model , partly due to a lack of suitable data . Examples of genes that could be included in future models are CHE [45] and EBI [46] . More experiments and data are also needed to clarify the differences between CCA1 and LHY , the role of NOX as a part of the evening complex , and how PRR5 affects the localization of TOC1 . Additional non-transcriptional interactions should also be considered in future work . This includes protein interactions such as the regulation of LHY degradation by DET1 [47] , [48] . Most importantly , the recently discovered and highly conserved redox-related circadian oscillator is linked to the transcriptional clock [49] , [50] . Understanding that link may help explain why some clock components more easily remain rhythmic in experiments than in simulations . The insensitivity of PRR9 to LHY/CCA1 in the P2011–P2012 models , as illustrated by its unchanged level in the cca1;lhy mutant ( Figure S5A ) , shows one of the problems of constructing and fitting large models: The transcriptional activation of PRR9 by LHY/CCA1 looks like an important term in the model equations , but the effects of this term are small . To reduce the prevalence of such “dead” terms and parameters in the equations , we recommend examining their effects in isolation , as was done with the corresponding repression terms in Figure 4E . The ability of our model to reduce PRR9 expression in cca1;lhy ( Figure 4F ) can only be explained by indirect effects . CCA1 and LHY repress TOC1 , which in turn represses PRR7 and PRR9 , and the resulting indirect activation may be sufficient to counteract the direct repression by CCA1 and LHY . In general , in a highly interconnected system such as the circadian clock , it is perilous to draw conclusions about whether interactions are activating or repressing based only on altered expression levels in mutants . Previous models ( L2006–P2012 ) described the Arabidopsis circadian clock as primarily divided into two interacting feedback loops , the “morning loop” and the “evening loop” . In contrast , we describe the clock in terms of three main modules linked by transcriptional repression and many additional connections ( Figure 1 ) . Our results and experiences support an important point formulated by Hsu et al . [29]: The plant clock is best viewed as a highly interconnected , complex regulatory network , in which discrete feedback loops are virtually impossible to identify .
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Like most living organisms , plants are dependent on sunlight , and evolution has endowed them with an internal clock by which they can predict sunrise and sunset . The clock consists of many genes that control each other in a complex network , leading to daily oscillations in protein levels . The interactions between genes can be positive or negative , causing target genes to be turned on or off . By constructing mathematical models that incorporate our knowledge of this network , we can interpret experimental data by comparing with results from the models . Any discrepancy between experimental data and model predictions will highlight where we are lacking in understanding . We compiled more than 800 sets of measured data from published articles about the clock in the model organism thale cress ( Arabidopsis thaliana ) . Using these data , we constructed a mathematical model which compares favourably with previous models for simulating the clock . We used our model to investigate the role of positive interactions between genes , whether they are necessary for the function of the clock and if they can be identified in the model .
|
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2014
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Rethinking Transcriptional Activation in the Arabidopsis Circadian Clock
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Levels of certain circulating short-chain dicarboxylacylcarnitine ( SCDA ) , long-chain dicarboxylacylcarnitine ( LCDA ) and medium chain acylcarnitine ( MCA ) metabolites are heritable and predict cardiovascular disease ( CVD ) events . Little is known about the biological pathways that influence levels of most of these metabolites . Here , we analyzed genetics , epigenetics , and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis . Using genomewide association in the CATHGEN cohort ( N = 1490 ) , we observed associations of several metabolites with genetic loci . Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum ( ER ) stress ( USP3 , HERC1 , STIM1 , SEL1L , FBXO25 , SUGT1 ) These findings were validated in a second cohort of CATHGEN subjects ( N = 2022 , combined p = 8 . 4x10-6–2 . 3x10-10 ) . Importantly , variants in these genes independently predicted CVD events . Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated ( BRSK2 and HOOK2 ) . Expression quantitative trait loci ( eQTL ) pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system ( UPS ) arm . Moreover , culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease , induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP . Thus , our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis , and identifies novel genetic loci associated with CVD event risk .
Despite the strong heritability of cardiovascular disease ( CVD ) , its underlying genetic architecture remains incompletely characterized . Genomewide association studies ( GWAS ) have converged on association of CVD with a locus on chromosome 9p21 [1] , but the variants confer modest risk and are of unclear functional significance . One limitation of GWAS studies for complex diseases is the search for association with disease as a binary endpoint , rather than with molecular markers that define risk . An alternative approach is to search for variations in the genome that associate with variation in complex traits . In fact , many diseases can be defined by an underlying quantitative scale , and these “intermediate” traits may have a stronger functional relationship to the causative gene , thereby providing a stronger signal for the disease process . Metabolite levels measured by the emerging tools of metabolomics may be particularly useful for such studies . Indeed , integration of GWAS with metabolomic profiles in population-based cohorts [2] has demonstrated that as much as 12% of variance in metabolite levels is determined by single nucleotide polymorphisms ( SNPs ) . However , most studies of this type performed to date have not used disease-burdened cohorts , so clear linkages between genetic signals , intermediate phenotypes and disease remain to be discovered . Metabolomic profiling has identified novel biomarkers for CVD risk [3–5] . For example , a cluster of heritable [6] short-chain dicarboxylacylcarnitine ( SCDA ) metabolites measured in plasma ( comprised of the mono-carnitine esters of short-chain , alpha- , omega-diacids ) , a cluster of long-chain dicarboxylacylcarnitines ( LCDA ) , and a cluster of medium-chain acylcarnitines ( MCA ) predict CVD events in cardiovascular cohorts [4 , 5] , in patients undergoing coronary artery bypass grafting [3] , and add incremental risk prediction to robust clinical models inclusive of >20 variables [5] . Little is known about the biological pathways represented by these metabolites and how they may predispose to CVD . Thus , we hypothesized that integration of metabolomics with genetics , epigenetics , and transcriptomics could define novel mechanisms of CVD pathogenesis by identifying metabolic quantitative trait loci ( mQTL ) that are CVD risk factors . We performed a GWAS of metabolite levels in a large cardiovascular cohort referred for cardiac catheterization ( CATHGEN , N = 1490 ) and validated our findings in a second cohort ( CATHGEN , N = 2022 ) . A proportion of study subjects ( 44% ) did not have clinically significant atherosclerotic coronary artery disease at time of catheterization; regardless , all individuals were analyzed given that metabolites predict risk of CVD events even in individuals without coronary artery disease , and because these individuals are still at risk for these events . We found that genetic loci that strongly associate with SCDA levels also predict incident CVD events , and are linked to ER stress . Genes differentially methylated in subjects at the extremes of SCDA levels also report on ER stress . Gene expression quantitative trait loci ( eQTL ) pathway analysis identified ER stress as an expression module associated with disease risk , particularly highlighting the ubiquitin proteasome system ( UPS ) arm of ER stress . Thus , this multi-platform “omics” approach identified a molecular pathway ( ER stress and dysregulation of the UPS ) associated with a prevalent complex disease .
Factor 1 , factor 2 and factor 3 scores were used as the quantitative traits in GWAS analysis to identify mQTL . Q-Q plots suggested the presence of SNPs associated with levels of each of the three metabolite factors ( S2 , S3 and S4 Figs ) . Several SNPs were significantly associated with metabolite factor levels at genomewide significance ( p≤10−6 ) in additive models in the discovery cohort ( Fig 1A–1F ) and confirmed ( p≤0 . 05 ) in the validation cohort ( Table 2 ) . Specifically , eight SNPs were associated with factor 1 ( MCA ) levels in any race , but with only two of these SNPs showing more than nominal significance in the validation cohort ( Table 2 ) : rs10987728 ( in cyclin dependent kinase 9 [CDK9] ) and rs6738286 ( intergenic between transition protein 1 [TNP1] and disrupted in renal carcinoma 3 [DIRC3] ) . Twelve SNPs were associated with factor 2 ( LCDA ) levels in any race ( Table 2 ) , with only two of them showing more than nominal significance in the validation cohort ( rs12129555 just downstream from polymeric immunoglobulin receptor [PIGR] and rs17025690 in Usher syndrome 2A [USH2a] ) . Factor 3 ( SCDA ) showed the strongest mQTL with twelve SNPs being associated with SCDA levels in any race ( Table 2 ) , and four of these SNPs showing more than nominal significance in the validation cohort: rs2228513 in HERC1 HECT and RLD domain containing E3 ubiquitin protein ligase family member 1 ( HERC1 ) , rs10450989 in ubiquitin specific protease 3 ( USP3 ) , rs11771619 in round spermatid basic protein 1-like ( RSBN1L ) , and rs1869075 ( intergenic between F-box protein 25 [FBXO25] and glutamate rich 1 [ERICH1] ) . Effect sizes ( β , i . e . per 1 unit change in factor levels ) ranged from to -0 . 38 to 2 . 17 ( factor 1 ) , -0 . 19 to 1 . 16 ( factor 2 ) , and -0 . 43 to 1 . 72 ( factor 3 ) . In meta-analyses combining the race-stratified results , eleven SNPs were associated with factor 1 ( MCA ) levels , with three of these SNPs showing more than nominal association ( Table 3 ) ; one of these ( rs10987728 in CDK9 ) was also identified from race-stratified results and two ( rs16990949 in PDX1 C-terminal inhibiting factor 1 [PCIF1] ) and rs543129 [intergenic between cutaneous T-cell lymphoma-associated antigen 1 ( CTAGE1 ) and retinoblastoma binding protein 8 ( RBBP8 ) ] ) were new mQTL identified in these race meta-analyses . Eight SNPs were associated with factor 2 ( LCDA ) levels ( Table 3 ) ; one gene had been identified in race-stratified analyses ( ZNF521 ) but showed stronger association in the validation cohort in these analyses , and rs352216 near frizzled class receptor 3 ( FZD3 ) was a new mQTL . Factor 3 ( SCDA ) again had the largest number and strongest mQTL with fourteen SNPs associated with SCDA levels , with eight SNPs showing more than nominal significance in the validation cohort ( Table 3 ) . SNPs in USP3 , HERC1 and OLFM4|SUGT1 ( intergenic between olfactomedin 4 and SGT1 , suppressor of G2 allele of SKP1 [S . cerevisiae] ) had already been identified in race-stratified analyses; additional mQTL identified in these race meta-analyses included rs12589750 and rs3853422 ( in or near stonin 2 [STON2] and sel-1 suppressor of lin-12-like ( C . elegans ) [SEL1L] ) , rs930491 and rs11827377 ( both intergenic between ribonucleotide reductase M1 [RRM1] and stromal interaction molecule 1 [STIM1] ) , rs11242866 ( between solute carrier family 22 ( organic cation transporter ) , member 3 [SLC22A23] and PX domain containing 1 [PXDC1] ) , and rs4544127 ( near FRAS1-related extracellular matrix protein 2 [FREM2] and stomatin-like protein 3 [STOML3] ) . Thus , to summarize , the most robust results overall were for mQTL associated with SCDA metabolite levels ( factor 3 ) including an mQTL composed of USP3 ( rs10450989 ) and HERC1 ( rs2228513 ) ; and a locus composed of STON2 ( rs12589750 ) and SEL1L ( rs3853422 ) , with loci meeting genomewide significance in the discovery cohort ( p≤10−6 ) , strong significance in the validation cohort ( p = 2 . 4x10-3–7 . 7x10-7 , except rs3853422 which only showed borderline significance [p = 0 . 01] ) , and stronger association in the meta-analyses ( p = 1 . 6x10-6–7 . 2x10-12 ) . The next strongest overall results for SCDA mQTL ( based on race-stratified or race-combined meta-analysis p-values ) in descending order of significance were for RRM1|STIM1 , OLFM4|SUGT1 , SLC22A23|PXDC1 , RSBN1L , FBXO25|ERICH1 , and FREM2|STOML3 . The next strongest results overall were for mQTL associated with LCDA ( factor 2 ) levels with SNPs in PIGR , ZNF521 , USH2A and FZD3 showing more than nominal significance in the validation cohort . Finally , mQTL associated with MCA ( factor 1 ) levels included CDK9 , DIRC3 , CTAGE1|RBBP8 , and PCIF1 . We have previously shown that all three metabolite factors predict risk of incident CVD events , however the results from those studies were most robust for the SCDA metabolites [5] . Given these prior results , and the strength and consistency of findings for the SCDA metabolite factor in these GWAS analyses , we chose to focus the remainder of our analyses on this factor . Fig 2 and S5 Fig display Locus Zoom plots for these eight mQTL most strongly associated with SCDA metabolite factor levels . Interestingly , the majority of these ( i . e . HERC1 , USP3 , STIM1 , SUGT1 , FBXO25 and SEL1L ) encode proteins reporting on endoplasmic reticulum ( ER ) stress . SCDA mQTL were tested for association with incident CVD events using Cox proportional hazards time-to-event analyses in the combined discovery and validation datasets , using meta-analysis of race- and dataset-stratified results , unadjusted for multiple comparisons . Of these eight mQTL ( 15 SNPs ) loci , four SNPs predicted mortality in additive models: HERC1 rs2228513 ( p = 0 . 05 in race combined , p = 0 . 04 in whites only ) , RRM1 rs11826962 ( p = 0 . 03 ) , and FBOX025 rs1869075 ( p = 2 . 5x10-4 for blacks only , not significant in race combined analyses ) , with USP3 rs10450989 showing a trend for association ( p = 0 . 06 in race combined , p = 0 . 05 in whites only ) . FREM2|STOML3 rs4544127 showed a trend for association ( p = 0 . 06 ) . We observed for the HERC1 SNP a 33% event rate for non-carriers and a 36% event rate for carriers of at least one copy of the minor G allele ( the same allele associated with higher SCDA levels , S3 Table ) . Adjustment for SCDA levels in these models resulted in attenuation of the association between mQTL and CVD event ( S3 Table ) , suggesting that the relationship between these mQTL and CVD events is in part mediated through SCDA metabolite levels . To ensure that the relationships between SNPs and SCDA levels were not confounded by renal disease , we further adjusted for glomerular filtration rate . This adjustment caused no or minimal attenuation of the association for our strongest SNPs ( S3 Table ) . In multivariable models , we found minimal attenuation of the association between most SNPs and SCDA levels ( S3 Table ) , suggesting that these SNPs have effects on SCDA levels unrelated to other comorbidities . There was attenuation of association of SNPs near RRM1|STIM1 and STON2|SEL1L after adjustment ( although still significant at p<0 . 05 , unadjusted for multiple comparisons ) , suggesting that these SNPs have effects on SCDA levels mediated through these clinical factors , in particular renal disease . Visual comparison of the distribution of methylated probes revealed similar distributions in individuals with high and low SCDA levels ( N = 46 , combined methylation discovery and validation datasets , S6 Fig ) . After filtering based on Δβ values , the presence of multiple correlated probes in a gene , and adjustment for estimated cell type proportions , sex , age and race , probes in 28 genes showed differential methylation in SCDA extremes ( i . e . |Δβ|≥0 . 10 in ≥2 probes within a gene ) . Differential methylation in three of these genes was confirmed in the validation set based on |Δβ|≥0 . 10 ( BRSK2 , Hook2 and LMTK3 , Table 4 ) . Two of these genes , including the most significant one , report on ER stress: Hook2 ( four probes , Δβ 0 . 25–0 . 30 ) and BRSK2 ( four probes , Δβ 0 . 11–0 . 20 ) . Hook2 may be involved in pathways contributing to the ubiquitin proteasome system ( UPS ) arm of ER stress via its role in establishment and maintenance of pericentrosomal localization of aggresomes ( complexes of misfolded proteins , chaperones and proteasomes ) [8] . BRSK2 encodes brain selective kinase 2 , a serine/threonine kinase of the AMPK family that acts as a checkpoint kinase in response to DNA damage induced by UV irradiation . BRSK2 protein levels are down-regulated in response to ER stress and ER stress promotes localization of BRSK2 to the ER [9] . Knockdown of endogenous BRSK2 expression enhances ER stress-mediated apoptosis in human pancreatic carcinoma and HeLa cells [9] . Blood RNA microarray data were generated for N = 1204 CATHGEN individuals . We began by examining cis effects for the identified SNPs; however , many of the top SNPs did not have available cis-transcripts after extensive QC . Rs9591507 , rs17573278 , rs894840 , and rs9285184 ( all in OLFM4|SUGT1 ) , rs11771619 ( RSBN1L ) , rs1869075 ( FBXO25 ) , and rs1886848 ( SULF2 ) showed evidence of cis-regulation ( S4 Table ) . HERC1 and USP3 are not well-represented on the microarray ( one probe per gene ) ; there was only a minimal trend toward association between the HERC1 and USP3 SNPs with HERC1 expression ( p = 0 . 16 and 0 . 19 , respectively ) and no association with the USP3 transcript . We then performed eQTL analyses to find evidence of trans-acting pathways ( S4 Table ) . When analyzed as single transcripts , among the top ten transcripts associated with HERC1 rs2228513 and USP3 rs10450989 were USP39 ( p = 0 . 0002 and p = 0 . 0004 , respectively ) and CYLD ( p = 0 . 00015 and p = 0 . 0007 ) , suggesting that these SNPs show functional relationships with expression of trans-acting pathways related to the UPS arm of ER stress . USP39 has a role in pre-mRNA splicing and is essential for recruitment of the U4/U6 . U5 tri-snRNP to the prespliceosome . The tumor suppressor CYLD is a deubiquitinating enzyme , acts as a negative regulator of NF-kappa-B signaling , and plays a pro-inflammatory role in vascular smooth muscle cells [10] . Cis- and trans-eQTL analyses were not adjusted for multiple comparisons , as we were looking for focused functional effects for each SNP . Using GSEA [11] , we then identified KEGG pathways of transcripts associated with each SNP; nominal p-values are reported . The most significant pathway associated with HERC1 rs2228513 was “ubiquitin mediated proteolysis” ( p = 0 . 01; p = 0 . 12 for USP3 rs10450989 ) . The most significant pathway for rs10450989 was “RNA degradation” ( p = 0 . 03 ) . Pathways associating with the other SNPs reported on various cellular processes: rs930491 and rs11827377 ( RRM1|STIM1 ) with RNA polymerase pathway ( both p = 0 . 001 ) ; rs11826962 ( RRM1|STIM1 ) with JAK-STAT signaling pathway ( p<0 . 0002 ) ; rs17573278 ( OLFM4|SUGT1 ) with Alzheimer’s disease pathway ( p = 0 . 008 ) ; rs894840 ( OLFM4|SUGT1 ) with glycosaminoglycan biosynthesis ( p<0 . 0002 ) ; rs12589750 and rs3853422 ( STON2|SEL1L ) with ribosome pathway ( p<0 . 0001 and p = 0 . 001 , respectively ) and FC Gamma R mediated phagocytosis pathway ( p = 0 . 001 for both ) . The Alzheimer’s disease pathway includes components of ER stress and there is evidence that neuronal death in Alzheimer’s disease may arise from ER dysfunction . The ER is also thought to play an important structural role in phagocytosis . Finally , we performed GSEA for the correlation between SCDA levels with genomewide RNA expression; nominal p-values are reported . The most significant KEGG pathways were oxidative phosphorylation ( p<0 . 0002 ) , Parkinson’s disease ( p<0 . 0002 ) , cardiac muscle contraction ( p<0 . 0002 ) , porphyrin and chlorophyll metabolism ( p = 0 . 002 ) , and the proteasome pathway ( p = 0 . 008 ) . The proteasome is an integral component of the UPS arm of ER stress , degrading cellular proteins that are modified by ubiquitin . Also , an integral part of the Parkinson’s disease pathway includes components of the UPS . In this and prior studies [4–6] , SCDA were measured using a flow-injection-MS/MS method that is ideal for rapid profiling of samples , but full resolution of isomeric species comprising each SCDA metabolite peak is not achieved . C6-DC represents a SCDA that loads heavily on the PCA-derived SCDA factor in our studies , which can be comprised of either the branched-chain methylglutaryl acylcarnitine or the straight chain adipoyl acylcarnitine isomers . To resolve these metabolites , we adapted a liquid chromatography ( LC ) -MS/MS method [12] . Peak identification was facilitated by in-house chemical synthesis of internal standards for the two targeted analytes [13] . Using this method , we re-analyzed 29 human plasma samples from our original studies [5] that contained the highest C6-DC levels . We found that in the majority of individuals ( 19 of 29 ) , the clearly predominant C6-DC isomer was the branched-chain 3-methylglutaryl carnitine metabolite , and in in 23 of the 29 individuals levels of the branched chain isomer were higher than the straight chain isomer ( S7 Fig ) . The correlation between the C6-DC measured by flow injection-MS/MS with each of these LC-MS/MS measured isomers further confirms that it is primarily the branched-chain isomer accounting for the signal ( r2 = -0 . 06 , p = 0 . 8 for straight chain isomer; r2 = 0 . 67 , p = 1 . 8x10-4 for branched-chain isomer ) . Interestingly , one potential source of the branched-chain 3-methylglutaryl carnitine metabolite is the branched-chain amino acid leucine . Our previous studies have shown an association of branched-chain amino acid metabolites with coronary artery disease [4 , 7] . The above findings linking ER stress to SCDA metabolites led us to question whether nutrient-induced accumulation of dicarboxylacylcarnitines would be accompanied by ER stress in cultured cells . Exposure of human HEK293 kidney cells to 500 uM fatty acids for 24 hours ( a condition designed to mimic elevated fatty acid levels observed in human obesity ) increased cellular production and efflux of several long , medium and short-chain dicarboxylacylcarnitines ( Fig 3A and 3B ) . Interestingly , fatty acid-induced production of dicarboxylacylcarnitines was accompanied by elevated expression of the molecular chaperone protein BiP ( Fig 3C ) , a well-recognized marker of ER stress . At low doses of the ER stress agent tunicamycin ( lower than required to cause cytotoxicity ) , fatty acid exposure also augmented BiP expression ( Fig 3C ) . Together , these results point to an intriguing connection between cellular carbon load , dicarboxylic acylcarnitines and proteotoxicity .
We have analyzed metabolomics , genetics , epigenetics and transcriptomics together to establish genomewide associations between a cluster of SCDA metabolites that predict CVD events and specific genetic loci . Our findings implicate the UPS arm of ER stress as a factor influencing SCDA levels and CVD event pathogenesis . Several previous studies have successfully mapped metabolites to genetic loci [2] , but primarily have not triangulated such genetic variation with disease endpoints and functional studies . Key findings of the current study include: ( 1 ) SNPs and CpG probes in genes reporting on components of ER stress were associated with levels of SCDA metabolites previously shown to predict CVD events [3–5]; ( 2 ) several of these SNPs themselves also predicted CVD events; ( 3 ) some of the SNPs/genes were linked with SCDA metabolites and ER stress through eQTL analyses; ( 4 ) the isomeric composition of the peak containing the major SCDA metabolite C6-DC was clarified; and ( 5 ) in cultured cells , nutrient-induced accumulation of SCDA metabolites occurred in parallel with increases in the ER stress marker BiP . Subjects in the CATHGEN cohort have a high prevalence of obesity , hyperlipidemia and diabetes ( Table 1 ) . Thus , our in vitro experiment may be viewed as a mimetic of the metabolic environment to which CATHGEN subjects are commonly exposed . Our strongest finding was for two SNPs ( HERC1 rs2228513 and USP3 rs10450989 ) that are in LD ( r2 = 0 . 99 ) despite being separated by 104 kB . Rs2228513 is a missense variant ( serine to phenylalanine ) that is predicted to be “probably damaging” by PolyPhen , but no functional evaluation has been reported . Rs10450989 is an intronic SNP . The HERC gene family encodes a group of large proteins that contain multiple structural domains including a C-terminal HECT domain found in a number of E3 ubiquitin protein ligases . HERC1 is involved in membrane trafficking and may also act as an E3 ubiquitin-protein ligase , a protein that accepts ubiquitin from an E2 ubiquitin-conjugating enzyme and then directly transfers the ubiquitin to targeted substrates . Rs2228513 corresponds to residue 3152 , which does not map to a specific domain in the protein . Our eQTL results suggest that this SNP is associated with differential expression of genes within a pathway reporting on the UPS . USP3 encodes ubiquitin-specific protease 3 which mediates release of ubiquitin from degraded proteins by disassembly of the polyubiquitin chains in the ER . Deubiquitination has been implicated in cell cycle regulation , proteasome-dependent protein degradation , and DNA repair [14] . Interestingly , an intergenic SNP 58 kB upstream from USP3 ( rs10519210 ) was the strongest SNP associated with heart failure in a GWAS from the CHARGE consortium [15] . Rs10519210 not associated with SCDA levels in our study ( p = 0 . 16 ) and is not in LD with rs10450989 ( r2 = 0 . 002 ) . Our next strongest finding was for a locus in/near STON2 and SEL1L . Rs12589750 is an intronic SNP within STON2 and rs3853422 is intergenic between STON2 and SEL1L . SEL1L plays a role in the ER-associated protein degradation ( ERAD ) machinery , and is part of a complex necessary for the retrotranslocation of misfolded proteins from the ER lumen to the cytosol where they are then degraded by the proteasome in a ubiquitin-dependent manner . Dysfunctional protein degradation causes ER stress . Other mQTL included SNPs near RRM1 and STIM1; STIM1 encodes a calcium sensor in the ER that translocates to the plasma membrane upon calcium store depletion to activate calcium release-activated calcium channels . STIM1 induction , redistribution and clustering are important during ER stress when calcium stores are depleted [16] . FBXO25 is one of 68 human F-box proteins that serve as specificity factors for a complex composed of s-phase-kinase associated protein 1 ( Skp1 ) and cullin1 ( SCF ) , that act as protein-ubiquitin ligases , targeting proteins for destruction across the UPS . FBXO25 is cardiac specific and acts as a ubiquitin E3 ligase for cardiac transcription factors [17] . Rs17573278 and rs9591507 are intergenic SNPs >400 kB downstream from OLFM4 and SUGT1 . SUGT1 is required cell cycle transitions and encodes a novel subunit of the SCF ubiquitin ligase complex [18] . OLFM4 encodes an anti-apoptotic protein that promotes tumor growth . The functions of the other SCDA mQTL loci are unclear . Given the strength of association of SCDA metabolites ( factor 3 ) with CVD and their particular strength of association in the current GWAS analyses , we chose to focus our subsequent analyses on SCDA . However , we did also identify mQTL for LCDA and MCA , both of which have also been shown to predict CVD events . LCDA are metabolic intermediates of long chain fatty acid oxidation in the mitochondria or peroxisomes . The most significant mQTL for LCDA metabolite levels included PIGR , USH2a , ZNF521 and FZD3 . PIGR is a member of the immunoglobulin superfamily and ZNF521 is involved in regulation of early B-cell factor , suggesting a potential relationship between LCDA levels and immune and/or inflammatory pathways as a link to CVD . MCA are byproducts of mitochondrial fatty acid oxidation . The most significant mQTL for MCA show no obvious potential biologic relationship to mitochondrial function and/or CVD . More epidemiologic and functional work is necessary to clarify these links . Importantly , and unique to this study , we have observed an association of mQTL and disease phenotypes . The SNPs most significantly associated with SCDA levels ( HERC1 and USP3 ) were also associated with CVD events , with a consistent direction of effect ( G allele associating with higher SCDA levels and events ) . STIM1|SEL1L SNPS were not associated with CVD events despite their strong association with SCDA levels; this may be due to limited power related to the low MAF in racial subsets . Adjustment for SCDA levels in these models resulted in attenuation of the association between SNP and CVD event suggesting that the relationship between underlying mQTL and CVD events is in part or in full mediated through SCDA metabolites and not through a different biological pathway . In combination , these results suggest potential functional and pathway relationships between SCDA metabolites and CVD events . We also integrated transcriptomics and whole genome methylation with SNP and metabolomic data sets . eQTL identified ER stress pathways , and specifically those reporting on the ubiquitin proteasome pathway , as associated with the SNPs linked to SCDA via GWAS , and with SCDA metabolites themselves . Whole genome methylation identified epigenetic regulation of genes in ER stress pathways to be associated with extreme SCDA levels . These results support the concept that these polymorphisms and ER stress underlie the relation between SCDA metabolites and CVD events . Finally , we clarified the biochemical structure of the metabolite most strongly accounting for the C6-DC SCDA peak; these results will enable more accurate identification of the source pathways for C6-DC and other SCDA in future studies . Many SCDAs result from the catabolism of amino acids , ω-oxidation of fatty acids or perhaps represent products of microbial metabolism [19] , but the reasons for their accumulation in plasma in at-risk subjects , and how they may be related to CVD pathogenesis remain uncertain . Based on the convergence of GWAS , transcriptomic , metabolomic and functional data presented herein , we hypothesize that genetic and epigenetic variation predisposes to increased susceptibility to ER stress through proteasome dysfunction ( reflected by the observation of upregulation of expression of ER stress genes ) , with ER stress in turn contributing to increased production of SCDA metabolites . This pathway of increased ER stress then leads to increased risk of CVD events , with SCDA metabolites and the genetic variants themselves predicting increased risk by reporting on this pathway ( Fig 4 ) . Epigenetic variation could be the influence of environmental or lifestyle factors inducing methylation changes; in this working model , diet and lifestyle-induced dyslipidemia and hyperglycemia could result in methylation changes as a regulatory mechanism to handle nutrient overload , thus predisposing to dysregulated ER stress which then leads to subsequent CVD events . The UPS arm of the ER is responsible for the removal of misfolded proteins but is sometimes insufficient , for example , in the setting of increased production of misfolded proteins . The associated proteasome functional insufficiency can lead to cellular dysfunction and cell death , with cardiomyocytes being particularly vulnerable due to limited regenerative capability [20] . The UPS has been hypothesized to be involved in atherosclerosis based on the recognized roles of inflammation , oxidative stress , and endothelial dysfunction in this condition , and the intertwined relationships between the UPS and those pathways [21] . Preclinical evidence of the role of the UPS in atherosclerosis includes studies showing that oxidized LDL inhibits proteasomal activity in macrophages leading to apoptosis [22] , and data suggesting that the UPS may contribute to foam cell formation by suppression of apoptosis of lipid-bearing macrophages by aggregated LDL in in vitro models [23] . Studies of proteasome inhibition have shown conflicting data; Hermann et al . found aggravation of atherosclerosis [24] and myocardial dysfunction [25] in pigs treated with proteasome inhibition , whereas a recent study showed reversal of uremia-induced atherosclerosis with proteasome inhibition in rabbits [26] . Human studies suggesting the role of the UPS in atherosclerosis are limited . Very small studies have shown greater amounts of ubiquitin conjugates in carotid endarterectomy tissues with unstable as compared with stable plaque morphologies [27] and increased UPS activity in carotid tissue from patients with symptomatic compared with asymptomatic carotid disease [28] . While preclinical studies have suggested the role of UPS in atherosclerosis as secondary to oxidative stress or other pathophysiologies , our identification of genetic variants in UPS/ER stress genes using unbiased analyses in our human cohorts provides strong support for the direct etiologic role of the UPS in promoting long-term cardiovascular risk . Importantly , we note that while ER stress is a common pathway in several disorders , we believe that the convergence of results on the UPS highlights its unique relationship to SCDA metabolism . Our findings could have significant translational implications beyond CVD . Our primary objective of discovery of novel genetic risk variants using an mQTL approach was successful; the unexpected finding of genetic variation predisposing to ER stress could have much broader importance to human disease . Indeed , the response to ER stress is a trait that is known to be heritable in humans [29] , but the genetic architecture has not been characterized . Equally as important , our data suggest the presence of easily quantifiable circulating biomarkers of ER stress , traditionally measureable only in tissue through ER stress-responsive gene expression studies . Thus , these results could have more wide-reaching implications for ER stress research in humans . Our prior work solidified the role of SCDA metabolites as predictors of CVD events [4 , 5]; the current study has implications for clinical translation using SCDA metabolites for improved risk stratification even beyond CVD given the central role of normal and dysfunctional ER stress in health and disease . The strengths of this study are the use of a priori defined discovery and validation cohorts; integration of genetics , epigenetics , metabolomics , transcriptomics in large cohorts; and careful biochemical refinement of the most strongly associated SCDA metabolite . Importantly , this represents one of the first studies to successfully identify genetic variants through mapping of intermediate metabolomic traits that themselves associate with disease endpoints . Our prior work had consistently identified SCDA metabolites as incremental predictors of CVD events , but little was known about the biological pathways underlying that association; the genomewide , multiple platform molecular approach taken in our study facilitated identification of the UPS more rapidly than other scientific methods . This work also adds an important finding to the metabolomics literature , namely that SCDA metabolites may be reporting on increased or dysregulated ER stress and specifically to proteasome functional insufficiency or dysregulation . There are limitations to the study; the study population was comprised of individuals referred due to a suspicion of CVD and thus represents a disease-prone population . However , we note that 44% of study participants did not have significant coronary artery disease , highlighting the importance of the detailed angiographic phenotype to ensure that coronary artery disease is not confounding the relationship between genetic factors and outcome . Further , the high burden of CVD risk factors mirrors that of the general population , enabling generalizability of the study findings . Some of the results were isolated to a racial subset because the identified SNPs were either monomorphic or extremely rare in other races , underscoring the potential importance of including non-Caucasian races in such studies . Race-stratified sequencing of these genomic regions may identify different variants in these genes present in other races that may also serve as SCDA and CVD genetic variants . We a priori chose a p-value ≤10−6 as genomewide significant based on the commonly used threshold at the time we embarked on this study , and as a balance between the overly conservative Bonferroni correction and presence of linkage disequilibrium across the genome . More contemporary GWAS platforms cover a greater number of SNPs and include imputed SNPs in analysis , thus p<10−8 is now often considered genomewide significant; most of the key SNPs in this study would meet that threshold in combined meta-analyses , but not in the discovery cohort alone . The significance level also did not account for testing of two genetic models and for race-stratified analyses , however , most of the identified mQTLs would remain significant even after accounting for such multiple testing ( p<3 . 0x10-7 ) . More importantly , the use of a validation cohort and convergence of diverse omic’ data on the UPS obviate concerns about type I error with the threshold used for this study . Finally , while our study overall analyzed metabolomics with genetics , epigenetics and transcriptomics , not all individuals were profiled with all platforms , such that we co-analyzed genetic , epigenetic and transcriptomic data with metabolomics data one pair at a time . The ultimate goal for an eventual true systems biology approach would integrate all molecular platforms to unravel molecular pathways . However , to our knowledge this is the largest study deploying four diverse platforms in conjunction with cardiovascular event outcomes to date , and our consistent findings across platforms support further mechanistic interrogation of the identified pathway . Our results highlight the power of combined molecular analyses and mapping of intermediate disease-related biomarkers for identifying the genetic architecture underlying common complex diseases , and could lead to improved CVD event risk prediction models as well as further mechanistic investigations of the role of the ubiquitin proteasome system in CVD .
The overall objective of this study was to integrate metabolomic , genetic ( genomewide association study [GWAS] ) , transcriptomics and epigenetic data in a large human cohort to identify the genetic architecture regulating metabolite levels ( metabolites shown to be incrementally predictive of CVD events [4 , 5] ) and thereby identify novel CVD risk genes . The analytic process was as follows ( S1 Fig ) : ( 1 ) a GWAS was conducted of metabolite factor levels in a discovery cohort ( N = 1490 ) individuals from the CATHGEN biorepository; ( 2 ) SNPs meeting genomewide significance from the discovery cohort were validated in a second cohort ( N = 2022 ) CATHGEN subjects; ( 3 ) to identify potential epigenetic variation regulating SCDA metabolite levels ( factor 3 ) , analyses of whole genome methylation profiling of CATHGEN individuals with extremes of SCDA metabolite levels was performed ( N = 46 ) ; ( 4 ) to elucidate potential downstream biological pathways , these validated GWAS SNPs were then tested for association using genomewide transcriptomic data ( i . e . , eQTL , N = 1204 CATHGEN individuals ) ; similar analyses were conducted using SCDA metabolite levels and transcriptomic data . These analyses identified the UPS arm of ER stress and functional in vitro studies of that pathway were then conducted . Individuals were selected from the CATHGEN biorepository of patients referred for evaluation of ischemic heart disease recruited sequentially through the cardiac catheterization laboratories at Duke University ( Durham , NC ) [30] . After informed consent , blood was obtained from the femoral artery , immediately processed to separate plasma , and frozen at -80°C . Individuals were fasting for a minimum of six hours prior to collection . Patients with severe pulmonary hypertension or transplant were excluded . The discovery cohort for mQTL GWAS analysis of metabolite levels consisted of a coronary artery disease ( CAD ) case-control sample; CAD cases were defined as having one to three coronary arteries with clinically significant stenosis ( i . e . >50% ) . Controls were defined as not having clinically significant CAD ( i . e . zero coronary arteries with >50% stenosis ) and being free of cardiovascular disease , peripheral vascular disease and with a normal ejection fraction ( LVEF>40% ) , and were matched to cases on age , race and sex ( 745 cases and 745 matched controls ) . This CAD definition was also used as a covariable in multivariable models assessing the association between mQTL and metabolite levels . To ensure generalizability of the mQTL results , the validation cohort for the metabolite GWAS consisted of a sequential cohort of 2022 CATHGEN individuals [30] , and was not constrained on CAD or other status . Significant mQTL were tested for association with incident CVD events ( death at any time during follow-up ) . All CATHGEN participants provided informed , written consent for participation in the CATHGEN biorepository at the time of enrollment . The Duke Institutional Review Board ( IRB ) approved the CATHGEN biorepository and this substudy . The Illumina Human Omni1-Quad Infinium Bead Chip ( Illumina , San Diego , CA , USA ) was used for genotyping in both the discovery and validation cohorts following the manufacturer’s protocol using 200 nanograms of DNA . Quantification of DNA samples prior to genotyping was performed using the Quant-iT PicoGreen dsDNA reagent in a 96-well plate format ( Life Technologies , Grand Island , NY , USA ) . DNA quality was assessed using gel electrophoresis . All samples were scored on a zero to five scale and samples with a score <3 were not further used . Briefly , the samples were denatured and amplified overnight , followed by fragmentation , precipitation and resuspension . DNA was then hybridized to the Illumina BeadChip for 16–24 hours , washed to remove unhybridized DNA , and then labeled with nucleotides to extend the primers to the DNA sample . After the genotyping protocol , BeadChips were imaged using the Illumina iScan system . Genotypes were called using Illumina’s GenomeStudio V2010 . 2 software ( version 1 . 7 . 4 Genotyping module ) . Any SNPs with <98% call frequency , minor allele frequency ( MAF ) <0 . 01 in all races , or out of Hardy-Weinberg equilibrium ( p<10−6 ) were excluded , resulting in the following number of autosomal SNPs for analysis: 785 , 945 in whites; 881 , 891 in blacks; and 871 , 209 in the “other” race ( primarily Native American ) . Samples with <98% call rates for all SNPs , gender mismatches , cryptic relatedness , or with outlying ethnicity ( as determined by multidimensional scaling plots of a linkage disequilibrium-pruned set of SNPs ) were excluded ( 172 samples ) . Quantitative determination of levels of 63 metabolites ( 45 acylcarnitines , 15 amino acids , total ketones , β-hydroxybutyrate , and total non-esterified fatty acids [NEFA] ) was performed in N = 3512 individuals from the CATHGEN study ( N = 1490 for discovery cohort , N = 2022 for validation cohort ) , using methods as we have done previously [4–6] . Ketones ( total and β-hydroxybutyrate ) and NEFA were measured on a Beckman-Coulter DxC600 clinical chemistry analyzer , using reagents from Wako ( Richmond , VA ) . For MS-profiled metabolites ( acylcarnitines , amino acids ) , proteins were first removed by precipitation with methanol . Aliquoted supernatants were dried , and then esterified with hot , acidic methanol ( acylcarnitines ) or n-butanol ( amino acids ) . Analysis was done using tandem flow injection MS with a Quattro Micro instrument ( Waters Corporation , Milford , MA ) . Quantification of the “targeted” intermediary metabolites was facilitated by addition of mixtures of known quantities of stable-isotope internal standards . Given the use of internal standards permitting absolute quantification of the metabolites in micromolar concentrations , values below the lower limits of quantification ( LOQ ) were reported and analyzed as “0” . Metabolites with >25% of values below LOQ were not analyzed ( two acylcarnitines: C6 and C7-DC ) . RNA purification processing was done utilizing Qiagen PAXgene Blood RNA MDx Kits in frozen whole blood PAXgene tubes . Strict adherence to the PAXgene Blood RNA MDx Kit Handbook , Second Edition , July 2005 protocol was maintained throughout the purification process . The purification process failed on 384 samples ( four batches of ninety-six samples each ) during processing for unidentified reasons and the samples were not repeated . Biotinylated total RNA was generated using the Illumina TotalPrep RNA amplification kit ( Life Technologies , Grand Island , NY , USA ) ; 200 nanograms of RNA was used for the kit . The quality of the RNA was determined using the Bioanalyzer RNA Nano chip assay ( Agilent , Santa Clara , CA , USA ) . Quantification of the RNA was determined using the Quant-iT RiboGreen RNA Assay Kit . Samples with RIN scores less than 6 . 0 were not carried forward . The Human HT-12v3 Expression BeadChip ( Illumina , San Diego , CA ) was used for quantitative RNA profiling and scanned on the Illumina iScan system according to manufacturer’s protocol . Biotinylated RNA ( 750 nanograms ) was hybridized to the BeadChip and washed; Cy3-SA was then introduced to the hybridized samples and the BeadChips scanned on the Illumina iScan system according to manufacturer’s protocol . Quality control ( QC ) and background subtraction was performed using Illumina GenomeStudio tools . Probes with a detection p-value <0 . 05 and detected in >50% of samples were retained for analysis . Expression values were log2 transformed and quantile normalized using Robust Multichip Average ( RMA ) methods . Results were visually inspected for outliers and sample failures after plotting for variance components comprising eight distinct and standard QC variables at the plate , chip and individual level . A total of 12 , 800 probes passed the detection and QC filters and 1204 samples passed the QC and outlier filters . Principal components analysis ( PCA ) with varimax rotation was used for data reduction of metabolomic data from the combined cohorts ( S1 Table and S2 Table ) using SAS v9 . 1 ( Cary , NC ) . Factor 1 ( composed of a cluster of medium-chain acylcarnitines [MCA] ) , factor 2 ( composed of a cluster of long-chain dicarboxylacylcarnitines [LCDA] ) , and factor 3 ( composed of a cluster of short-chain dicarboxylacylcarnitine [SCDA] metabolites [similar to our previous studies [4 , 5]] ) , were used as the quantitative traits for GWAS . Eigenstrat was used to define principal components ( PCs ) in GWAS . Four eigenvectors were used as PCs in whites , two in blacks , and seven in the “other” race category . Race-stratified linear regression models for each SNP ( additive and dominant ) , adjusted for age , sex , race-specific PCs and metabolite batch , were constructed using PLINK [31] . Race-stratified results were also combined with meta-analysis using METAL [32] . Genomic inflation factors ( λ ) were <1 . 0 . Significant SNPs were defined as those showing genomewide significance ( p<10−6 ) in the discovery cohort and nominal association ( p<0 . 05 , unadjusted for multiple comparisons ) in the validation cohort . Significant SNPs were then: ( 1 ) analyzed using meta-analysis of the cohorts using METAL [32]; ( 2 ) tested for association with metabolite factor levels after adjustment for glomerular filtration rate and in multivariable models ( adjusted for BMI , hypertension , CAD , diabetes , left ventricular ejection fraction , dyslipidemia , smoking and renal disease ) ; and ( 3 ) tested for association with time-to-death using Cox-proportional hazards modeling in the combined cohorts . Expression quantitative trait loci ( eQTL ) analyses of SNPs and SCDA levels were conducted using linear regression adjusted for age , race , sex and batch . Gene Set Enrichment Analysis ( GSEA ) [11] , using the Preranked tool , was used on the resultant p-values for each SNP or SCDA covariate effect on expression levels to identify enriched KEGG pathways . GWAS analyses were corrected for multiple comparisons based on the above defined genomewide significance; other analyses were not adjusted for multiple comparisons and nominal unadjusted p-values are reported , with a p≤0 . 05 considered statistically significant . For the methylation studies , we analyzed blood samples from a discovery cohort composed of 11 individuals from the combined CATHGEN cohorts who had the highest SCDA factor levels and 12 individuals with the lowest levels; and a validation cohort of 12 individuals with the next highest SCDA factor levels and 11 individuals with the next lowest levels; all 46 individuals were selected from those with RNA expression microarray data also available . DNA was isolated from blood mononuclear cells and sodium bisulfite treated prior to being prepped for analysis on the Illumina HumanMethylation 450K BeadChip following the manufacturer’s guidelines , using the Zymo EZ DNA Methylation Kit using manufacture’s protocol ( Zymo Research Corporation Irvine , California USA ) . The alternative incubation condition recommended if using the Illumina Infinium Methylation Assay was used ( supplied in the manufacturer’s instruction manual appendix ) . Converted DNA was amplified , fragmented and hybridized to the Human Methylation27 , RevB bead chip pool of allele-differentiating oligonucleotides . We removed probes with detection p-value> . 05 in >10% of samples , data based on fewer than three beads , and probes previously identified as cross-reactive with other genomic locations [33] . Samples were checked for gender mismatch using principal components analysis ( PCA ) of probes on chromosome X and assay controls were inspected to ensure good performance on all samples . After QC , the original group of 485K probes was reduced to 473K probes . Color bias correction and background adjustment were performed using lumi [34] , followed by quantile normalization of methylated , unmethylated , type I and type II probes separately using wateRmelon [35] . Finally , we used Beta Mixture Quantile dilation ( BMIQ ) for intra-array normalization [36] . After preprocessing , overall methylation levels ( β ) were calculated as the ratio of methylated to total signal ( i . e . β = M / ( M + U ) ) where M is the methylated signal intensity for a probe , U is the unmethylated signal intensity , and β therefore ranges from 0 ( unmethylated ) to 1 ( methylated ) . Δβ was calculated as the mean methylation difference between the high and low SCDA groups at each probe . To identify candidate regions of interest , we prioritized probes with |Δβ|>0 . 10 in the discovery set ( N = 1287 ) . After removing probes with a common SNP ( MAF> . 01 ) in the CpG or single-base extension site , we filtered to known genes containing at least two probes each with |Δβ|>0 . 10 within a 1 kB region ( n = 97 probes in 28 genes ) . Finally , we restricted our probes with probes with |Δβ|>0 . 10 and the same direction of effect in both datasets ( i . e . hypermethylation in high SCDA samples versus low , three genes ) . Although our primary criteria for follow-up were Δβ values and the presence of multiple correlated probes in a gene , we also tested for differential methylation using linear models and empirical Bayes methods as implemented in limma [37] . Our standard model adjusted for estimates of cell-type proportions present in each sample using the method of Houseman , et al . [38]; we also ran a sensitivity analysis that additionally included age , sex and race . Adipoyl carnitine and 3-methylglutaryl carnitine were synthesized from carnitine chloride and the corresponding cyclic acid anhydride according to the method of Johnson [13] . Products were confirmed by mass spectrometry . The liquid chromatography ( LC ) -MS/MS method of Maeda et al . [12] was extensively modified . Acylcarnitines were derivatized to butyl esters . The analytical platform was converted to a UPLC format using an Acquity UPLC HSS T3 column and the ion pairing reagent was changed to triethyl ammonium acetate . The carnitines were eluted using a linear gradient using water as solvent A and 95/5 v/v acetonitrile/water as solvent B starting at 20% B .
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Cardiovascular disease is a strongly heritable trait . Despite application of the latest genomic technologies , the genetic architecture of disease risk remains poorly defined , and mechanisms underlying this susceptibility are incompletely understood . In this study , we performed genome-wide mapping of heart disease-related metabolites measured in the blood as the genetic traits of interest ( instead of the disease itself ) , in a large cohort of 3512 patients at risk of heart disease from the CATHGEN study . Our goal was to discover new cardiovascular disease genes and thereby mechanisms of disease pathogenesis by understanding the genes that regulate levels of these metabolites . These analyses identified novel genetic variants associated with metabolite levels and with cardiovascular disease itself . Importantly , by utilizing an unbiased systems-based approach integrating genetics , gene expression , epigenetics and metabolomics , we uncovered a novel pathway of heart disease pathogenesis , that of endoplasmic reticulum ( ER ) stress , represented by elevated levels of circulating short-chain dicarboxylacylcarnitine ( SCDA ) metabolites .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis
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In this study we show that incentives ( dog collars and owner wristbands ) are effective at increasing owner participation in mass dog rabies vaccination clinics and we conclude that household questionnaire surveys and the mark-re-sight ( transect survey ) method for estimating post-vaccination coverage are accurate when all dogs , including puppies , are included . Incentives were distributed during central-point rabies vaccination clinics in northern Tanzania to quantify their effect on owner participation . In villages where incentives were handed out participation increased , with an average of 34 more dogs being vaccinated . Through economies of scale , this represents a reduction in the cost-per-dog of $0 . 47 . This represents the price-threshold under which the cost of the incentive used must fall to be economically viable . Additionally , vaccination coverage levels were determined in ten villages through the gold-standard village-wide census technique , as well as through two cheaper and quicker methods ( randomized household questionnaire and the transect survey ) . Cost data were also collected . Both non-gold standard methods were found to be accurate when puppies were included in the calculations , although the transect survey and the household questionnaire survey over- and under-estimated the coverage respectively . Given that additional demographic data can be collected through the household questionnaire survey , and that its estimate of coverage is more conservative , we recommend this method . Despite the use of incentives the average vaccination coverage was below the 70% threshold for eliminating rabies . We discuss the reasons and suggest solutions to improve coverage . Given recent international targets to eliminate rabies , this study provides valuable and timely data to help improve mass dog vaccination programs in Africa and elsewhere .
Canine rabies has been reported as one of the neglected diseases of the developing world [1 , 2] . Caused by Lyssavirus , it is a zoonotic infection of the central nervous system that invariably leads to death . The disease is transmitted through the saliva of the infected carrier with domestic dogs being the principle infectious source and reservoir of the disease [3] . Endemic in Tanzania , studies show that approximately 1 , 500 rabies deaths occur annually [4 , 5] . Many societies develop associations with dogs for different purposes ranging from security , companionship , food acquisition and religious beliefs . Despite these benefits , however , keeping dogs can pose a risk to human health through bite injuries and the transmission of pathogens such as the rabies virus [6] . Although rabies is not considered a human health priority [7] , the demand for post-exposure prophylaxis ( PEP ) in developing countries like Tanzania results in a substantial economic burden due to high costs of vaccination , the direct and indirect costs associated with patient treatment and income loss [8 , 9] . It is estimated that 3 . 9 billion people living in in more than 150 countries are at risk from rabies resulting in between 7 and 15 million people receiving PEP and more than 59 , 000 people dying from rabies each year . Ninety nine percent of these deaths occur in Africa and Asia [9–12] . The annual economic losses associated with rabies have been estimated to be approximately 8 . 9 billion US dollars [13] . Rabies also impacts the health of wild animal species . In the Serengeti , an ecosystem in northern Tanzania that is surrounded by large agro-pastoralist and pastoralist human populations with relatively dense population of dogs ( 9 . 4 dogs/km2 ) , repeated outbreaks in the 1980’s and 1990’s dramatically reduced the number of African wild dogs ( Lycaon pictus ) [14 , 15] . Despite being effective at controlling and or eliminating rabies , vaccination programs targeting domestic dogs are relatively rare in the developing world . Socio-economic factors such as inadequate resources , lack of political commitment , weak inter-sectorial cooperation , limited accessibility to , and the high cost of , modern vaccines , and a general lack of community awareness and cooperation are factors that hamper effective control of rabies in these countries [16–18] . The critical vaccination coverage level of 39% to 57% of the dog population is sufficient to eliminate rabies [19] . However , in areas with high dog population turnover , empirical observations and rabies transmission models suggest 70% of the dog population be vaccinated repeatedly for canine rabies to be eradicated . Indeed , in dog populations with high birth rates and death rates such as in Tanzania , repeat vaccination every few months may be required in order to prevent the herd immunity declining below a critical threshold [4 , 11] . Since 2003 the Serengeti Health Initiative ( SHI ) has carried out annual rabies vaccination campaigns in six districts surrounding the Serengeti National Park , typically employing a central-point strategy whereby villages are requested to bring their dogs to a central point for immunization . To monitor coverage following vaccination the proportion of immunized dogs has been estimated using either: i ) a randomized household questionnaire survey ( HHQ ) , in which the proportion of vaccinated dogs in a sample of village households is calculated; or ii ) a mark-re-sight method ( hitherto referred to as transect survey ) , in which dogs attending the clinic are marked and the proportion of marked dogs estimated by observation during transect surveys on the day following vaccination . These methods are relatively cheap and quick and they have been shown to be feasible in estimating vaccination coverage [3 , 4 , 20] . However , to the author’s knowledge , the accuracy of these methods at quantifying rabies vaccination coverage has never been tested . The vaccination coverage achieved is the critical factor that determines whether the SHI’s campaign to control rabies is successful and it is imperative that the assessment methods used are accurate . The primary objective of this study , therefore , was to measure the accuracy of the two established methods through comparison with a ‘gold-standard’ village-wide census ( VWC ) , whereby every village household was visited and the true vaccination coverage determined . Vaccination coverage is increased if more villagers bring their dogs to the central point clinic on any given day . A secondary objective , therefore , was to quantify the impact that incentives have on dog owner participation in the central point vaccination clinics .
The study was conducted in Bunda and Serengeti ( human population 335 , 060 and 249 , 420 respectively [21] ) Districts of the Mara Region ( 34°-35°E , 1°30´-2°10´S ) in northwestern Tanzania . The districts , which are composed of mixed agro-pastoralist communities , are among the seven districts that SHI has been conducting annual mass dog vaccination campaign since 2003 . Ten central-point vaccination clinics were carried out in ten villages ( n = 5 in Bunda District , n = 5 in Serengeti District ) between June to July and November to December 2013 . Vaccination schedule dates were set in advance and , as per the SHI’s standard operating procedure , on the day before vaccination the SHI team visited the targeted village , announcing with loud speakers and posting posters in prominent places that dogs should be brought to the clinic the following day . On arrival at the clinic each dog was registered , and age , sex and prior vaccination history recorded . Following vaccination all dogs were fitted with a brightly coloured collar and marked on both flanks with a stripe of water-soluble purple spray and a vaccination certificate was given to the owner . Demographic data obtained by the HHQ were also used to calculate the proportion of households that keep dogs , the human to dog ratio , and the number of dogs per household and per dog owning household . These demographic data collected by the VWC and the HHQ were compared to determine the accuracy of the latter as a method of demographic data collection . To evaluate the impact that incentives have on the number of dogs being brought for vaccination ( ‘turnout’ ) , 62 villages were , in 2013 , randomly allocated to four intervention groups: i ) vaccinated dogs received brightly coloured collars ( n = 10 ) , ii ) owners that brought a dog were given a brightly coloured wristband ( n = 8 ) ; iii ) vaccinated dogs received collars and owners were given a wristband ( n = 26 ) , and ( iv ) neither collars nor wristbands were provided ( i . e . owners received only vaccination certificates ) ( n = 18 ) . Scheduling challenges arising from the creation and re-designation of new villages in 2013 precluded a more balanced design . In addition data from the SHI’s 2012 vaccination campaign was made available so that the difference in the number of dogs vaccinated in 2012 and 2013 could be calculated . Thereafter we compared the difference in villages that received an incentive in 2013 ( village groups i–iii ) with the difference in those that received none in both years ( village group iv ) . We also compared turn out in villages that received the different incentive combinations ( village groups i–iii ) . The costs of immunizing a single dog in a particular village can be calculated by the following equation: costperdog=fixedcosts+ ( variablecosts×totalnumberofdogsvaccinated ) totalnumberofdogsvaccinated The fixed costs ( salaries , vehicle costs , per diems etc . ) were the same in villages with and without incentives given out , whilst the variable costs ( syringes , needles , vaccination record cards , plus the cost of the incentive etc . ) varied according to how many dogs turn up and whether an incentive was given out . In villages where incentives were not handed out the variable costs are given by β and in villages where incentives are handed out the variable costs are given by β + γ , where γ is the cost of the incentive . The number of dogs vaccinated is given by n: Costperdog ( incentivevillage ) C1=fixedcosts+ ( β×n ) + ( γ×n ) n1 Costperdog ( incentivevillage ) C1=fixedcostsn1+β+γ Costperdog ( nonincentivevillage ) C2=fixedcosts+ ( β×n ) n2 Costperdog ( nonincentivevillage ) C2=fixedcostsn2+β For the incentive to be cost effective , therefore: C1≤C2 fixedcosts ( C1 ) n1+β+γ≤fixedcosts ( C2 ) n2+β To calculate the break-even point we re-arranged the equation to solve for γ . In doing so the variable costs drop out of the equation leaving only the fixed costs to determine what the break-even point is and whether the incentive was cost effective: γ≤fixedcosts ( C1 ) n1−fixedcosts ( C2 ) n2 To parameterize the equation we used the mean fixed cost per village of US$578 [22] and the mean number of dogs vaccinated per village in 2012 ( n1 ) and the calculated mean when incentives were given out ( n2 ) . The costs ( labour , fuel etc . ) that were incurred while carrying out the VWC , transect survey and household questionnaire were recorded and the average cost per village was calculated . Dog owners attending the vaccination clinic in ten villages were asked to rate how likely it would be that they would bring their dogs to the vaccination clinic if they knew that incentives ( collars or wristbands ) would be given out: very unlikely ( 1 ) , unlikely ( 2 ) , no difference ( 3 ) , likely ( 4 ) and very likely ( 5 ) . In addition , they were asked whether they preferred wristbands or collars . To determine how vaccination coverage at the level of the sub-village is affected by the distance ( km ) villagers need to walk to reach the central-point clinic , data belonging to the SHI was made available for analysis . The dataset , which was collected by the VWC method , contained coverage data at both the village and sub-village level for ten villages that had been targeted in the 2011 campaign . For each sub-village , the distance in kilometers to the central point and the vaccination coverage , calculated using the same survey questionnaire used in the VWC , are given . Data obtained were entered in to spreadsheets using Microsoft Excel 2010 and analyzed using R [23] . An ANOVA of repeated measures , followed by a pairwise t-test with Bonferroni adjusted p-values , was used to compare the vaccination coverage estimates obtained by HHQ , transect survey and VWC . Paired t-tests were used to test the difference in turnout between 2012 and 2103 in villages where incentives were , and were not , given out . Chi-squared and paired t-tests were used to analyse the population characteristic data obtained by the HHQ and VWC . A one-way ANOVA was used to determine the effect that different combinations of incentives had on vaccination turnout . A chi-squared test was used to analyze owner preference for collars and wristbands . A Pearson correlation was used to examine the relationship , at the sub-village level , between distance from the central-point clinic and vaccination coverage . The study was carried out under the supervision of the SHI , which is permitted through the Tanzania Commission for Science and Technology to conduct dog vaccination programs in northern Tanzania ( permit number: 2013-275-ER-2005-141 ) . The study was approved by the ethics and research committee of the Nelson Mandela African Institution of Science and Technology Senate and School of Life Sciences and Engineering ( permit number: NM-AIST/M . 067/T . 12 ) . Prior to the administration of the questionnaires verbal consent was obtained from the head of each household or , if not available , an adult family member .
The vaccination coverage estimates calculated are shown in Table 1 and Fig 1 . When both adult dogs and puppies were included , the coverage estimates ranged from 41–71% ( mean 57 . 4% ) ( VWC ) , 39–63% ( mean 50 . 8% ) ( HHQ ) and 50–83% ( mean 64 . 5% ) ( transect survey ) . The HHQ underestimated the coverage by 6 . 6% , whilst the transect survey overestimated the coverage by 7 . 1% . An ANOVA of repeated measures indicated that there was a statistically significant difference between the three tests ( df = 2 , F = 8 . 48 , p = 0 . 003 ) with pairwise t-tests ( with Bonferroni adjusted p-values ) indicating that the transect survey estimate was significantly different to the estimate of the HHQ ( p = 0 . 03 ) . The estimates from the VWC were not different from those of either the HHQ or the transect survey at conventional levels ( p = 0 . 14 and 0 . 06 respectively ) . When only adult dogs were included , the coverage calculations ranged from 47–76% ( mean 64 . 1% ) ( VWC ) , 44–76% ( mean 56 . 4% ) ( HHQ ) and 50–83% ( mean 64 . 5% ) ( transect survey ) . The HHQ underestimated the coverage by 7 . 7% and transect survey overestimated the coverage by 0 . 4% . An ANOVA of repeated measures indicated that there was no statistically significant difference between the three tests ( df = 2 , F = 8 . 48 , p = 0 . 06 ) . Pairwise t-tests with Bonferroni adjusted p-values , however , indicated that the coverage estimate of the HHQ was significantly different to that of the VWC ( p = 0 . 01 ) , whilst estimates from the transect survey were not different from those of either the VWC or the HHQ ( p = 1 . 0 and 0 . 34 respectively ) . The VWC was carried out on foot , took two people and , on average , six days to complete . At a daily cost of $20 per worker the average total cost of a VWC was $240 / village . The transect survey consisted of three different 3 km transect routes , taking approximately one hour to complete and driven five times . These activities required four people to work for two days at a cost of $20 / day each , totaling $160 . With an approximate fuel consumption of 7 km / litre , and a total of 45 km driven per village , the average fuel use per village was 6 . 4 litres . With an approximate cost of $1 . 56 / litre , the fuel cost per village was $10 . Therefore the average cost of carrying out a transect survey was $170 per village . The HHQ was conducted by three people and took three days to complete . At a daily cost of $20 per worker , the average cost was $180 per village . The number of dogs being brought for vaccination in 2012 and 2013 is shown in Table 2 . Overall turnout was 23% ( mean of 42 dogs / village ) higher in 2013 compared to 2012 . When turn out in 2012 and 2013 is compared in villages with and without incentives we found that an average of 19 more dogs per village were brought for vaccination in villages without incentives ( Fig 2 ) . This increase was not significant ( t = -1 . 326 , df = 18 , p = 0 . 2; 95% CI: -49 . 2 to 11 . 1 ) . Whilst on average 53 more dogs were brought in villages with incentives . This was significant ( t = -5 . 5187 , df = 42 , p < 0 . 000001; CI: -72 . 60324 to -33 . 72234 ) . Incentives therefore resulted in , on average , 34 more dogs being brought for vaccination per village . Different combinations of incentives had no effect on vaccination turnout ( F = 0 . 98 , df = 2 , 40 , p = 0 . 4 , 95% CI: 33 . 7–72 . 6 ) . The mean number of dogs vaccinated by the SHI per village in 2012 was 189 . With the mean fixed operational cost per village of $578 , this results in a cost per dog of $3 . 06 . Use of incentives increased the turn out by an average of 34 dogs per village , resulting in a mean of 223 dogs vaccinated per village at a cost of $2 . 59 per dog . The break-even cost , under which the incentive must be to be cost-effective , was $0 . 47 . Out of 261 respondents , 107 ( 41% ) preferred dog collars , whilst 113 ( 43% ) preferred wristbands and 41 ( 16% ) had no preference . Approximately 98% of the respondents liked the incentives and were happy to see vaccinated and unvaccinated dogs being easily distinguished . In total there were 738 respondents from the two districts who did not vaccinate some or all of their dogs . The reasons given are as shown in Table 4 . The data set made available by the SHI is available in the Supplementary Information S1 and contains the sub-village names , their distance from the respective central-point vaccination clinics and the vaccination coverage levels as calculated by a VWC . A Pearson distance–coverage correlation indicated a significant negative relationship between distance and coverage ( r = -0 . 27 , t = -2 . 1 , df = 57 , p = 0 . 04 ) suggesting that as distance to the central-point clinic increased so vaccination coverage at the sub-village level decreased .
This paper provides the first assessment of the accuracy of vaccination coverage estimates made by household questionnaire ( HHQ ) and transect surveys through comparison with a village-wide census ( VWC ) “gold standard” method . Additionally , though collars have been commonly used to aid the identification of dogs whilst estimating vaccination coverage [3 , 20 , 24] , this is the first study to quantify the impact that collars and wristbands used as incentives have on owner participation in mass dog vaccination campaigns . Two principle findings emerged: i ) both of the trial methods , HHQ and transect survey , accurately estimated the vaccination coverage ( as compared to the gold standard method of VWC ) , however the HHQ was significantly less accurate when puppies were not included; ii ) there was a significant increase in the number of dogs brought for vaccination in villages where incentives were used . Our study included the use of wristbands and collars as incentives for the purpose of encouraging community members to bring their dogs for vaccination . We found that the incentives had an impact , increasing vaccination turnout in comparison with villages where no incentives were handed out . Because the villagers were not aware in advance that the collars or wristbands would be handed out , it seems likely that the brightly coloured incentives exerted their effect ( when worn by owners or vaccinated dogs ) by attracting further owners to bring their dogs to the vaccination points . Logically , and through an economy of scale , the more dogs that turn up for a village vaccination clinic the cheaper the immunization per dog becomes . We calculated the reduction in the cost per dog to be $0 . 47 , which gives a threshold under which the price of the incentive must remain to be cost-effective . Different combinations of incentives ( collars alone , wristbands alone or collars in combination with wristbands ) had no significant effect on increasing vaccination turnout . When the owners were asked whether they liked the collars and wristbands , nearly all responded positively and agreed that it was helpful to be able to distinguish vaccinated dogs . As there was no preference for one type of incentive , it would be sensible to invest in dog collars rather than wristbands , as collars can be used both as an incentive and for marking vaccinated dogs . Mass dog vaccination is the most effective method to control rabies in endemic regions [11] . It is important , however , that 70% of the dog population is immunized to create sufficient herd immunity so that the transmission of the virus is blocked [11 , 19] . It is important therefore to be able to reliably assess post-vaccination coverage . Carrying out a post-vaccination VWC is a highly accurate method , as data is collected from every household in the village . However , this method is very time consuming and expensive . Quicker and cheaper methods , such as the HHQ and transect survey assessed in this study , are often used [3 , 4 , 20] . To the author’s knowledge this is the first time these methods have been validated against a VWC . Although the HHQ and the transect survey tended to under- and over-estimate the coverage respectively , we found , when puppies were included in the calculation , no significant differences with the vaccination coverage estimates made by the gold standard . However the accuracy of the transect survey estimate was only just above conventional significance . As only adult dogs tend to be visible on a transect survey , and many puppies are not brought for vaccination , this was expected . It follows , therefore , that when puppies were not included in the calculation the transect survey became highly accurate . However the HHQ became significantly less accurate when puppies were not included , underestimating the coverage by an average of 10% . Indeed , whether puppies were , or were not , included the HHQ tended to underestimate the vaccination coverage . Regarding cost , the transect survey and the HHQ were similarly expensive whilst the VWC was approximately 37% more expensive than both . However the transect survey took less time , and was more simple to carry out . Transect surveys are limited , however , as they only enable vaccination coverage estimation , whereas the HHQ can be modified to include a range of useful demographic data . In summary , the transect survey compared well with the gold standard whether or not puppies were included , whilst the HHQ was only accurate when puppies were included . Given that within a few months puppies will grow up to become active members of the dog community , it seems sensible to include them in the calculation of vaccination coverage . In this situation one needs to be cautious about relying on an estimate made by a transect survey as we have calculated it to be approximately 7% higher than the real coverage . The HHQ , which tended to underestimate the coverage , provides a more conservative estimate . Given this , the similar cost implications and the potential added value that can be provided by the collection of wider demographic data , we recommend the HHQ . If time is a constraint , however , the transect survey provides a quicker method of assessment . Despite the positive impact that incentives had on vaccination turnout , the vaccination coverage estimates from the ten villages in our study were on average 16% below the recommended coverage of 70% required to disrupt rabies [11] . The reasons given for non-participation in the clinics were consistent with other studies [20 , 24] , with over a third of respondents who had not brought their dogs for vaccination claiming their dogs had run away , whilst others thought their puppies were too small for vaccination . Given the impact that unvaccinated puppies have on vaccination coverage , this reason should be addressed by sensitizing owners to the fact that puppies of any age can be effectively immunized [25] and that failure to vaccinate them may allow rabies to persist [4 , 11 , 18] . Despite the advertising campaign carried out the day before the clinic , over a quarter of the respondents that did not bring their dogs claimed to have been unaware of the vaccination campaign . This could be attributed to the difficulty in accessing all areas of a village when advertising the campaign by loudspeaker from a vehicle . Although likely to take considerably longer , advertising by foot , so that all sub-village areas are targeted , will probably improve this . The vaccination campaign in the study villages was carried out during the season of cultivation and it is likely that a proportion of the respondents that said they were not at home were busy with farming activities which prevented them attending vaccination . Scheduling campaigns to take place outside of harvesting or planting season might help to further increase coverage . Additionally , having been the target of rabies vaccination campaigns for over ten years , it is possible that the reduced incidence of rabies in the target villages has caused people to become complacent about the disease; a pattern of behaviour that can lead to the re-establishment of rabies . Furthermore , Tanzanian villages are typically large with widespread sub-village areas , requiring people living at the periphery to travel long distances on foot to reach a central-point vaccination clinic . Although having to walk a long way to the central-point was not given as a reason for non-attendance the findings from the sub-village distance–coverage correlation indicated that vaccination coverage , at the level of the sub-village , decreases as the distance to the central point increases . Carrying out secondary satellite clinics in peripheral sub-village areas , or visiting remote households on foot , would address this but would also increase costs considerably . The collection of demographic data allows the human and domestic dog population characteristics to be characterised , which is important for the design of vaccination campaigns . Although the HHQ significantly overestimated the proportion of dog owning households , the other estimates , including the human to dog ratio , important for planning vaccination campaigns , compared well with the gold-standard data collected by the VWC . Further , the human to dog ratios estimated were consistent with previous studies in rural areas [24 , 26 , 27] , but were considerably lower when compared to urban and rural coastal areas [3 , 6] . As pet ownership in urban and coastal areas , particularly Muslim coastal communities , has been shown to be less popular [6] this finding was not surprising . In conclusion , we find that vaccination coverage estimates determined by both household questionnaire and transect surveys were accurate when all dogs were included in the calculations , and that both methods can be relatively cheaply employed . However as the transect survey tends to overestimate the coverage , caution is required when using this method . Given the added value of the accurate demographic data that can be obtained through HHQ , and that this method tends to provide caution by underestimating coverage , we conclude this method to be preferable . The use of collars and wristbands as incentives in dog vaccination coverage clinics had a significant impact on vaccination turnout and , assuming cheap options are available , they can reduce the cost of immunization per dog and we therefore recommend their use . However improving the dissemination of advertising , for example by involving local leaders to ensure that the importance of participation , by dogs of all ages , is transmitted to the most remote areas of each village , is required . Furthermore scheduling campaigns around key farming activities might further improve coverage .
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It is estimated that 59 , 000 people die from canine-mediated rabies each year , over 99% in developing countries where rabies is endemic and nearly half of the victims are children . The annual global cost has been estimated at 8 . 6 billion dollars . Yet with highly effective vaccines and a single species of reservoir host ( the domestic dog ) rabies is entirely preventable through mass dog vaccination . These disease burden statistics , and the evidence that dog vaccination is highly effective at eliminating human rabies , have led the World Health Organisation ( WHO ) , together with the Food and Agriculture Organization ( FAO ) and the World Organization for Animal Health ( OIE ) , to unite in their joint commitment to the global elimination of canine rabies . To be successful in this , vaccination campaigns must routinely achieve the 70% coverage levels required for rabies elimination . We used a mass dog rabies vaccination campaign in northern Tanzania to assess the accuracy of methods used for estimating coverage . Additionally we assessed the impact that incentives had on vaccination turn out . Our data showed that , despite under- and over-estimating the coverage respectively , both household questionnaire and mark-re-sight surveys were accurate when compared to a gold-standard method for estimating coverage . Given this tendency to provide a conservative estimate , whilst also providing opportunities for valuable demographic data to be collected , we recommend the household questionnaire survey method . Our data also indicated that the provision of incentives did significantly increase the number of dogs brought for vaccination .
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[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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Incentives Increase Participation in Mass Dog Rabies Vaccination Clinics and Methods of Coverage Estimation Are Assessed to Be Accurate
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Population bottlenecks followed by re-expansions have been common throughout history of many populations . The response of alleles under selection to such demographic perturbations has been a subject of great interest in population genetics . On the basis of theoretical analysis and computer simulations , we suggest that this response qualitatively depends on dominance . The number of dominant or additive deleterious alleles per haploid genome is expected to be slightly increased following the bottleneck and re-expansion . In contrast , the number of completely or partially recessive alleles should be sharply reduced . Changes of population size expose differences between recessive and additive selection , potentially providing insight into the prevalence of dominance in natural populations . Specifically , we use a simple statistic , BR≡∑xipop1/∑xjpop2 , where xi represents the derived allele frequency , to compare the number of mutations in different populations , and detail its functional dependence on the strength of selection and the intensity of the population bottleneck . We also provide empirical evidence showing that gene sets associated with autosomal recessive disease in humans may have a BR indicative of recessive selection . Together , these theoretical predictions and empirical observations show that complex demographic history may facilitate rather than impede inference of parameters of natural selection .
In diploid organisms , the fitness effect of an allele , or a group of alleles , can be categorized as additive , dominant or recessive , or as part of a more general epistatic network . A large body of existing work is devoted to the development of statistical methods for the detection and quantification of selection using DNA sequencing data , including comparative genomics and the sequencing of population samples [1–3] . However , much less progress has been made toward developing methods to identify the mode of selection as additive , recessive or dominant . Substantial experimental work in the last 50 years has been devoted to identifying the average dominance coefficient in model organisms , often with disagreement between different studies and techniques [4 , 5] . These studies , in an attempt to identify the relationship between dominance coefficients and selective effects , largely focus on mutation accumulation experiments and subsequent laboratory propagation , determining dominance coefficients from the viability of crosses [4 , 6] . At least one study attempts to determine the relationship between dominance coefficient and selective effect from natural populations , propagating crosses directly from wild-type samples , however the methodology relies on the often inapplicable assumption of mutation-selection balance [7] . A particularly useful overview of various techniques and studies can be found in [8] , with some more modern techniques described in [9] . Additionally , more recent work taking advantage of a large amount of yeast knockout data has made progress towards quantifying the distribution of dominance effects ( restricted to the discussion of nonsense mutations ) , with emphasis on the variance and skew of this distribution [10 , 11] . Despite these substantial steps forward , all of the methods employed rely on the ability to rapidly breed laboratory-friendly organisms , either for the purposes of mutation accumulation or production of homozygotes and heterozygotes through crosses . Unfortunately , such techniques are infeasible when dealing with long-lived macroscopic organisms , particularly in the case of humans . In the present work , we hope to provide steps towards the development of techniques applicable to natural populations of such organisms by making use of naturally occurring demographic events and describing the dynamic response of populations to such events . The genetics of model organisms and of human disease provide plenty of anecdotal evidence in favor of the general importance of dominance [12] . Although genome-wide association studies suggest that alleles of small effects involved in human complex traits frequently act additively , estimation of genetic variance components from large pedigrees suggests a substantial role for dominance in a number of human quantitative traits; LDL cholesterol levels , for example , have a substantial dominance component , as shown in [13] . Alleles of large effects involved in human Mendelian diseases often behave similarly to large effect ( and even lethal ) spontaneous and induced mutations in model organisms , such as mouse , zebrafish , or flies , that are frequently recessive [4 , 14] . In spite of these observations , the role of dominance in population genetic variation and evolution remains largely unexplored in the majority of diploid species and no formal statistical framework is currently available to identify dominance coefficients in natural populations deviating from mutation-selection balance . A number of theoretical studies suggested that demographic processes associated with the increase in variance of allele frequency distribution result in a more efficient removal of recessive deleterious alleles [15–18] . Such demographic scenarios include population bottlenecks , population subdivision , range expansion , and inbreeding . Increase in the variance of allele frequency distribution during a bottleneck can be characterized by inbreeding coefficient ( even in case of a panmictic population ) . For structured populations , the increase in variance is characterized by FST . Substantial theoretical work and associated experimental studies explored the removal of recessive variants due to increased inbreeding coefficient during sustained population bottlenecks [19–22] . Additionally , several studies note that bottlenecks have a strong effect on nonadditive variation , specifically loci with epistatic interactions [19 , 23–30] . To complement these analyses , we focus on genetic variation in panmictic populations that experienced a population bottleneck and subsequent re-expansion , similar to the scenario recently analyzed in [30] . Using a combination of theoretical analysis and computer simulations , we demonstrate that recessive selection can be qualitatively distinguished from additive selection in populations that recently recovered from a temporary bottleneck , and detail the dynamics of the average number of mutations per haploid . An important study by Kirkpatrick and Jarne [31] qualitatively described how , perhaps counterintuitively , the number of deleterious recessive alleles per haploid genome is transiently reduced after re-expansion following a population bottleneck , while the number of additively or dominantly acting alleles is increased . We focus on this insight and quantitatively extend the analysis of these dynamics to show that , in spite of a well-documented increase in the frequency of some recessively acting variants in founder populations , the average number of deleterious recessive alleles ( with dominance coefficient h ≪ 0 . 5 ) carried by an individual is reduced as a consequence of the bottleneck . With the growing availability of DNA sequencing data in multiple populations , these results demonstrate the potential to directly evaluate the role of dominance , either on a whole genome level , or in specific categories of genes . Population bottlenecks are a common feature in the history of many human populations . For example , the “Out of Africa” bottleneck involved the ancestors of many present-day human populations . Numerous recent bottlenecks affected , among others , the well studied populations of Finland and Iceland . More generally , bottlenecks followed by expansions are standard features in the recent evolution of most domesticated organisms , including an analogous “Out of Africa” event in Drosophila melanogaster [32] , highlighting the ubiquity of these events in natural populations . We suggest that complex demographic history may assist rather than complicate statistical inference of selection in population genetics . Here we focus on a comparison between two populations that recently split , after which their demographic histories diverged , one exhibiting a founder’s event ( a population bottleneck followed by subsequent re-expansion ) , and the other maintaining a fixed population size . We analyze their accumulated differences to shed light on the type of selection dominating the dynamics of deleterious alleles , and show that the average number of mutations per individual , 〈x〉 , is dependent on the mode of selection characterized by the average dominance coefficient , h . We introduce a measure BR ( the “burden ratio” defined below ) that is the ratio of per-haploid deleterious allele accumulation in the two populations . This potentially allows for the qualitative distinction between predominantly additive selection ( h ≈ 0 . 5 ) , where mutations accumulate due to relaxed selection during a bottleneck , resulting in BR < 1 , and predominantly recessive selection ( h ≪ 0 . 5 ) , where homozygous deleterious mutations are purged from the population after re-expansion from the bottleneck , resulting in BR > 1 , as shown in Fig 1 . For qualitative demonstration and development of intuition , the analysis assumes strictly additive and strictly recessive selection with a highly idealized demography . However , this behavior is not restricted to the simplified demographic model presented in this paper , but rather suggests a quite generic qualitative signature for the presence of recessive ( or near-recessive ) selection in comparison between two populations , one of which experienced a bottleneck event . Additionally , our simulations suggest the potential to distinguish between partially recessive and additive alleles , as the change in the qualitative behavior of BR occurs at intermediate values of the dominance coefficient , h . The temporal dependence of the “critical dominance coefficient” , hc , describing the boundary between BR > 1 and BR < 1 , as well as the sensitivity to partial recessivity , is discussed in the S1 Text . To ask whether the behavior of the BR statistic is consistent with the dynamics of recessive selection in natural populations , we perform a statistical analysis of genes annotated in the literature as causing autosomal recessive ( AR ) disease . We use the “Out of Africa” event to differentiate between variation in African and European populations , potentially allowing for the identification of recessive selection in natural human populations . We find that sets of AR disease genes show a statistically significant deviation from neutrality , with BR > 1 . This suggests that at least some disease-associated genes with autosomal recessive mode of inheritance may be under recessive selection . Although this observation is not surprising , it is nontrivial , as disease genes could be neutral , highly pleiotropic , or contain variants with different modes of inheritance . This analysis demonstrates the potential to use our methodology to identify sets of genes under predominantly recessive selection .
We work with a simple demography described by an ancestral population of N0 individuals that splits into two subpopulations , one with population size N0 equal to the initial population size ( “equilibrium” ) , and one with reduced bottleneck population size NB ( “founded” ) . The latter population persists at this size for TB generations before instantaneously re-expanding to the initial population size N0 , as shown in Fig 1 . Time t is measured after the re-expansion from the bottleneck , as we are interested in the dynamics during this period . Quantities measured in the equilibrium population , and equivalently prior to the split , are denoted with a subscript “0” . We consider only deleterious mutations with average selective effect of magnitude s > 0 , such that s represents the strength of deleterious selection . Extensions of this analysis to a full distribution of selective effects can be found in the S1 Text . The initial population is in a quasi-steady state with 2N0Ud deleterious alleles introduced into the population with a one-way mutation rate Ud per haploid individual per generation and rare fixation of deleterious alleles . In the absence of back-mutations , the population is not strictly in static equilibrium , however , this approximation is reasonable when the back-mutation rate and average derived allele frequencies are relatively low . In approximate equilibrium , the site frequency spectrum ( SFS ) , denoted ϕ ( x ) , for polymorphic alleles is given by Kimura [33] . ϕ e q ( x ) = 4 N U d e - 4 N s h x - 2 N s ( 1 - 2 h ) x 2 x ( 1 - x ) [ 1 - ∫ 0 x d y e 4 N s h y + 2 N s ( 1 - 2 h ) y 2 ∫ 0 1 d y e 4 N s h y + 2 N s ( 1 - 2 h ) y 2 ] ( 1 ) Here h ≥ 0 is the dominance coefficient for deleterious mutations , where h = 1/2 corresponds to a purely additive set of alleles , and h = 0 corresponds to the purely recessive case . For the present analysis , we primarily focus on these two limits , contrasting their effects on the genetic diversity . An expanded discussion of the treatment of intermediate dominance coefficients can be found in the S1 Text . The solution represents a mutation-selection-drift balance in which new mutations are exactly compensated for by the purging of currently polymorphic alleles by both selection and extinction due to stochastic drift . In this way , an approximately static number of polymorphic alleles exists in the population at any given time . As noted above , a qualitative insight on the effect of the bottleneck on recessive variation was previously obtained by noting that the expected change in frequency of recessive allele is accelerated due to the increased variance of allele frequencies ( inbreeding coefficient ) . We offer a different approach and attempt to quantitatively describe the difference in dynamics between additive and recessive variation . We follow the expected number of mutations per chromosome in the population , noting that it is simply the first moment of SFS . 〈 x 〉 = ∫ x ϕ ( x ) ( 2 ) When multiplied by s , this is the effective “mutation load” of each individual in the additive case , but in the case of purely recessive selection this is not proportional to the fitness , as selection acts only on homozygotes . We refer to this statistic generally as the “mutation burden” to avoid assumption of any given mode of selection . As described below , comparison between the mutation burden in the equilibrium and founded populations in the form of the “burden ratio” , BR , may prove useful in the identification of sets of alleles under recessive selection . B R ≡ 〈 x 〉 e q 〈 x 〉 f o u n d e d = { < 1 for additive selection > 1 for recessive selection ( 3 ) To gain intuition for this qualitative difference , we work to quantitatively understand the population dynamics in a simple demography , first for purely additive selection , and then for purely recessive selection for comparison . We checked our analytic results using a forward time population simulator , described in detail in the S1 Text . Given the ubiquity and analytic simplicity of the exponential decay in the additive scenario , we focus here on our predictions for recessive variation . We compare analytic expressions of BR ( tmin ) at the peak response given in Eq ( 21 ) for various selection coefficients . We simulated a wide range of bottleneck parameters to probe the limitations of our theoretical understanding . In Fig 4 , we demonstrate the accuracy of our analytic results , by plotting the ratio of the simulated values of BR ( tmax , s , IB ) to our analytic predictions BR ( tmax , s , IB ) as presented in Eq ( 21 ) . We arrange our simulated data by bottleneck intensity IB , as we expect the single-generation bottleneck approximation to break down as intensity is increased due to longer bottleneck duration TB ≫ 1 . As plotted , complete agreement between simulated data and analytic predictions is represented by a flat line at B R s i m / B R a n a l y t i c = 1 . As expected , we find deviations as we approach the limitations of our perturbative approximation , roughly around Tb ∼ 2NB/10 when IB ∼ 0 . 1 . Below these higher intensities , we find quite good agreement for all parameter sets well below 10% error , even at IB = 0 . 05 . Further comparison between simulation and analytic results is presented in S1 Text and illustrated in S2 Fig . The BR statistic provides a qualitative indication of recessive selection ( h ≪ 0 . 5 ) , in that values over one theoretically correspond to recessivity . This corresponds to a reduction in the average number of deleterious alleles per haploid locus in a founder population relative to a non-bottlenecked population . To test whether the statistic is sensitive to recessive selection , we analyze human exome data from the Exome Sequencing Project ( ESP ) [37] . We compare European Americans ( EA ) , known to have undergone a relatively intense bottleneck during the “Out of Africa” event , to African Americans ( AA ) , who have substantial African ancestry that did not experience this founder’s event . We aggregate a set of genes and compute the per-haploid mutation burdens , 〈x〉AA and 〈x〉EA for each gene set by summing the frequencies of all variants occurring in those genes within the AA and EA populations separately , such that 〈x〉AA≡∑ixiAA and 〈x〉EA≡∑ixiEA . This provides a group burden ratio score BR≡∑ixiAA/∑ixiEA for the entire gene set ranging from predicted additive ( or dominant ) with BR < 1 to predicted recessive with BR > 1 . While this strategy could in principle be applied directly to a single gene , substantial statistical fluctuations tend to make this measure unreliable on the individual gene level . We assemble sets of genes associated with known autosomal recessive ( AR ) diseases , some of which are potentially under recessive selection , and compute a corresponding BR score . In the absence of pleiotropy and the presence of purifying selection against these disease phenotypes , we naively expect these genes to act under partial ( h < 0 . 5 ) or total recessive selection ( h ≈ 0 ) . We check for significant deviation from BR = 1 in several gene sets: 44 genes associated with diseases with “autosomal recessive” in the name of the disease with at least 5 annotated variants in the Human Gene Mutation Database ( HGMD ) , 37 genes associated with congenital hearing loss ( HL ) and found only with AR mode of inheritance in a clinical genetics lab , and 1348 genes with Clinical Genomic Database ( CGD ) AR annotations [38–40] . Additionally , we aggregate non-overlapping HGMD and HL genes into a larger combined list of 72 genes . To compute BR gene scores , we assume that derived variants at a given locus are deleterious , and include derived alleles of all frequencies , including those fixed in one or both of the populations . We restrict our analysis to nonsense variants and non-synonymous variants predicted to be damaging using a human-free version of PolyPhen2 [36] developed to remove bias due the ancestry of the human reference . Derived alleles fixed in one of the two populations are included in the analysis of the burden , as they contribute to the weighted mean 〈x〉 . We estimate significance using bootstrapped standard errors , as described in detail in the S2 Text . First , we compute the burden ratio for all genes in the genome , and find no statistical deviation from one , replicating previously published results [35 , 36] . Analysis of the CGD gene set again shows no statistically significant deviation from one . Given the whole genome result , this is not unexpected , as this set of over 1000 genes is plausibly large enough to representatively sample the set of all genes . It is likely that many of these genes have only one or a few variants under recessive selection , with the rest being neutral or even dominantly acting . In contrast , we find statistically significant BR > 1 values in the potentially more reliable HGMD and HL gene sets , despite their small size , as well as in the combined set . We partially replicate our results from ESP using an independent dataset , from the 1000 Genomes Project ( 1KG ) , again finding statistical significance in the HGMD disease gene set [41] . A detailed discussion of the data sets and statistical analyses used is provided in S2 Text and detailed in S1 Table ( with full gene lists included in a supplemental spreadsheet ) . We find statistical significance for two separately obtained disease gene sets , as well as in the combined set . The HGMD gene set is significant in both ESP and 1KG . Additionally , we find null results in nearly all controls presented in S2 Text and detailed in S2 Table . Together , the empirical analysis provides suggestive evidence that genes associated with autosomal recessive disease and thus potentially under recessive selection can show significant burden ratio values BR > 1 . The resulting analysis is summarized in Table 1 . In light of these findings , we believe we have demonstrated the potential usefulness of this method for identifying sets of genes under recessive selection . Given the significant observed values of BR > 1 in these gene sets , one can gauge the degree of recessivity for a given set . Specifically , we can readily estimate the average dominance coefficient for damaging and nonsense mutations within a set of genes under the assumption that these mutations all act with a single average dominance coefficient h ‾ and an average selection strength s ‾ . We caution that estimates using a single h and s pair of values for all derived mutations may be inappropriate if there is substantial variance in either or both of these parameters . In the absence of information about the variance in dominance coefficients , we believe this approximation may still be informative ( if only as a rough guide ) in gene sets that clearly deviate from neutrality . Given the details of the Out of Africa demography , the data for the HGMD gene set are consistent with an average dominance coefficient h ‾ H G M D ≲ 0 . 2 ( with 95% confidence ) , however , this bound is conservative over all possible values of the average strength of selection in this gene set . For average selective strengths of s ‾ H G M D = { 0 . 001 , 0 . 01 , 0 . 1 } in damaging and nonsense variants , we find that the corresponding allowed average dominance coefficients are h ‾ H G M D ≲ { 0 . 15 , 0 . 2 , 0 . 05 } ( with 95% confidence ) , respectively . Note that the non-monotonicity in these values is a consequence of the behavior shown for the Out of Africa demography in Fig 3 . Additionally , all average dominance coefficients for HGMD are inconsistent with weak average selective strengths below roughly s ‾ H G M D ∼ 0 . 0003 . Complementary population data from distinct founder’s events may provide stricter bounds on both the average dominance coefficients and average selective strengths for a given gene set .
The increase in prevalence of recessive phenotypes following population bottlenecks has attracted the interest of geneticists for a long time [19 , 42] . Theoretical analysis of allele frequency dynamics in a population expanding after a bottleneck suggested that frequency of an individual allele may rise due to increased drift [42–44] . Here , we focus on a more general question of the collective dynamics of recessively acting genetic variation . In line with the qualitative description found in [31] , our analysis suggests that the number of recessively acting variants per haploid genome is reduced in response to a bottleneck and subsequent re-expansion . Generally , we have demonstrated that features of the derived allele spectrum of recessive deleterious polymorphisms behave distinctly from additively acting variation following a population bottleneck and subsequent re-expansion . The response of additive variation depends crucially on the average number of deleterious alleles , and on the number of generations for which selection is relaxed during the bottleneck . In contrast , the dynamics of recessive variation crucially depend on the variance of the site frequency spectrum , rather than the average number of mutations per individual , such that the accumulation of deleterious mutations can respond strongly even to a single-generation bottleneck . Importantly , the temporal dynamics of the accumulation of deleterious alleles depends qualitatively on dominance coefficient and quantitatively on selection coefficient . The qualitative dependence on dominance coefficient suggests that one can learn about recessivity from analysis of the population dynamics in response to a founder‘s event . If the variation is additive , the number of deleterious variants per a haploid genome is larger in a bottlenecked population than in a corresponding equilibrium population . If the variation acts recessively , this number is smaller . The selection coefficient determines the timing of response to a bottleneck . By explicitly analyzing the non-equilibrium response to a bottleneck , we suggest that naively confounding demographic features may actually shed light on underlying population genetic forces . In realistic populations , for example in modern humans , substantial work has been done to identify and understand the recent demographic history of geographically disparate populations [37 , 45–54] . In a recent paper , Simons , et al . [35] use the BR statistic on the whole genome level to empirically compare the accumulation of mutations in European Americans and African Americans . The authors find no statistically significant differences in the whole genome mutation burden of these populations , a result that was extended to all two-point comparisons between a diverse set of humans by Do , et al . [36] . To explain this observation , Simons , et al . derive a complementary theoretical treatment of the dynamics of segregating alleles using branching process techniques and extensive simulations , providing results that are consistent with those presented here . In the case of the “Out of Africa” event , a historically substantiated and believable demographic model can be used to understand the difference between African and European populations since their divergence . The comparison between populations that have and have not undergone a bottleneck can be used to elucidate plausible selection and dominance coefficients by making use of a simulated version of this demography . As shown in Fig 3 for the comparison between Africans and Europeans , a realistic demographic model can be used to bound the selection and dominance coefficients in modern populations based on a single observation , such as those detailed in [35 , 36] . Although the net number of recessive deleterious mutations is reduced as a consequence of a founder‘s event and subsequent re-expansion , the fitness of individuals carrying these alleles is not necessarily increased , as the number of homozygotes is known to increase after a population bottleneck . However , the number of heterozygous deleterious sites , or the average carrier frequency for associated alleles , is suppressed , such that the mating of individuals from disparate bottlenecked populations may result in a decreased incidence of recessive phenotypes in such mixed lineages . In studies of model organisms , this may have applications when comparing laboratory populations founded from a few wild type individuals to their corresponding natural populations . We have demonstrated that analysis of the BR statistic on the gene set level shows significant deviations above one in genes known to be responsible for autosomal recessive human disease . In principle , the results of this study can be extended to the analysis of any specific groups of genes beyond those with a known mode of inheritance . Sufficiently large subsets of alleles that are medically relevant may be analyzed in humans to identify the mode of selection for candidate variants of potentially recessive diseases . In sum , the non-equilibrium dynamics induced by demographic events is an essential , and indeed insightful , feature of most realistic populations . Population bottlenecks , abundant in laboratory populations and in natural species , have the potential to provide a novel perspective on the role of dominance in genetic variation .
Simulation details . We performed analysis using a forward time population simulator , custom written in C , available at http://genetics . bwh . harvard . edu/wiki/sunyaevlab/dbalick . For computational speed , the simulator only keeps track of allele frequencies in a freely recombining diploid system , rather than containing full genome information . We use an infinite sites model with a mutation rate of 2 × 10−8 per generation per site . Allele counts in the current generation are sampled based on the frequencies in the previous generation xold , the selection coefficient s , and the dominance coefficient h . We calculate the expected frequency xcurrent in the current generation as: x c u r r e n t = ( x o l d 2 ( 1 + s ) + x o l d ( 1 - x o l d ) ( 1 + s ) h ) ( x o l d 2 ( 1 + s ) + 2 x o l d ( 1 - x o l d ) ( 1 + s ) h + ( 1 - x o l d ) 2 ) . ( 25 ) The simulator has arguments for per base mutation rate Ud , selection coefficient s , and dominance coefficient h , with a default burn-in of 300 , 000 generations where sampling occurs every 100 generations in sped-up mode before transitioning to sampling every 1 generation at 1000 generations before time t = 0 . The code was designed to allow for flexible demographic histories , in order to accurately represent events such as the “Out of Africa” migratory event in human population genetic history . For the purposes of comparison to our analytic results , we ran simulations for a simple , square bottleneck of varying population sizes for both the equilibrium population with size 2N0 = 2 × 104 and bottlenecked populations with temporarily reduced sizes of 2NB = {2000 , 1000 , 400 , 200 , 100} for a duration of TB = {200 , 100 , 50 , 20 , 10} generations . These simulations were performed under both purely additive ( h = 0 . 5 ) and purely recessive ( h = 0 ) selection , for a wide range of selection coefficients s = {1 , 0 . 1 , 0 . 02 , 0 . 01 , 0 . 001} . For simulations of a range of selective effects and dominance coefficients shown in Fig 3 , we used a square bottleneck with parameter 2N0 = 20000 , 2NB = 2000 , TB = 100 , and tobs = 1000 and a realistic Out of Africa demography detailed in Tennessen , et al . [48] . Human polymorphism data . We analyze exome data from the Exome Sequencing Project ( ESP ) and validate some of our findings using exome data from the 1000 Genomes Project ( 1KG ) [37 , 41] . We use available frequency information for polymorphic variants to compute an average per haploid mutation burden per gene for all genes in ESP in 1088 European Americans ( EA ) with largely European ancestry and 1351 African Americans ( AA ) with substantial African ancestry . In 1KG , we compare 85 Northern Europeans from Utah ( CEU ) to 88 Yorubans ( YRI ) by computing the same statistic . We sum these mutation burdens over genes of interest to compute an aggregate BR score for a given gene set . Human-free Polyphen2 . To compute mutation burden gene scores for putatively deleterious mutations , we restrict our analysis to non-synonymous nonsense variants and variants predicted to be damaging using a human-free version of PolyPhen2 [36] . This software was developed to remove bias due to the mixed ancestry of the human reference sequence , and annotates derived alleles based on chimpanzee orthologs . Disease gene sets . We use several lists of genes associated with AR diseases that we naively expect to act under partial or total recessive selection . First we compile a set of genes from the Human Gene Mutation Database ( HGMD ) only associated with diseases with “autosomal recessive” in the disease name [38] . We restrict this set to genes with at least 5 disease-associated variants to guarantee sufficient polymorphism and reduce noise in the BR statistic . This set contains 38 genes that appear in the list of ESP scored genes ( 44 in 1KG ) and is referred to as “HGMD” . We use Congenital Hearing Loss as an example of a polygenic , largely recessive disease . We obtained an annotated gene list of AR genes associated with hearing loss from the Laboratory for Molecular Medicine ( LMM ) [39] . This list contains 30 genes in ESP ( 37 in 1KG ) and is referred to as “Hearing Loss” . Notably , this list excludes connexin 26 ( GJB2 ) , among other genes , which has additional association with AD hearing loss . Additionally , we assemble a combined list of all genes from HGMD and Hearing Loss , with a total of 60 genes in ESP ( 72 in 1KG ) after removing overlap , referred to as “Combined” . To assemble a larger , though noisier gene set , we use all annotated AR genes in the Clinical Genomic Database , referred to as “CGD” , which contains 1268 genes in ESP and 1348 genes in 1KG [40] .
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Dominance has played a central role in classical genetics since its inception . However , the effect of dominance introduces substantial technical complications into theoretical models describing dynamics of alleles in populations . As a result , dominance is often ignored in population genetic models . Statistical tests for selection built on these models do not discriminate between recessive and additive alleles . We show that historical changes in population size can provide a way to differentiate between recessive and additive selection . Our analysis compares two sub-populations with different demographic histories . History of our own species provides plenty of examples of sub-populations that went through population bottlenecks followed by re-expansions . We show that demographic differences , which generally complicate the analysis , can instead aid in the inference of features of natural selection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[] |
2015
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Dominance of Deleterious Alleles Controls the Response to a Population Bottleneck
|
The human papillomavirus DNA genome undergoes three distinct stages of replication: establishment , maintenance and amplification . We show that the HPV16 E6 protein is required for the maintenance of the HPV16 DNA genome as an extrachromosomal , nuclear plasmid in its natural host cell , the human keratinocyte . Based upon mutational analyses , inactivation of p53 by E6 , but not necessarily E6-mediated degradation of p53 , was found to correlate with the ability of E6 to support maintenance of the HPV16 genome as a nuclear plasmid . Inactivation of p53 with dominant negative p53 rescued the ability of HPV16 E6STOP and E6SAT mutant genomes to replicate as extrachromosomal genomes , though not to the same degree as observed for the HPV16 E6 wild-type ( WT ) genome . Inactivation of p53 also rescued the ability of HPV18 and HPV31 E6-deficient genomes to be maintained at copy numbers comparable to that of HPV18 and HPV31 E6WT genomes at early passages , though upon further passaging copy numbers for the HPV18 and 31 E6-deficient genomes lessened compared to that of the WT genomes . We conclude that inactivation of p53 is necessary for maintenance of HPV16 and for HPV18 and 31 to replicate at WT copy number , but that additional functions of E6 independent of inactivating p53 must also contribute to the maintenance of these genomes . Together these results suggest that re-activation of p53 may be a possible means for eradicating extrachromosomal HPV16 , 18 or 31 genomes in the context of persistent infections .
Human papilloma viruses ( HPVs ) are small , non-enveloped icosahedral viruses that infect epithelial linings of the body and are the causative agents of warts . Infection is thought to arise when a virus particle enters a dividing basal epithelial cell , accessed through a wound in the epithelia , wherein its viral genome is delivered to the nucleus and viral genes begin to be expressed [1] . The papillomavirus life cycle is intricately tied to the differentiation of the stratified squamous epithelia that they infect , with progeny virus exclusively generated in the suprabasal compartment [2]–[5] . HPVs are classified as cutaneous or mucosotropic depending upon the type of epithelia they infect . A subset of the mucosotropic HPVs , the so-called high risk HPVs , including HPV genotypes 16 , 18 and 31 , are associated with approximately 5% of human cancers including the vast majority of cervical cancers as well as other anogenital cancers and a growing fraction of head and neck cancers [6]–[10] . An important requirement for the onset of HPV-associated cancers is persistent infection by these high risk HPVs [11] . Prophylactic HPV vaccines hold great promise in preventing new infections but do not eliminate pre-existing infections [12] . Developing the means to eliminate persistent high risk HPV infections would be of great value in reducing the risk of cancer among patients already infected with high risk HPVs . The papillomavirus genome is an 8 kB circular double-stranded DNA that replicates as a nuclear plasmid in three distinct phases referred to as the establishment , maintenance and productive phases [13] . Establishment refers to the replication process by which the HPV genome establishes itself as a multi-copy extrachromosomal replicon , or nuclear plasmid , in undifferentiated basal cells . This stage of genome replication can be studied in vitro using short-term replication assays [14]–[16] . Using plasmids carrying the minimal cis element required for papillomavirus DNA replication , i . e . the viral origin of replication ( ori ) , it has been demonstrated that two papillomaviral genes , E1 and E2 , are required for the establishment phase for multiple papillomaviruses including bovine papillomavirus type 1 ( BPV1 ) as well as HPV6b , 11 , 16 and 18 [15]–[17] . When the initial host cell harboring the established HPV genome undergoes cell division , the HPV genome is replicated and partitioned to daughter cells at a constant copy number of 50–200 extrachromosomal genomes per cell: this phase of HPV replication is referred to as maintenance [13] , [18]–[20] . The expression of HPV genes required for maintenance differs among HPV types . While E6 is required for maintenance of HPV11 , 16 and 31 [21]–[23] , expression of E7 is only required for maintenance of HPV11 and 31 , but is dispensable for maintenance of HPV16 and 18 [21]–[24] . Likewise , E1∧E4 is important for maintenance of HPV16 , but is dispensable for maintenance of HPV11 , 18 and 31 [25]–[28] . Notably , while E1 is required for establishment of HPV16 , expression of E1 has been shown recently to be dispensable for maintenance of HPV16 [29] as had been demonstrated previously for BPV1 [30] . Finally , during the productive phase of replication , the HPV genome is amplified to a high copy number per cell and this stage of replication is restricted to fully differentiated cells [18] . Here E7 plays a critical role in amplification of HPV16 and HPV18 [22] , [24] and E6 is essential for robust amplification of HPV18 [31] , [32] . Additional viral genes including E1∧E4 and E5 have been shown to contribute quantitatively to this phase of viral DNA replication of HPV16 and HPV31 [26] , [27] , [33] . Identifying viral and cellular genes of importance to different stages of the HPV replicative life cycle may help define new strategies for treating persistent HPV-infections . In this study , we sought to identify the roles of E6 that are necessary and sufficient for high risk HPV maintenance in the context of the entire HPV genome . The HPV E6 protein consists of approximately 150 amino acids and contains two zinc finger motifs . High risk HPV E6 proteins also contain a PDZ binding domain at the C terminus [34]–[41] . E6 is known to interact with a number of cellular proteins and modulate multiple cellular processes including apoptosis , transcription , interferon responses and immortalization [42] . The most well-known biochemical property of high risk E6 proteins is their ability to bind the ubiquitin ligase E6AP and the tumor suppressor p53 in a tripartite complex that drives proteasome-dependent degradation of p53 [43]–[45] . Because activation of p53 can lead to apoptosis or growth arrest , it has been hypothesized that E6 plays an important role in the prevention of either cellular process through its destabilization of p53 , thereby allowing for the continued growth and expansion of cells harboring the HPV genome . Previous studies of E6 mutants within the context of the HPV31 genome indicated that the ability of 31E6 to degrade p53 is required for the maintenance of HPV31 [23] . Specifically , an HPV31 genome carrying a three amino acid mutation F45Y/F47Y/D49H in E6 ( E6 YYH ) , which in 16E6 had been previously shown to compromise E6-dependent degradation of p53 [46] , was defective for maintenance of the HPV31 genome [23] , [46] . Likewise , mutational studies of 16E6 placed within the context of the HPV31 genome demonstrated that 16E6 mutants deficient for decreasing p53 steady state levels are defective in the maintenance of the hybrid genome [47] . Thus , we hypothesized that in order for HPV16 to be maintained as an extrachromosomal genome , E6 must destabilize p53 . This hypothesis is necessary to test within the context of the HPV16 genome for two reasons . First , the role of another HPV gene , E7 , differs in its requirement for maintenance between different high-risk HPV types [22]–[24] . Secondly , the HPV31 E6 mutants used in previous studies were based off of mutants characterized from HPV16 E6 , but HPV16 E6 mutants do not always behave the same way when introduced into a different HPV type [48] , [49] . To test our hypothesis , we analyzed the capacity of the HPV16 genome carrying various mutations in the E6 gene to be maintained as an extrachromosomal nuclear plasmid in normal immortalized human keratinocytes ( NIKS ) , cells that retain wild type p53 [50] . The use of immortalized keratinocytes enabled us to directly examine the role of E6 that contributes to maintenance of the HPV16 genome independently of the role of E6 necessary for immortalization . Our mutational studies demonstrated that the ability of HPV16 E6 mutant genomes to inactivate p53 , but not mediate p53 degradation , correlates with the ability of the viral genome to be maintained as an extrachromosomal nuclear plasmid . However , these and prior results using subtle mutations in E6 must be interpreted conservatively , as such mutants of E6 proteins have only been analyzed for a small subset of biochemical activities . To more clearly determine that inactivation of p53 is necessary and/or sufficient to account for the role of E6 in plasmid maintenance of high risk HPV16 , 18 and 31 , we performed complementation studies using cells expressing a dominant negative form of p53 ( p53DD ) . We found that inactivation of p53WT ( wild-type ) complements the ability of HPV 16 E6-deficient genomes to be maintained at early passages . Surprisingly , we found that HPV31 E6-deficient genomes could be maintained at low levels in NIKS at early passages and HPV18 E6-deficient genomes could be maintained at low levels in NIKS and primary human foreskin keratinocytes . Inactivation of p53 also complemented the ability of HPV 18 and 31 E6 null genomes to be maintained as a nuclear plasmid at copy numbers similar to WT HPV genomes in NIKS , but did not rescue the ability of these genomes to be maintained at WT levels over several passages . These results demonstrate , for the first time , that inactivation of p53 is necessary for maintenance of HPV16 , 18 and 31 genomes at WT levels , but additional functions of E6 may contribute to maintenance of these genomes .
Full-length clones of HPV16 , HPV18 and HPV31 were subjected to site directed mutagenesis to generate mutations within the E6 open reading frame ( ORF ) as detailed in text S1 . All mutant genomes were sequenced in their entirety to confirm the introduction of the desired mutation and the absence of spurious changes in the viral DNA sequence . See text S1 for further description of the plasmids used in this study and their sources . NIKS ( Normal Immortalized KeratinocyteS ) and primary human foreskin keratinocytes ( HFKs ) have been previously described by and were obtained from Lynn Allen-Hoffman [50] . Using previously described conditions for their culture in monolayer [51] , NIKS and HFKs were transfected with recombinant HPV DNA genomes that had been released from their bacterial vector and re-circularized using T4 DNA ligase together with a plasmid conferring drug resistance ( either resistance to G418 or blasticidin ) , and subjected to drug selection . Colonies that outgrew were pooled and expanded . This initial population of pooled colonies is referred to as passage 0 ( P0 ) . These populations of cells were serially passaged and cryopreserved for later studies . In some cases colony-derived , clonal populations were isolated and characterized as indicated in the text . Details on the culturing conditions , preparation of DNA for transfection , and DNA transfections are provided within text S1 . To generate NIKS expressing p53DD and vector control transduced cells , cells were infected with pLXSNp53DD recombinant retrovirus that expresses the dominant negative form of p53 , p53DD , or the control vector pLXSN retrovirus . Transductants were selected by growth of cells in the presence of G418 , individual colonies were cloned , and expanded clones were subjected to p53-specific western analysis to identify clonal populations expressing p53DD . Further details regarding these steps are provided in text S1 . Total genomic or low molecular weight DNA was isolated from cells and subjected to HPV-specific Southern analysis as detailed in text S1 . Briefly , DNA from equivalent numbers of cells were digested with indicated restriction enzymes overnight , electrophoresed on agarose gels , transferred to nylon membranes , and HPV DNA was detected by hybridization to pools of radioactively labeled , HPV genotype-specific , single-stranded oligonucleotides . Alternatively , HPV16 DNA was quantified by real-time quantitative PCR ( qPCR ) as detailed in text S1 . To assess the function of p53 ( Entrez Gene ID: 7157 ) in cells , we monitored the responses of cells to actinomycin D . Briefly , cells treated with 0 . 5 nM–5 nM actinomycin D ( Sigma ) or vehicle ( dimethyl sulfoxide ( DMSO ) ( Sigma ) ) for 24 hours were harvested , fixed in ice cold ethanol , stained with propidium iodide , subjected to flow cytometry using a Becton Dickenson FACSCalibur , and cell cycle profiles analyzed using Flow Jo Version 9 . 4 . 11 software . The G1/S ratio was calculated by dividing the percentage of cells in G1 by the percentage of cells in S phase . The magnitude change in the G1/S ratio of control NIKS after vehicle and actinomycin D treatment was compared to the magnitude change in the G1/S ratio of experimental NIKS after vehicle and actinomycin D treatment using the Sen-Adichie test for parallelism in MSTAT version 5 . 5 . 1 software . As another means of assessing p53 function , steady state levels of p21 ( Entrez Gene ID: 1026 ) were determined by western blot analysis of cells likewise treated with actinomycin D or vehicle . Further details on these actinomycin D-based experiments are provided in text S1 .
To determine the requirements of E6 in the establishment and maintenance of the HPV16 genome , we introduced various mutations within the E6 gene in the context of the full-length wild type HPV16 genome . To determine if E6 was required for establishment and/or maintenance of the HPV16 genome as a nuclear plasmid , a stop codon at amino acid 7 was introduced by mutating nucleotide 122 of HPV16 from G to T to create the HPV16 E6STOP mutant genome . The HPV16 E6WT and HPV16 E6STOP genomes were excised from their bacterial vector , re-circularized and each was transfected with a plasmid expressing an antibiotic resistance gene into NIKS . Drug resistant colonies arising 2–3 weeks after selection were pooled to generate a population of cells ( referred to as passage 0 ) and were further passaged . Total genomic DNA was harvested from the expanded populations of cells at early passages ( passage 1 and 2 ) and analyzed by Southern hybridization using an oligonucleotide probe set specific for HPV16 . To determine the presence of mammalian replicated , extrachromosomal HPV16 genomes , total genomic DNA was digested overnight with BamHI plus DpnI or XhoI alone . Using these restriction enzyme digestions , we were able to: 1 ) discriminate HPV16 genomes that had replicated in the human cells from input transfected DNA because the latter is selectively sensitive to DpnI digestion , 2 ) determine if the viral genome was being maintained as an extrachromosomal plasmid by looking for the presence of circular viral DNA genomes in the samples cut with XhoI ( non-cutter of HPV16 ) , 3 ) determine if the viral DNA is integrated by looking for non-unit length viral DNA fragments in the samples cut with BamHI ( single cutter of HPV16 - data not shown ) , and 4 ) estimate copy number of the viral genome . The HPV16 E6WT genome was capable of replicating extrachromosomally in 56% of populations analyzed , but the HPV16 E6STOP genome was deficient in its ability to replicate extrachromosomally based upon the absence of detectable circular viral genomes ( Figure 1A and Table 1 ) . These results demonstrate that E6 is required for establishment and/or maintenance of HPV16 . Since the HPV16 E6STOP genome contains a stop codon at amino acid 7 , this should also inhibit expression of E6 splice products , E6*I and E6*II [35] , [36] . To determine if one of these proteins was sufficient to support maintenance of HPV16 genomes , NIKS were transfected with HPV16 E6*I and HPV16 E6*II mutant genomes which express 16E6*I or 16E6*II but not full length 16E6 . Southern hybridization and qPCR analysis of NIKS populations transfected and selected for with these mutant HPV16 genomes revealed that expression of E6*I or E6*II in the absence of full-length E6 did not rescue efficient replication of the viral genome . The low copy number levels for the HPV16 E6*I and HPV16 E6*II mutant genomes were sufficiently low that it was undetectable by Southern hybridization ( Figure 1D ) . When quantified by qPCR , the copy numbers of the HPV16 E6*I and E6*II mutant viral genomes were 0 . 11 and 0 . 02 copies per cell copy , respectively , which was well below the 2 . 68 copies per cell observed for HPV16 E6WT genome ( Figure 1E ) . After determining that E6 was required for stable maintenance of the HPV16 genome , we were interested in identifying the activities of 16E6 that are necessary for stable maintenance of HPV16 . To this end , we examined the maintenance of HPV16 genomes containing E6 mutants that differed in their ability to reduce p53 steady state levels . Compared to 16E6WT , the 16E6 R8S/P9A/R10T ( E6SAT ) mutant is deficient for binding p53 , decreasing p53 steady state levels , inhibiting p53-dependent transactivation and attenuating a p53 dependent G1/S growth arrest [39] , [52]–[55] . While deficient for inhibiting p53 activity , the 16E6SAT mutant still binds E6AP and increases telomerase activity at levels comparable to 16E6WT [39] , [53] , [54] . The 16E6I128T mutant binds both E6AP and p53 at 1–5% of the level observed with E6WT and is deficient for decreasing p53 steady state levels , but can prevent E7 induced acetylation of p53 at lysine 382 [48] , [56] . Southern analysis of NIKS transfected with these mutant genomes indicated that the HPV16 E6SAT genome was deficient for plasmid maintenance in NIKS , but the HPV16 E6I128T genome was competent for being maintained as an extrachromosomal genome in NIKS ( Figure 1B and Table 1 ) . Populations of NIKS harboring the HPV16 E6I128T extrachromosomal genome were further passaged to determine if the genome could be stably maintained . We found that the HPV16 E6I128T genome could be maintained extrachromosomally over at least 8 passages ( Figure 1C ) . We were also interested in determining if the C terminus of E6 , which is involved in binding PDZ domain containing proteins [38] , [39] , is required for maintenance of HPV16 . To test this , we used the HPV16 E6Δ146–151 mutant genome in which nucleotides 539–556 were deleted . While lacking the PDZ binding domain of E6 , 16E6Δ146–151 is still able to induce telomerase activity , bind p53 at 33% of the levels of 16E6WT and mediate degradation of p53 at 67% of the levels of 16E6WT [54] , [55] . When transfected into NIKS , this mutant genome was stably maintained as a nuclear plasmid over 8 passages ( Figures 1B , 1C and Table 1 ) . This result demonstrates that the PDZ binding domain of 16E6 is not required for stable maintenance of HPV16 . To ascertain if p53 was functional in NIKS harboring the viral genomes as extrachromosomal , nuclear plasmids ( HPV16 E6WT , E6I128T and E6Δ146–151 ) or in NIKS harboring viral genomes in the integrated state ( HPV16 E6SAT ) , previously frozen populations of NIKS transfected with these genomes were thawed and individual colonies were isolated and expanded . Southern blot analysis confirmed the genomic status of the HPV16 mutant genomes in these clonal populations ( Figure 2 A–D ) . As with the original populations , the derived clone harboring either the HPV16 E6I128T or E6Δ146–151 genomes retained the respective genome as a nuclear plasmid over at least 6 passages ( Figure 2 B–C ) . Consistent with results from our analysis of populations , the HPV16 E6SAT genome was found to be integrated in all of the three screened clones ( Figure 2D ) . The steady state level of p53 in each of these clones was analyzed by western blot . As predicted , the clone harboring the HPV16 E6WT or E6Δ146–151 genome had reduced steady state levels of p53 compared to non-transfected NIKS while NIKS harboring the HPV16 E6SAT or E6I128T genome did not display decreased steady state levels of p53 compared to non-transfected NIKS ( Figure 3A ) . We also analyzed the steady state levels of p53 in at least four independent populations of NIKS harboring HPV16 E6WT or E6I128T mutant genomes and saw similar results ( results not shown ) . Thus , the capacity of the HPV16 genome to be maintained as an extrachromosomal , nuclear plasmid does not correlate with the ability of E6 to reduce the steady state levels of p53; specifically , the E6I128T mutant HPV16 genome , which stably replicates extrachromosomally , fails to cause a decrease in p53 protein levels in the cells . Given this result , we wanted to determine the functional status of p53 in these HPV-positive epithelial cells . p53 function can be tested by measuring the response of cells to actinomycin D . Actinomycin D induces a p53-dependent G1 growth arrest and HPV16 E6 can inhibit this actinomycin D-induced growth arrest [55] , [57]–[59] . A clone of HPV-negative NIKS or a clone of NIKS harboring the HPV16 E6 WT or E6 mutant genomes was treated with vehicle ( DMSO ) or 0 . 5 nM actinomycin D for 24 hours , fixed , stained with propidium iodide and analyzed by flow cytometry to determine the percentage of cells in G1 , S and G2/M phases of the cell cycle ( Figures 3C and 3D ) . In the presence of actinomycin D , a higher percentage of NIKS accumulated at G1 and fewer cells were found in S phase resulting in an increased G1/S ratio compared to vehicle ( Figure 3D ) . Using the Sen-Adichie test for parallelism , the magnitude of change in the G1/S ratio of HPV negative NIKS after vehicle and actinomycin D treatment was compared to NIKS harboring each of the different HPV16 E6WT or mutant genomes . NIKS harboring HPV16 E6WT , E6I128T and E6Δ145–151 genomes significantly reduced the magnitude of change in the G1/S ratio after actinomycin D treatment compared to NIKS not containing HPV ( p<0 . 002 , Figure 3D ) , indicating that p53 was inhibited in its function in these cells . Cells harboring integrated HPV16 E6SAT genomes , when treated with actinomycin D displayed a heightened G1/S ratio indicative of p53 being functional ( Figure 3D ) . One clone of NIKS harboring the HPV16 E6 SAT genome showed a heightened G1/S ratio ( clone C ) , so we also analyzed the ability of clone D and E to attenuate or increase the actinomycin D induced G1/S ratio . The average actinomycin D induced G1/S ratio is shown in Figure 3E and demonstrates that clones harboring HPV16 E6SAT genomes have on average a greater magnitude in change in the G1/S ratio after actinomycin D treatment compared to NIKS not harboring HPV16 and that there is a large amount of variability in this change . Thus , the ability of E6 mutant genomes to be stably maintained as extrachromosomal , nuclear plasmids does correlate with the ability of these E6 mutants to inactivate p53-dependent function . In order to determine if 16E6's inactivation of p53 is sufficient to account for E6's role in plasmid maintenance , we created clones of NIKS transduced with a dominant negative , deletion mutant form of p53 that encodes only amino acids 1–14 and 302–390 of the mouse p53 protein ( p53DD ) [60] , [61] . The p53DD protein oligomerizes with p53WT and inhibits binding of p53WT to p53 specific DNA sequences [60] . This results in inactivation of p53WT as p53WT is consequently unable to transactivate p53 reporter plasmids and natural p53 target genes including p21 and HDM2 [60] , [62] , [63] . Clones of NIKS transduced with the empty retrovirus vector ( LXSN ) or retrovirus expressing pLXSNp53DD were created and total cell lysates were analyzed by western blot to determine the presence of p53DD . As seen in Figure 4A , the low molecular weight form of p53 is seen in p53DD transduced NIKS but not in the cells infected with the vector only . Consistent with previous reports , p53DD transduced NIKS also had increased steady state levels of p53WT [60] . Functional studies were then performed to confirm that p53DD inhibited p53WT in NIKS . We first analyzed the steady state levels of a p53 target gene , p21 , to see if p53DD could attenuate p53-dependent transactivation . After plating NIKS and treating cells for 24 hours with vehicle , 0 . 5 nM actinomycin D or 5 nM actinomycin D , total cell lysates were harvested and steady state levels of p21 were analyzed by western blot . The steady state levels of p21 increased in an actinomycin D dose dependent response in empty vector transduced NIKS , but not p53DD transduced NIKS ( Figure 4B ) . We also tested if p53DD NIKS could attenuate an actinomycin D induced , p53 dependent , G1/S growth arrest by treating cells with vehicle or 0 . 5 nM actinomycin D and analyzing the percentage of cells in G1 and S phase of the cell cycle by flow cytometry as described in the methods . The Sen-Adichie test for parallelism was used to compare the magnitude of change in G1/S ratio after vehicle or actinomycin D treatment in empty vector and p53DD NIKS . As shown in Figure 4C , p53DD NIKS significantly attenuated the actinomycin D induced growth arrest compared to empty vector transduced NIKS ( p<0 . 0001 ) . Together these results demonstrate that the presence of p53DD functionally inactivates p53WT in NIKS . We next asked if cells expressing p53DD could rescue maintenance of HPV16 E6 mutant genomes that were deficient for stable maintenance in parental NIKS . NIKS transduced with p53DD or NIKS infected with the vector only were transfected with wild type or E6 mutant ( E6STOP , E6SAT ) genomes and expanded populations were analyzed by Southern hybridization . While empty vector transduced NIKS supported maintenance of only the HPV16 E6WT genome , p53DD transduced NIKS supported maintenance of HPV16 E6WT , E6STOP and E6SAT mutant genomes ( Table 2 and Figure 5 ) . Thus , inactivation of p53 is necessary to account for E6's role in the maintenance of HPV16 as a nuclear plasmid . We were interested in determining if inactivation of p53 was sufficient to support maintenance of additional high risk HPVs , HPV18 and 31 in the absence of E6 . To test this , empty vector and p53DD transduced NIKS were transfected with HPV31 E6WT , HPV31 E6STOP , HPV18 E6WT or HPV18 E6STOP genomes . In empty vector transduced NIKS , HPV31 E6STOP genomes replicated extrachromosomally at early passages ( passage 1–2 , passage 2 shown in Figure 6A ) , albeit at reduced copy numbers compared to HPV31WT genomes . Since some HPV31 E6STOP genomes were present in empty vector NIKS , we were interested in determining if these genomes were capable of stable maintenance . The HPV31 E6STOP genomes were not detectable at later passages of these same cell populations ( passage 4–8; passage 6 shown in Figure 6B ) . In NIKS expressing p53DD , HPV31 E6STOP was maintained extrachromosomally at late passages but at a lower copy number compared to HPV31 E6 WT genomes in p53DD transduced NIKS ( Figures 6B ) . In empty vector transduced NIKS , HPV18 E6STOP genomes also replicated extrachromosomally at early passages ( passage 1–2 , passage 2 shown in Figure 6C ) with copy numbers similar to that of HPV18 E6WT . At later passages ( passage 4–8; passage 6 shown in Figure 5D ) , however , we again saw loss of HPV18 E6STOP replicons . In 2 of the 3 populations , there were barely detectable viral genomes present at passage 6 , while the third population showed a reduced copy number compared to the populations harboring HPV18 WT . By passage 8 the latter population that retained low copies of HPV18 E6STOP at passage 6 had barely any detectable HPV18 signal ( data not shown ) . In p53DD NIKS , all three populations that harbored HPV18 E6STOP at passage 2 retained it at passage 6 , although there was a trend for the copy number of these genomes to decrease in comparison to HPV18 E6WT genomes in p53DD NIKS . Thus in the case for high risk HPV31 and 18 genomes , stable maintenance , as defined here as the retention of extrachromosomal replicons over at least 8 passages , depends heavily on the presence of the E6 oncogene , and this dependence can be partially rescued by inactivation of p53 . It is possible that the ability of HPV18 and 31 E6 null genomes to be maintained at low levels in early passages of NIKS is due to the immortalization characteristic of NIKS . To determine if this was the case , we co-transfected primary human foreskin keratinocytes ( HFKs ) with a drug resistance gene and either the HPV18 E6WT or E6STOP genome . Southern blot analysis of low molecular weight DNA from these cells , taken at 5 . 5 weeks post transfection when the cells had expanded sufficiently , demonstrated that HPV18 E6WT and E6STOP reproducibly replicated extrachromosomally in HFKs ( Figure 6E ) . As observed in NIKS cells , the HPV18 E6STOP mutant genome replicated at a lower copy number compared to HFKs transfected with HPV18 E6WT mutant genome ( Figure 6E ) .
Our studies demonstrate that HPV16 E6 is required for maintenance of the HPV16 genome as an extrachromosomal nuclear plasmid and that inactivation of p53 by dominant negative p53 ( p53DD ) is sufficient to support maintenance of the HPV16 genome in the absence of E6 ( Figure 5 ) . Inactivation of p53 was also necessary to support maintenance of HPV16 since the HPV16 E6SAT mutant genome , which is deficient for inactivating p53 , was maintained only in NIKS transduced with p53DD ( Table 2 ) . Furthermore the ability of two other mutant genomes HPV16 E6I128T and HPV16 E6Δ146–151 to inactivate p53 ( as shown by their ability to attenuate a p53-dependent G1/S growth arrest ) correlated with the ability of these genomes to be maintained extrachromosomally ( Figures 1B , 3C and 3D ) . While inactivation of p53 was necessary for maintenance of HPV16 extrachromosomal genomes , decreased steady state levels of p53 were not necessary since the HPV16 E6I128T mutant is maintained extrachromosomally yet is deficient for decreasing p53 steady state levels ( Figure 3A ) . While the E6I128T mutant is deficient for decreasing p53 steady state levels , this mutant is capable of preventing E7 mediated acetylation of p53WT at lysine 382 [56] . Acetylation of p53 at K382 increases the ability of p53 to bind DNA and the ability of E6 mutants to inhibit p53 K382 acetylation correlates with the ability of 16E6 mutants to resist interferon induced growth arrest [56] , [64] . Thus , while the E6I28T mutant may not mediate p53 degradation , it may inhibit p53 function by preventing p53 acetylation . Cells harboring integrated HPV16 E6 SAT genomes had an increased magnitude of change in the G1/S ratio after actinomycin D treatment . There is no obvious explanation for this enhanced G1 arrest . It is possible that it reflects a consequence of this HPV genome being integrated in the host cell resulting in altered expression of cellular and/or other viral genes . Our results also demonstrate that the PDZ binding domain of 16E6 is not required for stable maintenance of HPV16 because the HPV16 E6Δ146–151 ( deletion of nucleotides 539–556 ) does not contain the PDZ binding domain yet is maintained extrachromosomally ( Figure 1B ) . Others have demonstrated that an HPV16 E6 mutant with a stop codon introduced at amino acid 148 , which truncates 16E6 at the PDZ binding domain , is deficient for stable maintenance [65] . Although both of these mutants lack the PDZ binding domain , the subtle differences in the specific mutations at the C terminus may differentially affect function and regulation of the 16E6 protein . As an example of how different C terminal mutations in E6 function , Kiyono et al . demonstrated that human mammary epithelial cells ( HMECs ) transduced with 16E6Δ140–151 fail to increase telomerase activity and fail to become immortalized while HMECs transduced with 16E6Δ146–151 can induce telomerase activity and can become immortalized [53] . It is possible that the 16E6Δ146–151 mutant removes a negative regulatory element of HPV16 E6 , and this may account for the difference between our studies and the studies of Nicolaides et al [65] . Consistent with a previous report that HPV31 E6 is required for maintenance of HPV31 as extrachromosomal replicons [23] , we detected only low levels of extrachromosomal HPV31 E6STOP genomes at early passages ( passages 1–2 ) , and these genomes were not detectable by passage 4 . Inactivation of p53 rescued the ability of HPV31 E6STOP genomes to be stably maintained to passage 6 albeit at lower copy numbers than HPV 31 E6WT genomes ( Figure 6B ) . In contrast , HPV18 E6STOP was maintained extrachromosomally in empty vector NIKS both at early and late passages , albeit at greatly reduced efficiency at the later passages ( i . e . , only 1 of 3 populations of HPV18 E6STOP retained detectable extrachromosomal HPV18 in the empty vector NIKS at passage 6 , compared to 3 out of 3 retaining it at passage 2 ) . These results indicate that there may be less of a requirement for E6 in the maintenance of HPV18 replicons than in HPV16 and HPV31 . HPV18 E6STOP genomes were also maintained extrachromosomally but at lower copy numbers compared to HPV18 in HFKS , demonstrating that these results are not specific to NIKS . Inactivation of p53 did increase the capacity of the HPV18 E6STOP to replicate extrachromosomally over time , as all 3 populations of HPV18 E6STOP transfected p53DD NIKS retained extrachromosomal HPV18 at passage 6 ( Figure 6D ) . Thus , we conclude that E6's inactivation of p53 contributes to plasmid maintenance for all three HPV genotypes tested . Our detection of replicated HPV18 E6STOP and HPV31 E6STOP in early passages of NIKS demonstrates that E6 is not absolutely required for the establishment of the HPV18 and HPV31 genome as an extrachromosomal replicon . This is not surprising as it has been previously shown that the papillomaviral E1 and E2 proteins are sufficient to drive replication of plasmids containing the origin of papillomavirus DNA replication [15]–[17] . This result is also consistent with those published by Wang et al . , which demonstrate that HPV18 E6 is required for robust amplification of HPV18 , but nonetheless some amplification is detected in organotypic rafts of HFKs harboring genomes deficient in full-length E6 [31] . It is impossible to determine the requirement of 16E6 in the establishment of HPV16 given the absence of replicated HPV16 E6STOP at early passages . That we could not detect HP16 E6STOP genomes in empty vector NIKS at early passages may simply reflect the difference in the efficiency of replication of these genotypes in NIKS . HPV16 E6WT routinely gives rise to lower copy numbers of replicated viral genomes in NIKS ( approximately 1–10 copies/cell ) when compared to HPV31 and HPV18 ( >50 copies/cell ) as observed through Southern blot analysis . Interestingly , ectopic expression of p53 attenuates establishment replication of BPV-1 , HPV-16 and HPV-18 origin of replication in cells also expressing the respective E1 and E2 genes but does not affect maintenance of at least the BPV-1 origin of replication [66]–[69] . We have observed that inactivation of p53 rescues maintenance of HPV18 and 31 E6 null genomes at early passages , but the copy number/stable maintenance of HPV18 and 31 E6 null genomes decreases with time . Thus , it is possible that inactivation of p53 by E6 alleviates the negative influence of p53 during establishment and early maintenance . This could explain why inactivation of p53 restores copy numbers of HPV18 and 31 E6 null genomes to copy numbers seen in WT genomes at early passages but not late passages . The trend of HPV18 and 31 E6 null genomes to decrease in copy number over time in NIKS expressing p53DD ( Figure 6C and 6D ) may indicate that there are other activities of E6 that contribute to its role in stable plasmid maintenance . Alternatively , it is possible that residual p53 activity in the NIKS expressing p53DD ( Figure 3B ) is detrimental to the continued maintenance of HPV18 and HPV31 E6 deficient genomes . Inactivation of p53 not only restored maintenance of HPV16 in the absence of 16E6 , but also increased the efficiency of maintenance of HPV16 E6WT genomes: the HPV16 E6WT genome was maintained in 38% of empty vector populations vs 82% of p53DD populations ( Table 2 ) . One interpretation of this result is that HPV16 E6 is less efficient than p53DD at inactivating p53 and that the retention of some functional p53WT in NIKS harboring HPV16 E6WT genomes is responsible for attenuating HPV16 replication . This is consistent with others' findings [66] , [68] . However , because the HPV16 E6WT genome replicated in 82% of the p53DD populations , whereas the HPV16 E6STOP genome replicated in only 38% of the p53DD populations and the HPV16 E6SAT genome replicated in only 50% of the p53DD populations , we further raise the possibility that an additional function of E6 , independent of p53 inactivation , contributes to maintenance of HPV16 . We hypothesize that this additional function of 16E6 is independent of the ability of HPV16 E6 to increase telomerase activity because HPV16 E6SAT can increase telomerase activity [53] , [54] but is not maintained as efficiently as HPV16 E6WT genomes in p53DD NIKS , and because NIKS are inherently immortalized independent of E6 [50] . One possible role of 16E6 that may contribute to maintenance of HPV16 is E6 mediated transcription from the HPV16 LCR [70] , [71] . Inactivation of p53 may be important to prevent apoptosis or senescence induced by the presence of the HPV genome and consequently E6 may prevent the loss of cells stably retaining HPV genomes . HPV-induced apoptosis or senescence could be triggered by the induction of DNA damage responses ( DDR ) . During establishment of HPV18 , Reison et al . demonstrated that the HPV18 genome co-localizes with γH2AX , a marker of DDR , [72]–[75] and likewise during maintenance of HPV31 , the HPV31 genome co-localizes with several DDR components including pATM ( S1981 ) , γ-H2AX , 53BP1 , Brca1 and Chk2 [76] . The ability of high risk HPV genomes to activate the DDR can be extended to HPV16; Sakakibara et al . demonstrated that human foreskin keratinocytes ( HFKs ) harboring extrachromosomal HPV16 , 18 and 31 genomes express higher amounts of phosphorylated Chk2 ( T68 ) than normal HFKs [77] . Activation of ATM as a consequence of DNA damage can lead to subsequent phosphorylation of p53 and consequently growth arrest , senescence and apoptosis ( reviewed in [78] ) . If the DNA damage response activated during the life cycle of HPV leads to activation of p53 , HPV E6 may be needed to inactivate p53 and thereby allow for the survival of the host cell . While we have attempted to follow the fate of cells transfected with HPV16 E6WT , E6STOP and E6SAT genomes , low transfection efficiencies of NIKS hampered our ability to determine if cells transfected with HPV genomes defective for inactivating p53 underwent a higher rate of growth arrest or apoptosis at early times following transfection . Results by Lepik et al . , however , show that while ectopic expression of p53 attenuates papillomavirus replication during establishment , p53 expression failed to induce detectable apoptosis or growth arrest [66] . Alternatively , but not necessarily exclusively , HPV E6 may need to inactivate of p53 in order to attenuate an interferon-mediated innate immune response that could inhibit stable maintenance of HPV . An interplay between p53 and the interferon response pathway has been previously linked to inhibition of Sendai virus and vesicular stomatitis virus replication and may have similar effects on HPV replication [79] , [80] . Consistent with this prediction , loss of extrachromosomal HPV16 genomes is correlated with an increased transcription of interferon-inducible genes [81] and treatment with interferon causes the loss of extrachromosomal papillomaviral genomes [82]–[84] . Notably , both HPV16 E6 and p53DD can decrease transcription of several interferon-induced genes in keratinocytes [85]–[87] . Thus , another possible explanation for how p53DD rescues the maintenance of HPV16 E6STOP genomes and confers stable maintenance of HPV18 and 31 E6 STOP genomes is the ability of p53DD to attenuate interferon signaling . Whether HPV needs to inactivate p53 in order to abrogate DNA damage responses or to inhibit interferon responses may not be mutually exclusive , since double stranded breaks can enhance interferon signaling through p53-dependent mechanisms [79] , [88] , [89] . Future work will be required to determine the exact reason behind the requirement of p53 inactivation for maintenance of HPV16 and stable maintenance of HPV18 and 31 and to identify additional roles of E6 that may contribute to maintenance of these genomes . Since p53WT negatively impacts establishment , maintenance and amplification of HPV papillomavirus genomes , it will be of interest to determine if p53 inhibits these different stages of replication in similar or different ways . Regardless , our results raise the interesting concept that drugs that can reactivate p53 in HPV-infected cells should be effective at eliminating persistent high-risk HPV infections and thereby reduce the risk of HPV-associated cancers in infected patients .
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Human papillomaviruses ( HPVs ) infect epithelial tissues . HPVs that infect mucosal epithelia cause infectious lesions in the anogenital tract and oral cavity . HPV infections are normally cleared by the immune system; however , in rare cases , infections can persist for years . Persistent infections by certain HPVs place one at a high risk of developing carcinomas of the cervix , other anogenital tissues , and the head/neck region . These HPVs are responsible for over 5% of all human cancers . For an HPV infection to persist , the viral circular genome must be maintained , i . e . replicated and inherited during cell division . In this study we define the mechanism by which the viral gene E6 contributes to the maintenance of the HPV genome . We demonstrate that E6 must inactivate the cellular factor , p53 , for the viral genome to be maintained . Significantly , p53 , is inactivated in many types of human cancers and because much research has been done on p53 , promising new drugs have been identified that can re-activate p53 . If such drugs can re-activate the p53 that has been inactivated by E6 , then we hypothesize that these drugs could be used to cure patients with persistent HPV infections and thereby reduce their risk of developing HPV associated cancers .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2013
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Inactivation of p53 Rescues the Maintenance of High Risk HPV DNA Genomes Deficient in Expression of E6
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Syndromes of hybrid dysgenesis ( HD ) have been critical for our understanding of the transgenerational maintenance of genome stability by piRNA . HD in D . virilis represents a special case of HD since it includes simultaneous mobilization of a set of TEs that belong to different classes . The standard explanation for HD is that eggs of the responder strains lack an abundant pool of piRNAs corresponding to the asymmetric TE families transmitted solely by sperm . However , there are several strains of D . virilis that lack asymmetric TEs , but exhibit a “neutral” cytotype that confers resistance to HD . To characterize the mechanism of resistance to HD , we performed a comparative analysis of the landscape of ovarian small RNAs in strains that vary in their resistance to HD mediated sterility . We demonstrate that resistance to HD cannot be solely explained by a maternal piRNA pool that matches the assemblage of TEs that likely cause HD . In support of this , we have witnessed a cytotype shift from neutral ( N ) to susceptible ( M ) in a strain devoid of all major TEs implicated in HD . This shift occurred in the absence of significant change in TE copy number and expression of piRNAs homologous to asymmetric TEs . Instead , this shift is associated with a change in the chromatin profile of repeat sequences unlikely to be causative of paternal induction . Overall , our data suggest that resistance to TE-mediated sterility during HD may be achieved by mechanisms that are distinct from the canonical syndromes of HD .
Transposable elements are selfish elements that have the capacity to proliferate in genomes even if they are harmful [1] . In response to this threat , mechanisms of small-RNA based silencing have evolved to limit TE proliferation . In the germline of animals , Piwi-interacting RNAs ( piRNAs ) function to maintain TE repression through both transcriptional and post-transcriptional silencing [2] . Critically , the epigenetic and transgenerational nature of piRNA-mediated TE control has been revealed by syndromes of hybrid dysgenesis ( HD ) [3 , 4] . HD is a syndrome of TE-mediated sterility that occurs when males carrying active copies of TEs are crossed with females where such copies are rare or absent [5–7] . The hybrid dysgenesis syndrome ( HD ) is defined as a combination of various genetic disorders such as genic mutations and chromosomal aberrations that lead to sterility in the progeny of intraspecific crosses [5–7] . Sterility during HD is mediated by mobilization of certain TE families carried by the paternal genome and absent in the maternal genome [6 , 7] . To date , there are several independent HD systems in Drosophila melanogaster . The most well described are the I-R and P-M systems , controlled by the I-element ( a non-LTR ( long terminal repeat ) retrotransposon ) and the P-element ( a DNA transposon ) , respectively [6–8] . Activation of paternally inherited TEs is explained by the fact that only the female maintains transgenerational TE repression via piRNAs transmitted through maternal deposition . When the female genome lacks certain TE families , female gametes also lack piRNAs that target these families . Thus , TE families solely transmitted through the male germline become de-repressed in the absence of repressive piRNAs inherited from the mother [2–4 , 9] . HD in D . virilis was initially observed when males of laboratory strain 160 and females of wild-type strain 9 were crossed . The F1 progeny exhibited up to 60% sterility , while sterility in the progeny of reciprocal crosses did not exceed 5–7% [10] . Similar to the D . melanogaster P-M system , the sterility of hybrids from dysgenic crosses is apparently the result of abnormal development ( atrophy ) of male and female gonads [10–12] . By analogy with the P-M system , strain 160 and strain 9 were called “P-like” ( P ) and “M-like” ( M ) , respectively . In contrast to I-R and P-M systems , the study of HD in D . virilis has demonstrated that multiple unrelated TEs belonging to different families are mobilized in dysgenic progeny [13–16] . The TEs presumably causal of dysgenesis and absent in M-like strain 9 include Penelope ( a representative of the Penelope-like element ( PLE ) superfamily ) , Paris and Polyphemus ( DNA transposons ) , as well as a non-LTR retrotransposon Helena [13–16] . A typical M-like strain 9 contains only diverged inactive remnants of these TEs . Additionally , piRNAs targeting Penelope , Paris , Polyphemus and Helena are highly abundant in the germline of strain 160 and are practically absent in strain 9 [17 , 18] . Thus , it has been suggested that the combined activity of these four asymmetric TEs , present only in strain 160 , underlies gonadal atrophy and other manifestations of HD in D . virilis . This large asymmetry in TE abundance between strains suggests that HD in D . virilis may be considered a model for understanding the consequences of intermediate divergence in TE profiles within a species . Nonetheless , recent studies have called into question whether the standard model of HD–described in D . melanogaster where sterility is caused by the absence of maternal piRNAs that target specific inducing TE families—applies in D . virilis [3 , 4 , 18 , 19] . This is because several “neutral” ( N ) strains exhibit “immunity” to HD in dysgenic crosses but lack maternal piRNA corresponding to Penelope elements , the presumptive primary driver of dysgenesis [19] . If Penelope is a key driver of dysgenesis , how do neutral strains exhibit "immunity" in the absence of maternally transmitted Penelope piRNA ? Two fundamental issues arise . First , as observed in D . melanogaster , is there a single major element that serves as a key driver of HD in D . virilis ? Second , do N-strains confer their resistance to HD solely through maternally provisioned piRNA or through alternate mechanisms ? Despite significant progress in understanding the morphogenetic events occurring during gametogenesis and embryogenesis in the progeny of D . virilis dysgenic crosses , these questions still need to be answered [11 , 18] . To answer these questions , by using small RNA deep-sequencing and qPCR , we decided to perform a comparative survey of maternal piRNA profiles across several “neutral” strains of different origin that did not quite fit the HD paradigm developed in the previous studies of this phenomenon [3 , 4 , 9 , 19] . Additionally , we developed transgenic strains containing a presumptive causative TE and did not detect a cytotype change after its propagation in the genome . The accumulated data failed to pinpoint a single TE or specific set of TEs responsible for their “immunity” and support a model in which resistance to TE-mediated sterility during dysgenesis may be achieved by a mechanism that varies across strains . We thus propose an alternate model to explain resistance to TE mediated sterility in D . virilis . Instead of solely being explained by maternal piRNAs that target inducing TE families , the chromatin profile of repeats in the maternal genome may confer general immunity to the harmful effects of TE mobilization .
To characterize the piRNA profiles across diverse strains that vary in resistance to HD , we performed small RNA sequencing on six D . virilis strains obtained from various sources ( see Materials and Methods ) and maintained in our laboratory for more than 20 years . These strains exhibit different levels of gonadal atrophy when crossed with males of P-like strain 160 . Two of them ( 9 and 13 ) represent strong M-strains ( they exhibit up to 65% of gonadal atrophy in the F1 progeny of the dysgenic cross ) and four ( 140 , Argentina , Magarach and 101 ) behave as “neutral” or N-strains when crossed with strain 160 males and , hence , did not exhibit gonadal atrophy ( less than 10% atrophied gonads ) in such crosses ( Fig 1 ) . Previous studies suggest Penelope element as a key driver of HD in D . virilis [15 , 20 , 21] . However , while N-strains 140 and Argentina both carry Penelope elements , two other N-strains–Magarach and 101 contain neither functional Penelope copies nor Penelope-derived small RNAs [19] . This observation questions the key role of Penelope as a factor determining HD in D . virilis and suggests that piRNAs targeting other asymmetric TEs , e . g . Polyphemus , Helena and possibly Paris , may provide immunity to HD [14 , 15 , 17 , 21 , 22] . To explore this possibility we performed a comparative analysis of both classes of small RNAs ( piRNAs and siRNAs ) in the ovaries of all selected M- and N-strains using the extended list of TEs and other repeats recently defined in D . virilis genome [18] . This analysis indicates that the total repertoire of targets for small RNA silencing in strain 160 ( P ) is significantly higher than in all other studied strains ( Figs 2A , 2B , S1A and S1B ) . Surprisingly , the global piRNA profile for known D . virilis TEs and other repeats is more similar between strain 160 ( P ) and M-strains ( R ( 160:9 ) = 0 . 83; R ( 160:13 ) = 0 . 74 , Spearman’s correlation coefficient ) than between strain 160 ( P ) and several N-strains ( R ( 160:140 ) = 0 . 71; R ( 160:101 ) = 0 . 7 ) ( Fig 2A and 2B ) . This suggests the possibility that protection is not mediated by a general maternal piRNA profile , but rather to certain specific TEs yet to be identified . To identify such candidates , we compared sets of piRNA targets distinguishing strain 160 ( P ) from both typical M-strains , 9 and 13 , and obtained a list of ten TEs in common across comparisons ( Fig 2C ) . These are TEs for which piRNAs are more abundant in strain 160 ( P ) when compared to both M-strains: Polyphemus , Penelope , Paris , Helena , Uvir , Skippy , 190 , 463 , 608 , and 1012 . However , comparing 160 ( P ) and N-strains , we find that piRNAs from Helena and Skippy are uniquely found at high levels in strain 160 ( P ) . Thus , if neutrality is conferred by piRNAs that uniformly target the same TE family or families , Helena and Skippy piRNAs are not likely to be required to prevent HD . However , among the eight remaining candidates , there is no shared family among the neutral strains ( N-strains and 160 ( P ) ) that have a piRNA profile that is similar across strains . For example , in contrast to 160 ( P ) , Penelope-derived piRNAs are more lowly expressed in strain Magarach ( N ) , Polyphemus-targeted piRNAs are more lowly expressed in strain 101 ( N ) and , finally , Paris-related piRNAs are lowly expressed in strain Argentina ( N ) and in strain 101 ( N ) ( Fig 2D ) . Thus , we failed to detect one candidate causative TE or combinations of certain TEs present in all neutral strains whose piRNAs guarantee immunity to HD ( Fig 2D ) . This suggests the possibility that maternal protection in crosses with strain 160 ( P ) males may be conferred by different mechanisms across the strains . A similar comparative analysis of siRNA expression between strain 160 ( P ) and M-strains demonstrated that siRNAs complementary to only Penelope and Helena elements are absent in the ovaries of strain 9 ( M ) and 13 ( M ) ( S1A and S1B Fig ) . However , we detected Penelope-homologous siRNAs only in half of the studied neutral trains i . e . strains Argentina and 140 ( S1C Fig ) . In the context of immunity to HD syndrome manifestations , probably the most important condition is to constantly maintain effective piRNA production in the germline . It is well known that ovarian piRNA pools consist of molecules generated by primary and secondary processing mechanisms . Due to germline expression of Ago3 and Aub proteins necessary for secondary processing ( “ping-pong” amplification ) , the germline specific piRNA pool can be assessed quantitatively by counting of “ping-pong” pairs [2 , 23] . We analyzed the “ping-pong” signature of piRNAs to the selected TEs and showed that these piRNA species contain ping-pong pairs in varying degrees ( S2 Fig ) . Importantly , all of them exhibit a signature of secondary piRNA processing indicating that production of these piRNAs takes place in the germline but each element lacks such a ping-pong signature in at least one or more of the neutral strains . In addition , Penelope expression was previously shown to be germline-specific by whole-mount RNA in situ hybridization [24] . In the present study , using the same technique with the ovaries of P-strain 160 , we confirmed that Paris , Polyphemus and Helena elements exhibit germline-specific expression pattern as well ( S3 Fig ) . We further examined the pattern of divergence among piRNAs that map to the consensus TEs since piRNAs derived from divergent sequences are likely derived from degraded TE insertions . Among the selected HD-implicated TEs , the ovarian piRNA pool contains a very small amount of Paris-targeting piRNAs that were detected only in two studied N-strains—140 and Magarach . Interestingly , only 10% of both sense and antisense-oriented piRNAs apparently originate from modern active copies of Paris elements while the rest of the Paris-complementary piRNAs were produced from ancestral highly diverged ones ( S4 Fig ) . The same applies to the Penelope-derived piRNAs in strain 101 ( N ) . All other piRNA species to HD-implicated TEs , especially in the antisense-orientation , in all studied neutral strains were practically identical to the consensus and , hence , apparently originated from active copies of these elements ( S4 Fig ) . This analysis further indicates that there is no active candidate inducer family , represented by sequence similar piRNAs , shared across all six neutral strains . Overall , these data indicate that , in terms of piRNA-mediated protection to HD in D . virilis neutral strains , there is no general rule in the context of ovarian piRNAs complementary to particular TEs implicated in HD . In other words , in neutral strains the maternally transmitted piRNA pool may include different amounts of piRNAs corresponding to various TEs and the repertoire of these TEs often radically differs between the strains with same cytotype . Syndromes of HD are explained by maternal protection against paternal induction and Penelope has long been considered the primary driver of paternal induction [18 , 20 , 22] . In the previous section we demonstrated that maternal piRNAs that target Penelope are not necessary to confer neutrality but , as neutrality may arise through different mechanisms , we sought to determine whether Penelope was either sufficient for induction or Penelope piRNA sufficient for protection . We thus characterized a simulation of natural invasion through the analysis of two transgenic strains of D . virilis containing full-size Penelope copies introduced into a typical D . virilis M-like strain 9 ( the stock is assigned as w3 ) originally devoid of functional copies of this TE . Our previous experiments demonstrated that introduced Penelope underwent active amplification and occupied more than ten sites in the chromosomes of the transgenic strains [19] . However , at that time ( in 2012 ) we did not detect any Penelope-derived small RNA species in these transgenic strains . Subsequent to the early analysis performed in 2011–2012 , we have now found that Penelope is actively transcribed in these two strains and exhibits steady-state RNA levels equal to or even higher than in strain 160 ( Fig 3A ) . We further observed piRNAs in both transgenic strains , indicating that some of Penelope copies acquired the properties of piRNA-generating locus ( Fig 3B ) . Thus , in strain Tf2 the level of piRNAs homologous to Penelope is only half as much as that observed in P-like strain 160 . The analysis of Penelope-derived piRNAs indicates a distribution of piRNAs along the entire Penelope body and clear-cut ping-pong signature ( Fig 3B ) . Similar to strain 160 , more than half of the Penelope-derived piRNAs in both strains originate from active and highly similar Penelope copies with few mismatches to the canonical sequence ( Fig 3C ) . In contrast , Penelope piRNAs identified in the untransformed M-like strain 9 ( w3 ) are highly divergent and likely derive from inactivated Penelope copies ( termed “Omegas” ) located in heterochromatic regions of the genome [25 , 26] . Interestingly , the pool of Penelope derived small RNAs in transgenic strains are primarily piRNAs . This is in contrast to inducer strain 160 and D . melanogaster strains transformed with Penelope [19] , where Penelope-derived siRNAs are the major class ( S5 Fig ) . Surprisingly , both transgenic strains containing multiple Penelope copies and abundant piRNAs behave exactly as the original M-like strain 9 in dysgenic crosses ( Fig 4 ) . They neither have the capacity to induce HD paternally nor protect against HD maternally . Therefore , the introduction of full-size Penelope into an M-like strain accompanied by its propagation , active transcription and piRNAs production was not sufficient to modify the cytotype . These results also indicate that the presence of piRNA complementary to Penelope in the oocyte is not the only prerequisite to prevent gonadal sterility when crossed with males of P-like strain 160 . Along these lines , it has been shown recently that the number of P-element and hobo copies per se has very little influence on gonadal sterility suggesting that HD is not determined solely by the dosage of HD-causative elements [27] . The above results demonstrate that the maternal piRNAs that target all , or even most , asymmetric TEs that likely cause dysgenesis are not necessary to confer neutral strain status ( Fig 2 ) . Furthermore , Penelope piRNAs are not sufficient for maternal protection and the presence of active Penelope copies is not sufficient for paternal induction ( Figs 3 and 4 ) . This begs the question: What are the necessary and sufficient factors of HD in D . virilis ? Among the analyzed strains , neutral strain 101 represents a special case . This is due to the fact that the genome of this strain does not produce piRNAs to the most-described HD-implicated TEs , e . g . Paris , Helena , Polyphemus and a very small amount of divergent Penelope-homologous piRNAs ( Figs 2 and S4 ) . In the course of our long-term monitoring of the gonadal atrophy observed in the progeny of dysgenic crosses involving P-like strain and various laboratory and geographical strains of D . virilis , we often observed significant variation in the level of sterility in the progeny of the same crosses occurring with time . Strikingly , among these strains , we have identified a spontaneous change from neutral cytotype to M-like one . Thus , while an old laboratory strain 101 kept in the Stock Center of Koltzov Institute of Developmental Biology RAS maintained a neutral cytotype for the whole period of observation ( 2011–2017 ) the same strain kept in our laboratory gradually became M-like strain ( Fig 5 ) . We considered the possibility that this shift in cytotype could be explained by changes in the TE profile between the strains . Surprisingly , Southern blot and PCR analyses demonstrate that 101 N- and M- substrains have identical TE profiles for Penelope , Paris , Polyphemus and Helena ( Figs 6A and S6 ) . Additionally , qPCR analysis failed to detect any significant changes in the expression levels of the major asymmetric TEs as well as other described TEs in the compared variants ( neutral vs M-like ) of this strain ( Fig 6B ) . These data rule out the possibility of strain contamination with a lab M-strain . To understand the observed differences in the cytotype of strain 101 variants we performed additional small-RNA sequencing . Indeed , the piRNA profile of strain 101 ( N ) has significantly higher piRNA levels ( compared to 101 ( M ) ) for five previously undescribed repeats ( 315 , 635 , 850 , 904 and 931 ) ( Fig 7A ) , indicating that differences in cytotype could be attributed to these repeats . Among these piRNA species , only piRNAs targeting 315 and 635 elements comprise many ping-pong pairs and , hence , are generated predominantly by germline-specific secondary processing mechanism ( Fig 7B ) . Based on sequence similarity to the TE consensus , at least 25% of antisense-oriented piRNA molecules apparently originated from modern active elements , with the exception of piRNAs targeting the 904-element ( S7A Fig ) . Focusing on the three elements ( 315 , 635 , 850 ) with maximal piRNA expression levels , we compared both variants of strain 101 in more detail to determine if differences in repeat profile could explain differences in cytotype . Element 315 encodes three open reading frames ( ORF ) . According to the protein-domain structure , two ORFs appear to encode gag and pol genes . The third ORF has no homology to the described TEs and possibly encodes an env gene . Thus , element 315 probably represents a retroelement . Since we failed to find any homology of the 315 element to the described families of TEs in Sophophora subgenus we propose that this element is an exclusive resident of Drosophila subgenus . Element 635 has some homology to the Invader element of D . melanogaster , which belongs to the Gypsy family of LTR-containing retrotransposons . However , it has no long terminal repeats ( LTRs ) in its sequence . Finally , short 850 element ( 749 nt ) doesn’t encode any ORF and seems to be non-autonomous . Importantly , based on Southern blot and PCR analysis , these particular repeats did not undergo amplification in the neutral variant of strain 101 and both compared substrains exhibit identical restriction patterns of these elements , similar to that of P-like strain 160 ( S7B and S7C Fig ) . Hence , the observed cytotype shift as well as the differences in piRNA pool to these elements apparently do not stem from differences in copy number among 101 substrains . Interestingly , we observed a significant increase of expression levels of 315 and 635 elements ( p < 0 . 05; t-test ) , but not 850 , in the ovarian mRNA pool of M-like substrain 101 compared to the neutral substrain ( Fig 7C ) . Overall , these results demonstrate that the capacity for these repeats to produce piRNAs is lower in the 101 ( M ) strain , even in the absence of movement . What could lead to differences in the piRNA profile for these repeats between the 101 ( N ) and 101 ( M ) strains in the absence of movement ? Studies of piRNA-generating loci in Drosophila revealed that the H3K9me3 mark , which serves as a binding site to recruit HP1a and its germline homolog Rhino , is required for transcription of dual-strand piRNA-clusters and transposon silencing in ovaries [2 , 28 , 29] . We hypothesized that a shift of the chromatin state in strain 101 modified the ability of particular genomic loci , carrying 315 , 635 , 850 elements , to produce piRNA species . These changes in piRNA profile may be an indication of a chromatin-based modification that may confer resistance to HD sterility in the neutral 101 substrain . To test this hypothesis , we estimated the levels of H3K9me3 and HP1a marks by ChIP combined with qPCR analysis in the ovaries of two cytotype variants of strain 101 . The analysis showed significant increase of H3K9me3 levels on genomic regions containing 315 , 635 and 850 elements ( enrichment > 2 . 5 , p < 0 . 05 ) as well as slight increase of HP1a enrichment in the neutral variant of strain 101 compared to the M-like substrain ( Figs 7D and S8 ) . In turn , Ulysses carrying regions used as a control demonstrated equal levels of the H3K9me3 mark , consistent with Ulysses-targeting piRNA levels being almost equal in the strain 101 variants ( Fig 7D ) . This indicates that certain repeats have experienced shift in their chromatin profile , but that this shift is not global . A similar phenomenon has been recently described in I-R HD system in D . melanogaster [30] . In that comparative analysis of two reactive strains ( weak and strong ) , it was shown that despite having a similar number of copies of the I-element , these strains significantly differ by enrichment of Rhino at the 42AB piRNA-cluster containing I-elements remnants . Furthermore , a lower level of I-element targeted piRNA species was observed in the strong-reactive strain as a result [30] . Given these differences , it is possible that these elements are the primary drivers of dysgenesis in D . virilis . To further test the hypothesis that activation of these elements could contribute to HD , we compared first piRNA levels of all these elements in the ovaries of the F1 progeny from dysgenic-like and reciprocal crosses using variants of strain 101 and P-like strain 160 . These experiments demonstrate that piRNAs targeting 315 , 635 , and 934 elements showed similar levels in the ovaries of F1 hybrids from dysgenic crosses ( 101 ( N ) x 160 ) and parental neutral strain 101 , but lower levels in progeny of reciprocal crosses where such piRNAs would not be maternal ( 160 x 101 ( N ) ) ( Fig 7E ) . Thus , the maternally provisioned piRNAs complementary to 315 , 635 and 931 elements are required to stimulate the generation of the corresponding piRNAs in the progeny , as shown in other systems of HD [3 , 4] . However , in the analysis of steady-state mRNA levels of these TEs in the ovaries of dysgenic and reciprocal progeny of crosses between 101 substrains and P-like strain 160 , we failed to obtain any induction of 315 , 635 and 850 elements exceeding their levels of parental strains ( Fig 7F and 7G ) . On the contrary , the ovaries of F1 hybrids from the reciprocal ( non-dysgenic ) crosses involving strains 101 ( N ) males and 160 ( P ) females showed even significantly higher expression levels of these elements in comparison to dysgenic ones . Moreover , the dysgenic and reciprocal hybrids of M-like substrain 101 and strain 160 ( P ) showed no differences in the mRNA levels of the studied elements ( Fig 7F and 7G ) . These results indicate that activation of these elements per se is unlikely to be causative to HD because 101 ( N ) and 101 ( M ) have identical TE profiles . We therefore considered the possibility that what distinguishes strain 101 ( N ) from 101 ( M ) may have an epigenetic basis or , alternately , an unknown genetic change that alters repeat chromatin . If so , then lack of piRNAs to these elements in 101 ( M ) could explain the M-cytotype . To test this , we compared piRNA levels and family level abundance with inducer strain 160 ( P ) . Critically , none of these elements show increased piRNA levels in strain 160 ( P ) compared to strain 9 ( M ) ( Fig 7H ) . Thus , asymmetry in the piRNA pool for these particular elements is not a necessary condition for dysgenesis . According to the recent studies differences in parental expression levels of genic piRNAs may contribute to the dysgenic manifestations in the progeny [18 , 30] . With this in mind , we compared the expression of genic piRNAs in the ovaries of both 101 substrains and did not observe significant differences in their levels ( S9A Fig ) . Ping-pong of genic piRNA profiles are also exhibit high similarity between these strains ( S9B Fig ) . Based on these data , we concluded that differences in genic piRNAs unlikely have impact on the observed cytotype shift . Overall , we have shown that the enrichment of heterochromatic marks ( H3K9me3 and HP1a ) in the genomic regions containing 315 , 635 and 850 elements is significantly lower in M-like variant of strain 101 compared to neutral one . Together , these data provide further evidence that the mechanism of maternal repression may significantly vary among strains . However , additional experiments involving Rhino ChIP and genome sequencing of strain 101 are needed to clearly prove this assumption and identify the loci responsible for the enhanced piRNA production in one of the two 101 substrains . One of the main consequences of activation of a particular asymmetric TE in the progeny of dysgenic crosses is their expression level excess compared to both paternal strains and reciprocal hybrids [3 , 15 , 18 , 31] . Studies of the I-R syndrome of HD in D . melanogaster demonstrate higher expression of the I-element in the F1 progeny from dysgenic crosses compared to reciprocal ones [3 , 30 , 31] . This is due to the maternal deposition of piRNAs targeting the I-element and its effective silencing in only one direction of the cross . Additionally , various studies of HD systems , including the D . virilis syndrome , demonstrated that transgenerational inheritance of piRNAs is able to trigger piRNA expression in the next generation by changing the chromatin of piRNA-clusters due to paramutation [3 , 4 , 32–34] . However , a pattern of higher TE expression in the absence of complementary maternal piRNA is less apparent in D . virilis . Despite strain asymmetry in genomic content and piRNA abundance of Penelope and several other TEs , germline piRNA pools do not differ drastically between reciprocal F1 progeny , with the exception of Helena element [18] . We therefore sought to determine whether this atypical pattern was also observed in crosses with other strains , focusing on asymmetric Penelope , Paris , Polyphemus and Helena as well as Ulysses present in all strains . As expected , ovarian mRNA levels revealed a complete correspondence with the piRNA expression levels among strains ( Figs 8A , 2A and 2B ) . For example , we detected both Penelope mRNA and piRNA expression in 140 ( N ) and Argentina ( N ) , but neither were evident in Magarach ( N ) and 101 ( N ) . However , in all cases when females from M-like strains are crossed with strain 160 males , ovarian levels of expression are uniformly significantly higher for only one asymmetric TE–Polyphemus ( fold change 3 , 5 , 3 . 5 , p < 0 . 05 , t-test , in dysgenic hybrids with strains 9 ( M ) , 13 ( M ) and 101 ( M ) , respectively ) ( Fig 8B and 8C ) . In most cases the observed differences in expression for Penelope and Paris elements in the ovaries of dysgenic and reciprocal hybrids were not dramatic and when exist rarely exceed 1 . 5–2 fold . Moreover , in the crosses involving neutral strains and strain 160 , we failed to detect any characteristic differences in TEs expression between reciprocal hybrids ( Fig 8B and 8C ) . Thus , independent of maternal piRNA profile , all reciprocal crosses with neutral strains show similar levels of expression . However , the two variants of strain 101 give different results when crossed with P-like strain 160 . In spite of the fact that 101 substrains contain equal levels of piRNAs complementary to the HD-implicated TEs , in the case of the M-like variant we observed higher levels of expression in the dysgenic hybrids for Penelope ( fold change 3; p < 0 . 05 , t-test ) and Polyphemus ( fold change 3 . 5 , p < 0 . 05 , t-test ) . Moreover , increase of Ulysses element ( found in all D . virilis strains ) expression ( fold change 3 , p < 0 . 05 , t-test ) was demonstrated in the dysgenic ovaries of 13 ( M ) and 160 ( P ) hybrids ( S10A Fig ) . These results demonstrate that factors other than maternal piRNA abundance lead to variation in resident TE expression in crosses between strain 160 and 101 substrains . For the neutral 101 strain , we failed to detect significant differences in the hybrids from both directions of crosses for any of TEs tested ( Fig 8B ) . With the exception of a few TEs and repeats , piRNA abundance in the ovaries from dysgenic and reciprocal progeny exhibited no drastic differences including piRNAs complementary to asymmetric TEs ( Figs 8B and S11 ) . Surprisingly , Helena , which maintains high level of asymmetry of the maternal pool of piRNAs in the progeny , exhibits very similar levels of correspondent mRNA expression in the hybrids obtained in both directions of crosses ( Fig 8B ) . In spite of overall similarity , piRNA pools in the ovaries of F1 progeny are able to comprise significantly different number of ping-pong pairs to all of transposons studied ( S10B Fig ) . For example , in the ovaries from dysgenic progeny ( strain 160 males ) with strains 9 ( M ) and Argentina ( N ) females , the number of ping-pong pairs to Penelope , Paris and Polyphemus was 2-3-fold lower than in the ovaries from reciprocal hybrids ( S10B Fig ) . We have also found that enrichment of the H3K9me3 mark on Penelope , Paris , Polyphemus and Helena sequences does not differ significantly in the F1 progeny of dysgenic and reciprocal crosses ( S10C Fig ) . Thus , we propose that piRNA-mediated transcriptional gene silencing of these HD-implicated TEs is similar in both directions of crosses and maternally provisioned piRNAs to these TEs are not necessary to stimulate the production of correspondent piRNA species in the progeny . These results are in agreement with recently published data [18] . In summary , it should be emphasized that in contrast to the I-R system in D . melanogaster , where maternal deposition of I-element piRNAs results in dramatic increase of piRNA expression targeting I-element in the progeny and efficient suppression of I-element activity , in D . virilis maternally provisioned piRNAs do not always guarantee efficient generation of the correspondent piRNAs in the progeny to maintain silencing of complementary TEs and provide adaptive genome defense . We conclude that in D . virilis the determination of asymmetric TEs expression levels in the ovaries of the progeny from dysgenic and reciprocal crosses does not allow one to unambiguously assign causality for HD to specific TE families . This fact points to an alternate mode of HD in D . virilis .
The standard explanation for the phenomenon of hybrid dysgenesis is that TEs inherited paternally become germline activated in the absence of maternal piRNA . Here , however , we suggest that repression of paternal TEs by maternal piRNA may not be the sole mechanism of protection against this form of hybrid sterility . Using the D . virilis system of HD as a model , we have demonstrated that neutral strains exhibiting “immunity” to hybrid dysgenesis in D . virilis do not share a consistent pattern of piRNAs complementary to TEs likely causative of dysgenesis . Strikingly , the introduction and propagation of one presumably causal TE ( Penelope ) in the genome of M-like strain does not even change the cytotype of the transformed strains . Finally , we identified a shift of cytotype from N to M that occurred in a strain without changes in the expression or copy number of asymmetric TEs implicated in HD . The observed “immunity” of neutral strains to HD manifestations is apparently established by an increased repertoire of repeats that become targets for piRNA biogenesis as well as a modified chromatin state of several genomic regions compared to M-like strains . These studies suggest that hybrid dysgenesis in D . virilis cannot be solely explained by the well-established “hybrid dysgenesis paradigm” , developed in D . melanogaster . Rather , other properties of the genome contribute to maternal protection . The precise molecular mechanisms underlying “susceptibility” of D . virilis strains to TEs invasion requires further investigation .
Seven D . virilis strains , namely 9 ( Batumi , Georgia ) , 13 ( Krasnodar , Russia ) , 101 ( Japan ) , Argentina ( Argentina ) , Magarach ( Crimea , Russia ) , 140 ( laboratory strain ) and laboratory strain 160 were used in this study . Original fly stocks are available in the Stock Center of Koltzov Insitute of Developmental Biology RAS . In addition , two previously described 165 and 247 strains [19] were used , designated in this paper as Tf1 and Tf2 , respectively . These strains were obtained as a result of transgenesis of the full copy of Penelope retroelement into 9 strain ( 19 ) . All flies were reared on standard agar-yeast-sugar-raisins medium at the constant temperature regime ( 25°C ) . Since the start of monitoring for cytotype shift ( 2011 ) stocks of both substrains of 101 ( from the Stock Center of Koltzov Institute of Developmental Biology RAS and ours ) are reared on the same medium and an equivalent population size ( not more than 20 flies per vial ) has been maintained . The dysgenic crosses involved males of P-like 160 strain and females of all aforementioned strains ( 9 , 13 , 101 , Argentina , Magarach and 140 ) . As a control , reciprocal crosses were performed . Monitoring and counting of gonadal atrophy were conducted as described [11] . Total RNA was extracted from ovaries of 7–10 days old females using Extract RNA reagent ( Evrogen , Russia ) . Total RNA was extracted from both 101 substrains after the second confirmation of cytotype shift in 2016 . To prepare the small RNA fraction for cloning , total RNA from ovaries ( ~ 25 μg ) was separated , using 15% polyacrylamide gel electrophoresis containing 8 M Urea . After incubation in an ethidium bromide solution ( 0 . 5 μg/ml ) , gel fragments corresponding to the small RNA fraction were excised , using chemically synthesized RNA corresponding to 21 and 29 nts as size markers . Cloning of small RNA libraries was performed by Illumina TruSeq Small RNA prep kit ( Illumina , USA ) according to the manufacturer’s protocol . Sequencing was conducted on an Illumina NextSeq 500 platform . As a result of deep-sequencing we obtained 5–14 million reads of small RNAs for each library . Pre-processing procedure included: 3’-adapter trimming , filtration of reads by length ( >18 nt ) and quality ( 80% of nt have ≥ 20 Phred quality ) . Pre-processed reads were further subjected to subtraction of reads matching to all rRNA , tRNA , snRNA and miRNA sequences . The selected reads were mapped to the latest release of D . virilis genome by Bowtie [35] , requiring a perfect match . In order to identify siRNAs and piRNAs , the sequenced reads were mapped to the canonical sequences of TEs obtained from combined libraries of annotated and computationally predicted D . virilis transposons and repeats sequences [18] . In addition , recently described DAIBAM MITE ( GenBank: EU280326 ) and Tetris ( GenBank: KF723713 . 1; KF723710 . 1 ) elements sequences were considered [36 , 37] . For genic piRNAs mapping the latest annotation of D . virilis transcripts was used ( r1 . 06 ) and the alignment performed with requirement of perfect match . Less than 25 CPM of mapped siRNAs and piRNAs per transposons or transcripts were considered as lowly expressed and discarded . Length distribution and counting of siRNAs and piRNAs reads , nucleotide biases , ping-pong signatures , coverage of transposon sequence by piRNAs were analyzed with accordance to the well-described technique [23 , 38] using custom scripts written in Python . Venn diagrams were made using Venny 2 . 1 ( http://bioinfogp . cnb . csic . es/tools/venny/ ) . Scatter plots were created using Plotly ( https://plot . ly ) . For analysis , cDNA was prepared from 2 μg Turbo-DNAase ( Ambion , USA ) treated total RNA using oligo ( dT ) primer and MMLV reverse transcriptase ( Evrogen , Russia ) . PCR was performed on ABI PRISM 7500 System ( Applied Biosystems , USA ) . Detection of amplification products was carried out using SYBR Green 1 with the presence of ROX reference dye ( Evrogen , Russia ) in accordance with the manufacturer’s protocol . Quantification was normalized to ubiquitously expressed rp49 gene and calculation of relative expression levels was performed using the equation 2-ddCt . Specificity of amplified products was verified by sequencing as well as melting curve analysis . The resulting value of the expression level for each sample was determined basing on at least three biological replicates . Sequences of used primers are shown in S1 Table . Dissection of ovaries , fixation , Proteinase K treatment , re-fixation and hybridization steps were performed as described [24] . Matrices for probe preparation were prepared by PCR ( sequences of used primers are shown in S1 Table ) of genomic DNA of 160 strain . Labeling of RNA probes with DIG-11-UTP ( Roche , France ) was made by MAXIscript T7 kit ( Ambion , USA ) . Anti-DIG-AP antibodies ( Roche , France ) were used in 1:2000 dilution . Images obtained by binocular microscope Nikon Alphaphot-2 YS2 ( Japan ) . To analyze genomic TE profiles , DNA samples ( ~ 10 μg ) were digested by restriction enzymes ( Penelope–SacI; Paris , Polyphemus and 850 –PvuII; Helena–XbaI; 315 –NcoI; 635 –PvuI ) , fractionated through 0 . 8% agarose gel and transferred onto Hybond-XL membrane ( Amersham Biosciences , USA ) . Hybridization was carried out at 60°C overnight in solution containing 6xSSC , 10 mM EDTA , 0 . 5% SDS and 5x Denhardt’s solution . The PCR-prepared matrices were used for probe preparation . Primers can be found in S1 Table . Labeling of probe with ( P32 ) -dATP was performed using Decalabel kit ( Thermo Scientific , USA ) . PCR was performed , in addition to Southern analysis , to compare the presence of full copies of TEs in the genomes of 160 , 9 , 101 ( N ) and 101 ( M ) strains . Amplification was performed using ScreenMix kit ( Evrogen , Russia ) . PCR products were separated in 1 . 5% agarose gel including ethidium bromide ( 0 . 5 μg/ml ) for detection . Reaction using primers to rp49 gene represents a loading control . Used primers were the same as for probe preparation in previously described hybridization procedure . Chromatin from Drosophila ovaries ( ~ 100 pairs for each IP experiment ) was extracted and immunoprecipitated according to the published protocol [39] . ChIP experiments were carried out using commercially available antibodies anti-H3K9me3 ( ab8898 ) ( Abcam , UK ) and anti-HP1a ( C1A9 ) ( DSHB ) . To bind antibodies Pierce protein A/G agarose ( Thermo Fisher Scientific , USA ) was used . Quantitative PCR was applied to evaluate the protein enrichment in the genomic loci . Percent of precipitated chromatin was calculated according to input values following normalization to actively transcribed rp49 gene . The resulting value represents the mean of two biological replicates . The error is indicated by the standard error of mean ( SEM ) . Primer sequences are presented in S1 Table . Student’s t-test was used to compare groups with each other ( qPCR and ChIP-qPCR data ) . P-values ≤ 0 . 05 were considered statistically significant .
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Transposable elements ( TE ) can proliferate in genomes even if harmful . In response , mechanisms of small-RNA silencing have evolved to repress germline TE activity . Syndromes of hybrid dysgenesis in Drosophila—where unregulated TE activity in the germline causes sterility—have also revealed that maternal piRNAs play a critical role in maintaining TE control across generations . However , a syndrome of hybrid dysgenesis in D . virilis has identified additional complexity in the causes of hybrid dysgenesis . By surveying factors that modulate hybrid dysgenesis in D . virilis , we show that protection against sterility cannot be entirely explained by piRNAs that control known inducer TEs . Instead , spontaneous changes in the chromatin state of repeat sequences of the mother may also contribute to protection against sterility .
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2018
|
Spontaneous gain of susceptibility suggests a novel mechanism of resistance to hybrid dysgenesis in Drosophila virilis
|
Leptospirosis is an important zoonotic disease that causes considerable morbidity and mortality globally , primarily in residents of urban slums . While contact with contaminated water plays a critical role in the transmission of leptospirosis , little is known about the distribution and abundance of pathogenic Leptospira spp . in soil and the potential contribution of this source to human infection . We collected soil samples ( n = 70 ) from three sites within an urban slum community endemic for leptospirosis in Salvador , Brazil . Using qPCR of Leptospira genes lipl32 and 16S rRNA , we quantified the pathogenic Leptospira load in each soil sample . lipl32 qPCR detected pathogenic Leptospira in 22 ( 31% ) of 70 samples , though the median concentration among positive samples was low ( median = 6 GEq/g; range: 4–4 . 31×102 GEq/g ) . We also observed heterogeneity in the distribution of pathogenic Leptospira at the fine spatial scale . However , when using 16S rRNA qPCR , we detected a higher proportion of Leptospira-positive samples ( 86% ) and higher bacterial concentrations ( median: 4 . 16×102 GEq/g; range: 4–2 . 58×104 GEq/g ) . Sequencing of the qPCR amplicons and qPCR analysis with all type Leptospira species revealed that the 16S rRNA qPCR detected not only pathogenic Leptospira but also intermediate species , although both methods excluded saprophytic Leptospira . No significant associations were identified between the presence of pathogenic Leptospira DNA and environmental characteristics ( vegetation , rat activity , distance to an open sewer or a house , or soil clay content ) , though samples with higher soil moisture content showed higher prevalences . This is the first study to successfully quantify the burden of pathogenic Leptospira in soil from an endemic region . Our results support the hypothesis that soil may be an under-recognized environmental reservoir contributing to transmission of pathogenic Leptospira in urban slums . Consequently , the role of soil should be considered when planning interventions aimed to reduce the burden of leptospirosis in these communities .
Leptospirosis is a life-threatening , zoonotic disease of global importance , with more than 1 million cases and approximately 60 , 000 deaths estimated annually , predominately in developing tropical countries [1] . The disease is caused by spirochetes of the genus Leptospira , which contains 35 species , 13 of which in the pathogenic group [2 , 3] . Pathogenic Leptospira chronically colonize the renal tubules of animal reservoirs and are excreted with the urine . Humans are incidental hosts , and often acquire the infection after seasonal or intense precipitation events [4–6] , when pathogenic Leptospira in contaminated soil , mud , or water penetrate abraded skin or wounds [7 , 8] . Clinical manifestations of leptospirosis range from mild or asymptomatic to severe illness , such as Weil’s disease [7 , 9] , and pulmonary hemorrhage syndrome [9 , 10] , which cause high case fatality rates . Urban leptospirosis has emerged as a pandemic which disproportionately affects residents of slum communities around the world [11] . Poor sanitation and an abundance of food sources provide ideal conditions for the maintenance of large rodent populations , specifically the Norway rat ( Rattus norvegicus ) , which are the primary animal reservoirs of pathogenic Leptospira in urban environments [12–16] . Infrastructure deficiencies facilitate the transmission to humans [17–19]: Open sewers and inadequate drainage systems allow contaminated water to pervade surrounding soil and water , and unpaved walkways expose residents to contaminated dirt and mud . Thus , the human-environment interface plays a critical role in the epidemiology and transmission of leptospirosis in urban slums . While previous studies have found Leptospira spp . in puddles , sewers , streams , and soil in endemic regions [20–25] , the distribution and dynamics of leptospires in the environment , particularly in soil , are largely unknown . To date , few publications have reported pathogenic Leptospira in soil , presumably because leptospirosis is generally considered to be a water-borne disease , and thus environmental studies have focused preferentially on aquatic matrices [20 , 21] . Previous studies that successfully analyzed soil reported very low prevalence among samples ( 4 . 9% in China [26] ) , or the isolation of only a few pathogenic strains in Philippines , Malaysia and New Caledonia [2 , 23 , 24 , 27 , 28] . These studies , however , were based on culture isolation of leptospires , followed by molecular identification . Culture techniques lack sensitivity because of pathogenic Leptospira spp . being overgrown by the autochthonous soil microbiota or saprophytic and intermediate Leptospira [23 , 24 , 29] . Notably , a recent study by Thibeaux et al . [25] reported a 57 . 7% prevalence in soil samples from a suspected environmental infection site in New Caledonia by using a qPCR targeting lipL32 . In this study , we aimed to quantify the pathogenic Leptospira load in soil samples from an urban slum community in Salvador , Brazil . Previous studies have shown this community has a high burden of disease [6 , 18 , 30] and a widespread presence of pathogenic Leptospira in its surface waters [31] , making it an excellent location for an environmental survey of the pathogen . Since Norway rats are the predominant pathogenic Leptospira reservoir in this community [14] , we hypothesized that the presence of rats would be associated with the occurrence and abundance of the pathogen in soil . As urban slum communities in tropical regions share many socioeconomic , structural , and environmental characteristics [32 , 33] , our study may help inform potential public health interventions in similar epidemiological settings around the world .
We conducted this study in the community of Pau da Lima , an urban slum located in Salvador , Brazil . This site has been extensively described in previous studies [18 , 19] . Briefly , the community encompasses four interconnected valleys within 0 . 46 km2 ( Fig 1A ) , with a population of 14 , 122 inhabitants residing in 3 , 689 households , according to a 2003 census [18] . The community lacks adequate sanitary infrastructure , resulting in untreated wastewater and rain runoff flowing through open sewers in the lower parts of the valleys . Leptospirosis is endemic in Pau da Lima , with a mean annual infection incidence of 37 . 8 per 1 , 000 inhabitants , and 19 . 8 severe cases per 100 , 000 inhabitants [30] . We selected three collection sites to represent a range of microenvironments present within the community ( Fig 1B ) . Site A ( 900 m2 ) ( 12°55'22 . 2"S , 38°26'04 . 2"W ) was located along an open sewer at the bottom of the valley , and included households , areas of domestic animal raising , and thick vegetation ( Fig 2A ) . The steep , high banks of the sewer served as a barrier to separate households from the sewage , which limited potential flooding . Site B ( 900 m2 ) ( 12°55'17 . 9"S , 38°26'07 . 2"W ) was situated at a higher elevation next to the valley slope and had closed sewage drains , paved stairs , and patios ( Fig 2B ) . There was limited vegetation , although fences and barriers , coupled with the sheer valley slope , restricted access . Site C ( 400 m2 ) ( 12°55'24 . 8"S , 38°26'06 . 3"W ) was situated at the bottom of the valley and in proximity to an open sewer with low embankments , allowing frequent flooding of surrounding areas during heavy rainfall periods . The thick vegetation and water-logged soil made part of the site inaccessible . We partitioned collection sites into 5 m x 5 m squares ( A and C ) or 10 m x 10 m ( B ) ( Fig 2A and 2B ) . A larger grid was used at Site B , as many areas were impassible due to the decreased number of sampling locations and the challenging terrain ( Fig 2B ) . We collected soil and sewage samples in the rainy season between July and August 2014 ( S1 Fig ) . A tracking board to monitor rat activity in the collection sites was placed as described previously [34] within all grid squares that were accessible and contained exposed soil . Tracking boards were evaluated daily over the course of three days for evidence of rat activity as ascertained by the identification of footprints , scrapes , and tail slides [34] . After the three days , one or two soil samples of 100–200 g were collected at a depth of 5–10 cm from non-adjacent areas within 30 cm of the edge of each tracking board between 9am and 12 . 30pm . Grid squares that were inaccessible because of private property , dense vegetation or water-logged soil , or contained no exposed soil were not included in the sampling . In total , we collected soil samples from 23 , 7 and 11 grid squares in sites A , B and C , respectively for a total of 35 , 14 and 22 soil samples . If a portion of an open sewer was included in the grid square and was accessible , two 50 mL samples for each sampling point were collected . The presence of vegetation and distance to open sewers and households was recorded for each grid square . The soil moisture and clay content were measured for one sample from each grid square . Samples were placed in aseptic containers , transported to the laboratory , and processed within 6 h . To maximize the recovery of Leptospira DNA from soil samples , we developed an extraction protocol and determined its efficiency by performing spiking experiments with known concentrations of L . interrogans ( S1 Supplementary methods ) . The final procedure consisted in the following steps: Subsamples of 5 g of soil were mixed with 40 mL of sterile double-distilled water and vortexed at maximum speed for 2 min . Samples were centrifuged at 100 rcf for 5 min . The supernatant was recovered and centrifuged at 12 , 000 rcf for 20 min at room temperature . The pellets were recovered , resuspended in 1 . 5 mL of sterile double-distilled water and centrifuged at 12 , 000 rcf for 20 min . Finally , the samples were decanted and the pellets were frozen at -80°C . Sewage samples ( 40 mL ) were processed as described previously [35] . DNA was extracted from pellets using PowerSoil DNA Isolation Kit ( Mo Bio Laboratories ) . An extraction blank ( sterile double-distilled water ) was added to each extraction batch to monitor for cross-contamination . We quantified Leptospira spp . loads using two TaqMan assays targeting the lipL32 gene or the 16S rRNA gene as described previously [36 , 37] with minor modifications . Briefly , all reaction mixtures ( 25 μL ) contained 12 . 5 μL Platinum qPCR SuperMix ( Life Technologies ) , 0 . 2 μg/μL of bovine serum albumin ( Ambion ) , and 5 μL of DNA template . The lipL32 reactions included 500 nM each of primers LipL32-45F and LipL32-286R , and 100 nM of LipL32-189P probe ( S1 Table ) . 16S rRNA reactions included 300 nM each of primers Lepto F and Lepto R , and 200 nM of 16S probe . Amplifications were performed using a 7500 Fast Real-Time PCR System ( Life Technologies ) with the following conditions: an initial step of 2 min at 50°C , followed by 2 min at 95°C , and 40 cycles of amplification ( 15 s at 95°C and 1 min at 60°C ) . Genomic DNA obtained from L . interrogans serovar Fiocruz L1-130 [38] was used to construct calibration curves with concentrations ranging from 2 × 102 to 2 × 109 GEq/mL , which we included in each qPCR run . Efficiencies were always higher than 92 . 5% . All samples were run in duplicate , and included non-template controls in each plate row to detect any contaminating DNA . All negative controls ( extraction controls and non-template controls ) were negative . All DNA extractions and quantitative PCR ( qPCR ) analyses were performed according to the minimum information for publication of quantitative real-time PCR experiments ( MIQE ) guidelines [39] . To determine the specificity of the lipL32 and 16S rRNA qPCRs for pathogenic , intermediate and saprophytic Leptospira , we tested DNA extracts from 21 Leptospira species ( S2 Table ) as explained above , adjusting the concentration in each well to 107 GEq based on each genome’s size [40] . To confirm the specificity of the environmental qPCR reactions , we randomly selected and sequenced ( Sanger method ) 11/22 ( 50% ) of the soil samples with positive results for lipl32 . We also sequenced 27/78 ( 35% ) of samples with a positive result for 16S rRNA qPCR ( 25 soil and 2 sewage samples ) . In brief , qPCR products were purified from 2% agarose gels using the QIAquick Gel Extraction Kit ( QIAgen ) following the manufacturer’s instructions . The products were sequenced using primers LipL32-45F or Lepto-F for lipL32 and 16S rRNA , respectively , corrected using BioEdit 7 . 2 . 0 ( Ibis Biosciences ) , and the sequences compared using BLAST to those available in the NCBI . In addition , we performed a phylogenetic analysis for the lipl32 and 16S rRNA amplicons using the Phylogeny . fr platform [41] . Maximum Likelihood trees were inferred by PhyML 3 . 0 [42] using the Hasegawa-Kishono-Yano ( HKY85 ) substitution model and 1000 bootstrap replicates . We used FigTree v1 . 4 . 2 ( http://tree . bio . ed . ac . uk/software/figtree ) to visualize and edit the final trees . The 16S rRNA tree included Leptonema illini DSM 21528 as the outgroup . Leptospira concentrations were log10 transformed and analyzed as follows . The theoretical lower limit of quantification ( LOQ ) of the qPCR assays was calculated using the assumption that 1 copy of the targeted gene was amplified in a reaction ( 4 GEq/g ) . We assigned positive samples with concentrations below this threshold a value equal to the LOQ . Fisher’s exact test and the χ2 test were used to compare prevalence among sites and the associations of dichotomized environmental characteristics with the proportion of qPCR-positive samples . t-tests with a Welch’s correction were used to compare soil moisture content and clay component values between positive and negative qPCR samples . The median concentrations between sampling sites were compared using Kruskal-Wallis test with Dunn’s correction for multiple comparisons . Mann-Whitney test was used to compare the concentrations between soil and sewage at site C and the overall concentrations obtained by lipl32 and 16S rRNA qPCRs . Non-parametric tests were chosen due to the non-normal distribution of the data . Although equivalent parametric tests ( one-way ANOVA and t-test ) were inappropriate , technically , they supported the results of the non-parametric tests in all cases . To analyze the degree of agreement between lipL32 and 16S PCR detection methods , we used Cohen’s kappa coefficient . All statistical analyses were performed using GraphPad Prism 6 . 05 ( GraphPad Software Inc . ) , and multivariate models were fit using the GENMOD procedure with a GEE model in SAS v9 . 3 ( SAS Institute Inc . , Cary , NC ) to evaluate the relationship between the measured environmental characteristics and outcome of sample testing .
We collected 70 soil samples within the study area ( 34 , 14 , and 22 from sites A , B , and C , respectively ) ( Fig 2 ) . Of those 70 samples , 22 ( 31% ) were positive for pathogenic Leptospira as measured by the lipL32 qPCR ( Fig 3A ) . There were no significant differences in the proportion of positive samples between the three collection sites ( 26% , 21% and 45% , respectively; p = 0 . 78 ) ( Table 1 ) , indicating that pathogenic Leptospira were widespread in the study site . These prevalences are lower than those recently reported using the same qPCR method in river bank soils from active leptospirosis transmission sites in New Caledonia ( 57 . 7% ) [25] . Nevertheless , our results contrast with the very low number of pathogenic Leptospira isolates that are usually obtained from soil in endemic areas using culture-based approaches [23 , 24 , 26–28] , suggesting that molecular approaches may capture better the presence of the pathogen in soil . The concentration of pathogenic Leptospira among positive samples was predominantly low ( median: 6 GEq/g ) , but varied by two orders of magnitude ( range: 4–4 . 31×102 GEq/g ) even within the same collection grid . This indicates a considerable heterogeneity of environmental loads within the slum microenvironment . Furthermore , there were no significant differences in the concentration of the qPCR-positive soil samples among the three collection sites ( p = 0 . 16 ) ( Fig 3A ) . Among the eight sewage-water samples collected from site C , seven ( 88% ) were positive by the lipL32 qPCR with a median concentration of 0 . 5 GEq/mL . Together our results showed that pathogenic Leptospira were present in low concentrations in soils sampled from diverse microenvironments within the urban slum . Contact with mud in the peridomiciliary environment was previously identified as a risk factor for leptospirosis infection in this setting [18] , which suggests that soil may serve as an important environmental reservoir of the pathogen . Intense rainfall events during the rainy season would cause mobilization and dispersion of pathogenic Leptospira from soil to run-off as described for other environmental pathogens such as E . coli , Salmonella spp . , Cryptosporidium spp . and fecal indicator bacteria [43–48] . Simultaneously , run-off originated in the higher areas of the valley may contaminate soil in the lower areas with pathogenic Leptospira through flooding and sewer overflow . Thus , soil may act as a source and a recipient of the pathogen depending on the specific location and weather conditions . Furthermore , the low concentrations found in soil are in agreement with those found in sewage and standing water in a previous study conducted in the same setting [31] , which supports the hypothesis that the environmental load of pathogenic Leptospira is generally low , even in endemic areas . The dynamics and characteristics of water-based mobilization and dispersion of Leptospira to and from the soil reservoir within the slum community , and the role that low environmental concentrations may have on the risk of acquiring leptospirosis , will require detailed studies beyond the scope of our methods . In contrast to the lipL32 qPCR results , the 16S rRNA qPCR detected Leptospira from 60/70 ( 86% ) soil samples , significantly more than detected by the lipL32 qPCR ( p<0 . 0001 ) . Higher prevalences were found at sites A and C ( 88% and 100% , respectively ) than site B ( 57% ) ( p<0 . 0014 ) ( Table 2 ) . Among positive samples , the median concentration was 4 . 16×102 GEq/g ( range: 4–2 . 58×104 GEq/g ) , significantly higher than the one detected by lipL32 qPCR ( 6 GEq/g , p < 0 . 0001 ) . All eight sewage samples from Site C were also positive using the 16S qPCR , with a mean concentration of 2 . 09×102 GEq/mL ( range: 98–2 . 81×102 ) , nearly 9-fold higher than that detected by lipL32 qPCR ( 24 GEq/mL , p = 0 . 0003 ) . Notably , all soil and sewage samples that were positive using the lipL32 assay were positive with the 16S assay , though there was a poor agreement between the qualitative results obtained by the two methods ( Cohen’s Kappa coefficient = 0 . 14± 0 . 05 ) ( Table 2 ) Given the discrepancy of results obtained with the two-qPCR methods ( Table 2 ) , we analyzed the specificity for detecting pathogenic Leptospira for each method . We sequenced the lipL32 amplicon from 11/22 ( 50% ) lipL32 qPCR-positive soil samples . In all cases , the sequences presented similarities greater than 92% with lipL32 gene sequences from pathogenic Leptospira deposited in GenBank ( S3 Table ) and clustered with species from the pathogenic group ( Fig 4A ) . These results confirmed that the lipL32 qPCR was highly specific for pathogenic Leptospira in soil as it was previously shown in sewage [31] . We also sequenced 27/78 ( 35% ) 16S qPCR-positive samples ( 25 soil and 2 sewage samples ) . All the sequenced 16S rRNA amplicons clustered with species from the intermediate Leptospira group ( Fig 4B ) . As observed elsewhere [49] , a single mismatch in the approximately 50 bp fragment sequenced discriminates between intermediate and pathogenic Leptospira groups . Indeed , the reverse primer used in the 16S qPCR is degenerated at position 14 allowing for the hybridization with T and C bases , and thus , may detect both pathogenic and intermediate species ( S1 Table ) . Of note , 6 sequences that were positive for both lipL32 and 16S presented a double peak in the sequencing chromatogram at the mismatch position . This indicates that both sequences coexisted in the sample [49] , although in all cases the highest peak was the one belonging to the intermediate group . To conclusively determine the specificity of the both qPCRs , we tested 21 type strains from the pathogenic , intermediate and saprophytic groups . Lipl32 qPCR showed signal only for pathogenic species , and excluded intermediate and saprophytic ones . In contrast , all pathogenic and intermediate species gave positive results for 16S rRNA qPCR and no signal was observed for the saprophytes ( S2 Table ) . Therefore , 16S rRNA qPCR detects not only pathogenic Leptospira , but also intermediate species . Since the pathogenicity of the intermediate group is not well established , we considered only the results obtained with lipL32 qPCR for subsequent analyses . Bivariate and multivariate analyses identified no significant associations between the presence of pathogenic Leptospira DNA in soil and environmental characteristics such as vegetation , distance to an open sewer or a house , or soil clay content ( Table 1 ) . However , we found that 62% of samples with a moisture content higher than 20% were positive , while only 21% were positive when the moisture was lower than 20% , which is consistent with previous observations that higher soil moisture content is associated with increased Leptospira isolation [23 , 50] . Additionally , previous studies have reported that Leptospira persist for a longer time in moist and super-saturated soils than in drier ones , although the duration of survival is also dependent on the serovar and other characteristics of the soil such as pH [51–53] . Furthermore , against our initial hypothesis , we did not find any significant association between rat activity and the presence of pathogenic Leptospira in soil . A potential explanation is that the direct association with rats is confounded by other animal sources of pathogenic Leptospira both domestic ( cows , pigs and dogs ) and wildlife ( opossums and bats ) that coexist in this urban slum [15 , 34] . Alternatively , as discussed above , some of the pathogenic Leptospira detected may have originated in other parts of the valley and contaminated the soil through run-off or floodwater , making rat activity an unreliable proxy for the presence of the pathogen . Finally , we cannot rule out that the tracking board method was not a sufficient to assess rat activity at the fine scale at which the variation of the presence and concentration of pathogenic Leptospira in the soil seems to occur . Studies with larger sample sizes and an increased diversity of sites sampled are required to track the origin of pathogenic Leptospira in soil and determine relationships with environmental characteristics potentially obscured by our relatively small sample size . The concentrations of Leptospira in soil detected using the 16S qPCR were higher than those detected by lipL32 in all samples . Moreover , the difference between both measurements was higher than 0 . 60 log10 units in all but one sample ( mean difference and SD: 2 . 05±0 . 89 log10 units ) . Since 16S qPCR detects pathogenic and intermediate species while lipL32 qPCR detects only pathogenic ones and both methods exclude saprophytic Leptospira ( S2 Table ) , the observed concentration differences suggest that most of the signal detected with 16S qPCR originates from intermediate species . Hence , Leptospira species from the intermediate group may be more ubiquitous and present in significantly higher concentrations in soil from this community relative to pathogenic ones . Intermediate species such as L . fainei , L . licerasiae , L . wolffii , and L . broomii have been linked to human leptospirosis cases [54–58] , although they are not considered as virulent as the species from the pathogenic group , and thus are less relevant from a public health perspective . It is important to note that no cases of leptospirosis caused by an intermediate species has been reported in Pau da Lima during 15 years of active surveillance [6 , 18 , 30 , 59] . Previous studies of pathogenic Leptospira in the environment using 16S qPCR [20 , 49 , 60] might have led to a overestimation of the burden of the pathogen . Our results illustrate the importance of using highly specific tests to detect pathogenic bacteria in estimations of disease burden and environmental reservoir load . Inherent limitations of qPCR in environmental samples may influence the accuracy of our estimates and ability to evaluate risk associations . First , qPCR may be detecting DNA from dead or damaged cells that have lost the ability to cause infection and therefore , our results may overestimate the environmental risk . On the other hand , although we optimized sample processing , DNA extraction , and detection methodologies to reduce DNA loss and PCR inhibition , we may have underestimated pathogenic Leptospira loads in the soil if they were below the LOD . Second , our sampling scheme may not have completely captured the heterogeneity in the urban slum environment . While we evaluated three study sites representative of different microenvironments within the slum , there may be additional heterogeneity with respect to soil type , climatic conditions , land use , and rat activity levels , which should be further explored . Finally , the relatively small sample size limited our ability to draw robust conclusions concerning environmental factors contributing to positive and negative soil samples . To date , most research regarding the environmental reservoirs of pathogenic Leptospira has focused on water matrices such as sewage , puddles , wells , or freshwater . Our results are the first to successfully quantify the burden of pathogenic Leptospira in soil from an endemic region , and indicate that soil is an additional environmental reservoir in the life cycle of pathogenic Leptospira . As with other environmentally transmitted diseases , the mobilization of leptospires from the sub-surface soil , either by heavy rainfall , flooding , or excavation , would contribute to environmental exposures with a sufficient dose to produce infection in humans . Furthermore , understanding the specific role and impact of soil as an environmental reservoir and the relation of low environmental concentrations to the risk of human disease is critical to our knowledge of the leptospirosis transmission cycle . Importantly , our data suggest that efforts to eliminate or reduce access to recognized transmission sources , such as open sewers , may not be sufficiently effective to decrease the risk of infection . Consequently , the role of soil in the transmission dynamics and epidemiology of leptospirosis should be considered when designing public health interventions in endemic areas .
|
Leptospirosis is a globally distributed zoonotic disease that disproportionately affects vulnerable populations in urban slums . The disease is transmitted by direct contact with water , soil , or mud that has been contaminated with infected urine shed from chronically infected animals . Despite the critical role the environment plays in the epidemiology of the disease , the contribution of soil to the transmission cycle remains largely undescribed . Herein , we investigated the distribution of pathogenic Leptospira in soil samples from an endemic urban slum in Brazil . We found pathogenic Leptospira in nearly one-third of the soil samples , predominantly in low concentrations ( <5×102 GEq/g ) . However , we observed considerable variation in the distribution and concentration of the pathogen at the fine spatial scale within the slum . Our results indicate that soil is likely an important additional environmental reservoir of pathogenic Leptospira in urban slums and prevention strategies should consider soil to help prevent the transmission of the disease in similar settings .
|
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] |
2018
|
Quantification of pathogenic Leptospira in the soils of a Brazilian urban slum
|
Mycetoma is a neglected , chronic , localized , progressively destructive , granulomatous infection caused either by fungi ( eumycetoma ) or by aerobic actinomycetes ( actinomycetoma ) . It is characterized by a triad of painless subcutaneous mass , multiple sinuses and discharge containing grains . Mycetoma commonly affects young men aged between 20 and 40 years with low socioeconomic status , particularly farmers and herdsmen . A 30 year-old male farmer from an ethnic minority in Phin District , Savannakhet Province , Lao PDR ( Laos ) developed a painless swelling with multiple draining sinuses of his right foot over a period of approximately 3 years . X-ray of the right foot showed osteolysis of tarsals and metatarsals . Aerobic culture of sinus discharge yielded large numbers of Staphylococcus aureus and a slow growing Gram-positive rod . The organism was subsequently identified as Nocardia aobensis by 16S ribosomal RNA gene sequencing . The patient received antimicrobial treatment with amikacin and trimethoprim-sulfamethoxazole according to consensus treatment guidelines . Although slight improvement was noted the patient left the hospital after 14 days and did not take any more antibiotics . Over the following 22 weeks the swelling of his foot subsequently diminished together with healing of discharging sinuses . This is the first published case of Actinomycetoma caused by Nocardia aobensis and the second case of Actinomycetoma from Laos . A treatment course of only 14 days with amikacin and trimethoprim-sulfamethoxazole was apparently sufficient to cure the infection , although long-term treatment up to one year is currently recommended . Treatment trials or prospective descriptions of outcome for actinomycetoma should investigate treatment efficacy for the different members of Actinomycetales , particularly Nocardia spp . , with short-term and long-term treatment courses .
Mycetoma is a chronic , localized , progressively destructive , granulomatous infection caused either by fungi ( eumycetoma ) or by aerobic actinomycetes ( actinomycetoma ) . The disease was added to the WHO list of neglected diseases and conditions in 2013 [1] . It is most likely acquired by traumatic inoculation of the causative organism into the subcutaneous tissue , usually of the foot although any part of the body can be affected . Mycetoma is characterized by a triad of painless subcutaneous mass , multiple sinuses and discharge containing grains [2] . It commonly affects young adults , particularly males aged between 20 and 40 years . The male/female ratio is approximately 3:1 . People of low socioeconomic status and manual workers such as farmers , labourers and herdsmen are most frequently affected [3 , 4] . Consensus treatment guidelines for eumycetoma and actinomycetoma recommend long-term treatment over 6–12 months with antifungal or antibacterial drugs [5] . However no comparative clinical trials of treatment of this condition have ever been undertaken . It is possible that the taxonomically diverse range of causative agents of eumycetoma and actinomycetoma may require more differentiated therapeutic regimens . Here we report a case of actinomycetoma caused by Nocardia aobensis , which was cured after short-term antibiotic treatment .
Written informed consent was obtained from the patient for publication of this case report and any accompanying images . The board of directors of Lao-Oxford-Mahosot Hospital Wellcome Trust Research Unit , Bernhard Nocht Institute for Tropical Medicine and Savannakhet provincial hospital approved this case report for publication . A 30 year-old male farmer from an ethnic minority group in Phin District , Savannakhet Province , Lao PDR , reported the development of a painless swelling of his right foot over approximately 3 years . He had no history of trauma or animal bites . Multiple draining sinuses developed over time discharging serous fluid . The patient was afebrile with normal vital signs and physical examination was unremarkable except for a massive tumour-like lesion of the right foot with multiple sinuses on the dorsal and plantar surfaces ( Fig 1A , 1B , and 1C ) . WBC: 9500/μL , Hb: 5 . 5 mmol/L , HCT 31% , MCV: 58 fL , PLT: 568 , 000/μL Lymphocytes 22% , Monocytes 14% , Granulocytes 64% Blood glucose: 4 . 2 mmol/l , creatinine: 53 . 1 μmol/l WBC: 7000/μL , Hb: 8 . 9 mmol/L , HCT 45% , MCV: 71 fL , PLT: 278 , 000/μL Lymphocytes 24% , Monocytes 7% , Granulocytes 69% creatinine: 70 . 8 μmol/l X-ray of the right foot before treatment showed osteolysis of tarsals and metatarsal , particularly metatarsals II–V , the cuneiforms and cuboid and a pathologic fracture at the base of metatarsal V . ( Fig 2A ) . X-ray of the right foot 10 months after treatment showed significant improvement at the metatarsal shafts II–V with healing of the fracture at metatarsal V , but still osteolysis at metatarsal bases II–V , the cuneiforms and cuboid . Joint lines between metatarsals and tarsals are not identifiable ( Fig 2B ) . Aerobic culture of sinus discharge yielded large numbers of Staphylococcus aureus and a slow growing Gram-positive rod , which was apparent after 5 days’ incubation ( Fig 3B ) . Gram stain preparation showed branching Gram-positive rods ( Fig 3A ) . The organism was identified as Nocardia aobensis in two independent laboratories after amplification and sequencing of the 16S ribosomal RNA gene ( 839bp: coverage 839/839 , identity 100% , e-value 0 . 00 , Accession Number KP250991; 670bp [hypervariable regions V3–V7]: coverage 670/670 , identity 100% , e-value 0 . 00 , Accession Number KP404096 ) and blast analysis against the NCBI database [6] . Mycetoma Actinomycetoma caused by Nocardia aobensis The patient received amikacin ( 15mg/kg/day ) intravenously combined with trimethoprim-sulfamethoxazole ( TMP-SMX ) ( 7/35 mg/kg/day ) per os for 14 days . Although slight improvement was noted at that stage , with a decrease of discharge and closure of sinuses , the patient left the hospital against medical advice for traditional treatment in his village and did not take any more antibiotics ( Fig 4 ) . Over the following weeks the swelling of his foot subsequently diminished together with healing of discharging sinuses . This was confirmed when he was seen 22 and 43 weeks after antibiotic treatment at the health centre in his village and the provincial hospital ( Fig 1D , 1E , and 1F ) . He resumed physical work in the forest without limitation and reported a significant overall improvement of his state of health . X-ray of his right foot showed significant improvement at the metatarsal shafts , but still signs of osteolysis at the metatarsal bases , the cuneiforms and cuboid . The initial anaemia and thrombocythaemia , most likely the result of chronic infection , returned to normal 10 months after treatment .
The incidence of mycetoma in Laos is not known . Only one case of actinomycetoma , caused by Actinomadura madurae , from Xieng Khouang province in the northern part of the country has been published [7] . The patient’s history and the clinical appearance of his foot were suggestive of mycetoma and microbiological culture and molecular biological identification of Nocardia aobensis confirmed the diagnosis of actinomycetoma . Correct identification of the causative agent is crucial in order to choose the appropriate treatment . More than 30 species have so far been identified as aetiological agents of mycetoma worldwide [8] . Actinomadura madurae , Actinomadura pelletieri , Nocardia brasiliensis , Nocardia asteroides and Streptomyces somaliensis are most frequently responsible for causing actinomycetoma [4] . The patient described is to our knowledge the first confirmed case of actinomycetoma caused by Nocardia aobensis and adds one more causative agent to the list . Nocardia aobensis was first described in 2004 after having been isolated from sputum of Japanese patients [9] . Antimicrobial susceptibility testing has not been done for the isolate described here , but most Nocardia spp . including Nocardia aobensis , are susceptible to amikacin and TMP-SMX [10] . In 1987 , Welsh et al . reported a study which included 15 patients treated for actinomycetoma , all but one of which were caused by Nocardia brasiliensis , with cycles of amikacin alone ( 2 cases ) and amikacin with TMP-SMX ( 13 cases ) . Treatment with amikacin 15mg/kg/day for 3 weeks together with TMP-SMX 7/35mg/kg/day for 5 weeks was defined as 1 cycle . The patients were all cured after 1–3 cycles , with 4 patients cured after 1 cycle , 8 patients cured after 2 cycles and 3 patients cured after 3 cycles [11 , 12] . In 1982 a young man with severe actinomycetoma and pulmonary involvement caused by Nocardia brasiliensis was successfully treated with one cycle [13] . Based on their experience with 56 patients Welsh et al . recommend 1–4 cycles with amikacin and TMP-SMX in severe cases of actinomycetoma that do not respond to TMP-SMX alone , achieving a cure rate of approximately 90% [5] . The number of cycles is dependent on the clinical and bacteriological response and varies from case to case . In our patient , a clinical improvement with closure of sinuses was noted after only two weeks of amikacin and TMP-SMX ( Fig 4 ) . Swelling was still significant at that time and took 22 weeks to resolve , which under normal circumstances might have misled the clinician in charge to continue the treatment for a longer period , although it appears that cure had already been achieved after 2 weeks . Current practice may thus entail some “overkill” . However , although haemoglobin and platelet count returned to normal values 43 weeks after treatment , radiological changes of metatarsal and tarsal bones had not completely disappeared at that time and this requires further follow up , because recurrence 2 years after remission has been previously reported [5] . Clinical trials or prospective descriptions with short-term and long-term antimicrobial treatment courses and longer periods of follow up are needed to inform optimal antibiotics and particularly treatment duration . Actinomycetoma affects mostly poor villagers in remote communities and shorter treatment courses would significantly reduce the financial burden and side effects of amikacin and TMP-SMX .
To our knowledge this is the first published patient with actinomycetoma caused by Nocardia aobensis and the second case of actinomycetoma from Laos . A treatment course of only 14 days with amikacin and TMP-SMX appears to have been sufficient to cure the infection as defined by 43 weeks follow up . Trials or prospective descriptions of efficacy of different antimicrobial therapy with short-term and long-term treatment courses for actinomycetoma should investigate treatment outcome separately for different members of Actinomycetales , particularly Nocardia spp .
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Mycetoma is a neglected tropical disease caused either by fungi or aerobic actinomycetes . It predominantly affects poor people in remote communities , where access to health care is very limited and people usually rely on traditional treatment . The incidence of mycetoma in the Lao PDR is not known , although the first case of mycetoma from the northern part of the country was published only recently . The present case report is the second case from the Lao PDR and the first published case of actinomycetoma caused by Nocardia aobensis . Data from the literature and the present case suggest that far shorter courses of antibiotics than those usually recommended might be sufficient to treat actinomycetoma caused by Nocardia spp . , although these observations need to be confirmed by further studies . Shorter treatment courses would reduce drug side effects and the financial burden on patients . The latter is particularly important for low-income countries like the Lao PDR with very limited resources for health care .
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[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Discussion",
"Conclusion"
] |
[] |
2015
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Case Report: Actinomycetoma Caused by Nocardia aobensis from Lao PDR with Favourable Outcome after Short-Term Antibiotic Treatment
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Post-translational protein modifications such as phosphorylation and ubiquitinylation are common molecular targets of conflict between viruses and their hosts . However , the role of other post-translational modifications , such as ADP-ribosylation , in host-virus interactions is less well characterized . ADP-ribosylation is carried out by proteins encoded by the PARP ( also called ARTD ) gene family . The majority of the 17 human PARP genes are poorly characterized . However , one PARP protein , PARP13/ZAP , has broad antiviral activity and has evolved under positive ( diversifying ) selection in primates . Such evolution is typical of domains that are locked in antagonistic ‘arms races’ with viral factors . To identify additional PARP genes that may be involved in host-virus interactions , we performed evolutionary analyses on all primate PARP genes to search for signatures of rapid evolution . Contrary to expectations that most PARP genes are involved in ‘housekeeping’ functions , we found that nearly one-third of PARP genes are evolving under strong recurrent positive selection . We identified a >300 amino acid disordered region of PARP4 , a component of cytoplasmic vault structures , to be rapidly evolving in several mammalian lineages , suggesting this region serves as an important host-pathogen specificity interface . We also found positive selection of PARP9 , 14 and 15 , the only three human genes that contain both PARP domains and macrodomains . Macrodomains uniquely recognize , and in some cases can reverse , protein mono-ADP-ribosylation , and we observed strong signatures of recurrent positive selection throughout the macro-PARP macrodomains . Furthermore , PARP14 and PARP15 have undergone repeated rounds of gene birth and loss during vertebrate evolution , consistent with recurrent gene innovation . Together with previous studies that implicated several PARPs in immunity , as well as those that demonstrated a role for virally encoded macrodomains in host immune evasion , our evolutionary analyses suggest that addition , recognition and removal of ADP-ribosylation is a critical , underappreciated currency in host-virus conflicts .
Post-translational modifications ( PTMs ) of proteins regulate a wide variety of cellular processes , including several aspects of innate immunity against pathogens . As a result , pathogens have evolved mechanisms to block , reverse or usurp this machinery in order to successfully replicate within their hosts [1] . For example , numerous viruses subvert the dynamics of phosphorylation , employing kinases , substrate mimics and phosphatases to disrupt host signaling [1] . Likewise , addition and removal of acetyl groups by histone acetyltransferases ( HATs ) and deacetylases ( HDACs ) can have a dramatic effect on viruses such as HIV , herpesviruses , polyomaviruses and papillomaviruses . In response , several viral classes encode proteins to specifically disrupt host phosphorylation and acetylation [2] . Beyond small-molecule PTMs , conjugation and cleavage of ubiquitin and ubiquitin-like molecules has emerged as an important point of cellular regulation that several viruses target or subvert in order to replicate [3] . In contrast , ADP-ribosylation is still poorly characterized for its role in innate immunity , despite being one of the first identified PTMs . Transfer of ADP-ribose ( ADPr ) from NAD+ ( nicotinamide adenine dinucleotide ) to proteins is catalyzed within eukaryotic cells by members of the PARP ( poly-ADP-ribose polymerase ) , or ARTD ( ADP-ribosyltransferase , diphtheria toxin-like ) protein family ( Figure 1A ) [4] , [5] . The best-studied PARPs , including the founding member PARP1 , catalyze the formation of long , branched chains of ADP-ribose known as poly-ADP-ribose ( PAR ) [4] , [6] , [7] , [8] . These PAR-forming enzymes perform critical housekeeping functions , such as nucleation of DNA-damage foci ( PARP1 and 2 ) and proper chromosome segregation during mitosis ( PARP5a ) [7] , [8] . In contrast to these well-described functions , most human PARP proteins are poorly understood , in part due to their lack of conservation in model organisms such as C . elegans and D . melanogaster [4] , [9] , [10] . In total , 17 genes in the human genome contain PARP domains , with each gene containing a variety of other functional domains that likely endow each PARP with their individual functions ( Figure 1A ) [4] , [10] . Many of the poorly-characterized human PARP proteins are found in the cytoplasm [11] and are predicted to only catalyze addition of a single ADPr , rather than PAR , to proteins [4] , [9] , [10] . Several recent descriptions of PARP functions in cellular signaling , miRNA regulation and stress granule formation [12] , [13] , [14] suggest that many functions for cytoplasmic ADP-ribosylation , especially mono-ADP-ribosylation , likely remain uncharacterized . Moreover , the discovery that a subset of macrodomain containing proteins can , in addition to binding mono-ADP-ribosylated proteins , also remove mono-ADP-ribose from proteins [15] , [16] , sheds further light on the regulation and function of this dynamic PTM . One function of ADP-ribosylation may be to regulate viral infectivity and pathogenesis , consistent with the role of other PTMs in immunity . For example , both vaccinia virus [17] and herpes simplex virus [18] require ADP-ribosylation activity for viral replication . Moreover , diverse RNA viruses , such as alphaviruses , hepatitis E virus , rubella virus and SARS coronavirus encode one or more macrodomains , potentially conferring the ability to specifically recognize , and possibly reverse , ADP-ribosylation upon these viruses [19] . Mutations in the macrodomain of Sindbis virus led to reduced virulence in mice [20] . Similarly , mutations in the SARS coronavirus macrodomain sensitized the virus to the antiviral effects of the signaling cytokine , interferon ( IFN ) [21] . As IFN functions as one of the primary mediators of the innate immune system against viruses [22] , these results indicate that macrodomains , and therefore ADP-ribosylation , could be important viral regulators of host immunity . Moreover , host PARP genes can play a direct role in antiviral immunity . For example , overexpression of PARP13 , also known as ZAP or ZC3HAV1 ( Zinc-finger CCCH-type antiviral protein 1 ) , is sufficient to restrict replication of several different families of viruses , including a retrovirus ( murine leukemia virus [23] ) , filoviruses ( Ebola and Marburg [24] ) , a togavirus ( Sindbis [25] ) and a hepadnavirus ( Hepatitis B virus [26] ) . This antiviral activity is mediated through direct binding of viral RNA by PARP13 , followed by recruitment of the exosome and specific degradation of viral RNA [27] , [28] , although more recently , additional signaling roles for PARP13 have been proposed [14] , [29] . Beyond the well-described PARP13-mediated antiviral functions , PARP1 , 7 , 10 and 12 have been shown to play roles in repressing viral replication [30] , [31] , [32] , [33] , although the mechanisms of these antiviral actions are unknown . While these results indicate that there may be a role for individual PARPs in regulating viral infectivity or pathogenesis , there has been no cohesive model for how ADP-ribosylation may influence host-viral interactions . We reasoned that if ADP-ribosylation is the focus of a host-virus conflict , we might see evolutionary signatures of positive ( diversifying ) selection acting on the specific host genes involved . Positive selection is a hallmark of host genes locked in genetic conflict with viruses that counter-evolve to evade the host antiviral defenses , and has been seen in both antiviral kinases and antiviral ubiquitin ligases [34] . Positive selection is characterized by the accumulation of amino acid-altering , nonsynonymous changes in the DNA at a rate that is greater than the accumulation of neutral , synonymous changes . When such protein changes are recurrently selected for ( due to their adaptive advantage ) , the ratio of nonsynonymous to synonymous substitution rates exceeds one ( dN/dS > 1 , where dN is the nonsynonymous substitution rate and dS is the synonymous substitution rate ) . Such analyses can not only identify a gene that has evolved under positive selection but can also pinpoint domains and even individual codons within that gene located at the direct interface between host and viral factors [35] , [36] . We previously analyzed primate PARP13 orthologs to determine if the direct antiviral activity of PARP13 has led to a genetic conflict with viruses . Indeed , consistent with its antiviral function , we found a robust signature of positive selection in PARP13 in primates [37] . Interestingly , despite the fact that the zinc-finger domains of PARP13 directly bind viral RNA [27] , we found no signature of positive selection in these domains . Instead , we found sites of positive selection in the PARP catalytic domain , implying that this domain is a target for genetic conflict with viruses [37] . Although this domain in PARP13 appears to lack catalytic activity [4] , we nevertheless found that its removal from PARP13 decreased the level of viral restriction [37] , arguing that some function of the PARP domain remains intact . Thus , using an evolutionary signature of positive selection as a guide , we were able to identify a domain important for the antiviral activity of PARP13 . To address whether ADP-ribosylation plays a broad role in viral immunity , we wished to take a comprehensive evolutionary approach to look for evidence of rapid evolution in all of the human PARP genes . We reasoned that evolutionary signatures of recurrent adaptation , such as those previously observed in PARP13 , might reveal other uncharacterized PARP proteins that are involved in host-virus interactions . We therefore screened all 17 human PARP genes and their primate orthologs for signatures of recurrent positive selection . Contrary to expectations that most PARP genes are involved in ‘housekeeping’ functions , we found that nearly one third of human PARP genes bore signatures of recurrent genetic conflicts . In addition to PARP13 , our evolutionary screen revealed four other PARP genes that have evolved under very strong positive selection in primates: PARP4 , 9 , 14 and 15 . Two of these genes ( PARP14 and 15 ) have also undergone dramatic gene turnover ( gain and loss ) during vertebrate evolution , an additional hallmark of gene innovation also seen in innate immunity genes such as APOBEC3 and TRIM5 [38] , [39] . Based on their rapid evolution , we hypothesize that these four additional PARP genes are involved in as-yet-undescribed host-virus conflicts . Importantly , we anticipate that the identification of these rapidly evolving PARP genes and domains will enable future experiments to elucidate the role ADP-ribosylation plays in viral replication and host immunity .
Motivated by our hypothesis that ADP-ribosylation may be an important PTM in host-virus conflicts , and our prior use of positive selection analyses to identify an important antiviral domain in PARP13 , we investigated whether any of the other 16 human PARP genes also show signatures of recurrent positive selection . We searched publicly available primate genome sequences and identified orthologs of all 17 human PARP family members from a minimum of four hominoids , two Old World monkeys and one New World monkey . We performed a series of maximum likelihood analyses to detect recurrent positive selection for each PARP gene alignment . These analyses determine whether a model allowing positive selection at a subset of amino acid residues is a statistically better fit to the sequence data than a model that does not allow for positive selection . Using PAML software [40] , we found that five PARP genes showed highly statistically significant ( p-values <0 . 0001 ) signatures of positive selection ( Figure 1B ) . In addition to confirming our earlier findings on PARP13 , we found that PARP4 ( also known as vPARP ) and the three macrodomain-containing PARP genes ( PARP9/BAL1 , PARP14/BAL2 and PARP15/BAL3 ) all show signatures of positive selection . We followed up our PAML analyses with the more conservative PARRIS software implemented in the HyPhy package [41] , which takes into account recombination and variation in synonymous substitution rates across codons . Using PARRIS , we again found these five PARP genes to be clearly distinct from the remaining 12 as judged by likelihood ratio tests ( LRT ) allowing or disallowing positive selection ( Figure 1B ) . While our limited screen of seven orthologs in PARRIS only gave a statistically significant p-value ( <0 . 01 ) for PARP4 and PARP13 , analysis of additional sequences of PARP9 , PARP14 and PARP15 met statistical significance ( see below ) . Finally , we performed branch-site analyses [42] to look for episodic signatures of positive selection on all 17 primate PARPs . We found that only PARP4 , PARP9 and PARP13 demonstrated statistically significant signatures of episodic positive selection ( Figure S1 ) . This initial screen might underestimate the total number of PARP genes evolving under positive selection , firstly because our search is restricted to the primate lineage ( selection might have operated only in other mammalian lineages ) and secondly because we use only seven orthologs . Although such small alignments may lack power to detect weak selection , previous simulation studies have shown that strong selection on a subset of residues can be detected using PAML even with rather limited species surveys [43] . Given the signatures of positive selection we observed for PARP4 , 9 , 14 and 15 in this initial screen , we characterized these four genes in further detail , collecting additional orthologous sequences to examine which domains contain positively selected residues in order to create a model for how viral conflict may have driven their evolution . PARP4 , also known as vPARP ( vault PARP ) is a catalytically active poly-ADP-ribosyltransferase that is a component of widely conserved , large cytoplasmic ribonucleoprotein structures known as “vaults” . Vaults are barrel-shaped particles composed of three proteins , MVP ( major vault protein ) , PARP4 , and TEP1 ( telomerase associated protein ) , as well as vRNA ( vault RNA ) [44] . The function of vaults is unknown , but they have been implicated in drug resistance , cancer and immunity . In support of a role in immunity , MVP , the core structural component of the >10 mDa mass of vaults , is upregulated by IFN , and vaults are most highly expressed in immune cell types such as dendritic cells and macrophages [45] . From the alignment of seven PARP4 orthologs , we noted a ∼360 amino acid region that was much more divergent than the rest of the protein ( Figure 2A , Alignment S1 ) . This protein segment is completely encoded by the largest exon of PARP4 ( exon 30 in humans ) . To illustrate the unusual selective pressures on exon 30 , we performed a pairwise dN/dS comparison of human and rhesus PARP4s . We found that whereas the overall dN/dS ratio over PARP4 is 0 . 63 , the dN/dS ratio for exon 30 alone is 1 . 75 ( >95% confidence for dN/dS > 1 ) ( Table S3 ) . This striking discrepancy between the evolution of exon 30 and the rest of the protein raised the possibility that this exon alone was responsible for the signature of positive selection in PARP4 . We therefore repeated our positive selection analyses with exon 30 alone and found a robust signature of positive selection . In contrast , the remainder of PARP4 showed no signature of positive selection upon removal of exon 30 ( Figure 2B ) . Although we cannot formally rule out the possibility of weak selection acting outside exon 30 in PARP4 , our analysis strongly suggests that exon 30 of PARP4 has uniquely evolved under strong recurrent positive selection in primates . Because this evolutionary signature is isolated to a single exon , we next asked whether exon 30 is ever excluded from the PARP4 transcript . We searched human and rhesus expressed sequence tag ( EST ) databases and found that all isoforms of PARP4 include exon 30 , suggesting that exon 30 is important for PARP4 function . Next , we searched the region encoded by exon 30 for sequence or structural homology to other protein domains . Surprisingly , secondary structure prediction software ( JPRED [46] ) indicated that the region encoded by exon 30 in human PARP4 is almost entirely disordered . Taken together , we conclude that PARP4 has evolved under recurrent positive selection in primates , but that positive selection is focused on the disordered region encoded by exon 30 alone . We explored the signature of adaptive evolution in exon 30 of PARP4 in more detail by sequencing exon 30 from genomic DNA from additional primates ( Table S1 ) . Analysis of a total of 15 primate PARP4 exon 30 sequences confirmed our initial screening results that this region has evolved under positive selection ( PAML p-value <0 . 0001 , PARRIS p-value <0 . 01 ) ( Figure S2A and Alignment S1 ) . These analyses also identified several codons within exon 30 that display dramatic signatures of recurrent positive selection ( Table S4 ) . For instance , despite being in close proximity in the primary sequence to codons that are strictly conserved across primates , codon 1517 has undergone at least six amino acid changes during approximately 45 million years of simian primate evolution , with a calculated dN/dS ratio >3 ( Figure 2C ) . We also found that this pattern of rapid evolution in exon 30 extends to other vertebrate lineages . Despite high conservation in the rest of the PARP4 protein , the sequence and length of the largest exon ( corresponding to human exon 30 ) in PARP4 is highly variable among vertebrates . Consistent with our results in primates , all closely related pairs of vertebrate PARP4 orthologs analyzed demonstrated a signature of purifying selection throughout much of PARP4 contrasting with evidence for positive selection in the region corresponding to exon 30 of human PARP4 ( Figure 2D and Table S3 ) . To gain further insight into PARP4 evolution outside of primates , we asked whether other mammalian lineages show evidence for recurrent positive selection as we observed in primates . To do this , we took advantage of publicly available bat genome sequences , which , like primates , are divergent enough to provide sufficient evolutionary divergence , but not so divergent that the rate of synonymous mutation ( dS ) is saturated . Using sequences from 10 bat species ( Alignment S2 ) , we again found that PARP4 has evolved under recurrent positive selection in its largest exon ( PAML p-value <0 . 0001 , PARRIS p-value <0 . 01 ) ( Figure S2B-C ) . PAML identified six positively sites with high confidence ( Figure S2B-C , Table S5 ) . Although there is no overlap between positively selected sites identified in primates and bats , we found nine residues to be absolutely conserved across all 25 primate and bat species we analyzed ( Figure S2B-C ) , suggesting substantial constraint even within this rapidly evolving disordered protein domain . Combined , these broader phylogenetic analyses indicate that a single PARP4 region has been subject to positive selection throughout mammalian and bird evolution , suggestive of an ancient conflict with intracellular pathogens . Our evolutionary screen also revealed strong signatures of positive selection in PARP9 , PARP14 and PARP15 . Strikingly , these three genes encode the only three human proteins that contain both a PARP catalytic domain and macrodomains , and are the only human genes to encode more than one macrodomain . The macrodomain is unique among protein domains in its ability to recognize mono-ADP-ribosylated proteins [47] . Furthermore , some macrodomains have recently been shown to catalyze the removal of mono-ADPr [15] , [16] . Although the molecular functions of macro-PARPs are unclear , the presence of both PARP domains and macrodomains may conceivably allow them to both add and specifically recognize and/or reverse protein ADP-ribosylation . This , combined with the presence of macrodomains in viruses , prompted us to explore in more depth the evolution of other human macrodomain-containing proteins and ADP-ribosylhydrolases . Apart from the macro-PARPs , we found no evidence for positive selection in any other human gene encoding a macrodomain or ADP-ribosylhydrolase ( Figure S3 ) , suggesting that the combination of the macro- and PARP domains is important for their rapid evolution and , consequently , for their putative antiviral roles . In order to further pinpoint which domains and codons in the macro-PARP genes have evolved under positive selection , we sequenced additional macro-PARP orthologs from a diverse panel of primates . Combining these with publically available sequences , we aligned and analyzed 15 or more orthologs for each macro-PARP gene ( Table S1 , Figure S4 ) . Based on these expanded alignments , we confirmed the results of our initial screen; all macro-PARP genes have evolved under positive selection in simian primates ( PAML p-value <0 . 0001 , PARRIS p-value <0 . 01 ) . In contrast to the recurrent positive selection on only a single exon of PARP4 , we found that positively selected sites were broadly distributed throughout the macro-PARP genes ( Figure 3A ) . For all three macro-PARPs , we observed strong evidence of positive selection acting on the macrodomains . However , removal of the macrodomain-containing segments did not result in a loss of positive selection signatures , indicating that both macrodomains as well as other domains have evolved under positive selection ( Figure 3B ) . For instance , we found significant evidence for positive selection in the PARP domain of PARP14 ( Figure 3B ) , similar to PARP13 [37] . In contrast , our analyses did not reveal evidence of positive selection acting on the PARP domains of PARP9 and PARP15 ( Figure 3B ) , although it is possible that sequencing of additional orthologs might reveal more subtle signatures of selection . Thus , we conclude that macro-PARPs are evolving very rapidly , including substantial positive selection in the macrodomains of all three macro-PARPs . Our finding that macrodomains encoded by macro-PARP genes have evolved under positive selection motivated us to investigate whether equivalent residues were rapidly evolving in each macrodomain . Such a conserved pattern could suggest that related genetic conflicts ( for example , similar viral pathogens ) drove their evolution . Instead , we observed that a different set of residues is rapidly evolving in each macro domain at a primary sequence level ( Figure 3C , Tables S6-S8 and Alignment S3 ) . While equivalent amino acids are not evolving in all macro-PARPs , it is possible that positive selection has acted on a single three-dimensional protein surface . We therefore modeled the positively selected residues from PARP9 and PARP14 macrodomains onto a structure that has been determined for the first macrodomain of PARP14 [48] . We found that positively selected residues map to a single surface of each macrodomain , but that each macrodomain shows positive selection on a distinct surface ( Figure 3D ) . As each positively-selected surface is distinct relative to the site of ADP-ribose binding , these results suggest that ADP-ribose binding is not being altered or optimized by positive selection of the macrodomains . Instead , our findings suggest that each macrodomain has engaged in its own evolutionary arms race with as-yet-unidentified pathogen factors ( see Discussion ) . Because most antiviral genes do not serve essential housekeeping functions , they can be lost during periods when selective pressures are relieved , for example during periods when fewer relevant viral pathogens are prevalent in the population . In contrast , selection to increase the breadth of antiviral specificities could also lead to increase in gene copy number [34] . As a result of these repeated rounds of innovations , many organisms undergo dramatic changes in their antiviral gene repertoires over evolutionary timeframes , as has been observed with APOBEC and TRIM genes in mammals [38] , [39] . In our initial evolutionary screen , we had observed that most of PARP15 is missing from the white-cheeked gibbon genome . Coupled with previous findings of PARP15 absence in the mouse genome [10] , we therefore investigated PARP genes in general , with an emphasis on the macro-PARP genes , for signatures of rapid gene turnover . From our investigation of all seventeen PARP genes across a wide range of vertebrates , we found that PARP15 is unique in its pattern of recurrent loss ( Figure 4A ) . In contrast , other PARP genes are present in all genomes we examined , with the exception of PARP10 , which has been lost in the carnivore lineage . To explore the dynamics of PARP15 birth and loss , we conducted a more in-depth survey of PARP15 genes in vertebrate genomes ( Figure S5 ) . We found that PARP15 was born early in mammalian evolution via a partial duplication of PARP14 , consisting of the second and third macrodomains and the PARP domain . We found that PARP15 has been independently lost via deletion or inactivating mutations in five different mammalian lineages; PARP15 is therefore absent from gibbons , all glires ( rodents and lagomorphs ) , the cow/sheep/dolphin clade , alpaca/camel , and armadillo ( Figure 4B ) . Elephant and manatee have a conserved but shorter form of PARP15 , missing the first of the two macrodomains . In contrast to these losses in PARP15 , we identified several PARP14 duplications that occurred both within and outside the lineage that contains PARP15 . For instance , although fish and birds lack PARP15 orthologs , many fish and bird genomes have one or more additional copies of PARP14 that could possibly serve PARP15-analogous functions . Guinea pig and bushbaby each appear to have at least one extra intact copy of PARP14 , with the caveat that in each case a single exon is within a genome assembly gap . The microbat ( Myotis lucifigus ) genome contains at least eight PARP14/15 genes , of which at least two copies are intact ( two additional genes are incomplete in the assembly but are uninterrupted in available sequence by stop codons or frameshifts , suggesting they are also intact ) ( Figure 4B ) . Moreover , pairwise comparisons of duplicated PARP14 genes in microbat and bushbaby suggest that these paralogs may have regions that have rapidly diverged under positive selection ( Figure S7 ) , although additional sequences will be required to strengthen such a conclusion . Coupled with our findings that both PARP14 and PARP15 are evolving under positive selection in primates ( Figure 3 ) , the gene turnover we describe for PARP14 and PARP15 supports the idea that these genes have been selected for functional innovation , perhaps in response to a recurrent genetic conflict with pathogens .
Post-translational protein modifications are a common regulatory mechanism for modulating protein activity , stability and localization . As such , numerous viruses manipulate host PTM machinery to regulate their own replication or evade host antiviral immunity . Research aimed at understanding these viral strategies has provided critical insight into the host processes mediated by PTMs , including tyrosine phosphorylation and regulation of histone acetylation [1] , [2] . Inspired by the fact that signatures of positive selection can be used to highlight important genes and PTMs in host-virus conflicts , we performed an evolutionary screen on all of the primate PARP genes to ask if ADP-ribosylation is an important player in host-virus dynamics . Contrary to what would be expected of a PTM that is solely dedicated to housekeeping functions , we found strong evidence for rapid evolution in five of seventeen primate PARP genes , suggesting a broad involvement for PARPs , and ADP-ribosylation , in genetic conflicts . Moreover , we observed evolutionary signatures that suggested an ancient history of conflict for these PARP genes . For example , we see positive selection on PARP4 in diverse mammalian clades and recurrent gain and loss of PARP14 and PARP15 across vertebrates . Our findings suggest that PARP4 , 9 , 13 , 14 and 15 are each locked in a genetic conflict , likely with one or more pathogenic agents . Our data do not exclude the possibility that other genetic conflicts , perhaps in addition to viral conflicts , drove PARP positive selection . Indeed , the first discovery of manipulation of host processes by ADP-ribosylation emerged from the study of bacterial toxins ( e . g . , diphtheria , cholera toxins ) [49] , leaving open the possibility that bacterial or eukaryotic pathogens drove the evolution of PARP genes . However , we hypothesize that viruses may be significant or even the primary pathogens in these evolutionary arms races for several reasons . First , numerous viruses replicate poorly when ADP-ribosylation is inhibited , including viruses that replicate in the nucleus ( HSV ) [18] and cytoplasm ( vaccinia ) [17] . Second , several families of mammalian RNA viruses , including corona- and togaviruses , have non-structural proteins that contain macrodomains . In both corona- and togaviruses , disruption of viral macrodomains has been shown to reduce virulence [20] , [21] , and in the case of coronaviruses , this reduced virulence is due to increased sensitivity to the antiviral activity of interferon ( IFN ) [21] . This suggests a simple model in which the macrodomains ( at least in coronaviruses ) are required to counteract some IFN-stimulated host gene product . Although the identity of that IFN-stimulated factor is unknown , we note that several of the rapidly evolving PARP genes we identify here , including PARP9 , PARP13 and PARP14 , are upregulated by IFN [50] , [51] . Furthermore , overexpression of PARP9 , independent of IFN , is sufficient to upregulate several known antiviral effectors [50] . Finally , overexpression of several PARP genes has been shown to inhibit replication of viruses , the most well-described example being PARP13 . Taken together , we favor a model in which PARP gene evolution has been driven primarily by genetic conflicts with viruses . The patterns of evolution of the PARP genes allow us to make several inferences about the role of these proteins in genetic conflicts . First , the fact that we observe a robust evolutionary signature of positive selection in PARP4 , 9 , 13 , 14 and 15 argues strongly that these genes are important for organismal fitness . Similar to strong evolutionary conservation , signatures of positive selection indicate that fixation of a particular allele , in this case , a novel allele , results in a strong enhancement of fitness . While rapid evolution may seem antithetical to functional constraint , in fact positive selection is a common hallmark of critical host immunity genes [34] . Thus , we infer that the functions of the rapidly evolving PARP genes we have identified are important for fitness in the face of rapidly-evolving pathogens . Second , we also find that PARP14 and PARP15 show recurrent gene duplication and loss . This form of genetic innovation is another common hallmark of immunity genes . Gene losses occur during periods of relaxed selection due to non-exposure or extinction of relevant pathogen ( s ) , whereas gene duplications often provide additional genetic substrates for diversifying selection to increase anti-pathogen repertoires [34] , [52] . While other PARP proteins , such as PARP1 , PARP7 , PARP10 and PARP12 [30] , [31] , [32] , [33] , have been identified as having antiviral functions , our initial screen suggests they have not been subject to strong recurrent antagonistic evolution with viral factors in primates , perhaps because their encoded proteins do not directly interact with virus-encoded factors . Instead , our analyses lead to our novel hypotheses that PARP4 , PARP9 , PARP14 and PARP15 , as well as the molecular complexes they reside in , possess antiviral activity . For instance , PARP4 is a component of large cytoplasmic structures known as vaults , whose functions are poorly understood . Although vaults are extremely ancient , dating back to the origin of eukaryotes , they have been lost in multiple lineages [9] , suggesting that they are not universally necessary to perform an essential , housekeeping function . Instead , there are several tantalizing pieces of evidence that vaults may be involved in immunity . These include an increased number of vaults in immune cell types , IFN-upregulation of MVP , the major component of vaults , and upregulation of noncoding vault RNAs ( vRNAs ) on infection with pathogens such as Epstein-Barr virus [45] . PARP4 itself is present at ∼10 molecules per vault , but its functional role there is unknown [44] . However , our observation that the positively selected residues we find in PARP4 are localized to a single disordered region in PARP4 suggests a model for its role in vault-mediated immunity . Such a localized pattern of positively selected sites is reminiscent of two well-characterized rapidly evolving antiviral factors , TRIM5a and MxA , shown to be on the 'offensive' ( i . e . directly binding to viral proteins ) side of the host-virus conflict [34] . TRIM5a and MxA both use their rapidly evolving regions , also in the context of multimeric complexes , to directly recognize and target viral proteins , lentiviral capsids in the case of TRIM5a and orthomyxovirus nucleoproteins in the case of MxA [35] , [36] . Thus , we infer that the positively selected region of PARP4 ( exon 30 in humans ) has evolved to maintain recognition of a factor encoded by pathogens that can infect many diverse mammalian lineages , or is a common means to counteract independent unrelated pathogens . This interaction may be used to directly ADP-ribosylate viral components , which could affect their activity and impede infection . Alternatively , independent of ADP-ribosylation , PARP4 interaction may recruit viral proteins to the vault structures within virally infected cells , wherein the vault proteins might sequester viral proteins and thereby impede their infectivity . Likewise , our data highlight macrodomains as likely focal points of host-virus conflicts . However , in contrast to PARP4 , which we hypothesize is on the ‘offense’ i . e . , specifically targeting viral proteins , the widely distributed pattern of positively selected sites within the macro-PARPs is reminiscent of other host immunity factors that are evolving on the ‘defensive’ side ( i . e . , directly targeted by viral antagonists ) of evolutionary arms races [34] . In these cases , the host factor is performing a general antiviral function , such as shutting down host mRNA translation in the case of the antiviral protein PKR ( Protein Kinase R ) , or transducing an antiviral transcriptional program as in the case of the antiviral protein MAVS ( Mitochondrial Antiviral Signaling ) . As a result of their broad action , PKR and MAVS are antagonized by an array of proteins from diverse viral lineages that interact with different regions on the proteins [53] , [54] , [55] , [56] , [57] . The widely distributed pattern of positive selection in PKR [58] and MAVS [59] likely reflects this ‘defense’ against ( or escape from ) multiple antagonists . We postulate that the dispersed pattern of selection we observe in PARP9 , 14 and 15 similarly reflects selection to escape recognition by a variety of distinct viral antagonists of a hypothesized PARP-mediated antiviral response ( see below ) , rather than selection to maintain or establish recognition of viral target proteins . This ‘defense’ model to explain macro-PARP evolution , combined with the importance of virally encoded macrodomains for the fitness of several RNA viruses , allows us to generate a mechanistic hypothesis for the conflict that may have driven the rapid evolution of macro-PARP genes . In our model , ADP-ribosylation functions as a post-translational modification of either host or viral factors ( Figure 5A ) . We posit that macro-PARP proteins are recruited to sites of ADP-ribosylation by their macrodomains , most of which are predicted to be able to recognize , but not remove ADP-ribose ( Figure S5 ) , to exert either direct antiviral functions or recruit other antiviral factors . Recruitment of catalytically active macro-PARP genes could also facilitate further ADP-ribosylation of target proteins , allowing macro-PARP proteins to rapidly ‘amplify’ an initial signal of ADPr . Such a model of amplification by recruitment and additional ADP-ribosylation by PARP proteins has been seen at sites of DNA damage , where PARP1 activation by ADPr leads to increased ADP-ribosylation [7] , [8] . We hypothesize that some viruses have overcome this macro-PARP-mediated antiviral response by direct antagonism of macro-PARP proteins ( Figure 5B ) . Such antagonism could drive the rapid evolution we see in several regions of the macro-PARP genes , including but not limited to the macrodomains . However , other viruses , such as togaviruses and coronaviruses , have evolved their own macrodomains to either cleave ADP-ribose ( Figure 5C ) or compete with macro-PARP proteins ( Figure 5D ) , in order to overcome the effects of the macro-PARP proteins . Although speculative , our model provides testable hypotheses about the genetic and physical interactions between PARP macrodomains , viral macrodomains , and ADP-ribose , and their consequences in terms of determining outcomes of viral infections in cells . The exact antiviral consequences of macro-PARP action , and their cellular context , still remain unclear . However , recent studies on macro-PARPs implicate two candidate cellular processes . First , several PARP proteins ( PARPs 5a , PARP13 , PARP14 and PARP15 ) have been shown to be important for nucleation of stress granules in the cytoplasm , with ADP-ribosylation modulating miRNA activities [14] , [29] . This suggests that ADP-ribose in stress granules , or the miRNA functions that are altered by ADP-ribosylation , are targets for arms races with viruses . Stress granules have been shown to have antiviral properties stemming from mRNA sequestration , degradation and translational repression [60] . In contrast , several viruses localize to stress granules and employ them for replication [60] . Our model suggests that stress granule-associated PARP genes may be evolving to either combat the hijacking of stress granules or miRNA by viruses , or as direct mediators of the antiviral functions of stress granules or miRNAs . Alternatively , macro-PARPs may act at the level of gene expression , where ADP-ribosylation and macro-PARPs may influence transcription regulatory complexes . Indeed , after the initial discovery that PARP9 was highly expressed in aggressive B-cell lymphomas [61] , PARP9 and 14 were shown to regulate expression of several immunity-related genes [50] , [62] . Thus , one possible explanation for positive selection in the macro-PARP genes is that viral antagonists target them to prevent transcription of antiviral genes . Such viral antagonism could not only inform us of the role for macro-PARPs in the cells , but could also be used as a guide to devise useful interventions for treatment of the aggressive lymphomas that are associated with high PARP9 expression . Whether macro-PARPs are operating in stress granules or for antiviral transcription , or in both processes , our model suggest that host macrodomains , and ADP-ribosylation , play a critical role in formation of antiviral complexes , whereas viruses actively target these complexes for antagonism . To summarize , our evolutionary findings of recurrent positive selection of five PARP genes and gene turnover in two of those genes , together with previous observations by others ( inhibition of viral replication by some PARP genes , viral modulation by chemical inhibitors of PARP activity , pathogenicity dependent on virally-encoded macrodomains in diverse RNA viruses ) argue that ADP-ribosylation is a fundamental determinant of host-virus conflicts . Our results raise compelling hypotheses for the function of rapidly evolving PARP genes in these conflicts , and highlight the insights that can be gained from evolutionary analyses of previously poorly characterized genes .
Publically available genome assemblies from human ( Homo sapiens ) , chimpanzee ( Pan troglodytes ) , orangutan ( Pongo abelii ) , white-cheeked gibbon ( Nomascus leucogenys ) , rhesus macaque ( Macaca mulatta ) , baboon ( Papio anubis ) and marmoset ( Callithrix jacchus ) were queried for PARP genes . The PARP12 gene is in a poorly assembled region of the orangutan genome and was therefore incomplete . The PARP15 gene is almost entirely deleted from the white-cheeked gibbon genome; exon 4 is still present but contains a stop codon . We therefore used PARP12 and PARP15 sequences from the publically available gorilla ( Gorilla gorilla ) genome assembly to ensure that seven primate sequences were used in all analyses . PARP4 exon 30 sequences were amplified from DNA isolated from cell lines obtained from Coriell Cell Repositories ( Camden , NJ ) , the FrozenZoo ( San Diego , CA ) , ATCC ( Manassas , VA ) and the Tulane National Primate Research Center ( Covington , LA ) ( Table S1 ) . Sequences were amplified by PCR using Phusion ( New England Biolabs ) polymerase using primers that anneal to the introns around exon 30 ( primer sequences in Table S2 ) . PARP9 , 14 and 15 sequences were amplified from RNA isolated from cell lines ( Table S1 ) . Sequences were amplified by one step reverse-transcription PCR using SuperScript III One-Step RT-PCR with Platinum Taq ( Invitrogen ) to produce complementary DNA ( cDNA ) using the primers listed in Table S2 . Repeated attempts to amplify PARP15 from Siamang gibbon failed , supporting the conclusion that gibbons have lost PARP15 . cDNAs were directly sequenced using internal primers by Sanger sequencing . Sequences from gorilla and squirrel monkey ( Saimiri boliviensis ) were obtained from publically available genome assemblies . PARP4 exon 30 sequences from primates have been deposited to Genbank under accession numbers KJ699095-KJ699100 . PARP9 , 14 and 15 mRNA sequences have been deposited to Genbank under accession numbers KJ697725-KJ697749 . PARP sequences were aligned in Geneious [63] and alignments were edited to remove gaps and ambiguities . Maximum likelihood ( ML ) tests were performed with codeml in the PAML software suite [40] . Aligned sequences were subjected to ML tests using NS sites models disallowing ( M8a ) or allowing ( M8 ) positive selection . The p-value reported is the result of a chi-squared test on twice the difference of the likelihood values between the two models using one degree of freedom . All analyses were consistent when performed with varying models of codon frequency ( F61 and F3×4 ) and varied starting omega values ( 0 . 4 and 1 . 5 ) . Residues with recurrent signatures of positive selection with a posterior probability greater than 0 . 95 were identified using a Bayes Empirical Bayes ( BEB ) analysis in PAML and the F3×4 codon frequency model . A second set of maximum likelihood tests was performed using PARRIS in the HyPhy software suite [41] , which also compares models disallowing or allowing positive selection . We report twice the difference in the log likelihood values ( LRT ) , and a p-value based on that difference . Signatures of episodic positive selection were calculated in two ways . Overall dN/dS ratios for each branch of the phylogenetic tree were calculated using the free ratio model in PAML . A branch-site test ( Branch-site REL [42] ) for statistically significant signatures of episodic positive selection was performed using the HyPhy software suite [41] . K-estimator [64] was used for all pairwise sequence analyses of dN/dS ratios . For comparisons of the large exon of vertebrate PARP4 ( e . g . human and rhesus exon 30 ) , we used K-estimator to distinguish high pairwise dN/dS values due to positive selection from the possibility that these sequences are neutrally evolving , but that stochastic fluctuations in small mutation numbers cause apparently large dN/dS ratio differences . For a pair of sequences with a certain number of observed mutations , K-estimator uses Monte Carlo simulations to obtain "bootstrap" estimates of how likely it would be to see high dN/dS values if sequences were neutrally evolving . For example , comparing human and rhesus PARP4 exon 30 ( dN/dS ratio of 1 . 75 ) , there is greater than 95% confidence that a dN/dS ratio of 1 . 75 represents a significant signature of positive selection . Sliding window analyses were performed on pairs of aligned vertebrate PARP4 and PARP14 sequences with a window size of 150 codons and a step size of 50 codons . To reconstruct the dynamics of PARP14 and 15 gain and loss , publically available vertebrate genome assemblies and gene prediction datasets were queried for PARP genes using a combination of blast searches [65] , pairwise comparisons of genomic sequences using dotter [66] and the sim4cc program [67] that aligns reference cDNA sequences to genomic sequences from other species . We eliminated from further analysis any PARP sequences that contained frameshifts or nonsense mutations , but retained some genes that were missing up to three exons within genome assembly gaps . Protein sequences were aligned using CLUSTALW [68] with manual adjustment and maximum likelihood phylogenetic trees ( 1000 bootstrap replicates ) were constructed using PhyML [69] using the best-fitting evolutionary model ( JTT+I+G+F ) as determined by Prottest [70] . Trees were displayed using MEGA [71] . Macrodomains from PARP9 and 14 were aligned and mapped to the known structure of the first macrodomain of PARP14 complexed with ADP-ribose ( PDB code 3Q6Z ) [48] . Figures were generated using PyMol [72] .
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The outcome of viral infections is determined by the repertoire and specificity of the antiviral genes in a particular animal species . The identification of candidate immunity genes and mechanisms is a key step in describing this repertoire . Despite advances in genome sequencing , identification of antiviral genes has largely remained dependent on demonstration of their activity against candidate viruses . However , antiviral proteins that directly interact with viral targets or antagonists also bear signatures of recurrent evolutionary adaptation , which can be used to identify candidate antivirals . Here , we find that five out of seventeen genes that contain a domain that can catalyze the post-translational addition ADP-ribose to proteins bear such signatures of recurrent genetic innovation . In particular , we find that all the genes that encode both ADP-ribose addition ( via PARP domains ) as well as recognition and/or removal ( via macro domains ) activities have evolved under extremely strong diversifying selection in mammals . Furthermore , such genes have undergone multiple episodes of gene duplications and losses throughout mammalian evolution . Combined with the knowledge that some viruses also encode macro domains to counteract host immunity , our evolutionary analyses therefore implicate ADP-ribosylation as an underappreciated key step in antiviral defense in mammalian genomes .
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2014
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Rapid Evolution of PARP Genes Suggests a Broad Role for ADP-Ribosylation in Host-Virus Conflicts
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In resource-poor areas , infectious diseases may be important causes of morbidity among individuals infected with the Human T-Lymphotropic Virus type 1 ( HTLV-1 ) . We report the clinical associations of HTLV-1 infection among socially disadvantaged Indigenous adults in central Australia . HTLV-1 serological results for Indigenous adults admitted 1st January 2000 to 31st December 2010 were obtained from the Alice Springs Hospital pathology database . Infections , comorbid conditions and HTLV-1 related diseases were identified using ICD-10 AM discharge morbidity codes . Relevant pathology and imaging results were reviewed . Disease associations , admission rates and risk factors for death were compared according to HTLV-1 serostatus . HTLV-1 western blots were positive for 531 ( 33 . 3% ) of 1595 Indigenous adults tested . Clinical associations of HTLV-1 infection included bronchiectasis ( adjusted Risk Ratio , 1 . 35; 95% CI , 1 . 14–1 . 60 ) , blood stream infections ( BSI ) with enteric organisms ( aRR , 1 . 36; 95% CI , 1 . 05–1 . 77 ) and admission with strongyloidiasis ( aRR 1 . 38; 95% CI , 1 . 16–1 . 64 ) . After adjusting for covariates , HTLV-1 infection remained associated with increased numbers of BSI episodes ( adjusted negative binomial regression , coefficient , 0 . 21; 95% CI , 0 . 02–0 . 41 ) and increased admission numbers with strongyloidiasis ( coefficient , 0 . 563; 95% CI , 0 . 17–0 . 95 ) and respiratory conditions including asthma ( coefficient , 0 . 99; 95% CI , 0 . 27–1 . 7 ) , lower respiratory tract infections ( coefficient , 0 . 19; 95% CI , 0 . 04–0 . 34 ) and bronchiectasis ( coefficient , 0 . 60; 95% CI , 0 . 02–1 . 18 ) . Two patients were admitted with adult T-cell Leukemia/Lymphoma , four with probable HTLV-1 associated myelopathy and another with infective dermatitis . Independent predictors of mortality included BSI with enteric organisms ( aRR 1 . 78; 95% CI , 1 . 15–2 . 74 ) and bronchiectasis ( aRR 2 . 07; 95% CI , 1 . 45–2 . 98 ) . HTLV-1 infection contributes to morbidity among socially disadvantaged Indigenous adults in central Australia . This is largely due to an increased risk of other infections and respiratory disease . The spectrum of HTLV-1 related diseases may vary according to the social circumstances of the affected population .
The Human T Lymphotropic Virus type 1 ( HTLV-1 ) is an oncogenic retrovirus that preferentially infects CD4+ T cells [1] . Worldwide , HTLV-1 infects at least 5–10 million people who predominantly dwell in areas of high endemicity in southern Japan , the Caribbean basin , parts of South America and inter-tropical Africa . A smaller endemic focus is present in central Australia [2] and we have recently shown this to be due to infection with the HTLV-1c subtype [3] . Epidemiological and clinical associations have been best described for populations in the Caribbean basin , South America and Japan [1] . A minority of HTLV-1 carriers experience clinically significant sequelae , including a rapidly progressive hematological malignancy , Adult T cell Leukemia/Lymphoma ( ATLL ) [4] , [5] , and inflammatory disorders , such as HTLV-1 associated myelopathy/tropical spastic paraparesis ( HAM/TSP ) [6] . A severe exudative eczema , infective dermatitis , predominantly affects children [7] . In Japan and the Caribbean , life-time risks range between 0 . 3–4% for HAM/TSP , 1–5% for ATL [1] and approach 10% for HTLV-1 associated malignancy or inflammatory diseases overall [1] . Infectious diseases also contribute to HTLV-1 related morbidity and mortality . Severe scabies [8] , mycobacterial infections [9] and symptomatic infection with the nematode parasite Strongyloides stercoralis [10] , [11] are all more frequent among HTLV-1 carriers . In areas endemic for HTLV-1 and S . stercoralis , HTLV-1 infection is the major risk factor for complicated strongyloidiasis or ‘hyperinfection’ , which is associated with pulmonary involvement [12] and life-threatening sepsis due to enteric bacterial pathogens [13] . Infection with S . stercoralis may also reduce the latent period required for the development of ATLL [14] . HTLV-1 infection reduces clearance rates of hepatitis C virus and increases the risk of liver disease and liver disease-related deaths [15] . Whether the risk of chronic hepatitis B virus ( HBV ) infection is similarly affected is unknown . Interactions between HTLV-1 related inflammatory diseases and infection have also been demonstrated . Infective dermatitis , for example , typically affects HTLV-1 carriers from lower socio-economic backgrounds and predisposes to skin infections with bacterial pathogens [7] , which may progress to life-threatening invasive disease [16] . Recently , we reported high rates of HTLV-1 infection among socially disadvantaged Indigenous adults with bronchiectasis in central Australia [17] . Clinically significant pulmonary disease is not a feature of HTLV-1 infection in other developed countries [18]–[20] , and we suggested that recurrent lower respiratory tract infections ( LRTI ) might contribute to this risk in our study population . The spectrum of HTLV-1 related clinical diseases may therefore differ according to social status and the risk of environmental exposure to other pathogens . However , demonstrating such an effect requires diagnostic capabilities that may not be available in developing countries in which a heavy burden of infectious diseases affects a population with a high prevalence of HTLV-1 infection . Central Australia is well placed to study the associations between poverty and infectious diseases [21] . HTLV-1 is endemic to this region and infects 7 . 2–13 . 9% [22] , [23] of socially disadvantaged Indigenous adults . There has been no attempt to control HTLV-1 transmission among the Indigenous residents of central Australia , most of whom reside in isolated remote communities in conditions of considerable socio-economic disadvantage [21] . Those who live in the major regional center of Alice Springs dwell in either overcrowded ‘town camps’ , which have poor amenities and limited refuse disposal , or are integrated with the majority of the non-Indigenous population within the township's suburbs [21] . Central Australia also has the highest reported blood stream infection ( BSI ) incidence rates [21] and the highest prevalence rate of adult bronchiectasis [17] worldwide . Prevalence rates of chronic HBV infection exceeded 20% in some communities prior to the introduction of vaccination [24] . Consequently , infection-related mortality rates approach those of some African countries prior to the current HIV pandemic [25] . A single well-resourced community-based hospital , Alice Springs Hospital ( ASH ) , serves this region of 1 , 000 , 000 km2 ( Fig . 1 ) . Critically ill patients are retrieved by air to tertiary referral centers 1 , 500 km away . Medical services are provided without charge and , notwithstanding the poor social circumstances of the resident population , sophisticated radiological , microbiological and other diagnostic facilities are readily available . The present study describes the spectrum of HTLV-1 associated diseases that affects socially disadvantaged Indigenous adults in central Australia .
This study was approved by the Central Australian Human Research Ethics Committee , which is a regional committee supervised by the National Health and Medical Research Council of Australia . All adults ( age ≥15 years ) admitted to ASH between 1st January 2000 and 31st December 2010 who had an HTLV-1 screening test performed were identified from the hospital pathology data-base . HTLV-1 testing at ASH is performed where there are clinical suspicions of HTLV-1 related diseases , including malignancy , neurological disease , strongyloidiasis and bronchiectasis . Demographic data including ethnicity , dates of birth and death , indigenous status and place of residence were obtained for all patients from the ASH patient management system . For each admission between 1st January 2005 and 31st December 2010 International Statistical Classification of Diseases and Related Health Problems , Tenth Revision , Australian Modification ( ICD-10 AM ) morbidity codes relating to non-communicable diseases , possible HTLV-1 related conditions and infectious diseases were also extracted ( Table S1 ) . Discharge morbidity codes for admissions prior to 2005 were not available and patients who died prior to this date were therefore excluded from statistical analysis . All data were de-identified prior to analysis . Infectious diseases were grouped according to ICD-10 AM codes; i ) sepsis or bacterial infection for which a focus was not stated , ii ) specified foci of infection and iii ) strongyloidiasis ( Table S1 ) . HTLV-1 related conditions included ATLL , HAM/TSP , bronchiectasis and infective dermatitis . Cases of ATLL and HAM/TSP were also sought from specialist neurological and hematological units that provide tertiary level care to ASH patients . Case notes , microbiology , radiology and other relevant pathology results were reviewed for all patients with possible HTLV-1 related conditions including ATLL , neurological disorders , bronchiectasis and infective dermatitis . Place of residence was categorized as i ) remote ( >80 km from Alice Springs ) , ii ) Alice Springs town camp and iii ) urban ( resident in Alice Springs , but not in a town camp ) . Remote residence was further divided into quadrants ( north , south , east and west ) relative to Alice Springs . Results for S . stercoralis serology , HBV serology and blood cultures were obtained from the ASH pathology data-base . During the study period , S . stercoralis serology was performed using an in-house enzyme-linked immunosorbent assay based on antigen extracts of Strongyloides ratti , which is highly sensitive and specific . A blood culture from which a pathogen was isolated defined a ‘BSI episode’ . Repeated culture of the same organism from blood culture was regarded as a separate ‘episode’ only if blood samples were drawn more than one month apart . Blood stream infections excluded potential contaminants including coagulase negative staphylococci , bacillus spp . , coryneforms and viridans streptococci unless grown from more than one BC in a 24 hour period and Acinetobacter spp in the absence of an identifiable focus . For statistical analysis , the major BSI pathogens were grouped according to their most likely origin: i ) skin ( Staphylococcus aureus and Streptococcus pyogenes ) , ii ) respiratory ( Streptococcus pneumoniae and Haemophilus influenzae ) , iii ) urinary tract ( Escherichia coli ) and iv ) gastrointestinal tract ( Enterobacteriaceae other than E . coli ) . ‘Definite bronchiectasis’ was defined as an ICD-10 AM code for bronchiectasis that was confirmed by High Resolution Computed Tomography ( HRCT ) chest according to American College of Chest Physicians criteria . ‘Possible bronchiectasis’ was defined as an ICD-10 AM code for bronchiectasis in the absence of HRCT chest confirmation of this diagnosis . A diagnosis of ATLL [4] and HAM/TSP [26] was made using established criteria . Cases of HAM/TSP were categorized as ‘probable’ if the clinical presentation was consistent with HAM/TSP in the absence of confirmatory analysis of cerebrospinal fluid ( CSF ) [26] . Initial screening tests were performed using the Serodia HTLV-1 particle agglutination assay ( Fujirebio , Japan ) or Architect rHTLV-I/II assay at the Royal Darwin Hospital , Northern Territory of Australia , ( 1458 ) or the Institut Pasteur , Paris ( 156 ) . Positive samples were again tested using both the Serodia HTLV-1 particle agglutination assay and Murex HTLV-I+II test kit ( Murex Diagnostics , Dartford , UK ) ( National Serological Reference Laboratory , Melbourne ) or an indirect immunofluorescence assay ( IFA ) using an HTLV-1-transformed human T cell line ( MT2 ) ( Institut Pasteur ) . HTLV-1 serostatus was then confirmed by Western blot ( HTLV Blot 2 . 4 , MP Diagnostics ) using stringent criteria for all samples for which screening tests were positive . Categorical variables were summarized using frequency and percentage and compared using a Chi-square test or , in the case of small numbers , a Fisher's Exact test . Multiple simultaneous comparisons were adjusted for using a Bonferroni correction . Continuous variables were assessed for significant departures from normality with normally distributed variables summarized using mean and standard deviation ( SD ) and compared using a t-test whilst skewed variables were summarized using median and inter-quartile range ( IQR ) and compared using a Wilcoxon rank-sum test . Predictors of HTLV-1 seropositivity were examined using Poisson regression with robust standard errors . Strongyloides admissions ( identified by ICD-10 AM codes ) , rather than serology , were included in the multivariable model because these are more likely to reflect symptomatic strongyloidiasis [10] , [11] , [27] . Direct modeling of relative risk ( RR ) using Poisson was preferred over Odds Ratios ( OR ) from logistic regression to estimate RR due to the frequency of the outcome studied . A link test was used to assess the model for specification error whilst overall goodness of fit was assessed using both visual examination of residuals coupled with a likelihood-ratio test and a Pearson goodness-of-fit test . Incidence rates of admission count by diagnostic group were expressed as a proportion of the total number of HTLV-1 seropositive and seronegative patients respectively . Predictors of admission counts for a range of diagnostic groups according to HTLV-1 seropositivity were examined using negative binomial regression and are presented with their negative binomial 95% confidence intervals . Negative binomial modeling was preferred over straight Poisson regression due to over-dispersion in admission count outcome variables . The model coefficients represent the estimated change in admission counts for a particular level of a predictor variable . The influence of HTLV-1 seropositivity on admission count was adjusted for demography and comorbidities . In the case of admissions with asthma , LRTI , pneumonia and chronic obstructive pulmonary disease , the model was adjusted for both definite and possible bronchiectasis and tobacco smoking . A link test was used to assess the model for specification error whilst overall goodness of fit was assessed using both visual examination of residuals coupled with a likelihood-ratio test and a Pearson goodness-of-fit test . Predictors of hepatitis B surface antigen ( HBsAg ) positivity were analysed using logistic regression . In this case , a logistic approach was preferred secondary to the rarity of the outcome . Overall model fit was assessed using a Hosmer & Lemeshow goodness-of-fit test . Predictors of time to mortality were examined using Cox Proportional Hazards Regression . Analysis of scaled Schoenfeld residuals were used to assess compliance with the proportional hazards assumption . For this analysis patients with possible bronchiectasis were assumed not to have the condition . All reported p-values are two-tailed and for each analysis p<0 . 05 was considered significant . All analyses were conducted using Stata version 12 ( StataCorp , College Station , Texas ) .
HTLV-1 seropositivity rates among males increased significantly with age ( <45 years , 106/329 ( 32 . 2% ) ; ≥45 years , 135/319 ( 42 . 2% ) ; p = 0 . 008 ) . Rates were otherwise not significantly different between age groups or genders ( Table 1 ) . Seropositivity rates differed according to place and type of residence . Rates were lowest among residents of communities north of Alice Springs ( 14 . 6% ) and highest among those from communities to the south ( 64 . 3% ) and west ( 37 . 5% ) ( Fig . 1 ) ( Table 1 ) . Seropositivity rates were higher among town camp residents ( 42 . 6% ) and lowest among those living elsewhere in the township ( 27 . 0% ) . Demographic risk factors for HTLV-1 infection after multivariable analysis included age ( adjusted RR , 1 . 01 per year; 95% CI , 1 . 01–1 . 02; p = 0 . 000 ) and residence in communities to the south ( aRR 3 . 83; 95% CI , 2 . 64–5 . 57; p = 0 . 000 ) and west ( aRR 2 . 77; 95% CI , 1 . 54–3 . 37; p = <0 . 001 ) of Alice Springs relative to those in the north ( Table 2 ) . Nearly 70% of patients ( HTLV-1 seropositive , 391; HTLV-1 seronegative , 621 ) recorded at least one discharge code for sepsis with no focus specified during the study period . Although HTLV-1 carriers more often recorded discharge codes for sepsis with no focus specified ( Table 3 ) and had higher admission numbers for this category ( Table 4 ) , these associations were lost after adjusting for covariates ( Table 5 ) . HTLV-1 carriers were also more likely to experience a BSI ( Table 6 ) and had more BSI episodes after adjusting for covariates ( Table 5 ) . When analyzed according to the most likely origin of infection , BSI from a probable gastrointestinal source remained significantly associated with HTLV-1 infection in a multivariable model ( aRR , 1 . 36; 95% CI , 1 . 05–1 . 77; p = 0 . 020 ) ( Table 2 ) . Among 988 ( 68 . 1% ) patients tested , 127 ( 12 . 9% ) were HBsAg positive of whom 16 ( 12 . 6% ) were also HBeAg positive ( Table 6 ) . The geographic distribution of HBsAg positivity was similar to that of HTLV-1 seropositivity . Risk was greatest among residents of remote communities to the south ( unadjusted odds ratio ( uOR ) , 3 . 98; 95% CI , 2 . 23–7 . 10 ) and west ( uOR , 2 . 23; 95% CI , 1 . 25–3 . 99 ) compared with northern communities and was reduced for urban relative to remote residents ( uOR , 0 . 30; 95% CI , 0 . 14–0 . 64 ) . Although HTLV-1 infected patients were more likely to be HBsAg positive ( HTLV-1 seropositive , 65/201 ( 32 . 3% ) ; HTLV-1 seronegative , 62/338 ( 18 . 3% ) ( p = <0 . 001 ) ( Table 6 ) , exposure to HBV was more frequent among HTLV-1 seropositive patients ( anti-HBc positive: HTLV-1 seropositive , 59 . 6%; HTLV-1 seronegative , 51 . 9% ) ( p = 0 . 021 ) ( Table 6 ) and HBsAg positivity was not associated with HTLV-1 infection in a multivariable model ( Table 2 ) . Among 338 deaths that occurred during 5 , 739 years of follow-up , 120 ( 23 . 7% ) were HTLV-1 seropositive and 218 ( 23 . 1% ) were HTLV-1 seronegative . There was no difference between HTLV-1 seropositive and seronegative patients in median age of death ( HTLV-1 seropositive , 56 . 9 years; IQR , 46 . 2 , 63 . 9 ) ; HTLV-1 seronegative , 53 . 2 years; IQR , 44 . 4 , 62 . 5 ) ( Table 1 ) . Demographic risk factors for death included male gender and increasing age ( Table 7 ) . Bronchiectasis ( HR , 2 . 07; 95% CI , 1 . 45–2 . 98; p = 0 . 000 ) and BSI with Enterobacteriaceae other than E . coli ( HR 1 . 78; 95% CI , 1 . 15–2 . 74; 0 . 009 ) remained significant predictors of death after multivariable analysis ( Table 7 ) . Other risk factors for death were S . pneumoniae BSI ( HR , 1 . 70; 95% CI , 1 . 09–2 . 64; p = 0 . 018 ) and non-communicable diseases ( chronic liver disease , diabetes and malignancy ) ( Table 7 ) .
In a hospitalized cohort of Indigenous Australian adults , we found an HTLV-1 seropositivity rate ( 33 . 3% ) that was approximately three times the estimated background rate in central Australia ( 7 . 2–13 . 9% ) [22] , [23] . This suggests that HTLV-1 associated morbidity in our study population may substantially exceed that resulting from the occasional cases of ATLL and HAM/TSP that are reported here . Consistent with its global epidemiology [2] , HTLV-1 carriers were more likely to live in poverty in town camps or remote communities and more often had a history of harmful alcohol consumption . HTLV-1 infection was associated with strongyloidiasis and blood stream infections with enteric pathogens; however , respiratory diseases contributed most to HTLV-1 related morbidity in this socially disadvantaged Indigenous population . After adjusting for covariates , HTLV-1 infection was associated with bronchiectasis and with increased admission numbers for all respiratory conditions studied with the exception of chronic obstructive pulmonary disease . Pulmonary involvement is common among HTLV-1 carriers elsewhere . Radiological abnormalities , for example , have been reported in 50% of Japanese patients with HAM/TSP and 30% of asymptomatic HTLV-1 carriers who were examined by chest X-ray [28] and chest CT [29] , respectively . Airway involvement is frequent in this population; chest CT reveals bronchiolitis or bronchitis in 19% [30] and bronchiectasis in 18–26% [29] , [30] of cases . Lymphocyte infiltration of bronchioles [31] and partial bronchiolar obstruction [31] , [32] are the histopathological correlates of these radiological findings . Lymphocytes obtained from HTLV-1 carriers by bronchoalveolar lavage ( BAL ) have high HTLV-1 proviral loads [33] , [34] and these are correlated with those of peripheral blood [31] . An inflammatory response to the HTLV-1 antigen load derived from infected lymphocytes is thought to be the major determinant of other HTLV-1 related inflammatory diseases [35] . Airway inflammation in response to HTLV-1 antigens , such as the immuno-dominant regulatory protein , Tax [30] , may therefore provide the pathological basis for clinical associations with asthma and LRTI other than pneumonia in our Indigenous cohort and for the increased incidence of self-reported asthma among HTLV-1 carriers in the USA [20] . Nevertheless , clinically significant pulmonary disease is an uncommon feature of HTLV-1 infection in developed countries [18]–[20] . In contrast , HTLV-1 infection contributes to bronchiectasis prevalence rates among Indigenous adults in central Australia that are the highest reported worldwide [17] . In the present study , 142 cases of bronchiectasis were confirmed by HRCT and nearly 60% of these patients were HTLV-1 infected . Consistent with our previous study [17] , bronchiectasis was associated with a very high early mortality . Previously we have shown that HTLV-1 infection is associated with more extensive bronchiectasis , more frequent right heart failure and with bronchiectasis-related deaths [17] . In a recent case-control study the mean HTLV-1 proviral load in peripheral blood lymphocytes was significantly higher among HTLV-1 infected patients with bronchiectasis [36] . An HTLV-1 mediated inflammatory process [35] may therefore underlie HTLV-1 associated pulmonary disease in our study population . Disease progression to multifocal bronchiectasis might then follow further pulmonary injury resulting from recurrent LRTI , which were more common among HTLV-1 carriers in the present study . Consistent with the results of other studies [27] , [37] , HTLV-1 carriers in central Australia were not at increased risk of serologically defined strongyloidiasis . Nevertheless , HTLV-1 infection in other populations is associated with a higher larval burden and with increased risks of symptomatic , recurrent and complicated strongyloidiasis [10] , [11] , [27] . Our study design and the use of serological tests to diagnose strongyloidiasis preclude any assessment of disease severity . However , HTLV-1 carriers in the present study were more likely to be admitted with a diagnosis of strongyloidiasis and had higher admission numbers for this condition , findings that could result from a higher larval burden . Unfortunately , our analysis of admission numbers for strongyloidiasis might also be confounded by the acknowledged disease association with HTLV-1 infection , which may lower the clinical threshold for administering antihelminthics to HTLV-1 carriers and increase the likelihood that a Strongyloides-related ICD-10 AM code is recorded . The association between HTLV-1 infection and strongyloidiasis in central Australia therefore requires confirmation in a prospective study . Nevertheless , high rates of S . stercoralis infection were found among Indigenous adults in an arid region of Australia that would appear otherwise hostile to soil transmitted helminths . The presence of HTLV-1 infected ‘core transmitters’ who carry a high larval burden may be central to the survival of S . stercoralis in this environment and could increase the risk of S . stercoralis infection among other community members . Strongyloidiasis may also contribute to the very high BSI incidence rates that have been reported in central Australia [38] . Among Indigenous adults in this region , enteric gram-negative bacilli are the most common pathogens isolated from blood [38] and we have previously reported BSI-related deaths among patients with complicated strongyloidiasis [13] . In our Indigenous Australian cohort , respiratory and infection-related morbidity were increased among HTLV-1 carriers in the absence of an increased risk of death . However , an effect of HTLV-1 infection on mortality may be obscured by analysis according to HTLV-1 serological status rather than HTLV-1 proviral load , which is closely associated with HTLV-1 related diseases [1] . Certainly , the recent finding of higher HTLV-1 proviral loads among HTLV-1 carriers with bronchiectasis [36] suggests that stratifying mortality by HTLV-1 proviral load may more accurately reflect risk in our patient population . Interestingly , an increased risk of death among HTLV-1 carriers in Guinea-Bissau [39] , [40] is associated with higher HTLV-1 proviral loads [41] . A modest increase in all-cause mortality has also been reported among HTLV-1 carriers in Japan [42]; however , no such association has been found for blood donors in the USA [43] . These geographic differences in HTLV-1 associated mortality might reflect environmental conditions in resource poor areas that predispose to recurrent respiratory tract infections and expose HTLV-1 carriers to other pathogens , such as Mycobacterium tuberculosis [39] and S . stercoralis [12] . The retrospective nature of this study results in a number of limitations . First , patients with HTLV-1 related diseases were identified from discharge morbidity codes . Attempts were made to identify other patients with these conditions by contacting specialist medical units to which such patients are referred; however , cases may have been missed if these were not coded or referred appropriately . Consequently , our data are likely to under-estimate the actual burden of HTLV-1 related diseases in this population . The risk of bronchiectasis attributable to HTLV-1 infection is also likely to be underestimated because individuals who had not received radiological confirmation of this diagnosis were assumed not to have the condition . Similarly , the effect of HTLV-1 infection on respiratory conditions may be underestimated because ‘possible’ bronchiectasis was included in the final model to account for the increased risk of respiratory infection resulting from structural lung disease . Determining the strength of other possible associations was dependent on the accuracy of discharge coding; however , with the possible exception of strongyloidiasis noted above , this is unlikely to vary according to HTLV-1 serological status . Finally , we assumed that HTLV-1 infection was acquired in most cases prior to the period in which ICD-10 AM codes were collected . The low annual incidence rate of HTLV-1 seroconversion among discordant couples [1] suggests that this is likely to be the case . Indeed , vertical transmission may be relatively more important in our study population due to the substantial risks posed by the custom of prolonged breast-feeding [44] . Strengths of the study are the large sample size , which included 10% of the region's Indigenous adult resident population , the presence of a single well-resourced hospital that serves this population and the use of data from different sources to study the HTLV-1 related associations reported here . In a setting of overcrowded housing , inadequate health hardware and poor community hygiene [45] , [46] , HTLV-1 infection substantially increases respiratory and infection-related morbidity . Socially disadvantaged HTLV-1 carriers in our Indigenous Australian cohort experienced more BSI episodes and were more often admitted with respiratory conditions including LRTI and bronchiectasis , which was the major independent risk factor for death . In contrast to other developed countries [1] , infection-related complications were more common than either ATLL or HAM/TSP . The spectrum of HTLV-1 related diseases is therefore likely to vary according to the social circumstances of the affected population . These findings have not been reported previously; however , access to the medical facilities required to confirm these diagnoses is limited in developing countries in which populations with a similar burden of disease exists . Clearly , the benefits accrued by controlling the vertical transmission of HTLV-1 in a resource poor setting must be considered relative to the capacity of the health care system to ensure the safety of alternative sources of infant nutrition . However , our data provides strong support for public health interventions , such as improvements to housing and community hygiene , that limit the exposure of HTLV-1 carriers to other pathogens .
|
The Human T-Lymphotropic Virus type 1 ( HTLV-1 ) infects at least 5–10 million people worldwide . In developed countries , the most frequently reported HTLV-1 associated diseases include a fatal hematological malignancy , Adult T-cell Leukemia/Lymphoma ( ATLL ) , and the neurological disorder , HTLV-1 associated myelopathy ( HAM ) , which arise in <10% of HTLV-1 carriers during their lifetime . However , most HTLV-1 carriers live in resource-poor areas where infectious diseases , such as strongyloidiasis , could be more important causes of morbidity . Demonstrating such an effect is difficult due to the resource constraints experienced by developing countries in which populations with a substantial burden of infectious diseases reside in areas that are highly endemic for HTLV-1 . This is not the case in HTLV-1 endemic central Australia where Indigenous Australians have , for example , among the highest reported blood stream infection rates worldwide in a setting in which sophisticated medical facilities are readily available . We report that bronchiectasis , blood stream infections and admissions with lower respiratory tract infections and strongyloidiasis are associated with HTLV-1 infection . These conditions were far more common than HTLV-1 associated malignancies or neurological conditions in this socially disadvantaged Indigenous population . The spectrum of HTLV-1 related diseases therefore varies according to the social circumstances of the affected population .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine"
] |
2014
|
Clinical Associations of Human T-Lymphotropic Virus Type 1 Infection in an Indigenous Australian Population
|
The role of glia in modulating neuronal network activity is an important question . Oligodendrocyte precursor cells ( OPC ) characteristically express the transmembrane proteoglycan nerve-glia antigen 2 ( NG2 ) and are unique glial cells receiving synaptic input from neurons . The development of NG2+ OPC into myelinating oligodendrocytes has been well studied , yet the retention of a large population of synapse-bearing OPC in the adult brain poses the question as to additional functional roles of OPC in the neuronal network . Here we report that activity-dependent processing of NG2 by OPC-expressed secretases functionally regulates the neuronal network . NG2 cleavage by the α-secretase ADAM10 yields an ectodomain present in the extracellular matrix and a C-terminal fragment that is subsequently further processed by the γ-secretase to release an intracellular domain . ADAM10-dependent NG2 ectodomain cleavage and release ( shedding ) in acute brain slices or isolated OPC is increased by distinct activity-increasing stimuli . Lack of NG2 expression in OPC ( NG2-knockout mice ) , or pharmacological inhibition of NG2 ectodomain shedding in wild-type OPC , results in a striking reduction of N-methyl-D-aspartate ( NMDA ) receptor-dependent long-term potentiation ( LTP ) in pyramidal neurons of the somatosensory cortex and alterations in the subunit composition of their α-amino-3-hydroxy-5-methyl-4-isoxazolepr opionicacid ( AMPA ) receptors . In NG2-knockout mice these neurons exhibit diminished AMPA and NMDA receptor-dependent current amplitudes; strikingly AMPA receptor currents can be rescued by application of conserved LNS protein domains of the NG2 ectodomain . Furthermore , NG2-knockout mice exhibit altered behavior in tests measuring sensorimotor function . These results demonstrate for the first time a bidirectional cross-talk between OPC and the surrounding neuronal network and demonstrate a novel physiological role for OPC in regulating information processing at neuronal synapses .
Oligodendrocyte precursor cells ( OPC ) in the mammalian central nervous system ( CNS ) characteristically express the chondroitin sulfate proteoglycan nerve-glia antigen 2 ( NG2 ) ( SwissProt Q8VHY0 ) , a type-1 membrane protein [1]–[5] . In contrast , NG2 expression is lacking in other glia and neurons . These NG2+ OPC represent 5%–8% of total cells in the adult brain [6] , [7] and are ubiquitously spread throughout the grey and white matter: they are unique among glia in forming glutamatergic and GABAergic synapses with neurons [8] , [9] . These neuron-OPC synapses are present in all major brain areas including hippocampus , cerebellum , corpus callosum , and cortex [10]–[14] . Differentiation of OPC into oligodendrocytes is associated with a down-regulation of NG2 expression and a loss of synapses in spite of the retention of functional glutamate ( Glut ) receptors [15] , [16] . OPC respond to neuronal activity; recent studies showed that OPC differentiation and migration [17] , [18] , as well as myelination appear to be under the control of neuronal activity [19]–[22] . Definition of the underlying molecular mechanisms by which neuronal activity influences OPC ( reviewed in [23] , [24] ) , as well as feedback mechanisms enabling OPC to respond to and potentially modulate neuronal activity , has remained elusive ( reviewed in [25] ) . Studies to date have only described a unidirectional communication between neurons and OPC at synapses [8] , [26] . The NG2 protein contains two neurexin-like ( lamininG-neurexin-sex hormone binding globulin [LNS] ) domains at the N-terminus [27] , suggesting it may function at synapses similar to LNS domain containing neurexins [28] , [29] . Moreover , the intracellular C-terminus has a PDZ-binding motif , which binds the intracellular α-amino-3-hydroxy-5-methyl-4-isoxazolepr opionicacid ( AMPA ) receptor-binding PDZ protein GRIP and may orientate OPC AMPA receptors ( AMPARs ) at sites of neuronal contact [30] . An NG2 ectodomain has been reported to be extractable in aqueous buffers from the extracellular matrix ( ECM ) , suggesting that NG2 cleavage occurs in vivo in the normal CNS [31] , [32] . Recent results demonstrated activity-dependent cleavage of the synaptic neuronal adhesion molecules N-cadherin and neuroligin1 by the α-secretase ADAM10 with subsequent modifications of synaptic structure and function [33] , [34] . Additionally , postnatal deletion of neuronal ADAM10 activity resulted in epileptic seizures , learning deficits , altered spine morphology , and synaptic dysfunction [35] . Cleavage by α- and γ-secretases and signaling properties of the fragments generated has been best characterized for the Notch protein , where a membrane bound C-terminal fragment ( CTF ) and an intracellular domain ( ICD ) are generated [36] , [37] . In the present study , we show that NG2 is constitutively cleaved by α- and γ-secretases , leading to a 290 kD ectodomain as a major product , a membrane-associated CTF of 12 kD , and a short ICD of 8 . 5 kD . In vivo cleavage and release of the NG2 ectodomain into the ECM can be increased by distinct stimuli increasing network activity . In many cases these stimuli directly promote NG2 cleavage in isolated primary OPC . Inhibition of ADAM10 blocks both this activity-dependent release and also the constitutive cleavage of the ectodomain , identifying ADAM10 as the major protease cleaving NG2 under physiological conditions . To elucidate the functional role of NG2 cleavage and the OPC-derived NG2 ectodomain , we studied the electrophysiology of pyramidal neurons in the somatosensory cortex in mice lacking the NG2 protein ( NG2−/− mice , NG2-knockout ) . We observed a strong impairment of N-methyl-D-aspartate receptor ( NMDAR ) -dependent long-term potentiation ( LTP ) and reduced Glut receptor currents at these neuronal synapses . Furthermore , we observed that inhibition of ADAM10 in control mice mimics the NG2−/− phenotype , reflected by a reduction in NMDAR-dependent LTP . Neuronal AMPAR- and NMDAR-mediated currents are reduced in NG2−/− mice , while AMPAR but not NMDAR reveal an altered subunit composition at neuronal postsynapses in NG2−/− mice: strikingly altered AMPAR characteristics could be restored to the wild-type ( WT ) pattern by addition of recombinant protein comprising the conserved N-terminal LNS domains of the NG2 ectodomain to the slices . These NG2 domains also increased levels of c-fos in Glut-stimulated slices of the somatosensory cortex , demonstrating that they affect activity-dependent gene expression in target neurons . NG2−/− mice reveal altered behavior in tests measuring sensorimotor function . Taken together , our data demonstrate for the first time that OPC not only respond to , but are also able to modulate the neuronal network . They show that the NG2 protein itself is part of this regulatory mechanism , via activity-dependent cleavage and release of the NG2 ectodomain from OPC . Furthermore , we identify the two conserved LNS domains of the NG2 ectodomain as potent modulators of neuronal activity and gene expression .
To analyze NG2 processing , we used a well-characterized cell line of murine OPC ( Oli-neu ) [38] . These cells , in contrast to primary OPC ( pOPC ) , can be readily transfected and represent a good model system , since all cells express endogenous NG2 and are arrested in their differentiation . Overexpression of the α-secretases ADAM10 ( A10 ) and ADAM17 ( A17 , TACE ) in OPC reduced by over 2-fold the levels of full-length ( FL ) NG2 ( 300 kD , cyto AB ) ( see Figure 1D ) in post nuclear ( PN ) cell-lysates after 48 h ( Figure 1A ) . Culture of OPC for 6 h with the specific ADAM10 inhibitor GI254023X ( GI ) resulted in a 2 . 5-fold increase in levels of the FL protein ( Figure 1B ) . To visualize size differences due to α-secretase-dependent shedding of NG2 more easily , a shortened recombinant form of NG2 , NG2_del with a Flag tag in the extracellular domain was expressed ( Flag_NG2_del ) ( Figure 1C ) [39] . Lysates analyzed for the largest protein fragments , revealed the FL ( 66 kD ) and the α-secretase cleavage product , an ectodomain of 54 kD ( Figure 1C ) , analogous to the 300 kD FL and 290 kD ectodomain of endogenous NG2 . Next we investigated the generation of a membrane bound CTF of NG2 and its cleavage by the γ-secretase complex . In OPC expressing NG2_del ( Figure 1D ) , levels of the corresponding CTF fragment increased 4 times compared to endogenous CTF in control cells with no NG2_del expression ( Figure 1E ) . Additionally the endogenous NG2 CTF runs at exactly the same size as the CTF from NG2_del ( ∼12 kD ) , again verifying an α-secretase-mediated cleavage of NG2 and NG2_del at the same site and the creation of an 290 ( or 54 ) kD ectodomain . To distinguish overexpressed from endogenous NG2 CTF , expression of NG2_del with an intracellular c-terminal Myc tag ( Figure 1D ) was analyzed after expression in three different cell lines . γ-secretase activity was inhibited by application of DAPT for 24 h , resulting in a further increase of Myc tagged NG2 CTF ( Figure 1F ) . In OPC , levels of the Myc tagged NG2 CTF increased 6-fold when the γ-secretase was inhibited . In human embryonic kidney 293 ( HEK ) cells the CTF levels increased 12-fold in the presence of DAPT . Incubation of the γ-secretase inhibitor with a mouse embryo fibroblast ( MEF ) line , which lacks γ-secretase activity owing to a genetic deletion of the presenilin 1 and 2 genes , did not affect levels of the NG2 CTF . Increased CTF levels of amyloid precursor protein ( APP ) were used as a control to demonstrate the inhibition of γ-secretase activity by DAPT ( Figure 1F and 1G ) . These results demonstrate γ-secretase-mediated cleavage of the NG2_del derived CTF . Similarly , culture of untransfected OPC for 24 h in the presence of DAPT resulted in a 2-fold increase of CTF levels derived from the endogenous NG2 ( Figure 1G ) . As reported originally by the Barres group [40] , we also observed that culture in the presence of DAPT caused an accelerated differentiation of OPC as indicated by a down-regulation of NG2 protein expression ( Figure 1G ) . To further analyze the sequential cleavage of NG2 by α- and γ-secretases we used a cell-free assay . Purified crude membranes ( CMs ) from OPC were incubated for 2 h with different combinations of specific protease inhibitors ( GI , ADAM10 inhibitor; GW , A17/10 inhibitor and DAPT , γ-secretase inhibitor ) and compared to the control with standard protein inhibitors ( PIs; 1× control ) . Membrane associated proteins ( P100 ) were subsequently separated from soluble proteins ( S100 ) generated within the 2 h of incubation by ultracentrifugation ( Figure 2A ) . A protein band at 300/290 kD was detectable in P100 representing full length NG2 protein and the 290 kD ectodomain ( mc AB ) ( see Figure 2D ) . Additional major bands of truncated but high molecular proteins were detectable at 275 and 190 kD , which are likely to be additional ectodomains . In S100 all three theoretical ectodomain fragments were detected , although the levels were lower compared to forms of similar size in P100 , suggesting that substantial amounts of the NG2 ectodomain bind to the membrane . The ectodomain origin of these cleavage forms was supported by their failure to react with the NG2 cyto AB ( Figure S6A ) . Application of α-secretase inhibitors ( GI or GW ) alone or in combination with the γ-secretase inhibitor ( GI and DAPT ) , led to a significant reduction of the 290 kD ectodomain in S100 ( Figure 2B ) . Incubation with DAPT alone had no effect . The generation of the NG2 CTF ( present in the P100 fraction only ) ( Figure 2A ) was also influenced by the inhibitors: GI or GW as well as GI and DAPT reduced CTF levels while DAPT alone increased the CTF levels ( Figure 2B ) . These results demonstrate that the α-secretase ADAM10 is responsible for the majority of the shedding in this paradigm , and that the ectodomain shedding is independent of γ-secretase activity . Furthermore , α-secretase cleavage is mandatory for subsequent cleavage by the γ-secretase . Incubation of the membranes with inhibitors of the β-secretase had no effect , excluding the activity of the β-secretase in this process ( Figure S6B ) . The NG2 ICD was enriched in a crude-membrane fraction from Oli-neu ( Figure 2C ) and levels were decreased by γ–secretase inhibition , suggesting a role in a membrane-associated complex ( Figure 2C and 2D ) . It has recently been reported that cleavage of the synaptic cell adhesion molecule neuroligin1 , expressed by neurons , is under the control of electrical activity with modulatory effects on synaptic function [34] , [41] . To investigate if NG2 cleavage is similarly regulated , primary OPC from P9 mouse brain were isolated by magnetic beads coupled to monoclonal antibody recognizing NG2 . After 1 day of culture , the cells were incubated with ( I ) picrotoxin , forskolin , and rolipram ( PFR ) inducing chemical LTP ( cLTP ) for 20 min; ( II ) 4-aminopyridine and bicuculline ( 4AP + BCC ) , a weak potassium and a GABAA channel blocker , known to depolarize neurons , for 20 min; ( III ) Glut for 10 min . In some cases the cells were pre-incubated with the NMDAR antagonist MK801 prior to incubation with Glut , or with the ADAM10 inhibitor GI for 15 min prior to stimulation with PFR or Glut . We observed a significantly reduced level of NG2 FL protein in PN cell lysates after incubation with 4AP + BCC , and after incubation with Glut or Glut+MK801 ( Figure 3A ) . PFR treatment did not alter NG2 FL levels . After pre-incubation with the ADAM10 inhibitor GI , neither Glut nor PFR altered NG2 FL levels . These results imply that ADAM10 cleavage-dependent reduction of NG2 FL protein can be increased by activity directly in primary OPC . The NG2 ectodomain of 290 kD can be extracted with PBS from the ECM of the rodent brain ( Figures 3B and S1 ) [31] , [32] . To analyze the effect of activity-dependent effects of the whole neural network on NG2 cleavage within OPC , we subjected acute hippocampal slices to cLTP ( PFR incubation ) or incubation with 4AP + BCC and analyzed levels of the released NG2 ectodomain . Here we extracted ECM proteins by 30 min incubation with chondroitinase ABC , which removes exclusively sugar side chains from proteins , subsequent to the stimulation . The resulting samples contain only soluble , extracellular proteins as membrane proteins are not extracted in the absence of detergent , similar to the extraction of the ectodomain from tissue with PBS described above but with less mechanical stress . These samples thus contain only shedded soluble NG2 ectodomain . Strikingly , levels of the NG2 ectodomain were increased 2 . 5-fold after 15 min of PFR ( Figure 3C ) . Levels slightly decreased with ongoing recovery time and returned to starting levels after 180 min of recovery time ( Figure 3C ) . In order to identify the protease responsible for the activity-dependent ectodomain shedding , we incubated the slices in the presence of the metalloprotease inhibitor GM6001 or the ADAM10 inhibitor GI . Both compounds completely inhibited the NG2 ectodomain shedding induced by PFR ( Figure 3D ) . In the presence of the ADAM10 inhibitor GI , the ECM-associated levels of the NG2 ectodomain were reduced to below those of the control , demonstrating that basal levels of NG2 cleavage in OPC are ADAM10-dependent . Incubation of acute slices with 4AP + BCC , which depolarizes neurons and affects OPC as described above , increased NG2 ectodomain levels in the ECM in a comparable fashion to incubation with PFR ( Figure 3D ) . Next we investigated a potential effect of the cleaved NG2 ectodomain on neuronal synaptic transmission . To address this question , we used transgenic mice with ablation of NG2 ( NG2−/− ) . In these mice OPC do not express NG2 ( NG2−/− OPC ) [42] . Whole-cell recordings were made from L2/3 pyramidal neurons in the somatosensory cortex; these are contacted by NG2−/−-OPC that express enhanced yellow fluorescent protein ( EYFP ) ( green in the Figure 4A ) . We analyzed NMDAR-dependent LTP as a typical form of synaptic long-term plasticity . Cortical pyramidal neurons were current-clamped at a membrane-potential of −80 mV , and excitatory postsynaptic potentials ( EPSPs ) were evoked by electrical stimulation in layer IV that stimulated ascending afferent fibers projecting onto these pyramidal neurons . Baseline EPSPs were initially recorded for 10 min before applying an LTP inducing stimulation protocol that consisted of presynaptic high-frequency theta-burst stimulus ( TBS ) paired with postsynaptic depolarization . This protocol is known to induce high presynaptic glutamate release as well as an enhanced opening of postsynaptic glutamate receptors due to the membrane depolarization [43] . This LTP stimulation protocol , induced an increase of the EPSP amplitude of EPSPs in pyramidal neurons of WT control mice up to 79 . 4%±2 . 8% within 5 min post-TBS ( Figure 4B1 and 4E ) ; these were maintained for up to 60 . 1%±6 . 2% after 20–30 min post LTP induction ( TBS ) ( Figure 4B1 and 4F ) . To test the strength of neuronal synaptic plasticity associated with the absence of NG2 , we repeated the LTP experiment at the same synaptic connections in NG2−/− mice . Strikingly , in neurons of NG2−/− mice only a minor potentiation of EPSPs was detected within 5 min post-TBS ( 7 . 2±2 . 6 ) ( Figure 4B1 and 4E ) , which was maintained up to 23%±2 . 9% after 20–30 min post-TBS ( Figure 4B1 and 4F ) . The NMDAR-dependency of this form of LTP was confirmed by bath application of D-AP5 ( which blocks NMDAR ) during TBS in controls , resulted in no potentiation ( 0 . 19%±2 . 51% ) ( Figure 4B2 ) . ADAM10 is the major metalloprotease responsible for NG2 cleavage , whose activity is promoted by stimulation of the neural network . To examine the physiological relevance of NG2 ectodomain processing by ADAM10 for neuronal activity , we used the metalloprotease blocker GM6001 and the ADAM10-specific inhibitor GI , which we had shown prevents activity-dependent release of the NG2 ectodomain ( Figure 3A and 3D ) and repeated LTP recordings in cortical slices from control ( WT ) and NG2−/− mice . Following a pre-incubation period of 1 h , GM6001 abolished the induction of NMDAR-dependent LTP in controls and mimicked a NG2−/−-like phenotype , as reflected by a small EPSP increase of 9 . 8%±3 . 3% after 20–30 min post LTP induction by TBS ( Figure 4C ) . GM6001 did not alter the level of EPSPs in neurons of NG2−/− mice ( 20–30 min post-TBS: 6%±2 . 3% ) ( Figure 4C ) . Similar results were obtained when the experiments were repeated substituting GI for GM6001 , which also prevented LTP induction in neurons of control mice ( 5 . 6%±1 . 3% ) , but did not affect neurons of NG2−/− mice ( 2 . 5%±2 . 0% ) ( Figure 4D ) . These data suggest that the ectodomain of NG2 is released by the action of the metalloprotease ADAM10 in the vicinity of neuronal synapses and can modulate glutamatergic transmission between cortical pyramidal neurons . Subsequently we examined intrinsic membrane properties of L2/3 pyramidal neurons and found no differences in membrane capacitance and input resistance after NG2 deletion ( Figure S2 ) , thereby most likely excluding influences of altered ion channel conductance on the cellular excitability in NG2−/− mice . Interestingly pyramidal neurons of NG2−/− mice displayed a slightly hyperpolarized resting membrane potential ( ΔVm = −3 . 3±0 . 1 mV ) ( Figure S2 ) . We examined basal glutamatergic neurotransmission at L4-to-L2/3 synapses in NG2−/− mice and recorded spontaneous excitatory postsynaptic currents ( sEPSCs ) . These signals were exclusively mediated by glutamatergic AMPA receptors , since we blocked the activation of GABA- and NMDARs by bath application of PTX ( 50 µM ) and D-AP5 ( 25 µM ) , respectively . We found no differences in NG2−/− mice compared to WT , the mean frequency and peak amplitude of sEPSCs were not altered in L2/3 pyramidal neurons ( Figure S3 ) . Next we assessed paired pulse facilitation of synaptic currents to detect potential changes of presynaptic glutamate release . The paired pulse ratio , which was calculated from two consecutive evoked EPSCs , was similar in NG2−/− and control mice ( Figure S4 ) . Thus , together with unchanged sEPSCs , these data suggest that presynaptic glutamate release is unaffected in neurons of NG2−/− mice . NMDAR-dependent LTP is often associated with a reduction in the number or changes in the subunit composition of postsynaptic glutamate receptors [42] , [43] . To examine the functional properties of glutamatergic AMPARs and NMDARs at excitatory synapses , we recorded AMPAR- and NMDAR-currents within the same neuron . AMPAR-mediated currents were recorded at −80 mV , a potential where NMDARs are rarely open , followed by detection of NMDAR currents at +60 mV in the presence of DNQX ( 20 µM ) , which blocks AMPAR activity . Strikingly , both types of receptor currents were reduced in their amplitudes in NG2−/− mice , with AMPAR currents being impaired by 24 . 5%±2% compared to controls and the NMDAR current component being decreased by 43 . 7%±2 . 2% ( Figure 5A and 5B ) . Accordingly , we observed a shift in the ratio of NMDARs to AMPARs ( NG2−/−: 0 . 8±0 . 07 versus control: 1 . 0±0 . 1 ) ( Figure 5C ) . However , despite the drop in the amplitude of NMDAR currents , the kinetic properties ( Figure 5F and 5G ) and the current-voltage relation of NMDAR currents ( Figure 5H ) remained unchanged with NG2 deletion , suggesting no alteration of subunit composition . In contrast , one kinetic parameter of AMPAR currents ( Figure 5D and 5E ) , the decay time constant , was significantly decreased in neurons of NG2−/− mice ( 8 . 9±0 . 4 ms ) compared to controls ( 10 . 7±0 . 7 ) ( Figure 5E ) , indicating an altered subunit composition of AMPARs but not NMDARs in the NG2−/− mice . To further investigate the functional properties of AMPARs at L4-to-L2/3 synapses of pyramidal neurons , we assessed a typical current-voltage ( I-V ) relationship of AMPAR-mediated currents . Strikingly , we found a strongly decreased slope , also called inward-rectification , of the resulting I-V curve at positive potentials in the NG2−/− mice , while WT controls displayed a nearly linear I-V relationship ( Figure 6A ) . The rectification index ( RI ) was significantly smaller in pyramidal neurons of NG2−/− mice ( 0 . 4±0 . 03; range: 0 . 2–0 . 8 ) compared to controls ( 1 . 0±0 . 07; range: 0 . 6–1 . 6 ) ( Figure 6B ) . These results suggest the presence of Ca2+-permeable ( CP ) -AMPARs at L4-to-L2/3 synapses of NG2−/− mice , which was further confirmed by repeating the recordings of AMPAR currents in the presence of NASPM ( 250 mM ) , a selective inhibitor of CP-AMPAR channels [44] at a holding potential of −80 mV . Bath application of NASPM reduced the initial peak amplitude of AMPAR currents by 26 . 6%±8 . 0% in the NG2−/− , while AMPAR currents in controls remained unaffected ( 4 . 8%±2 . 1%; n = 6 ) ( Figure 6C and 6D ) . These data suggest that both CP and Ca2+-impermeable AMPARs are present in the postsynaptic membrane of L2/3 pyramidal neurons from NG2−/− mice . The nearly linear I-V relation of AMPAR currents in the presence of NASPM further substantiates this assumption ( Figure 6C and 6D ) . Moreover , subsequent bath application of GYKI53655 ( 25 µM ) , an antagonist of all AMPAR , blocked effectively all current responses in both NG2−/− ( 88 . 8%±1 . 8% ) and control groups ( 91 . 9%±1 . 7% ) ( Figure 6D ) . These data confirm that the remaining current components in the presence of NASPM were mediated by AMPARs and not by other glutamate receptors like kainate receptors . In order to investigate a potential direct influence of the NG2 ectodomain , in particular the LNS domains , on the observed AMPAR I-V relation in NG2−/− mice , we pre-incubated cortical slices for 1 h with purified recombinant protein comprising alkaline phosphatase ( AP ) -tagged LNS domains of the NG2 ectodomain ( LNS-AP ) . Strikingly , application of the NG2 LNS domains restored the AMPAR currents in NG2−/− mice to WT-levels , as reflected by the presence of a normal linear I-V relationship ( Figure 6E and 6F ) . In contrast a pre-incubation with the AP tag alone ( control ) did not alter the I-V relation of the AMPAR currents . Finally we also tested the effects of the NG2-LNS domains on neuronal activity in an independent approach . The expression level of c-fos , an immediate early gene and a marker for neuronal activity [45] was analyzed in cortical slices of NG2−/− tissue after incubation of the slices with 1 mM Glut for 10 min to activate the neuronal network . Pre-incubation of slices with the LNS protein domains resulted in more c-fos+ neurons compared to slices preincubated with AP alone ( Figure 7 ) . To investigate possible effects of the altered electrophysiological properties of cortical neurons in NG2−/− mice on mouse behavior , we measured pre-pulse inhibition ( PPI ) of the acoustic startle response in these animals . In this assay , the startle response of the animals is measured after initial presentation of a weaker sensory stimulus ( the pre-pulse ) . Normally , the response is diminished after a pre-pulse and it is thought to reveal sensorimotor gating , i . e . , the ability to filter sensory input [46] . We found a significant reduction of PPI in NG2−/− animals in comparison to WT littermates ( Figure 8A ) , where the NG2−/− mice still reacted strongly to the stimulus in spite of the pre-pulse . As a test for sensory input , the olfactory habituation/dishabituation test was performed . Olfactory sensations are integrated in the olfactory cortex and are a part of the somatosensory cortex ( Figure 8B ) . The NG2−/− mice spent less time sniffing the two presented odors compared to WT animals . Notably , motor cortex-associated behavior assessed by the Rotarod or CatWalk tests ( Figure 8C and 8D ) was unchanged in NG2−/− mice . Learning and memory was tested by contextual fear conditioning ( Figure 8E ) and the Morris Water Maze test ( Figure 8F ) . In both tests , no differences were observed between genotypes .
We show here that NG2 can be cleaved by α- and γ-secretases in a sequential manner similar to other type-1 membrane proteins such as Notch , APP , L1 , N-cadherin , and neuroligin1 [33] , [47]–[50] . We identified ADAM10 as the major constitutively acting α-secretase , similar to the cleavage of Notch [51] . ADAM10 cleavage of proteins generally results in two fragments , a released ectodomain and a membrane bound CTF . In the case of NG2 , we found an ectodomain of ∼290 kD that is ∼10 kD smaller than the FL protein and a CTF of 12 kD . These findings match the reported NG2 ectodomain fragment of 290 kD described previously [31] . So far , CTFs or ICDs have not been reported for NG2 in contrast to the proteins described above [52] , [53] . The NG2 CTF fragments were detected in membrane fractions and were more abundant when the γ-secretase was inhibited . These results suggest a functional role for the CTF fragment and demonstrate constitutive processing by the γ-secretase leading to the creation of an NG2 ICD , which was often found associated with the cell-membrane similar to the ICD of APP [54] . FL NG2 protein is expressed by OPC within the CNS and the ectodomain is likely to be contributing to the ECM [31] , [55] . Interaction with collagen V&VI and β1 integrin has been shown , compatible with this concept [56] , [57] . Interestingly , we found the NG2 ectodomain to be highly adhesive for OPC membranes ( Figure 2A ) and membrane fractions from total forebrain ( Figure 3B ) . We also observed as reported previously , that a fraction of the 290 kD ectodomain is soluble in aqueous buffers . Our results using isolated OPC show that NG2 is processed on OPC by endogenous ADAM10 and γ-secretase in a constitutive manner and confirm that all cleavage fragments identified originate from OPC membranes . We observed that after cleavage , part of the NG2 ectodomain is deposited in the ECM and can be extracted with chondroitinase ABC , which cleaves glycosaminogycan chains thus freeing proteoglycans from their potential association with the ECM , allowing their extraction in a soluble fraction without detergent . In our experiments ECM proteins are extracted from acute slices after incubation with activity-modulating chemicals . The amount of detergent-free extractable ectodomain rapidly increases after incubation of the slice ( and thus the network ) , with PFR , which is known to induce cLTP by increasing cAMP levels in neurons [58] . Interestingly , ectodomain levels in this fraction returned to starting levels after 180 min , demonstrating that subsequent to shedding a fast removal of the ectodomain fragment ensues . Removal of the released ectodomain from the ECM fraction may be due to binding to cell-surface receptors and subsequent internalization or further proteolytic processing . ADAM10 appears to be the protease responsible for both the PFR-induced and constitutive cleavage in vivo , as ADAM10 inhibition reduced NG2 ectodomain cleavage to below control levels in the presence of PFR . Thus ADAM10 can be considered as the constitutively active protease releasing NG2 ectodomain and CTF , and neuronal activity further increases this cleavage . The activity-dependence of NG2 ectodomain cleavage can furthermore be shown by stimulation of slices with 4AP + BCC , which is reported to inhibit repolarization by blocking voltage-dependent potassium channels [59] , and also increases NG2 ectodomain levels in the ECM . Since in these treatments of acute slices we are potentially affecting all neural cell types , we also repeated the experiments with isolated primary OPC . These were subjected to the same activity-inducing chemical treatments as the slices and in addition we tested the effect of incubation with glutamate . We observed that 4AP + BCC but not the PFR treatment stimulated NG2 cleavage on isolated OPC . Incubation of OPC with the neurotransmitter glutamate additionally increased ADAM10-dependent cleavage of NG2 independent of NMDAR activity . The combination of the effects we observed in an OPC cell line , primary OPC and the results in acute slices , suggest the following scenario . OPC have high densities of AMPAR at their synapses , which enable direct synaptic response to glutamate in vivo [8] , [10] , thus presenting a rapid signaling mechanism that potentiates ADAM10-dependent NG2 ectodomain cleavage in addition to the constitutive ADAM10-dependent cleavage . With respect to the mechanism of activity-dependent ADAM10 cleavage , we show that induction of chemical LTP ( with PFR ) , a known stimulator of neuronal activity [58] , is likely to function via the neuronal network as it did not increase NG2 ectodomain cleavage in isolated OPC . OPC exhibit voltage-dependent potassium channels [60] , which could explain why 4AP + BCC incubation of primary OPC also caused an increased release of NG2 ectodomain , as blocking both voltage-dependent potassium channels and GABAA receptors may lead to depolarization of the OPC , which is required for activity-dependent NG2 shedding . In neurons , ADAM10 is located at excitatory postsynapses [61] and we have confirmed that OPC also express ADAM10 . NG2 binds the PDZ domain protein GRIP in OPC , which itself binds to AMPAR forming a tripartite complex in OPC [30] . Thus an activity-dependent release of the NG2 ectodomain is likely to occur at neuron-OPC synapses resulting in increased levels of NG2 ectodomain in the ECM . These findings are similar to activity-dependent cleavage by ADAM10 of neuronal adhesion molecules such as neuroligin-1 and N-cadherin [34] , [62] . As an effect of NG2 ablation in OPC ( NG2−/− OPC ) , we found a diminished NMDAR-dependent LTP at neuron-to-neuron synapses of pyramidal neurons in the somatosensory cortex . We observed a similar lack of neuronal LTP in neurons of control mice 45 min after blocking NG2 cleavage by ADAM10 with metalloprotease or specific ADAM10 inhibitors , while the overall small potentiation in pyramidal neurons of NG2−/− mice remained unaffected by these inhibitors . These results demonstrate a major contribution of activity-dependent ADAM10 cleavage to the observed LTP changes . The neuronal cell adhesion molecule ( CAM ) neuroligin has recently been shown to be processed by ADAM10 in an activity-dependent manner at neuronal synapses , leading to alterations of the spine structure [34] and synaptic function . Additionally , other proteoglycans that are associated with the ECM , such as brevican [63] and tenascin R and C [64] , [65] , or the structural integrity of the ECM itself [66] influence long or short term potentiation at neuronal synapses . It is feasible that the released NG2 ectodomain directly interacts with a neuronal receptor , leading to modulation of glutamatergic receptor composition and glutamergic transmission at neuronal synapses . These findings are in accordance with previous results showing that processing of synaptic cell adhesion molecules such as neuroligin1 by ADAM10 correlates with efficient synaptic transmission [67] , [68] . These results suggest that ADAM10-mediated activity-dependent cleavage underlies the LTP alterations that we observe and also strongly argue that ADAM10 dependent ectodomain shedding of NG2 is a major contributory factor . To gain insight into the synaptic mechanism leading to the LTP phenotype in the somatosensory cortex of NG2−/− mice , we analyzed potential pre- and postsynaptic contributions . Basal synaptic transmission mediated by AMPARs was not altered at L4-to-L2/3 connections in NG2−/− mice . This result , together with an unchanged short-term plasticity as addressed by paired-pulse facilitation of excitatory synaptic transmission , makes impairments of glutamate release rather unlikely . Nevertheless , a lack of LTP induction is often associated with reduced density or changed subunit composition of glutamatergic receptors at these neuronal synapses [69] , [70] . In response to a constant stimulus strength , both NMDAR- and AMPAR currents were significantly reduced in L2/3 pyramidal neurons from NG2−/− mice compared to WT controls . However , alterations of NMDAR subunit composition could be excluded as the respective kinetics and the current voltage relationship remained unaffected by NG2 deficiency , hence suggesting a down-regulation of NMDARs per se . In contrast , AMPAR currents revealed remarkable differences between neurons of NG2−/− and WT mice , including shorter decay time constants and an inward rectification of their I-V curve at positive holding potentials . The latter is characteristic for CP AMPARs lacking the GluR2 subunit , where it is caused by a polyamine-dependent block [71] , [72] . Application of two selective antagonists , NASPM ( GluR2 lacking AMPAR ) and GYKI53655 ( total AMPAR ) , confirmed the functional expression of these ion channels at excitatory synaptic inputs onto L2/3 pyramidal neurons of NG2−/− mice . The presence of CP-AMPAR can explain the observed slightly hyperpolarized resting potential in the NG2−/− neurons ( Figure S2 ) , since a more hyperpolarized resting potential has been described previously in neurons expressing CP-AMPAR [71] . CP-AMPARs are normally down-regulated during development in cortical pyramidal neurons , but retained in certain types of GABAergic interneurons in the adult brain [73] , [74] . Here , similar to our studies , the insertion of CP-AMPARs is negatively correlated with the functional expression of CP-NMDARs in the postsynaptic membrane [75] , [76] , which influences the increase of intracellular Ca2+ and hence affects information processing within the somatosensory cortex . Our results thus show that shedding of the NG2 ectodomain regulated by neuronal activity has a profound impact on neuronal glutamate receptor currents and long-term synaptic plasticity in the somatosensory cortex . Strikingly , the observed inward rectification in the I-V relationship at positive holding potentials in NG2−/− mice could be restored to the WT phenotype by application of the N-terminal LNS domains of the NG2 ectodomain . In support of this , pre-incubation of cortical slices with the NG2 LNS domains prior to brief stimulation with glutamate increased activity-dependent neuronal c-fos expression in somatosensory neurons . These results demonstrate a direct influence of these specific domains [27] on the functional properties of AMPARs discussed above . Pyramidal neurons of NG2−/− mice have more functional CP-AMPAR at postsynaptic membranes , which supports the concept of a stabilizing effect of the NG2-LNS domains on AMPAR containing the GluR2 subunit , which are impermeable to calcium . The LNS domains have been postulated by in silico experiments to belong to the same superfamily as pentraxins [77] , [78] . Neuronal pentraxins such as Nptx2 ( Narp ) have been shown to bind to and stabilize GluR2 subunit-containing AMPAR at the neuronal plasma membrane [79] . Furthermore , application of the single LNS domain of β-neurexin 1 or β-neurexin 3 , respectively , is sufficient to restore heterologous synapse formation in knock-out animals for each of these neurexins [29] . An alternative splicing variant of α-neurexin 3 , resulting in an altered structure of one specific LNS domain , has recently been shown to impair postsynaptic AMPAR currents and LTP when introduced genetically [28] . The rescue in our experiments by recombinant NG2 LNS domains shows that these can diffuse within the slice to reach the sites of action on neurons . It is thus likely that endogenous NG2 ectodomain ( containing these LNS domains ) exhibits a limited diffusion within the ECM in vivo . The major 290 kD form of the soluble ( in detergent-free tissue extract ) NG2 ectodomain found by us and others is most likely mediating the endogenous NG2 signaling effects on neurons . We observed altered NMDAR and AMPAR properties of L2/3 neurons of the somatosensory system in NG2−/− mice . Functional integrity of the motorcortex ( which is adjacent to the somatosensory cortex ) was tested by two motor tests , Rotarod and CatWalk , and revealed no differences between the genotypes . A test assessing olfaction showed a reduced response to defined odors in the NG2−/− mice , which could reflect a changed integration of sensory input in the olfactory cortex , as part of the somatosensory cortex . NG2−/− mice also show impaired PPI in behavioral assays . Reduced PPI is associated with human diseases , such as schizophrenia , Huntington disease , Tourette syndrome , and obsessive-compulsive disorder [46]—diseases associated with an impaired integration of sensory data . Furthermore , receptors for three different neurotransmitters have been shown by pharmacological studies to participate in a reduction of PPI in rodents: stimulation of dopamine or serotonin receptors , or inhibition of NMDAR [46] , [80] , [81] . Two widely used learning and memory tasks ( contextual fear conditioning and Morris Water Maze ) showed no differences between NG2−/− and WT control animals . These results suggest that the observed NG2-dependent alterations of the neuronal system affect in particular the neuronal networks of the somatosensory cortex ( as tested by PPI ) , rather than those of the hippocampus-amygdala circuits ( as tested by contextual fear conditioning and Morris Water Maze ) . This issue has to be addressed by further behavioral and molecular studies , to reveal if neuronal network activity is most strongly affected in the somatosensory cortex by the reported synaptic phenotype in NG2−/− mice . We propose that synaptic signaling of the NG2 ectodomain influencing AMPAR/NMDR and LTP is likely to occur throughout the brain , as NG2 shedding on OPC seems to be a general phenomenon . On a molecular level , this could mean that in other areas of the brain such as the hippocampus , other regulators modulate LTP more strongly than the NG2 ectodomain . Taken together , our data provide compelling evidence that OPCs in the adult brain are functionally integrated in the neuronal network and not only respond to but modulate neuronal activity via newly identified mechanisms . We show that NG2 is cleaved by ADAM10 and the γ-secretase on OPC . Furthermore , cleavage by ADAM10 releases the NG2 ectodomain into the ECM in an activity-dependent mechanism , where it influences postsynaptic glutamate receptor currents and neuronal LTP in the somatosensory cortex . We identify the LNS domains of the NG2 ectodomain as potent modulators of neuronal synapses , as they rapidly restore the altered AMPAR kinetics observed in the NG2−/− mice to the WT pattern . These changes in sensorimotor processing are likely to underlie the behavioral alterations exhibited by NG2−/− mice . Our results demonstrate a bidirectional cross-talk between OPC and the surrounding neuronal network , and demonstrate a novel physiological role for NG2-expressing OPC in regulating information processing . They also suggest a possible approach for modulating neuronal network function in disease .
The OPC cell line Oli-neu was cultured as described [38] . HEK 293 ( Invitrogen ) and MEF ( PS1/2 KO , kind gift of C . Pietrzik ) cells were cultured as described in Text S1 . Cell lines were transfected with Lipofectamin2000 ( Invitrogen ) or polyethylenimine ( [PEI] , Sigma ) . Primary OPC ( pOPC ) were isolated from total brain of postnatal day 8–9 mice by magnetic cell sorting ( Miltenyi ) based on [82] . After 1 day in culture the sorted cell population consists of 90%–95% pure OPC [82] . Cells were lysed in Triton X-100 , after removal of nuclei by centrifugation , supernatants were defined as PN lysates . Alternatively cells were homogenized without detergent with a Potter S teflon pestle , nuclei were removed by centrifugation , and after high-speed centrifugation fractions were defined as cytoplasmic , or crude membrane ( CM ) pellet fractions . For the cell free protease assays , CMs were obtained and incubated with different combinations of specific protease inhibitors ( GI254023X [GI] , GW280264X [GW] ) [83]; DMSO and DAPT ( Sigma ) , β-secretase inhibitor II ( Calbiochem ) , Roche complete ( PI ) ( Roche ) . After ultracentrifugation , supernatant ( S100 ) and pellet ( P100 ) were taken for Western blot . Equal volumes or amounts of total protein were separated on 4%–12% NuPage BisTris gradient gels ( Invitrogen ) . Proteins were blotted on a PVDF membrane ( Millipore ) . HRP-conjugated secondary antibodies were used with hyper films ( GE ) for detection . Protein levels were normalized against those of GAPDH . Homozygous NG2-EYFP mice , ( NG2−/− ) , lack NG2 protein expression and were previously described [42] . All experiments were carried out in strict accordance with protocols approved by local Animal Care and Use Committee of Johannes Gutenberg University of Mainz . The two N-terminal LNS domains of NG2 ( amino acids 30–382 ) were cloned in the pAPtag-5 ( GenHunter ) plasmid with a C-terminal AP , a Myc and hexaHis Tag; the construct was named LNS-AP . The original plasmid coding only for AP with Myc hexaHis Tag was used as control ( AP ) . Proteins were purified from the cell and serum free medium of HEK over a nickel column ( Sigma ) . Proteins were pre-incubated for 1 h ( 10 µg/ml ) with acute slices for electrophysiology or immunocytochemistry ( c-fos ) . Acute rat hippocampal slices [84] were incubated for 15 min with PFR or 4AP + BCC and subsequently transferred to standard artificial cerebrospinal fluid ( aCSF ) without Mg2+ and protease inhibitors , followed by tissue digestion with chondroitinase ABC [32] and Western Blot analysis . NG2−/− mice and WT C57BL/6J mice ( P22–P30 ) were used . Coronal slices ( 300 µm ) , containing somatosensory cortex were prepared in standard artificial cerebrospinal fluid ( aCSF ) solution , containing ( mM ) : 125 NaCl , 2 . 5 KCl , 1 . 5 MgCl2 , 2 CaCl2 , 25 glucose , 25 NaHCO3 , 1 . 25 NaH2PO4 , bubbled with 95% O2/5% CO2 mixture ( pH 7 . 4 at 37°C ) . Whole-cell patch-clamp recordings were performed in layer 2/3 pyramidal neurons in the somatosensory cortex visually controlled by DIC optics . For investigation of c-fos expression in acute slices of the somatosensory cortex , slices were stimulated with glutamate ( 1 mM ) for 10 min after pre-incubation ( 1 h ) with purified LNS-AP or AP protein ( 10 µg/ml each ) . Experimental conditions ( LNS-AP and AP ) were compared from the same individual mouse and of a total of seven different mice were analyzed . All behavioral tests were performed with the same cohort of mice between 5–8 weeks of age . Only male littermates were used ( 11 NG2−/− and 10 WT animals ) . The tests performed were: Rota-Rod , CatWalk , test for olfaction , PPI , fear conditioning , Morris Water Maze . Statistical analysis was done by using SPSS or MS Excel . Data were tested for normal distribution with non-parametric one-sample Kolmogorov-Smirnov test . All quantitative data are expressed as mean ± standard error of the mean ( SEM ) . Significance was classified as follows: * , p≤0 . 05; ** , p<0 . 01; *** , p<0 . 001; n . s . p>0 . 05 . Classified by Student's t test or ANOVA with Dunnett's Multiple Comparison test . For detailed description of methods refer to Text S1 .
|
Although glial cells substantially outnumber neurons in the mammalian brain , much remains to be discovered regarding their functions . Among glial cells , oligodendrocyte precursors differentiate into oligodendrocytes , whose function is to enwrap nerves with myelin to ensure proper impulse conduction . However , oligodendrocyte precursors also comprise a stable population in all major regions of the adult brain , making up around 5% of the total number of neurons and glia . Synapses are classically formed between neurons . Nonetheless , oligodendrocyte precursors are unique among glial cells in that they receive direct synaptic input from different types of neurons; whether OPC also send signals to neurons is still unknown . Here we show a bidirectional communication between neurons and oligodendrocyte precursors: neuronal activity regulates the cleavage of a glial membrane protein and the release of an extracellular domain that in turn modulates synaptic transmission between neurons . Our data thus show that a particular subtype of glial cells , oligodendrocyte precursors , functionally integrate into the neuronal network and we link this bidirectional signaling to mouse behavior and disease .
|
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2014
|
Oligodendrocyte Precursor Cells Modulate the Neuronal Network by Activity-Dependent Ectodomain Cleavage of Glial NG2
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The intricate interactions between viruses and hosts include an evolutionary arms race and adaptation that is facilitated by the ability of RNA viruses to evolve rapidly due to high frequency mutations and genetic RNA recombination . In this paper , we show evidence that the co-opted cellular DDX3-like Ded1 DEAD-box helicase suppresses tombusviral RNA recombination in yeast model host , and the orthologous RH20 helicase functions in a similar way in plants . In vitro replication and recombination assays confirm the direct role of the ATPase function of Ded1p in suppression of viral recombination . We also present data supporting a role for Ded1 in facilitating the switch from minus- to plus-strand synthesis . Interestingly , another co-opted cellular helicase , the eIF4AIII-like AtRH2 , enhances TBSV recombination in the absence of Ded1/RH20 , suggesting that the coordinated actions of these helicases control viral RNA recombination events . Altogether , these helicases are the first co-opted cellular factors in the viral replicase complex that directly affect viral RNA recombination . Ded1 helicase seems to be a key factor maintaining viral genome integrity by promoting the replication of viral RNAs with correct termini , but inhibiting the replication of defective RNAs lacking correct 5’ end sequences . Altogether , a co-opted cellular DEAD-box helicase facilitates the maintenance of full-length viral genome and suppresses viral recombination , thus limiting the appearance of defective viral RNAs during replication .
RNA viruses replicate inside cells and they require many cellular factors to complete their infection cycle . The intricate interactions between viruses and hosts include evolutionary arms race and adaptation that is facilitated by the ability of RNA viruses to evolve rapidly due to high frequency mutations and genetic RNA recombination as well as reassortment of genomic components [1–3] . Interestingly , cellular and environmental factors affect viral RNA recombination , which is a process that joins two or more noncontiguous segments of the same RNA or two separate RNAs together [4 , 5] . Recombination could alter viral genomes by introducing insertions or duplications , combining new sequences , or leading to deletions or rearrangements . RNA recombination also functions to repair truncated or damaged viral RNA molecules [2 , 5–7] . Viral RNA recombination can affect virus population dynamics , contribute to virus variability , as well as function in genome repair that maintains the infectivity of RNA viruses [3 , 4] . Viral RNA recombination is intensively studied with Tomato bushy stunt virus ( TBSV ) , a tombusvirus infecting plants , using yeast ( Saccharomyces cerevisiae ) model host . TBSV is an outstanding model for both replication and recombination studies [8–12] . Systematic genome-wide screens with TBSV have led to the identification of more than 30 host genes affecting viral RNA recombination in yeast [8 , 9 , 13–15] . Among the host factors identified is the cytosolic Xrn1p 5’-to-3’ exoribonuclease ( Xrn4 in plants ) that suppresses TBSV recombination [16–18] . Xrn1p was shown to rapidly degrade cellular endoribonuclease-cleaved TBSV RNAs , termed degRNAs ( Fig . 1A ) [16–19] . The combined effects of cellular exo- and endoribonucleases determine the accumulation of degRNAs , which are especially active in RNA recombination , and thus , these cellular factors affect the frequency of viral RNA recombination events [9 , 18] . An additional key cellular factor involved in TBSV recombination is Pmr1 Ca++/Mn++ pump that controls Mn++ level in the cytosol [15] . Studies revealed that the cytosolic Mn++ level could greatly affect the properties/activities of the viral replicase , including its ability to synthesize RNA and switch templates . For example , high Mn++ level ( in the absence of Pmr1 ) leads to high frequency RNA recombination in yeast or plant cells as well as in a cell-free TBSV replication assay [15] . Tombusviruses code for two replication proteins , termed p33 and p92pol , which are translated directly from the genomic ( g ) RNA . p92pol RNA-dependent RNA polymerase [20 , 21] is produced through translational readthrough of the p33 stop codon [22–24] . The abundant p33 is an RNA chaperone that functions in RNA template selection/recruitment and in the assembly of the membrane-bound viral replicase complex ( VRCs ) [21 , 25–29] . A recent systematic screen with TBSV based on a temperature-sensitive ( ts ) library of yeast mutants ( Prasanth and Nagy , unpublished ) , identified the yeast Ded1p ATP-dependent DEAD-box RNA helicase as a cellular factor affecting TBSV RNA recombination . Ded1p and ten other yeast DEAD-box proteins , which are the largest family of RNA helicases , were also identified as pro-viral factors in TBSV replication in yeast [13 , 30–35] . DEAD-box helicases are known to be involved in all aspects of cellular metabolism [36–38] , in RNA virus replication [39–42] , viral translation [43 , 44] , and affect responses to abiotic stress and pathogen infections [45–47] . They function in RNA duplex unwinding , RNA folding , remodeling of RNA-protein complexes , and RNA clamping [48] . TBSV , which does not code for its own helicase , usurps the yeast DDX3-like Ded1p ( similar to the Arabidopsis AtRH20 DEAD-box helicase ) , to promote ( + ) -strand synthesis [49] . Ded1p/AtRH20 bind to the 3’-end of the TBSV minus-strand RNA , and by locally unwinding the dsRNA replication intermediate structure [50] , it renders the promoter sequence accessible to p92pol for initiation of ( + ) -strand RNA synthesis . Additional DEAD-box helicases , such as Dbp3p ( human DDX5-like ) and Fal1p ( eukaryotic translation initiation factor eIF4AIII-like ) , which are involved in ribosome biogenesis in yeast [51–53] , and the orthologous Arabidopsis RH2 and RH5 helicases bind to the 5’ proximal region in the TBSV ( - ) RNA [54] . This region harbors a critical replication enhancer element ( REN ) [55] . These co-opted cellular helicases can locally unwind the double-stranded ( ds ) structure within the REN of the replication intermediate and enhance ( + ) RNA synthesis [50 , 54] . Altogether , the co-opted cellular DEAD-box helicases work synergistically to enhance TBSV replication by interacting with the viral ( - ) RNA , dsRNA and the replication proteins within the VRCs [54] . In this work , we show evidence that Ded1p/AtRH20 helicases are strong suppressors of TBSV recombination in yeast and plants . In vitro assays show direct involvement of Ded1p in suppression of viral recombination , which requires its ATPase function . Moreover , the presented data support a new role for Ded1p in facilitating the switch from ( - ) -strand to ( + ) -strand synthesis . Interestingly , the eIF4AIII-like AtRH2 helicase enhances TBSV recombination in the absence of Ded1/AtRH20 , suggesting that the coordinated action of cellular Ded1/AtRH20 and AtRH2 helicases control viral RNA recombination events . We propose a model on the role of Ded1/AtRH20 in facilitating the replication of full-length viral RNAs with intact 5’ ends while inhibiting the replication of 5’-truncated viral RNAs , thus playing a major role in maintaining the intact genome structure for TBSV .
To characterize the role of the DDX3-like Ded1p DEAD-box RNA helicase of yeast in TBSV RNA recombination , first we utilized genetic approaches in yeast . Depletion of Ded1p resulted in ~5-fold increase in TBSV recombinant ( rec ) RNA accumulation ( Fig . 1B , lanes 13–16 ) . Similarly , yeast expressing either Ded1–95ts or Ded1–199ts temperature-sensitive mutants as a single source for Ded1p , led up to 5-to-10-fold increase in TBSV recRNA levels at the semi-permissive temperature ( Fig . 1C , lanes 13–16 and 21–24 versus 17–20 ) . Ded1–199ts also supported ~35-fold higher recRNA accumulation at a lower ( permissive ) temperature ( Fig . 1C , lanes 9–12 ) , suggesting that this particular mutant is especially suitable for viral RNA recombination studies . Ded1–199ts ( G368D mutation ) is known to debilitate its function in protein translation and intron splicing [56] , while Ded1–95ts ( T408I mutation ) does not affect splicing , but maybe involved in translation and RNA decay [57] . Altogether , the above yeast genetic approaches have conclusively demonstrated that the wt Ded1p helicase is a strong suppressor of TBSV RNA recombination in yeast cells . The most frequent recombinants in the TBSV system are generated via template-switching mechanism by the viral replicase using viral RNA templates that are cleaved by cellular endo- and exoribonucleases ( schematically shown in Fig . 1A ) [5 , 8 , 9 , 15 , 17 , 18 , 58] . The partially degraded ( 5’-truncated ) viral RNA products generated by the cellular nucleases are called degRNAs , which serve as templates for viral RNA recombination ( Fig . 1A ) [8 , 9] . Interestingly , the amounts of degRNAs also increased by ~3-to-10-fold , suggesting their efficient generation and replication in Ded1ts mutant yeasts ( Fig . 1C ) or in yeast with depleted Ded1p ( Fig . 1B ) . Interestingly , the degRNAs are superior templates for high frequency recombination when expressed in yeast cells in the presence of the viral p33/p92pol replication proteins ( Fig . 1D ) [8 , 9] . Both Ded1–95ts and Ded1–199ts supported 3-to-8-fold higher recRNA accumulation from the DI-RIIΔ70 degRNA template than the wt Ded1p did in yeast ( Fig . 1D ) . These data further supported the suppressor function of Ded1p in TBSV recRNA accumulation in yeast . The surprisingly robust accumulation of the 5’-truncated degRNAs in both ded1–95ts and ded1–199ts yeasts expressing the full-length DI-AU-FP repRNA ( Fig . 1C ) was likely due to enhanced efficiency of their replication , because expression of the representative DI-RIIΔ70 degRNA accumulated to high level ( up to ~5-fold increase ) in ded1–95ts and ded1–199ts yeast strains in comparison with the wt yeast ( Fig . 1D ) . These findings indicate an unexpected role of Ded1p in suppressing the replication of the 5’-truncated degRNAs . This is in contrast with the pro-viral role of Ded1p in enhancing the accumulation of TBSV DI-72 repRNA , which carries the authentic 5’ end sequence ( see also below ) [49 , 54] . Testing the accumulation of ( + ) versus the ( - ) RNA products revealed ~9-fold increased ( - ) recRNA production in case of ded1–199ts yeast at semi-permissive temperature in comparison with wt yeast ( Fig . 2A ) . Interestingly , similar to the high level of ( - ) recRNAs , accumulation of truncated ( - ) degRNAs was also increased by ~4-fold , while the amount of full-length ( - ) repRNA changed only slightly ( DI-AU-FP repRNA , Fig . 2A ) in ded1–199ts yeast . Altogether , ( - ) recRNAs accumulated to ~3-fold higher level than the full-length DI-AU-FP ( - ) repRNA in ded1–199ts yeast ( Fig . 2A ) . On the contrary , the DI-AU-FP repRNA was the most prevalent ( + ) RNA product , while the ( + ) recRNAs and ( + ) degRNA products accumulated to 3-to-7-fold lesser amounts than the ( + ) repRNA in ded1–199ts yeast ( Fig . 2A ) . Since ded1–95ts and ded1–199ts mutations are present within the RNA binding domain of the Ded1p helicase [56] , we have tested if the mutants show altered viral RNA binding characteristic when compared with the wt Ded1p . The EMSA assay with DI-72 ( - ) RNA template revealed that the purified ded1–95ts and ded1–199ts mutants bound to the viral ( - ) RNA with up to 25-fold reduced efficiency in vitro ( Fig . 2B ) . The low efficiency in viral ( - ) RNA binding by these Ded1p mutants could be the reason for these mutants supporting the increased rate of viral recombination , high level of degRNA accumulation and reduction in viral ( + ) -strand synthesis ( see Discussion ) . In comparison with the results obtained via ded1–95ts and ded1–199ts mutants , we observed a similar trend with increased accumulation of ( - ) recRNA and ( - ) degRNA products obtained with the recombinogenic DI-AU-FP repRNA , when yeast expressed Ded1p at a reduced level ( +doxycycline treatment , Fig . 3A-B ) . Altogether , these data revealed that Ded1p is important in regulation of ( + ) versus ( - ) RNA products and this regulation depends on the presence of the authentic 5’ end sequence from TBSV ( + ) repRNA . To confirm the importance of co-opted Ded1p in viral RNA replication and recombination , we also tested the accumulation of various Δ+ ) and ( - ) RNA products with the efficient DI-72 repRNA , which replicates to the highest level among all TBSV RNAs in yeast and plants cells [59 , 60] . As expected based on previous publications [49 , 61] , depletion of Ded1p by doxycycline in TET::DED1 yeast , reduced the accumulation of DI-72 ( + ) repRNAs by ~4-fold , while the accumulation of new ( + ) recRNAs and ( + ) degRNA products was below the detection limit ( top image in Fig . 3C , lanes 3–4 and 7–8 ) . Interestingly , however , ( - ) recRNA and ( - ) degRNA products , which were almost as abundant as the full-length DI-72 ( - ) repRNA , were detected in yeasts with depleted Ded1p level ( bottom image in Fig . 3C , lanes 3–4 and 7–8 ) . The corresponding ( - ) recRNA and ( - ) degRNA products were below detection limit in yeasts expressing Ded1p to high level ( bottom image in Fig . 3C , lanes 1–2 and 5–6 ) . Altogether , these results demonstrate that Ded1p plays a critical role in suppression of the formation and accumulation of recRNA and degRNA products during minus-strand synthesis . To dissect the inhibitory function of Ded1p in recRNA formation and degRNA replication , first we used an in vitro assay with isolated yeast membranes [62] . The yeast membrane fraction contains the tombusvirus replicase in complex with the viral RNAs , thus facilitating studies on the viral RNAs functionally associated with the replicase . Denaturing PAGE analysis of the in vitro replicase products revealed that both recRNAs and degRNAs were actively replicated by the tombusvirus replicase derived from ded1–199ts yeast ( ~13-to-21-fold higher level than in wt replicase ) , while these RNAs were barely detectable in the replicase from wt yeast ( Fig . 4A ) . In addition , ded1–199ts replicase supported ~6-to-7-fold higher level of ( - ) recRNAs and ( - ) degRNAs in comparison with slightly reduced DI-AU-FP ( - ) repRNA carrying the authentic 5’ end sequence in vitro ( Fig . 4B ) . The ( + ) recRNAs and ( + ) degRNAs accumulated to 3-fold higher level in ded1–199ts yeast than the corresponding RNAs in wt yeast , but ( + ) recRNAs and ( + ) degRNAs were ~12-fold less abundant than the DI-AU-FP ( + ) repRNA in vitro ( Fig . 4B-C ) . Thus , similar to the situation in yeast cells , wt Ded1p suppressed in vitro ( - ) -strand synthesis with the recRNAs and degRNAs , but not with DI-AU-FP repRNA carrying the authentic 5’ end sequence . The second assay was based on a cell-free extract ( CFE ) from yeast with depleted Ded1p that was used to assemble the tombusvirus replicase in vitro using purified recombinant p33/p92pol and ( + ) repRNAs ( Fig . 4D ) [49] . The CFE supports a complete replication cycle resulting in both ( - ) and ( + ) -stranded repRNA products [29] . As expected , Ded1p facilitates the production of ( + ) repRNAs carrying the authentic 5’ end sequence [Fig . 4E , lanes 3–4 , see reduced DI-72 repRNA accumulation in CFE with depleted Ded1p ( +dox ) ] [49] . Similarly , addition of the purified recombinant wt Ded1p to the CFE programmed with DI-AU-FP ( + ) repRNA , which carries the authentic 5’ end sequence , led to a ~50% increase in repRNA accumulation ( Fig . 4F , lane 2 ) , while the ATPase-deficient D1 mutant of Ded1p [49 , 63] could not stimulate repRNA replication in vitro ( Fig . 4F , lane 3 ) . On the contrary , addition of the purified recombinant wt Ded1p or D11 mutant with increased ATPase activity [63] to the CFE with the 5’-truncated DI-RIIΔ70 degRNA , led to ~40–50% decrease in degRNA accumulation ( Fig . 4G , lanes 2 and 4 versus lane 1 ) , while D1 mutant did not affect the replication of DI-RIIΔ70 degRNA in the CFE ( lane 3 ) . Based on these data from CFE assays , we conclude that Ded1p inhibits the replication of recRNAs or degRNAs missing the authentic 5’ end sequence likely through blocking the ( - ) -strand synthesis on these RNA templates . Based on known features of DEAD-box helicases in remodeling protein-RNA complexes [48 , 64] , we reasoned that Ded1p might be involved in releasing the p92 RdRp protein from the ( + ) RNA template at the end of ( - ) -strand synthesis , thus decreasing the chance for template-switching events ( see Discussion ) . To test this model , we developed an in vitro assay with a soluble form of p92 , called p92-Δ167N , which can specifically use TBSV-derived ( + ) RNA template for RNA synthesis in vitro in the presence of biotynylated UTP and other ribonucleotides as shown schematically in Fig . 5A [21] . The biotynylated viral dsRNA form was then captured via streptavidin beads ( Fig . 5B ) . We then added purified Ded1p to the beads to facilitate the putative release of the p92-Δ167N RdRp from the captured dsRNA product . The amount of dsRNA-bound versus released p92-Δ167N was measured by Western blotting ( Fig . 5B-C ) . These experiments revealed that three-times more p92-Δ167N was released from the viral dsRNA product when purified wt Ded1p was included in the assay ( Fig . 5C , lanes 4 versus 1 ) . In another assay , we used EMSA with MBP-p92-Δ167N and purified GST-Ded1p based on 32P-labeled RI ( + ) RNA as a probe . Both MBP-p92-Δ167N and GST-Ded1p bind to the probe when applied alone ( Fig . 5D , lanes 3 and 14 , respectively ) . However , when we added p92-Δ167N first to the probe , followed 15 min latter by addition of GST-Ded1p , then the release of the probe was detectable in the form of diffused label ( “smear” ) ( Fig . 5D , lanes 4–5 versus 6–7 with purified GST as a control ) . Interestingly , the release of the probe was dependent on the presence of ATP , suggesting that Ded1p requires ATP for this function ( Fig . 5D , lanes 8–9 versus 4–5 ) . The diffused label was also observed when Ded1p was added first to the RNA , followed by p92-Δ167N ( Fig . 5D , lanes 12–13 ) , suggesting that Ded1p and p92-Δ167N likely form a complex that releases the viral RNA . To establish the function of Ded1p during TBSV replication and RNA recombination , we examined if Ded1p affects these processes via controlling Xrn1p 5’-to-3’ exoribonuclease , which is a key enzyme in TBSV RNA stability and for suppression of TBSV RNA recombination in yeast [5 , 16–18 , 65] . For these studies , we expressed a 5’-truncated repRNA ( DI-ΔRI , Fig . 6A ) , which goes through further 5’-truncations ( up to ~70 nt , where RII ( + ) -SL hairpin structure stops the nuclease activity ) in the presence of Xrn1p in wt yeast ( Fig . 6A ) , while this truncation process is weak in xrn1Δ yeast ( Fig . 6B ) [65] . DI-ΔRI RNA did not accumulate in ded1–199ts yeast , similar to wt yeast ( Fig . 6B , lanes 13–16 and 1–4 ) , while DI- ( RI accumulated to high level in xrn1Δ yeast ( Fig . 6B , lanes 5–8 ) . Also , the profile of recRNAs accumulating in ded1–199ts yeast was similar to that in wt yeast and different from that in xrn1Δ yeast ( Fig . 6B ) . Thus , it seems that ded1p mutation does not affect TBSV RNA recombination and degRNA accumulation via inhibition of the Xrn1p activity . This conclusion was further supported by RNA stability experiments that showed comparable half-life for degRNA in ded1–95ts and ded1–199ts yeasts to the wt yeast ( Fig . 6C ) . Because TBSV replication is known to depend on two types of cellular DEAD-box helicases , namely the DDX3-like Ded1p/AtRH20 that bind to the 3’end of the ( - ) RNA and the eIF4AIII-like Fal1p/AtRH2 helicases that bind to a 5’ proximal enhancer element in the ( - ) RNA ( Fig . 7A ) [49 , 54] , we also tested the effect of expression of AtRH2 on TBSV recombination in yeast . We observed up to ~12-fold enhanced level of TBSV RNA recombination in wt and 26-fold increase in ded1–199ts yeasts expressing AtRH2 ( Fig . 7B , lanes 5–6 , 17–18 and 11–12 , 23–24 ) . In contrast , expression of AtRH20 helicase ( Fig . 7C ) , which is a Ded1p ortholog , suppressed recRNA accumulation in both wt and ded1–199ts yeasts ( Fig . 7B ) . Thus , different co-opted cellular helicases have opposite effects on TBSV recombination in yeast . To test if AtRH2 has direct function in TBSV recombination , we used the CFE-based TBSV replication assay prepared from yeast with depleted Ded1p ( Fig . 7D ) . Interestingly , the addition of purified recombinant AtRH2 increased the replication of the 5’-truncated DI-RIIΔ70 degRNA by ~2-fold and RNA recombination also by ~2-fold ( Fig . 7E , lanes 3–4 versus 1–2 ) . However , the stimulatory effect of AtRH2 on RNA recombination is neutralized by the addition of purified recombinant Ded1p helicase ( Fig . 7E , lanes 5–6 ) , suggesting that AtRH2 only promotes formation of recRNAs and the replication of the 5’-truncated degRNAs when Ded1p helicase is depleted . In other words , Ded1p helicase seems to be the dominant factor with its recombination suppressor activity . To confirm the roles of the above cellular helicases in TBSV RNA recombination in plants , we over-expressed AtRH2 and AtRH20 in Nicotiana benthamiana plants also expressing DI-AU-FP repRNA in the presence of Cucumber necrosis virus ( CNV ) , a closely related tombusvirus that serves as a helper virus for the TBSV repRNA . The helper tombusvirus provides the p33 and p92 replication proteins in trans for the replication of repRNA and the de novo generated recRNAs in this system . We found that the Ded1p ortholog AtRH20 suppressed TBSV recRNA accumulation by ~2-fold , while AtRH2 increased recRNAs by ~2-fold ( Fig . 8A ) . These data indicate that the different co-opted cellular helicases have opposite effects on TBSV recombination in plants . Over-expression of AtRH20 also suppressed the accumulation of the 5’-truncated DI-RIΔ degRNA and the further truncated degRNAs , ultimately resulting in ~3-fold less recRNA accumulation than in control plants ( Fig . 8B , lanes 4–6 versus 1–3 ) . Based on these results , we suggest that the roles of the two cellular helicases in plants are comparable to the functions of these helicases in vitro in the CFE assay and in yeast .
This work based on genetic approaches with Ded1p ts mutants or depletion of Ded1p in yeast and in vitro approaches with cell-free replication of TBSV RNAs strongly supports a TBSV recombination suppressor activity of the co-opted Ded1p cellular helicase . Since the ATPase-deficient D1 mutant of Ded1p does not have recombination suppressor activity in vitro ( Fig . 4 ) , it seems that Ded1p helicase has a direct inhibitory function in TBSV RNA recombination . The AtRH20 helicase , a plant ortholog of Ded1p , also has similar recombination suppressor activity in yeast and in plants . Importantly , the recombination suppressor activity of Ded1p is independent of the recombination suppressor activity of the previously characterized Xrn1p 5’-to-3’ exoribonuclease , which acts by efficiently removing degRNAs and recRNAs generated during TBSV replication ( Fig . 6 ) [16–18 , 65] . Altogether , Ded1p helicase is the first co-opted cellular factor in the viral replicase complex that has been shown to directly affect viral ( + ) RNA recombination . A previously demonstrated function of co-opted Ded1p helicase is to locally unwind the double-stranded RNA replication product after the ( - ) RNA synthesis is completed on the ( + ) RNA template ( Fig . 9A ) [49 , 50 , 54] . Ded1p then facilitates the loading of the viral replicase onto the 3’ end of the ( - ) -stranded RNA portion of the dsRNA intermediate with the assistance of the co-opted cellular glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) [49 , 50 , 54] . Thus , ultimately , Ded1p promotes the asymmetrical ( i . e . , excess ) production of new ( + ) -strand RNAs by allowing the selective use of the ( - ) RNA in the dsRNA intermediate template . However , this work also reveals a new role of Ded1p in inhibition of ( - ) -strand synthesis , especially with those RNA templates that lack authentic 5’ sequences , such as degRNAs and recRNAs ( Figs . 2–3 ) . Interestingly , the amount of ( - ) recRNAs and ( - ) degRNAs far exceeds the DI-AU-FP ( - ) repRNA in Ded1p deficient yeast or in vitro when Ded1p mutant is present , while the ( + ) repRNA is more abundant than ( + ) recRNAs or ( + ) degRNAs ( Figs . 2–3 ) . In case of the highly efficient DI-72 repRNA , the ( - ) recRNAs and ( - ) degRNAs are only detected when Ded1p is depleted ( Fig . 3 ) . Thus , one major function of the co-opted wt Ded1p is to promote the efficient replication of only the full-length viral RNAs , while suppressing the replication of 5’-truncated viral RNAs , lacking critical cis-acting elements . This novel function of Ded1p in maintenance of genome integrity seems to be manifested during ( - ) -strand synthesis . Ded1p-driven suppression of replication of degRNAs might be critical in cells loaded with cytosolic ribonucleases that likely generate many truncated viral RNAs . These defective RNAs could likely compete with the full-length viral RNAs for viral- and host factors , thus leading to reduced viral replication . However , the co-opted cellular Ded1p helicase facilitates proper replication of TBSV RNAs and protects TBSV from competition by defective viral genomes . Since Ded1p inhibits the replication of recRNAs or degRNAs lacking the authentic 5’ end sequence through blocking the ( - ) -strand synthesis on these RNA templates , lesser amount of defective viral dsRNAs could accumulate . The reduced amount of dsRNA is an advantage for the virus , because dsRNAs could efficiently trigger antiviral responses , such as RNAi ( or RNA silencing in plants ) [72–74] . Another surprising finding in this study is the stimulatory effect of a second group of co-opted cellular DEAD-box helicases on TBSV RNA recombination . Accordingly , over-expression of the eIF4AIII-like AtRH2 in yeast or plant cells led to increased level of recRNA accumulation ( Figs . 7–8 ) . The AtRH2 helicase binds to the 5’ proximal region of the viral ( - ) RNA , which harbors the RIII ( - ) REN , resulting in localized unwinding of the dsRNA replication intermediate [50 , 54] . Although this unwinding process is important for the replication of the full-length TBSV RNA , it seems that it only works “properly” for TBSV replication when Ded1p/AtRH20 helicase is also present in the replicase complex . Based on these observations , the emerging concept is that the coordinated action of these two co-opted cellular helicases is required for efficient replication of the full-length viral RNA . If Ded1p is missing or the eIF4AIII-like AtRH2 is present in excess amount within the replicase complex , then the frequency of viral RNA recombination increases and replication of 5’-truncated viral degRNAs becomes more efficient . Therefore , these conditions favor the rapid evolution of TBSV , which could be advantageous under some circumstances , but disadvantageous when the wt TBSV is the best-adapted to the host/environment . Previous works revealed roles for Ded1p/AtRH20 and AtRH2 DEAD-box helicases during TBSV ( + ) -strand synthesis [49 , 54] , which was based on local unwinding of the dsRNA replication intermediate to facilitate initiation of ( + ) -strand synthesis by the viral replicase ( Fig . 9A ) . However , this work unearthed a novel function for Ded1p helicase by showing an increased level of ( - ) RNA production from recRNAs and degRNAs in yeast expressing mutant Ded1p or with depleted level of Ded1p . To explain these findings , we propose that Ded1p helicase facilitates the displacement of the viral p92 RdRp protein from the dsRNA product at the end of ( - ) -strand synthesis , as shown schematically in Fig . 9A . In case of the full-length viral RNA , the localized unwinding of the “left side” of the dsRNA then promotes the association of the p92 RdRp with the 3’ cis-acting elements in the ( - ) RNA portion of dsRNA , followed by ( + ) -strand synthesis via strand-displacement mechanism as shown before [50] . Thus , basically , Ded1p/AtRH20 helicases could promote the switch from ( - ) - to ( + ) -strand synthesis . In case of the 5’-truncated RNAs , Ded1p/AtRH20 helicases could likely displace the p92 RdRp from the 5’ end of the degRNAs ( Fig . 9B ) . Displacement of p92 RdRp from the template would likely inhibit template-switching events during ( - ) -strand synthesis . Accordingly , in vitro assays support this model by providing evidence that Ded1p promotes dissociation of p92 RdRp from the viral RNA ( Fig . 5 ) . Moreover , Ded1p helicase might not be able to open the ds degRNA to facilitate initiation of ( + ) -strand synthesis due to the absence of RI ( - ) sequence ( i . e . Ded1p binding sequence ) in the ( - ) degRNA [49] . Indeed , all degRNAs identified lack the authentic 3’ end viral sequences in the ( - ) RNA [15 , 18 , 65] . Based on these , we propose that Ded1p helicase suppresses the use of 5’-truncated degRNAs in ( + ) -strand synthesis . Overall , the p92 displacement ability of Ded1p likely inhibits template-switching RNA recombination and the replication of recRNAs ( Fig . 9B ) . However , when Ded1p is depleted or mutant Ded1p is present , then p92 RdRp protein will not be efficiently displaced from the dsRNA [after finishing ( - ) RNA synthesis on the ( + ) RNA template] , and this condition then facilitates template-switching-based RNA recombination ( Fig . 9B ) . In addition , the replication of degRNAs and recRNAs is also increased in the absence of functional Ded1p , likely due to the presence of AtRH2 type helicase in the VRCs , which facilitates unwinding of the “right-side” of the dsRNA template , thus promoting re-initiation on the plus-strands of dsRNA templates to generate new minus-strands ( Fig . 9B ) . AtRH2 cannot facilitate re-initiation on the ( + ) RNA when Ded1/AtRH20 is present due to the recruitment of p92 to the ( - ) 3’-end sequences by Ded1p , long-range RNA-RNA interactions and additional cellular factors , such as GAPDH , as described earlier [54] . Altogether , the above events could explain the increased level of ( - ) RNAs from degRNAs and recRNAs in yeast either expressing mutant Ded1p or with depleted Ded1p . Overall , the novel function of the DDX3-like Ded1p/RH20 helicases is the down-regulation/inhibition of ( - ) RNA synthesis by promoting the efficient switch from ( - ) RNA to ( + ) RNA synthesis . Interestingly , this feature requires the authentic viral 3’ end sequences on the ( - ) RNA , suggesting similarities between telomeres and viral RNA synthesis in protection of the ends of linear nucleic acids [75 , 76] . Those viral RNAs lacking the authentic terminal sequences could replicate less efficiently in the presence of Ded1p/AtRH20 helicases , suggesting that TBSV recruits a cellular helicase to protect and promote the replication of the full-length viral RNAs , while suppressing the accumulation of recRNAs and degRNAs during viral infections . Therefore , based on this work , a new concept emerges on the roles of co-opted cellular helicases in maintaining viral genome integrity .
The yeast ( Saccharomyces cerevisiae ) strain BY4741 ( MATa his3 ( 1 leu2 ( 0 met15Δ0 ura3 ( 0 ) , R1158 and TET::DED1 ( yTHC library ) were obtained from Open Biosystems . The temperature-sensitive ( ts ) yeast strains ded1–95ts and ded1–199ts were of generous gift from C . Boone ( U . Toronto ) . The yeast expression plasmids LpGAD-His92 ( containing CNV p92pol gene behind the CUP1 promoter , LEU2 selection ) , and HpHisGBK-His33/DI-AU-FP ( co-expressing p33 from the CUP1 promoter and DI-AU-FP repRNA from GAL1 promoter , HIS3 selection ) , HpHisGBK-HFHis33/DI-72 ( co-expressing p33 from the CUP1 promoter and DI-72 repRNA from GAL1 promoter , HIS3 selection ) , UpGBK-His33/DI-AU-FP ( co-expressing p33 from the ADH1 promoter and DI-AU-FP repRNA from GAL1 promoter , URA3 selection ) have been previously described [8] . Plasmid HpGBK-His33/DI-RIIΔ70 was made by PCR-amplification of DI-72RIIΔ70 with primers #1546 ( CCGCGAATTCACGGATTAGAAGCCGCCGAGCGGGT ) and #1069 ( CCGGTCGAGCTCTACCAGGTAATATACCACAACGTGTGT ) . The PCR product was restriction digested with EcoRI and SacI and ligated into the plasmid HpGBK-His33/DI-72 to replace the full-length DI-72 fragment . The E . coli expression plasmids pMAL-Ded1 , pMAL-D1 , pMAL-D11 and pMAL-RH2 were prepared previously [49 , 54] . To prepare plasmids for expression of MBP-tagged Ded1p ts mutants , genomic DNA of ded1–95 or ded1–199 strains were used as templates in PCR with primers #3956 ( CCAGCTGCAGTCACCACCAAGAAGAGTTG ) and #3957 ( CCAGGAATTCATGGCTGAACTGAGCGAACAAG ) . The PCR products were cloned into pMalc-2x vector at EcoRI and PstI sites . For GST-Ded1p expression , pMAL-Ded1 was used as a template in PCR with primers #4308 ( TGGAACTTGGAATTGTTTACACCTTAGTCTGTTGACTTAA ) and #4309 ( CCAGCTCGAGTCACCACCAAGAAGAGTTG ) . The PCR products were cloned into pGEX-his-RE vector at SpeI and XhoI site . The plant expression plasmids pGD-RH2 , pGD-RH20 , pGD-CNV and pGD-DI-AU-FP were described previously [54 , 65] . To obtain plasmids HpGBK-His-RH20 and HpGBK-His-RH2 , the plasmids pMAL-RH20 or pMAL-RH2 [54 , 61] , respectively , were used as templates in PCR with primers #4315 ( CCAGGGATCCATGAGTGCATCATGGGCAG ) and #4316 ( CCAGCTGCAGCTAATCCCAAGCACTGGTC ) for RH20; and #4816 ( CCAGGGATCCATGGCGACAGCGAATCCTGG ) and #5117 ( CCAGCTGCAGTTAGATAAGATCAGCTACATTC ) for RH2 open reading frames . The PCR products were cloned into HpGBK-His vector at BamHI and PstI sites . Yeast strains were co-transformed with plasmids by using the lithium acetate/ssDNA/polyethylene glycol method , and transformants were selected by complementation of auxotrophic markers [77] . For TBSV recombination assay in BY4741 , ded1–95ts , ded1–199ts , R1158 and TET::DED1 , yeast strains were co-transformed with LpGAD-His92 and HpGBK-His33/DI-AU-FP , HpGBK-His33/DI-RIIΔ70 or HpHisGBK-HFHis33/DI-72 . The transformed BY4741 , ded1–95ts , and ded1–199ts strains were pre-grown at 23°C overnight in SC-LH- ( synthetic complete media without histidine and leucine ) media with 2% galactose . Then , 50 μM CuSO4 was added to the yeast cultures to launch virus replication and recombination . Yeast was grown at either 23°C or 29°C for 24 h before sample collection for analysis . The transformed R1158 and TET::DED1 strains were pre-grown at 29°C overnight in SC-ULH- ( synthetic complete media without uracil , histidine and leucine ) media with 2% galactose containing 10 μg/ml doxycycline . Then , 50 μM CuSO4 was added to the yeast cultures to launch virus replication and recombination at 23°C or 29°C for 24 h . In the complementation study , BY4741 and ded1–199ts strains were co-transformed with LpGAD-His92 , UpGBK-His33/DI-AU-FP and the indicated plasmids ( HpGBK-HisRH20 or HpGBK-HisRH2 ) expressing one of the host helicases . The transformed yeast strains were pre-grown at 23°C overnight in SC-ULH- media with 2% galactose , followed by the addition of 50 μM CuSO4 and culturing at 23°C or 29°C for 24 h . For viral RNA stability assay , BY4741 ded1–95ts , and ded1–199ts strains were transformed with UpYC-DI-RIIΔ70 [18] . The transformed yeast strains were grown at 23°C in SC-U- media with 2% galactose . After 24 h , the cultures were re-suspended in SC-U- media with 2% glucose and grown at 23°C or 29°C . The samples were collected at given time points mentioned in figure legend . To observe the TBSV DI- ( RI RNA recombination profile in BY4741 , ( Xrn1 , ( Met22 , and ded1–199ts yeast strains , they were co-transformed with HpGBK-His33 , LpGAD-His92 and pYC2-DI- ( RI . The transformed cultures were inoculated on to ULH-/glucose media and grown at 23°C for 12 hrs . Yeast cultures were collected by centrifugation and dissolved in ULH-/galactose media supplemented with 50 μM CuSO4 . Cultures were grown at 23°C for two days before sample collection for RNA analysis . TBSV RNA recombination was analyzed using total RNA extracted from yeast and plants . Standard RNA extraction and Northern blot analysis was performed as described in previous publication [78] . To detect TBSV ( + ) RNA or ( - ) RNA , we prepared 32P-labeled DI-72RIII/IV probe with in vitro T7-based transcription using PCR-amplified DNA obtained on HpGBK-His33/Gal1-DI-72 template with primers #22 ( GTAATACGACTCACTATAGGGCTGCATTTCTGCAATGTTCC ) / #1165 ( AGCGAGTAAGACAGACTCTTCA ) for ( + ) RNA detection; and primers #18 ( GTAATACGACTCACTATAGGAGAAAGCGAGTAAGACAG ) / #1190 ( GGGCTGCATTTCTGCAATG ) for ( - ) RNA detection . Typhoon FLA 9500 system ( GE ) and ImageQuant TL software were used to detect and quantify the bands in the gels . The repRNA and degRNA bands were identified based on molecular markers , while the recRNAs were identified based on previously characterized recRNAs [15 , 16 , 58 , 65] . Only the bands representing the major recRNAs ( which are pointed at in figures ) were quantified . All these RNAs were normalized based on ribosomal RNA level in all samples . Recombinant MBP-tagged helicase proteins and MBP-tagged TBSV p33 and p92 replication proteins or MBP-p92Δ167N were expressed in E coli and purified as published before [49] . Briefly , the expression plasmids were transformed into E . coli strain BL21 ( DE3 ) CodonPlus . Protein expression was induced by isopropyl-β-D-thiogalactopyranoside ( IPTG ) at 16°C for 8 h . After collection of the cultures by centrifugation at 4000 xg for 5 min , the cells were re-suspended and broken in reduced-salt column buffer ( 25 mM NaCl , 30 mM HEPES-KOH pH 7 . 4 , 1 mM EDTA , 10 mM β-mercaptoethanol ) . The lysate was centrifuged at 14 , 000 rpm for 10 min to remove cell debris . Then , the supernatant was incubated with amylose resin ( NEB ) at 4°C for 1 h . After washing the resin with 50 ml reduced-salt column buffer ( without β-mercaptoethanol ) , the recombinant proteins were eluted in maltose buffer ( column buffer containing 0 . 18% ( W/V ) maltose ) . The membrane-enriched fraction ( MEF ) was obtained as published previously [62 , 78] . Briefly , yeast strains were transformed and grown as described above for TBSV recombination in yeast . Yeast cultures were collected and processed to obtain the MEFs containing the in vivo-assembled replicase complexes as previously described [78] . Each membrane fraction preparation was adjusted based on the relative amounts of His6-tagged p33 and comparable amounts of replicase ( based on p33 ) from each preparation were used in the subsequent in vitro replicase assay . The replicase assay was performed as described [62 , 78] . Briefly , the in vitro assay ( 50 μl ) contained 10 μl of the normalized MEF preparations , 10 mM DTT , 50 mM Tris-Cl pH 8 . 0 , 10 mM MgCl2 , 0 . 1 U RNase inhibitor , 1 mM ATP , 1 mM CTP , 1 mM GTP and 0 . 1 μl of α32P-UTP ( 3000 Ci/mmol ) . Reaction mixtures were incubated at 25°C for 3h , followed by phenol/chloroform extraction and isopropanol/ammonium acetate ( 10:1 ) precipitation . 32P-labeled RNA products were analyzed in 5% acrylamide/8 M urea gels . To detect the membrane associated RNA , membrane preparations that contained comparable amounts of replicase were used to extract the viral RNA by standard phenol/chloroform extraction and isopropanol/ammonium acetate ( 10:1 ) precipitation . Then , the RNAs were analyzed by Northern blotting with ( + ) or ( - ) RNA specific probes . CFEs from BY4741 and TET::DED1 treated with 10 μg/ml doxycycline were prepared as described earlier [29 , 62] and adjusted to contain comparable amounts of total protein . The in vitro CFE-based assays were performed in 20 μl total volume containing 1 μl of adjusted CFE , 0 . 5 μg DI-72 ( + ) , DI-RIIΔ70 ( + ) or DI-AU-FP ( + ) RNA transcripts ( separately ) , 0 . 5 μg purified MBP-p33 , 0 . 5 μg purified MBP-p92pol ( both recombinant proteins were purified from E . coli ) [79] , 30 mM HEPES-KOH , pH 7 . 4 , 150 mM potassium acetate , 5 mM magnesium acetate , 0 . 13 M sorbitol , 0 . 4 μl actinomycin D ( 5 mg/ml ) , 2 μl of 150 mM creatine phosphate , 0 . 2 μl of 10 mg/ml creatine kinase , 0 . 2 μl of RNase inhibitor , 0 . 2 μl of 1 M dithiothreitol ( DTT ) , 2 μl of 10 mM ATP , CTP , and GTP and 0 . 25 mM UTP and 0 . 1 μl of 32P-UTP . 0 . 3 μg of MBP-Ded1 , MBP-D1 or MBP-D11 , respectively , was added to the assay to test their activities during viral RNA synthesis . Reaction mixtures were incubated for 3 h at 25°C , followed by phenol/chloroform extraction and isopropanol/ammonium acetate ( 10:1 ) precipitation . 32P-labeled RNA products were analyzed in 5% acrylamide/8 M urea gels [62] . The 32P-labeled full-length DI-72 ( - ) RNA and the RI ( + ) RNA were generated as described [79] . Ded1p and ts mutants were incubated with 5 ng of 32P-labeled DI-72 ( - ) RNA probe in a binding buffer ( 50 mM Tris-HCl [pH 8 . 2] , 10 mM MgCl2 , 1 mM EDTA , 10% glycerol , 200 ng of yeast tRNA [Sigma] , and 2 U of RNase inhibitor [Ambion] ) at 25°C for 15 min . After the binding , the samples were analyzed by 5% nondenaturing PAGE performed at 200 V for 1 h in a cold room . To test the template release activity , briefly , 32P-labeled RI ( + ) RNA probe was incubated with p92-Δ167N at 25°C for 15 min , followed by adding affinity-purified GST-Ded1p to the reaction with or without 1 mM ATP , then the reaction was incubated at 25°C for 30 min . In addition , probe was also incubated with proteins in a different order mentioned in figure legend . First , p92-Δ167N RdRp assay was used to produce the biotin-labeled partial dsRNA product [21] . Briefly , the in vitro RdRp reaction was performed in 20 μl total volume containing 1 μl of adjusted CFE ( soluble fraction only ) , 0 . 5 μg DI-mini ( + ) RNA transcript [21] , 0 . 5 μg affinity-purified MBP-p92-Δ167N , 30 mM HEPES-KOH , pH 7 . 4 , 150 mM potassium acetate , 5 mM magnesium acetate , 0 . 13 M sorbitol , 0 . 2 μl actinomycin D ( 5 mg/ml ) , 2 μl of 150 mM creatine phosphate , 0 . 2 μl of 10 mg/ml creatine kinase , 0 . 2 μl of RNase inhibitor , 0 . 2 μl of 1 M dithiothreitol ( DTT ) , 2 μl of 10 mM ATP , CTP , and GTP and 0 . 1 mM UTP and 0 . 1 μl of biotin-UTP . Reaction mixture was incubated at 25°C for 30 min . Note that we combined 10 separate in vitro reactions in the subsequent experiment . After incubation , the free , unincorporated biotin-UTP was removed by Sepharose G-25 column . Then , 200 μl of in vitro RdRp reaction mixture were incubated with Strepavidin-beads ( MagneSphere Magnetic Separation Products , Promega ) at 25°C for 10 min to capture the biotin-labeled RNA and the RNA-bound p92-Δ167N RdRp as well . Then , we washed the beads once with 0 . 1% SSC buffer , followed by incubation of the beads with GST-Ded1p or GST ( as a control ) in RdRp buffer ( 10 mM DTT , 50 mM Tris–Cl pH 8 . 0 , 10 mM MgCl2 ) with 1 mM ATP at 25°C for 10 min to elute ( release ) the p92-Δ167N RdRp from the streptavidin-bound RNA . Then , we collected and precipitated the eluted proteins with 10% TCA . The precipitated proteins ( eluate fraction in Fig . 5C ) were dissolved in 30 μl SDS buffer . We also recovered the p92-Δ167N RdRp from the streptavidin-bound RNA by boiling the beads in 30 μl SDS buffer for 5 min ( SDS fraction in Fig . 5C ) . All the protein samples were analyzed by Western blotting method with anti-MBP antibody to detect the amount of p92-Δ167N RdRp in the obtained samples . Cultures of Agrobacterium tumefaciens C58C1 strain carrying pGD-RH2 or pGD-RH20 were used for transient expression of Arabidopsis thaliana RH2 and RH20 [54 , 61] . N . benthamiana plants were infiltrated with A . tumefaciens carrying pGD-RH2 ( OD600 = 0 . 3 ) or pGD-RH20 ( OD600 = 0 . 3 ) together with pGD-CNV ( OD600 = 0 . 3 ) and pGD-DI-AU-FP ( OD600 = 0 . 3 ) to launch tombusvirus replication and induce RNA recombination . Leaf infiltration with A . tumefaciens carrying “empty” pGD plasmid was used as a control . We also performed agroinfiltration with pGD-p33 + pGD-p92+ pGD-DI-ΔRI at a final concentration of 0 . 3 ( OD600 ) . Three and four days after agro-infiltration , samples from the agro-infiltrated leaves were collected from the agroinfiltrated leaves . Total RNA was extracted and Northern blot analysis was performed as previously described [16] .
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A major force in virus evolution is the ability of viruses to recombine and change their genomes rapidly . Similar to viral replication that greatly depends on subverted cellular proteins , viral genetic recombination is also affected by host factors based on genome-wide screens with tomato bushy stunt virus ( TBSV ) in yeast model host . However , the roles of host factors in the viral genomic RNA recombination process remain elusive . In this paper , we show evidence , in yeast , plants and in vitro , that co-opted cellular helicases by TBSV affect viral recombination through suppressing template-switching and replication of the new recombinant viral RNAs . Based on the presented data , a new concept emerges on the roles of co-opted cellular helicases in maintaining viral genome integrity . Altogether , the hijacked cellular DEAD-box helicases are involved in maintenance of full-length viral RNA genome and suppression of viral RNA recombination , thus blocking the appearance of defective or recombinant viral RNAs during replication .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Coordinated Function of Cellular DEAD-Box Helicases in Suppression of Viral RNA Recombination and Maintenance of Viral Genome Integrity
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In preparation for dramatic morphogenetic events of gastrulation , rapid embryonic cell cycles slow at the mid-blastula transition ( MBT ) . In Drosophila melanogaster embryos , down-regulation of cyclin-dependent kinase 1 ( Cdk1 ) activity initiates this slowing by delaying replication of heterochromatic satellite sequences and extending S phase . We found that Cdk1 activity inhibited the chromatin association of Rap1 interacting factor 1 ( Rif1 ) , a candidate repressor of replication . Furthermore , Rif1 bound selectively to satellite sequences following Cdk1 down-regulation at the MBT . In the next S phase , Rif1 dissociated from different satellites in an orderly schedule that anticipated their replication . Rif1 lacking potential phosphorylation sites failed to dissociate and dominantly prevented completion of replication . Loss of Rif1 in mutant embryos shortened the post-MBT S phase and rescued embryonic cell cycles disrupted by depletion of the S phase–promoting kinase , cell division cycle 7 ( Cdc7 ) . Our work shows that Rif1 and S phase kinases compose a replication timer controlling first the developmental onset of late replication and then the precise schedule of replication within S phase . In addition , we describe how onset of late replication fits into the progressive maturation of heterochromatin during development .
Eukaryotic DNA replication begins at many locations throughout the genome , known as origins . Different origins initiate at different times during S phase on a schedule governed by an elusive replication timing program . The time it takes to duplicate the genome , the length of S phase , is set by the time when the last sequence completes replication . For over 50 years , the field has appreciated that late replicating sequences are found in the compacted portion of the genome known as heterochromatin [1][2][3] . Late replication is presented as a general property of heterochromatin , but how this property arises is unknown [2] . Additionally , embryonic development of many animals features dramatic modifications of replication timing [4][5][6][7] . In Drosophila , the length of S phase changes by over 50-fold during development [8][9][10] , and in the early Drosophila embryo , the heterochromatin does not replicate later than the rest of the genome . Late replication is then properly viewed as a feature that must be imparted to the heterochromatin at the beginning of every new generation . How S phase is retooled to do this is unknown . As worked out in yeast , the process of origin initiation involves a sequence of conserved biochemical steps that converts an origin into a bidirectional replication fork [11][12] . Origins are first licensed for replication through the loading onto double-stranded DNA ( dsDNA ) of two helicase complexes composed of 6 minichromosome maintenance proteins ( MCM2-7 ) . The resulting head-to-head double hexamer is known as a pre-replicative complex ( pre-RC ) . Activation of the pre-RC requires the coordinated assembly of a multiprotein complex called a replisome . Activation , also referred to as firing , is led by the action of 2 conserved cell cycle kinases: a cyclin-dependent kinase ( CDK ) and a Dbf4-dependent kinase ( DDK ) [13] . CDK and DDK are recruited to pre-RCs , where they phosphorylate substrates to initiate the transformation of the pre-RC into functional replication forks [14][15][16] . Local chromatin structure is thought to influence the efficiency of this step to alter the replication timing of different sequences [17] . Multiple studies have identified a number of pathways contributing to such local inputs , such as histone modification [18][19][20] and chromatin binding proteins [21][22] . Additionally , global factors , such as the competition among origins for limited replication components , have been suggested to impact timing [23][24] . However , we have little insight into how the varied inputs affecting the efficiency of pre-RC activation measure time to precisely schedule replication of different sequences during S phase or how this schedule is modulated during development . In light of these issues , the embryo provides a unique context in which to study the control of S phase duration because development profoundly changes it . Historically , the study of cell cycle timing has focused on the G1/S and G2/M transitions , but the early embryonic cell cycles lack gap phases , and it is the duration of S phase that changes [25][26] . In the D . melanogaster embryo , these specialized cell cycles are maternally programmed , synchronous , and occur in the absence of cell membranes . During the first 9 nuclear cycles , S phase completes in as little as 3 . 4 min [8] , and nuclei remain deep within the embryo . Beginning in cycle 10 , the nuclei reach the surface of the embryo , forming the blastoderm . During cycles 11–13 , the length of S phase gradually increases to 13 min . At the next cell cycle , the 14th , the embryo begins a conserved developmental period known as the mid-blastula transition ( MBT ) during which numerous changes occur: Interphase , which extends dramatically , has an S phase 14 that lasts 70 min , and it is followed by the first G2 [27][28] . After G2 of cycle 14 , cells enter mitosis 14 in a patterned program controlled by zygotic transcription [29] . We focused on the changes that occur to the DNA replication program at the MBT and on how these changes are introduced . As we show here , the first introduction of late replication results from the emergence of a single regulatory input with timing function . Prior work has shown that the prolongation of S phase at the MBT is caused by introduction of delays in the replication of satellite sequences [26] . During the preblastoderm cycles , all regions of the genome begin and end replication together , resulting in a short S phase . Even the 30% of the genome composed of blocks of repetitive DNA known as the satellite sequences , which are considered to be constitutively heterochromatic , lacks the marks of heterochromatin and replicates early . During S phases 11–13 , the satellite sequences experience progressively modest delays in replication timing . Then , these satellites experience major delays in S phase 14 in which a succession of different satellites begin and complete replication on a protracted schedule . Thus , onset of late replication causes the pronounced increase in the S phase duration , but the nature of the timer coordinating this schedule was unknown . Following their late replication in cycle 14 , the satellite sequences become heterochromatic , and late replication will be a characteristic feature of heterochromatic satellites for the rest of development . Uncovering how late replication develops will improve our understanding of what has been a widespread but mysterious feature of DNA replication . We know that the onset of late replication in the embryo follows a time course that is unrelated to appearance of other features of heterochromatin such as compaction , which is already evident in earlier cell cycles , or heterochromatin protein 1 ( HP1 ) recruitment , which occurs after replication in cycle 14 , or histone H3 methylated on lysine 9 ( H3K9me ) , which accumulates continuously and slowly over the course of interphase 14 [26][30] . Previous work demonstrated that activity of the cyclin-dependent kinase 1 ( Cdk1 ) kinase is a key determinant of the duration of S phase in the early embryo [31] . Persistent S phase Cdk1 activity during the shorter pre-MBT cycles drives heterochromatin to replicate early , and it is the programmed down-regulation of Cdk1 occurring at the MBT that allows the onset of late replication . However , it is unclear how the embryo interprets the activity of Cdk1 to produce this dramatic prolongation of S phase . We have discovered that Rap1 interacting factor 1 ( Rif1 ) —a conserved protein that interacts with protein phosphatase 1 ( PP1 ) and impacts telomere biology , DNA damage responses , and replication timing [32][33][34][35]—is an important regulator of early developmental changes in cell cycle timing . Amid reports of diverse roles for Rif1 , several studies emphasize the action of Rif1 to inhibit replication and show that Rif1 and DDK oppose each other , inhibiting or activating the pre-RC , respectively [36][37][38][39] . The literature has emphasized the possibility that Rif1-recruited PP1 could counter the action of DDK by dephosphorylating this kinase’s substrate , the MCM helicase complex , but genetic epistasis and molecular findings suggest that DDK also targets and inactivates Rif1 , suggesting that a more complex interplay of the activating kinases and the Rif1 inhibitor contributes to pre-RC activation [32] . While it is appreciated that Rif1 and its associated PP1 can inhibit the firing of origins , the eventual firing of these inhibited origins presumably requires an input to negate or override the repressive action of Rif1 . The nature of this signal , which would underlie the temporal programming for the late-replicating origins , is unknown . Additionally , how Rif1 contributes to developmental changes in replication timing is unknown . Our results describe how Rif1 connects the activity of Cdk1 to the onset of late replication in the embryo , thereby composing an active program that extends S phase at the Drosophila MBT . We provide new insights into Rif1 behavior that suggest an intimate role in a timing mechanism specifying the precise time at which different sequences replicate during S phase . In addition , our work allows us to provide a more complete description of the maturation of the heterochromatin during development .
Because of the stereotyped nature of the embryonic cell cycles ( summarized in Fig 1A ) , live imaging of fluorescently tagged proteins can be especially informative . We used clustered regularly interspaced short palindromic repeat ( CRISPR ) genome editing to tag the endogenous Rif1 protein with enhanced green fluorescent protein ( EGFP ) at its C-terminus ( S1 Fig ) . Rif1 is maternally provided ( S1 Fig ) and is widely distributed during the first 6 h of embryogenesis and thereafter shows increasingly tissue-limited expression [40] . Given ubiquitous presence of Rif1 protein in the early embryo , regulation of its activity ought to underlie any developmental or cell cycle modulations of Rif1 function at this stage . If Rif1 acts to delay the replication of heterochromatin , then we would expect the protein to be recruited to satellite sequences when the replication of these sequences is delayed in cycle 14 . The satellite sequences form compacted regions of chromatin that can be visualized as discrete bright foci of DAPI-stained DNA ( Fig 1B ) . These compacted foci of chromatin first acquire heterochromatic marks during cycle 14 , but given the absence of G1 in this cycle , a program for their delayed initiation must already be in place at the beginning of interphase 14 [26][30] . In S phase 14 , Rif1 was bound to many foci of compacted chromatin , while in the following G2 phase , the heterochromatin lacked Rif1 staining ( Fig 1 ) . Live imaging of Rif1-EGFP embryos ( S1 Movie ) during early embryogenesis revealed the dynamics of this change . Rif1-EGFP disappeared from individual foci as S phase progressed , and only a dim nuclear background was present by G2 of cycle 14 ( Cycle 14 , Fig 1D ) . Tracking individual foci in high-frame-rate movies showed that different Rif1 foci disappeared at different times ( Fig 1E ) . Often , only a single focus remained near the end of S phase before disappearing as cells entered G2 . This ordered loss of different Rif1 foci was reminiscent of the protracted schedule of late replication occurring in this cycle . To test the correspondence of Rif1 foci and satellite sequences , we marked specific satellite sequences by in situ hybridization or our recently developed transcription activator-like effector ( TALE ) -lights technique [41] . In embryos fixed during early S phase 14 , the single Y-chromosome-linked focus of AATAC satellite detected by DNA–fluorescence in situ hybridization ( FISH ) was costained by Rif1 ( right panels Fig 1C ) . In live embryos , a fluorescently tagged TALE-light protein engineered to bind the late replicating satellite-repeat 1 . 686 showed that Rif1 also binds the 4 foci of this sequence ( left panels in Fig 1C ) . During cycles 11–13 , S phase gradually and progressively gets longer due to incremental delays to satellite replication . In parallel with these changes , Rif1 showed weak and transient localization to foci in cycle 11 and progressively more intense and longer-lived foci in subsequent cycles ( S1 Movie , Fig 1D ) . Disappearance of Rif1 foci within each S phase was not instantaneous: The signal decayed from the outside-in over a few frames of our records; for instance , during S phase 13 , high-frame imaging showed that a focus of Rif1 disappeared over the course of approximately 2 min ( S2 Movie , Fig 1F ) . These observations show that Rif1 binds to satellite sequences as they become late replicating during embryogenesis and that Rif1 dissociates from satellite sequences as replication progresses . The correlation between the dissociation of the Rif1 localized to satellite foci and the onset of late replication motivated a closer examination of Rif1 dynamics during S phase . We have previously validated and utilized fluorescently tagged versions of the replication protein proliferating cell nuclear antigen ( PCNA ) as real-time probes for the progress of S phase [25] . PCNA travels with the replicating DNA polymerase , and its recruitment to different regions of the genome marks their replication . Using a transgenic line expressing an mCherry-labeled version of PCNA from its endogenous promoter ( S2 Fig ) , we were able to compare active DNA replication with the localization of Rif1 . During the first 10 min of S phase , the PCNA signal was intense and distributed throughout most of the nucleus . Following early replication , the generalized signal fades progressively , and the PCNA signal is predominantly limited to bright apical foci , which mark the late-replicating satellite sequences . Each late-replicating focus appears , persists , and declines in a stereotyped schedule , with the number of active foci gradually declining during more than an hour of interphase of cycle 14 ( Fig 2A , S3 Movie ) . Throughout this program , Rif1 did not overlap with the PCNA signal , indicating that once a region had initiated DNA replication , the Rif1 signal had already declined to background levels . As S phase progressed , different Rif1 foci disappeared at different times and were replaced within 1 min by PCNA ( S3 Movie ) . The last sequence to recruit PCNA was marked by Rif1 throughout S phase 14 until just before it recruited PCNA ( Fig 2A ) . Similar analyses in cycles 12 and 13 similarly revealed separation of Rif1 staining and replication . The observed timing suggested that replication of Rif1 staining regions awaits the dissociation of Rif1 . Additionally , a prior study of fixed mammalian cells documented that Rif1 does not colocalize with DNA stained by incorporation of labeled nucleotides , indicating that this dynamic nature of Rif1 localization is conserved [33] . The S phase of cell cycle 15 provides an alternative context to observe the relationship between Rif1 and replication . By cycle 15 , the embryo has completed the MBT , the cell cycle has lost synchrony , and morphogenetic movements have begun . The timing of mitosis 14 and entry into cycle 15 differs with position in the embryo but follows a stereotyped schedule that is zygotically controlled . Cycle 15 still lacks a G1 , so nuclei enter S phase immediately following mitosis 14 , but these cycle 15 nuclei exhibit more mature features . The satellite sequences enter cycle 15 after introduction of heterochromatic marks such as H3K9me and localized HP1 during cycle 14 [26] . Furthermore , the distinct foci of satellite sequences seen at the beginning of cycle 14 are merged in an easily identifiable chromocenter in the apical part of the nucleus . Despite these differences , a connection between Rif1 and the replication program was still observed . At late anaphase of mitosis 14 and the onset of cycle 15 , Rif1 was recruited rapidly to separating chromosomes and appeared especially bright over the leading edge of the advancing chromosomes , the site of pericentric satellite sequences that constitute the bulk of the heterochromatin . As the telophase nucleus formed , bright Rif1 signal was seen over the compacted chromatin of the chromocenter before the recruitment of PCNA to the nucleus ( S4 Movie , S2 Fig ) . At the onset of S phase 15 , PCNA was recruited only to euchromatic regions , and it did not overlap Rif1 ( Fig 2B ) . As S phase 15 progressed , PCNA was recruited to the edge of the compacted heterochromatin , where we have previously observed decompaction of HP1-staining chromatin [26] . Although aggregated in a single mass in the nucleus ( the chromocenter ) , individual satellite sequences remain as distinct subdomains and retain an individual replication schedule [26] . In agreement with this , Rif1 staining was progressively limited to more restricted regions within the chromocenter , with latest Rif1 foci dispersing toward the end of S phase ( Fig 2B , S5 Movie ) . Real-time records again documented a close connection between the loss of Rif1 from chromatin and the recruitment of PCNA to the underlying region . Having followed the progress of S phase globally , we next wanted to examine the replication of a specific heterochromatic sequence , the 1 . 686 satellite repeat . The simple repeated sequence 1 . 686 is found at 4 loci , one to the left and one to right of the centromeres of both chromosomes 2 and 3 . All these foci replicate together and show characteristic delays in their time in cycles 13 and 14 . TALE-light probes can be injected into embryos and used to track the repetitive DNA in real time [30] [41] . Purified mCherry-labeled TALE-light protein recognizing the 1 . 686 repeat was injected into syncytial embryos and filmed . As reported previously , the TALE-light was gradually recruited to 1 . 686 during interphase , with the signal appearing as compact foci . During replication , the TALE-light signal became noticeably fuzzier , presumably due to the decompaction of the heterochromatic DNA during its active replication [41] . Upon completion of replication , the TALE-light signal was again compact and obviously brighter . We use this reproducible behavior to indirectly follow the replication of 1 . 686 . During cycle 13 , we observed that Rif1 was recruited to 1 . 686 at the beginning of S phase and disappeared immediately before the decompaction and replication of the repeat . We observed intermediate intensities of Rif1 signal on 1 . 686 in the minute preceding its decompaction . Rif1 dissociation was relatively rapid but progressive , with the Rif1 signal decaying over the minute preceding 1 . 686 decompaction . After completing replication , 1 . 686 lacked Rif1 for the remainder of the cycle ( Fig 2C , S6 Movie ) . Thus , Rif1 dissociates from this specific satellite immediately prior to the onset of its replication . We also examined fixed embryos using FISH probes to localize another heterochromatic repeat , AATAC , and showed that Rif1 was bound to this repeat AATAC during early S phase 14 , but no such signal was observed in embryos aged to later in S phase after the replication of this sequence ( Fig 2D ) . These observations show that Rif1 dissociates from specific satellite sequences upon their replication . Our observations reveal that the dynamics of Rif1 interaction with chromatin parallel changes in replication timing . Rif1 association to satellite sequences began when these sequences first showed a slight delay in replication . While association was transient in the earlier cycles , Rif1 associated more persistently with satellites during the much-extended S phase of cycle 14 . Most dramatically , Rif1 dissociated from individual satellite sequences at distinct times that align with the onset of PCNA recruitment to those sequences . The disappearance of the last foci of Rif1 staining marked the onset of replication of the latest replicating sequence and anticipates the end of S phase . These parallels suggest that binding of Rif1 to sequences might defer their replication until its dissociation . If so , analysis of this interaction may give us insights into the regulation of late replication and S phase prolongation . Late-replicating sequences have to be specified before the onset of replication if they are to avoid early firing . In yeast and mammalian cells in culture , this is thought to occur well before replication at a critical time during G1 , known as the timing decision point [42][43] . However , in the G1-less embryonic cell cycles , the preparation for S phase is compressed and overlaps mitosis . Since cyclin:Cdk1 activity inhibits preparation of origins for replication , all of the preparations for replication happen between the down-regulation of cyclin:Cdk1 at the metaphase–anaphase transition and the onset of S phase upon entry into the next interphase . Real-time observation of green fluorescent protein ( GFP ) -tagged origin recognition complex 2 ( Orc2 ) protein revealed that Origin Recognition Complex ( ORC ) binds to the separating anaphase chromosomes prior to the midpoint of their separation [44] . The MCM helicase is loaded shortly later in anaphase [45] . Replication begins at mitotic exit without obvious delay . This suggests that at the time of the transition from mitosis to interphase , there is already some type of feature that distinguishes the satellites so that they do not begin replication immediately [26] . If Rif1 is to delay the replication time of specific sequences , we expect its recruitment to chromatin to occur during this period . Indeed , we observed binding of Rif1 to separating anaphase chromosomes before the recruitment of PCNA to the nucleus , which marks the start of interphase ( S2 Fig ) . However , as described below in cycles prior to cycle 15 , the specificity of Rif1 binding to satellite sequences emerges in concert with progression into interphase . We examined the initial binding of Rif1 by filming mitosis 13 and early interphase 14 . We observed an abrupt onset of faint and generalized binding of Rif1 to the chromosomes during late anaphase/telophase as previously observed in fixed samples ( Fig 3A ) [34][40][46] . Rif1 accumulation continued as the telophase nucleus formed . Although little was resolved in the compact and brightly staining telophase nucleus , by 1 min into S phase , brighter foci of staining became clear , and much of the nuclear signal quickly declined except in foci clustered at the apex of the nucleus where the foci of pericentric satellite sequences lie ( S2 Movie , Fig 3A ) . Thus , while a low level of generalized binding is clear in mitosis , specificity in the binding became evident only in the beginning of interphase , suggesting that there are two phases of binding . In contrast , in the transition to cycle 15 , the initial binding of Rif1 in anaphase , while still weak , was not uniform . During late anaphase 14 , Rif1 was clearly enriched at the leading region of the chromosome mass , where the pericentric heterochromatin resides ( Fig 3B , S4 Movie ) . This localization to the heterochromatic region was visualized without interruption as Rif1 continued to accumulate with entry into interphase 15 , which is accompanied by immediate onset of replication as this cycle still lacks a G1 phase . Thus , the character of the initial anaphase binding of Rif1 changes between anaphase 13 and anaphase 14 . Satellite sequences acquire some of the markings of heterochromatin , such as methylation and HP1 localization , during interphase of cycle 14 . These heterochromatic marks might then guide the initial interaction of Rif1 at anaphase 14 , but they would not be available to do so in anaphase 13 . Because recruitment of Rif1 began late in anaphase , just after the time when Orc2 was recruited to chromosomes , we wondered if pre-RC formation might be involved in Rif1 binding . Indeed , prior work in a Xenopus extract system suggests that this is true [47] . To test this , we examined Rif1 recruitment after the injection of embryos with purified geminin protein during mitosis 13 . Geminin blocks the formation of the pre-RC by inhibiting Cdt1 , a key helicase-loading factor , and prevents subsequent replication . Injection of geminin did not block the initial generalized binding of Rif1 to the late anaphase chromosomes or its nuclear accumulation in telophase nuclei but did block the emergence of localized Rif1 foci . Following geminin treatment , Rif1 was diffusely localized throughout the nucleus during interphase 14 . ( Fig 3C ) . We conclude that geminin blocks the localization of Rif1 to late-replicating sequences but emphasize that the results do not necessarily imply a direct involvement of pre-RC formation in this localization . Because geminin did not affect initial binding of Rif1 , it might be the downstream consequences of a failure to assemble pre-RCs that produces the observed result . Beginning in cycle 11 , the gradual lengthening of interphase depends in part on the conserved DNA replication checkpoint [26][48][49] . During cycle 13 , the checkpoint is required to delay activation of Cdk1 during S phase and prevent premature entry into mitosis . Embryos mutant for the checkpoint kinase ataxia telangiectasia and Rad3-related protein ( ATR; mei41 ) fail to delay mitosis 13 sufficiently and so enter a catastrophic mitosis before the completion of replication , resulting in massive chromosome bridging . Because Rif1 foci first became evident during these gradually slowing cycles , we wondered if the replication checkpoint might impact Rif1 recruitment . However , in mei41 embryos , both the initial binding of Rif1 during anaphase of M12 and its subsequent recruitment to nuclear foci in interphase 13 were indistinguishable from control embryos ( Fig 3D ) . We did observe that the disappearance of Rif1 foci was accelerated in mei41 embryos , and Rif1 was lost from chromatin before entry into a catastrophic mitosis 13 . We conclude that the recruitment of Rif1 to late-replicating sequences is independent of the replication checkpoint but that timing of Rif1 dispersal is accelerated in its absence . Prior work demonstrated that down-regulation of Cdk1 activity at the MBT plays a key role in extending S phase [30][31][50] . Cdk1 activity during the earlier rapid cell cycles was shown to be required for satellite sequences to replicate early and to sustain short S phases . The gradual decline in mitotic activators during cycles 11–13 contributes to the progressive lengthening of S phase . Finally at the MBT , the abrupt drop in Cdk1 activity is required for late replication and the resulting prolongation of S phase . These changes to Cdk1 parallel the changes we observed for Rif1 localization , so we investigated the connection between them . Experimental reduction of Cdk1 activity by injection of dsRNA to induce RNA interference ( RNAi ) against the 3 mitotic cyclins ( A , B , and B3 ) during cycle 10 arrests embryos in interphase 13 and extends the length of S phase 13 from 13 min to an average of 19 min [31] . Cyclin knockdown also affected the dynamics of Rif1 chromatin association . In arrested embryos , foci of Rif1 binding persisted for an average of 16 min , compared to 8 min in control-injected embryos ( Fig 4A and 4C ) . This delay in the loss of Rif1 foci paralleled , and slightly preceded , the delayed appearance of late-replicating PCNA signal . In contrast , as previously reported , increasing Cdk1 activity during cycle 14 by injecting mRNA for the mitotic activator cell division cycle 25 ( Cdc25 ) shortened S phase from over 1 h to an average of 22 min and can result in an early mitosis 14 , with no bridging , indicating that DNA replication was complete . Experimental Cdk1 activation also changed the Rif1 program . In Cdc25-injected embryos , foci of Rif1 association were evident for only an average of 18 min compared to 66 min in control-injected embryos ( Fig 4B and 4C ) . Real-time records documented that ectopic Cdk1 activity removed Rif1 from chromatin , allowing the underlying satellite DNA to initiate replication without the characteristic delays normally observed in S phase 14 ( S7 Movie , Fig 4B ) . We conclude that Cdk1 activity can accelerate both the release of Rif1 from chromatin and the late-replication program . Both experiments demonstrate that the timing of Rif1 dissociation from chromatin and the subsequent initiation of late replication are sensitive to the activity of Cdk1 during S phase . These results show that Cdk1 activity in early cycles normally promotes Rif1 dissociation from chromatin in pre-MBT embryos and that an artificial increase in Cdk1 in cycle 14 can do the same . The parallel effects of the experimental manipulations on Rif1 association and the progress of S phase further support suggestions that Rif1 association suppresses replication and that activation of origins in satellite sequences occurs in conjunction with Rif1 dissociation . The influence of Cdk1 on Rif1 suggests that the developmental program of Cdk1 down-regulation guides the observed changes in Rif1 dynamics and thereby S phase duration . In light of these findings , we can interpret the accelerated loss of Rif1 in mei41 embryos ( Fig 3D ) as a consequence of the faster activation of S phase Cdk1 in the absence of the replication checkpoint [51] . These observations suggest that activity of the Cdk1 kinase directly or indirectly regulates Rif1 interaction with chromatin . Work from both Saccharomyces cerevisiae and Schizosaccharomyces pombe indicates that the kinases CDK and DDK act on conserved phosphorylation sites to inhibit Rif1 and limit its ability to inhibit replication [37][38] . In these yeasts , phosphorylation of Rif1 is thought to block Rif1’s ability to recruit PP1 , hence preventing Rif1 inhibition of replication initiation . Like yeast Rif1 , the dipteran Rif1 homologs have a cluster of conserved CDK and DDK sites near the phosphatase interaction motif in the C-terminal part of the protein ( Fig 5A , S3 Fig ) . This region of Rif1 is also proposed to contain a DNA-binding domain [52][53] . These potential phosphorylation sites cluster in a region of the protein predicted to be of high intrinsic disorder [54] ( S3 Fig ) , a feature associated with phosphorylation events that regulate interactions [55] . Of particular interest are a number of conserved SS/TP sequence motifs . DDK is known to phosphorylate the first serine in SSP motifs only after a priming phosphorylation by CDK on the second serine . Full phosphorylation of such sites is likely to require the dual input of both CDK and DDK . We further examined the role of the more C-terminal potential phosphorylation sites in regulating the late replication activity of Rif1 . To determine if Rif1 is phosphorylated in vivo , we examined Rif1 from 1-h-old embryos , a time when the abundant maternally-provided Rif1 protein would be held inactive by Cdk1 . Protein extracts from pooled staged embryos were run on a phos-tag SDS-PAGE gel before or after treatment with lambda phosphatase and subjected to western blotting . All detectable Rif1 exhibited a phosphatase-reversed shift , indicating that most Rif1 is phosphorylated in the pre-MBT embryo ( Fig 5B ) . Comparison of protein samples from pre-MBT and MBT-age embryos revealed that the extent of the shift is somewhat reduced at the MBT stage , consistent with developmentally-regulated reduction in the degree of phosphorylation ( Fig 5B ) . Two studies in yeast suggested that phosphorylation of Rif1 inhibits its function by blocking interaction with PP1a [37][38] , although direct evidence for this idea is lacking , and the prior literature did not define a mechanism by which the repressive action of Rif1 is overcome . Drosophila Rif1 has previously been shown to bind to PP1a [40] , so we looked for a change to this interaction in conjunction with the developmental down-regulation of Cdk1 . As shown above , high Cdk1 activity in early pre-MBT embryos suppresses Rif1 association with chromatin and promotes a short S phase , whereas down-regulation of Cdk1 at the MBT is required for Rif1-mediated extension of S phase . Rif1 was immunoprecipitated out of lysates derived from 20-min collections of embryos aged for either 30 min ( pre-MBT ) or for 2 h and 15 min ( post-MBT ) . While we expected minimal association of PP1 to Rif1 in pre-MBT extract when Rif1 is robustly phosphorylated , western blotting showed a robust PP1 signal ( Fig 5E ) . Additionally , Rif1 immunoprecipitated from the post-MBT extract was accompanied by a similar amount of PP1 . Hence , the interaction between Rif1 and PP1a , at least at bulk levels , is not regulated in a way that explains the onset of late replication , and Rif1 appears to interact effectively with PP1 at early stages when it is phosphorylated and held inactive by Cdk1 kinase . To further explore possible regulation of Rif1 by phosphorylation , we mutated candidate phospho-sites . We selected 15 S/T residues within CDK or DDK consensus motifs located in the C-terminus of Rif1 and mutated them to alanine ( Fig 5A ) to prevent their phosphorylation . We reasoned that this phospho-site mutant Rif1 , hereafter referred to as Rif1 . 15a , might not be inhibited by S phase kinases and so act as a dominant gain-of-function allele . Ectopic expression of Rif1 . 15a during the blastoderm divisions by injection of in vitro-transcribed mRNA causes extensive anaphase bridging as typically seen when DNA replication is incomplete ( Fig 5C ) . We never observed this effect after injection of mRNA encoding wild-type Rif1 , arguing that this is not a simple overproduction phenotype . To test if the gain-of-function Rif1 mutant still operated through its associated phosphatase , we mutated the conserved PP1 interaction motif RVSF in the Rif1 . 15a construct . Ectopic expression of the resulting Rif1 . 15a-RaSa mutant did not disrupt cell cycle progression ( Fig 5C ) . In addition , we generated transgenes expressing either wild-type Rif1 or Rif1 . 15a under upstream activating sequence ( UAS ) control . Overexpression of Rif1 in the eye imaginal disc ( and more weakly throughout much of the head capsule ) using the eyeless-Gal4 driver did not disturb eye formation , whereas expression of Rif1 . 15a caused complete lethality with pupae developing into headless nearly adult flies ( Fig 5D ) . The severity of this phenotype suggests that expression of Rif1 . 15a disrupted the early proliferative period of the eye-antennal disc . These assays suggest that Rif1 . 15a has a damaging gain-of-function action , as might be expected if it were immune to regulation of its ability to inhibit DNA replication . Because our data indicated that the chromatin binding of Rif1 was regulated during S phase by Cdk1 activity , we examined the influence of mutation of the phospho-sites on Rif1 localization . Using mRNA injection , we expressed a GFP-tagged version of Rif1 . 15a and followed its localization and the consequence of its expression in live records . Embryos were injected with Rif1 . 15a-GFP mRNA during cycle 12 . The timing of this injection allowed sufficient fluorescent protein to accumulate so that its behavior could be followed throughout cell cycle 14 , while still minimizing the damage due to induced catastrophic mitoses in the earlier cycles . Rif1 . 15a was recruited to specific chromatin foci normally at the start of S phase , indicating that the mutated residues are not required for the binding specificity of Rif1 . Imaging Rif1 . 15a-GFP throughout cycle 14 yielded several interesting results that were never observed when imaging endogenous Rif1-GFP or ectopic wild-type Rif1-GFP expressed by mRNA injection . Unlike the dynamics of the wild-type protein , Rif1 . 15a continued to accumulate on heterochromatin throughout most of S phase 14 . It then showed a slow decline but remained bound in the following G2 and into mitosis 14 ( Fig 5F ) . The Rif1 . 15a foci on newly condensed mitotic chromosomes were localized to pericentric regions , where the satellites reside . On progression into anaphase , bridges were seen connecting the separating chromosomes , and Rif1 . 15a-GFP specifically labeled these chromatin bridges ( Fig 5F inset ) . As bridged nuclei exited mitosis , an unbound pool of Rif1 . 15a was recruited to the chromocenter , presumably after new pre-RCs were loaded . This abrupt recruitment of Rif1 . 15a shows that mutation of the selected sites did not fully eliminate cell cycle–regulated behavior of Rif1 . Nonetheless , the dramatic consequence of the phosopho-site mutations shows that these sites contribute importantly to Rif1 dissociation from chromatin and that in the absence of dissociation Rif1 . 15a is capable of blocking replication to give anaphase bridging when chromosomes are driven into mitosis . In contrast to previous suggested mechanisms , we conclude that the repressive action of Rif1 on DNA replication is regulated by kinase-driven dissociation from chromatin . A recent study reported that Rif1 was an essential gene in Drosophila based on partial lethality of a ubiquitously expressed RNAi against Rif1 [40] . We created a precise deletion of the Rif1 open reading frame ( ORF ) using CRISPR-associated protein 9 ( CRISPR-Cas9 ) ( S4 Fig ) . While the mutation does cause reduction in survival , we find that the homozygous rif1 null gives viable , reproductively competent flies that can be propagated as a stock . Zygotic loss-of-function rif1 mutants develop to adulthood with a reduced survival and a male-to-female ratio of 0 . 4 ( n = 189 flies ) . Additionally , embryos laid by rif1 mutant mothers ( hereafter called rif1 embryos ) have a reduced hatch rate ( 55% of control , n = 500 embryos ) . We conclude that Rif1 is dispensable in Drosophila , at least in our genetic background , and we suspect that the previously reported lethality and sterility included enhancement of the loss-of-function phenotype by off-target effects of the RNAi . Though surprised by the viability of the Rif1 deletion , it provided an opportunity to examine the phenotype of complete absence of function . Next , we utilized the rif1-null mutation to assess the role of Rif1 in the onset of late replication during cycle 14 . As discussed previously , real-time records of fluorescent PCNA allow us to follow the progress of S phase and estimate its overall length . In a wild-type S phase 14 , PCNA is widely distributed throughout most of the nucleus during the first 10 min but resolves into bright puncta that are obvious for over an hour into interphase , after which only a dim nuclear background is visible . During the final 30 min of S phase , a small number of bright PCNA foci appear and then disappear sequentially as a result of a protracted schedule of late replication ( Fig 6A ) . By using the disappearance of the last PCNA focus as an indication of the completion of replication , we determined that the average S phase 14 lasts for 73 min ( Fig 6A ) . In contrast , S phase 14 in rif1 embryos from rif1 mothers was significantly shorter , lasting an average of 27 min . Additionally , there were clear differences in the appearance of the PCNA signal as S phase progressed . The initial period of widespread early replication resolved into PCNA foci , but appearance of these foci was more simultaneous than sequential , and there was no protracted sequence of late foci ( Fig 6A ) . Thus , this S phase 14 resembled the earlier S phases in showing a marginal extension with slightly delayed replication of some foci . However , the normally dramatic extension of S phase 14 is dependent on rif1 . Failure to extend S phase 14 was observed in all embryos derived from homozygous mothers even though heterozygous fathers were included in the cross . We conclude that maternal Rif1 is required for the normal extension of S phase 14 . Because we had observed that the satellite 1 . 686 recruited Rif1 during S14 , we wondered if its replication time would be altered in rif1 embryos . To measure the replication time of this repeat , we injected the GFP-1 . 686 TALE probe into wild-type and rif1 embryos expressing mcherry-PCNA and recorded S phase 14 . We used the transient recruitment of mcherry-PCNA and the obvious decompaction of the marked 1 . 686 sequences as indictors of active replication of 1 . 686 . In control embryos , the 1 . 686 repeat began replication 18 min into S14 and completed by 30 min ( Fig 6B ) . In contrast , in rif1 embryos , 1 . 686 began replication by 4 min into S14 and completed by 13 min ( Fig 6B ) . We conclude that the 1 . 686 satellite sequence replicates with a minimal delay in S phase 14 in the absence of Rif1 and that the normally substantial delay requires Rif1 . During the MBT , the embryo degrades both the mRNA and protein of the mitotic activator Cdc25 . This allows the introduction of the first embryonic G2 after the completion of the prolonged S phase 14 . Mitosis 13 is then the last synchronous division during development , and mitosis 14 relies on the developmentally patterned zygotic expression of new Cdc25 . Perturbations that interfere with the down-regulation of Cdk1 can lead to an additional synchronous mitosis . Additionally , since down-regulation of Cdk1 occurs during S phase 14 , the embryo can also progress to an additional synchronous mitosis if S phase is eliminated or dramatically shortened , as seen following injection of geminin or alpha-amanitin , respectively [25][26] . We noticed that a small number of rif1 embryos ( 7% ) executed an early mitosis 14 at approximately 30 min into interphase . The observed mitoses were complete , with no bridged chromosomes , but there was substantial nuclear fall in ( Fig 6C , S8 Movie ) . We interpret the incomplete penetrance of the extra-division phenotype to be an indication that the duration of S phase in rif1-null embryos is close to a threshold so that , in most embryos , the cyclin:Cdk1 activity declines enough to introduce a G2 , but in some embryos , the residual maternal cyclin:Cdk1 function remains high enough to trigger mitosis upon the completion of the shorten S phase . The result shows that Rif1 is important for reliable coordination of the MBT . Previous work has shown that before the MBT , Cdk1 is required for driving a short S phase . Our finding that Cdk1 activity suppresses Rif1 function in cycle 14 ( Fig 4 ) suggests an explanation for the early role of Cdk1 in promoting short S phases; interphase activity of Cdk1 prevents Rif1 from prematurely introducing late replication . This model predicts that reducing Cdk1 activity would not be able to prolong a pre-MBT S phase in the absence of rif1 . To test this idea , we examined S phase 13 in wild-type or rif1 embryos after knockdown of mitotic cyclins , essential activators of Cdk1 , by RNAi . Wild-type control–injected embryos exhibit transient but obvious foci of PCNA staining during late S phase 13 and replicate their satellite sequences with a slight delay in this S phase . While rif1 embryos still exhibit PCNA foci , these foci are even shorter lived ( Fig 6D ) . Following injection of mitotic-cyclin RNAi , wild-type embryos increased the duration of S phase 13 from 14 min to 20 min . In contrast , rif1 embryos did not extend S phase after cyclin knock down ( Fig 6D ) . This demonstrates that the requirement for Cdk1 in the timely completion of S phase 13 can be bypassed by loss of rif1 . However , S phase 13 in the rif1 mutant embryos is still longer than very early embryonic S phases , which can be as short as 3 . 4 min . Thus , Cdk1 down-regulation of Rif1 contributes to S phase prolongation in cycle 13 , but there must be additional factors influencing the progressive prolongation of early cycles . The cell division cycle 7 ( Cdc7 ) -Dbf4 kinase complex ( or DDK ) is required for origin initiation in many systems . In S . cerevisiae , the essential function of DDK is thought to be the phosphorylation of the MCM helicase complex during pre-RC activation [16] . In both S . pombe and S . cerevisiae , the deletion of rif1 partially rescues S phase and viability in cdc7 mutants . Two functional interactions have been proposed to contribute to this finding . DDK appears to phosphorylate and inactivate Rif1 , thereby activating replication by a derepression input . Indeed , the presence of conserved DDK phosphorylation motifs in Rif1 suggests that DDK may synergize with CDK in the inactivation of Rif1 . This input would be dispensable in a rif1 mutant . Additionally , Rif1 is thought to inhibit replication by recruiting PP1 to the origin and dephosphorylating the MCM helicase , an action that opposes DDK . The loss of this opposing activity in a rif1 mutant might reduce but would eliminate the DDK activity required for MCM phosphorylation . We wanted to assess the possible parallels in Drosophila to clarify the involvement of Rif1 in replication control . Despite strong conservation , cdc7 has not been well studied in Drosophila . In Drosophila , cdc7 is an essential gene , and recent work has demonstrated that in complex with the dbf4 ortholog chiffon , Drosophila Cdc7 can phosphorylate Mcm2 in vitro and that cdc7 is required for endocycle S phases in follicle cells [56] . However , the function of DDK during mitotic S phase has not been described . To address this issue , we first tagged endogenous cdc7 with GFP using CRISPR-Cas9 . The resulting cdc7-GFP stock was healthy and fertile , indicating that the tag did not disrupt the essential function of Cdc7 . Time-lapse imaging of Cdc7-GFP embryos during syncytial development revealed that Cdc7 localization was cell-cycle regulated . Cdc7 was nuclear during interphase , dispersed into the cytosol during mitosis , and was rapidly recruited to late-anaphase chromosomes and concentrated in the telophase nucleus ( Fig 7A ) . Initial Cdc7 recruitment featured two transient bright foci followed by fine puncta , suggesting that it is recruited to chromatin at the time at which pre-RCs are undergoing activation during the syncytial cell cycles . Comparison of nuclear Cdc7 at equivalent times in subsequent cell cycles ( early S phase ) leading up to the MBT revealed a decline in the per-nucleus protein signal . Since nuclear size decreases with each division , if the amount of Cdc7-GFP in each nucleus were constant throughout these cycles , then the local intensity ( concentration ) of nuclear fluorescence would increase with each division . Instead , brightness decreases . This observation is consistent with subdivision of limited and/or declining pool of Cdc7 among an increasing number of nuclei . If level were limiting , this would result in diminishing availability of Cdc7 to fire origins in later cycles ( Fig 7B , S9 Movie ) . To determine if cdc7 is required for DNA replication during the early cell cycles , we depleted DDK from the embryo using maternal-tubulin Gal4 to drive RNAi against cdc7 during oogenesis . This setup did not interfere with egg production , although we found that expression of RNAi against cdc7 using the earlier acting maternal triple driver ( MTD ) -Gal4 did cause severe defects in egg morphology , indicating that cdc7 does play a role in the female germline . Embryos depleted of Cdc7 using maternal-tubulin Gal4 failed to hatch . Cytological examination of Cdc7-depleted embryos revealed penetrant defects during the early preblastoderm divisions . We observed multiple highly fragmented DNA masses that were unevenly distributed in the embryo interior , along with scattered abnormal mitotic structures ( Fig 7C ) . In all cases , nuclei failed to form a blastoderm , although in many cases , centrosomes appeared to continue to duplicate in the absence of any associated DNA ( Fig 7C ) . Such a dissociation of the embryonic nuclear and centrosome cycles has been described before in embryos injected with the DNA polymerase inhibitor aphidocolin during the preblastoderm cycles [57] . We conclude that Cdc7 is essential for effective nuclear cycles in the early embryo , consistent with a requirement in DNA replication . Next , we tested for a genetic interaction by depleting Cdc7 from rif1 mutant embryos using maternally expressed RNAi at 29 °C . In the absence of rif1 , 2% ( n = 242 ) of Cdc7-depleted embryos hatched , while Cdc7-depleted embryos from mothers heterozygous for rif1 ( rif1+ ) never hatched ( Fig 7E ) . Cytological examination demonstrated that removal of rif1 restored cell cycle progression to Cdc7-depleted embryos . rif1 mutants completed substantially more cell cycles than heterozygous control embryos , with most progressing to the blastoderm stage . Many of the blastoderm-rescued embryos showed abnormalities such as substantial nuclear fall in , disorganized nuclear spacing , and nonuniform nuclear density . Nonetheless , some of the observed embryos attempted cellularization and gastrulation ( Fig 7D ) , with the rare cases of hatching indicating occasional success . Reducing the temperature to 25 °C , thereby reducing the activity of the Gal4 protein driving the RNAi , improved the hatch rate of rif1 mutant embryos to 21% ( n = 281 ) while still causing 100% lethality in embryos from rif1 heterozygous mothers ( Fig 7E ) . We conclude that deletion of rif1 can restore embryonic cell cycle progression and early development to Cdc7-depleted embryos . However , this rescue is incomplete , likely because of altered regulation of the restored S phase in such doubly defective embryos . Early embryonic chromatin lacks specializations that come to distinguish different regions of the genome at later stages . Thus , the order of appearance of different specializations can give us insight into the hierarchy of regulation . Since late replication is considered a feature of heterochromatin , we expected its emergence to follow the embryonic appearance of the hallmarks of heterochromatin . Our recent work described the onset of localized H3K9me2/3 and HP1a [30] . While a very low level of modification and chromatin-bound HP1a was detected before the MBT , a period of abrupt accumulation of HP1a and more extensive H3K9me2/3 modification only occurred later , during S phase 14 . Here , we explore the relationship between this HP1a-centered program and the action of Rif1 in the control of late replication . During cycle 14 , Rif1-GFP and HP1a-red fluorescent protein ( RFP ) bound to localized foci in the same position but never at the same time . Rif1 foci disappear sequentially during cycle 14 , while HP1a is diffusely localized in early cycle 14 and is subsequently recruited to apical foci that multiply and intensify . Importantly , in live imaging of Rif1-GFP and HP1-RFP , we do not observe any overlap between the two signals in S14 ( Fig 8A ) . This finding is in accord with our finding that PCNA foci and Rif1 do not overlap ( Fig 2A ) and our previous demonstration that PCNA and HP1 foci do not overlap in cycle 14 [26] . Together with the timing of recruitment of these proteins to specific satellites , these observations show a sequence in which satellites lose associated Rif1 before they initiate replication , as marked by PCNA , and then complete replication before binding HP1 . We conclude that the introduction of late replication by Rif1 precedes the binding of HP1a in cycle 14 . In contrast , at the start of cycle 15 , both Rif1 and HP1a are rapidly recruited to the chromocenter , with Rif1 binding slightly earlier ( Figs 2B and 3B ) , and we have previously detected an influence of HP1 on replication timing in this cycle [30] . Given the earlier binding of Rif1 to satellite sequences in cycle 14 , Rif1 might direct subsequent heterochromatin formation . In fission yeast , Rif1 is required for the maintenance of silencing at some heterochromatic sites in the genome [58] . We examined whether Rif1 influences the emergence of HP1a-bound heterochromatin . GFP-HP1a was injected into either wild-type or rif1-null embryos and imaged during cycle 14 . We observed no difference between HP1a recruitment between the two genotypes , indicating that HP1a binds independently of Rif1 in the fly embryo ( Fig 8B ) . We had previously found that the recruitment of HP1a to the 359 bp–repeat satellite sequence during cycle 14 occurred only after its replication and was unimportant to the replication timing of this satellite in S phase 14 . However , this recruitment of HP1a was required for a shift of 359 replication to a much later time in S phase of cycle 15 [30] . Because our results demonstrate that the recruitment of HP1a to the heterochromatin during S phase 14 is independent of Rif1 , we wondered if the replication time of 359 was altered in rif1 embryos in cycle 15 . Live imaging of mCherry-PCNA-expressing rif1 embryos injected with GFP-359 TALE probes indicated that 359 still replicates late during S15 ( Fig 8C ) . We conclude that an HP1a-dependent program can delay replication of 359 sequences in cycle 15 without Rif1 input . It seems likely that this HP1a-dependent program operates to influence the replication of many heterochromatic sequences after cell cycle 14 .
Rif1 is widely conserved , and it has been implicated in several functions—notably , the control of telomere growth , replication timing , and DNA damage responses [35] . Despite this complexity , the association of Rif1 with replication timing in our studies appears to be uncomplicated by other actions of Rif1 . Two factors are likely to contribute to this . First , it is not clear that Rif1 serves the same spectrum of functions in all of the organisms in which it is found . For example , the distinctive telomeres of Drosophila do not appear to be regulated by Rif1 [52] . Additionally , previous tests of the function of Drosophila Rif1 in cultured cells and when ectopically expressed in other species suggested that Drosophila Rif1 protein might lack some functions attributed to the Rif1 of other species [52] . Second , even if the Drosophila Rif1 protein has additional functions at other stages in the life of the fly , the first time Rif1 functions in embryogenesis , its role appears to be to impose a replication timing program on S phase . Thus , this developmental context can isolate the replication timing role of Rif1 from other potential functions . In rif1 embryos , the early 3 . 4 min S phase is extended to 27 min by cycle 14 . Although much shorter than the 72-min S phase 14 in wild-type embryos , this rif1-independent extension of S phase resembled progression normally seen in the earlier blastoderm cycles ( 11–13 ) . A long-standing suggestion for embryonic slowing of the cell cycle is that the increasing number of nuclei titrate factors required for the speedy early S phases . Several factors might limit pre-RC activation . For example , Cdc7 has an input as demonstrated by its genetic interaction with Rif1 . Given that we saw diminishing concentration of nuclear Cdc7 as it was distributed to an increasing large number of nuclei over successive divisions , it is possible that developmental declines in this activating input could contribute to slowing of S phase , although at present , we do not have evidence demonstrating that this decline is of regulatory importance . Notably , the concentrations of several proteins that are recruited to the pre-RC during its maturation influence the speed and efficiency of pre-RC activation in yeast and in Xenopus [24][61] . Investigations of S phase extension occurring at the Xenopus MBT have emphasized multiple inputs influencing activation of the pre-RC [61][62] . A recent analysis suggested that Dbf4 related factor 1 ( Drf1 ) , the activating subunit for the Cdc7 kinase in the Xenopus embryo , is subject to active destruction at the MBT [63] . Failure to down-regulate DDK sensitized embryos to the further stress of overproduction of 3 replication factors that promote pre-RC maturation . Indeed , the authors suggest that titration of the maternal supply of these 3 replication proteins cooperate with active destruction of Drf1 to slow S phase at the MBT . Thus , evolution appears to have brought the same regulatory step under developmental control in very different organisms , but many factors complicate a comparison between systems , and here we emphasize that the detail of the dissection of the process in Drosophila has led us to a specific conclusion regarding Rif1 control of cell cycle slowing at the MBT in this organism . In contrast to the early progressive slowing of the cell cycle in Drosophila embryos , the abrupt extension of cell cycle 14 shows features of a distinct regulatory transition . It has switch-like features [64] . The triggering of this sudden extension of S phase is not simply due to a limitation of a factor , because unlike the earlier progressive extension of S phase , inhibition of transcription prevents the abrupt extension [26] . This shows that existing materials are adequate to support another relatively fast cycle and that the extension of cycle 14 involves an active process . And importantly , we have previously shown that the key event in triggering the extension is the down-regulation of cyclin:Cdk1 [31][50] . Here , we show that it also depends on the positive action of Rif1 as a repressor of replication and that this activity of Rif1 depends on the down-regulation of Cdk1 . In summary , we suggest that there are 2 distinct phases of S phase prolongation operating in the Drosophila embryo , one progressive and earlier and one abrupt and occurring at the onset of cycle 14 . The rif1 mutant is defective in the abrupt event that marks the MBT . We found it surprising that rif1 mutants have a highly penetrant phenotype with a specific failure to prolong S phase 14 yet produce viable progeny . This means that the prolongation of S phase 14 is not essential and that subsequent contributions of rif1 to development and survival are also dispensable . We would like to put this in context . The mutation of rif1 was not without major consequences . Both hatching of maternally deficient embryos and survival of zygotically deficient flies were compromised . So rif1 appears to be important , but a detailed characterization will be required to understand its contributions to survival . Nonetheless , it is clear that mutant embryos with a 27 min S phase 14 instead of the normal S phase duration of more than an hour can hatch . rif1 mutant embryos still undergo an MBT , and the majority of the embryos slow their cell cycle because they arrest in a G2 after their abnormally fast S phase 14 . A minority of the embryos undergoes a complete or partial extra syncytial cycle , suggesting that S phase timing contributes to regulation that normally introduces a G2 into the cell cycle at the MBT with great reliability . The late-replication program in cell cycle 14 precedes obvious appearance of heterochromatic marks on satellite sequences [30] . These marks do appear later in cell cycle 14 , and their appearance was not compromised in the absence of Rif1 . Thus , neither the selective localization of Rif1 to satellite sequences nor the specific time of replication of the satellites in cycle 14 is required to trigger or guide the appearance of the heterochromatic marks . Importantly , we showed previously that recruitment of HP1a and associated acquisition of other heterochromatin marks delay replication of the X-chromosomal 359-satellite repeat in cycle 15 [30] . Here we show that in the absence of Rif1 , the 359 repeat still exhibits late replication in cycle 15 , suggesting that heterochromatin can act by a Rif1-independent pathway to cause replication delay . While rif1 mutant embryos may show subtle alterations in the program of late replication in later cycles , presently the unique dependency of replication timing on Rif1 function appears limited to a narrow window of developmental time . Thus , survival of rif1 mutants does not assess the importance of late replication per se , only the impact of the delay in cycle 14 . Embryonic development presents early cell cycles with an unusual challenge—regulating cell division in the absence of transcription . Perhaps because of this early constraint , the biology of early embryos is streamlined and lacks many regulatory processes that appear later in development . When development introduces complications , it does so incrementally , highlighting individual regulatory circuits . By focusing on early development , we have been able to isolate and study the contributions of Rif1 to late replication and to S phase length . Our work uncovers a special developmental function for Rif1 in controlling the timely prolongation of S phase at the MBT and provides new insight into the control of late replication .
All D . melanogaster stocks were cultured on standard cornmeal-yeast medium . The following fly strains were used in this study: w1118 Canton-S ( wild type ) , His2Av-mRFP ( Bloomington stock number 23650 or 23651 ) , mRFP-HP1a ( 30562 ) , eyeless-gal4 ( 5535 ) , maternal tubulin-gal4 ( 7063 ) , UAS-shRNAcdc7 ( TRiP GL00585 ) , mei41D3 ( gift from Tin Tin Su , University of Colorado Boulder ) , mCherry-PCNA ( this study ) , rif1-EGFP ( this study ) , cdc7-EGFP ( this study ) , rif1- ( this study ) , UASp>Rif1-3xFlag ( this study ) , UASp>Rif1-15a-3xFlag ( this study ) . All transgenesis injections were performed by Rainbow Transgenic Flies , Camarillo , CA . The stocks rif1-EGFP and cdc7-EGFP were generated using CRISPR-Cas9 editing to modify the endogenous rif1 and cdc7 genes ( diagrammed in S1 Fig ) as described in [65] . Briefly , a single CRISPR target site was selected as close to the stop codon as possible . To direct homologous repair , approximately 1 . 5 kb of DNA on either side of the cut site was amplified from gDNA isolated from the vasa-Cas9 stock ( 51324 ) . Both homology arms , a 6xGlyGlySer-EGFP tag , and the endogenous 3’ UTR were cloned into the pHD-DsRed vector using Gibson Assembly . To generate gRNA plasmids , annealed DNA oligos were cloned into the pU6-BbsI-chiRNA vector . The donor plasmid and the gRNA plasmid were coinjected into vasa-cas9 embryos by Rainbow Transgenic Flies . After screening for DsRed+ progeny , successful modification was confirmed by PCR genotyping and anti-GFP immunoblotting . A single male containing a successful modification was backcrossed to our lab’s w1118 Canton-S stock for 5 generations to establish a stock . CRISPR-Cas9 editing was used to generate the rif1 null allele ( S4 Fig ) by replacing the rif1 ORF with a visible 3xP3-DsRed marker . Two CRISPR target sites were selected , one site directly upstream of the start codon and one site 14 bp upstream of the stop codon . Gibson assembly was used to construct a homologous repair donor plasmid containing approximately 1 . 5 kb of DNA homologous to the genomic sequence directly upstream of the first cut site , the DsRed marker , and approximately 1 . 5 kb of DNA homologous to the genomic sequence directly downstream of the second cut site . Both gRNA plasmids and the donor plasmid were coinjected into vasa-cas9 ( 51324 ) embryos by Rainbow Transgenic Flies . After screening for DsRed+ progeny , successful replacement of the rif1 ORF was confirmed by PCR genotyping ( S4 Fig ) and by Sanger sequencing across the recombinant breakpoints . A single male carrying the rif1 null allele was backcrossed to our lab’s wild-type strain for 5 generations to establish the rif1- stock . To generate the mCherry-PCNA transgenic stock , approximately 1 kb of sequence upstream of the pcna start codon , the mCherry-5xGlyGlySer tag , and the pcna gene were cloned into the pw+attB vector using Gibson Assembly . The resulting transgenesis plasmid and phiC31 mRNA were coinjected into attP-9a embryos ( 9744 ) to perform phiC31-mediated integration . To generate the UAS-Rif1 . WT-3xFlag and UAS-Rif1 . 15a-3xFlag transgenic lines , the rif1 ORF was amplified from embryo cDNA and inserted into the pENTR-D vector by TOPO cloning . In order to generate the phosphomutant Rif1 . 15a , a DNA fragment containing the mutated sequence was synthesized ( Integrated DNA Technologies , Redwood City , CA ) and used to replace the corresponding wild-type sequence in the ENTRY plasmid by Gibson Assembly . The ENTRY vectors were then recombined with the pPWF-attB construct using the LR Clonase II kit ( Invitrogen , Carlsbad , CA ) . The resulting transgenesis plasmids and phiC31 mRNA were coinjected into attP-9a embryos ( 9744 ) to perform phiC31-mediated integration . Plasmids and DNA sequences are available upon request . Embryos were collected on grape agar plates , washed into mesh baskets , and dechorionated in 50% bleach for 2 min . Embryos were then devitellenized and fixed in a 1:1 mixture of methanol-heptane before storing in methanol at −20 °C . Embryos were gradually rehydrated in a series of increasing PTx:Methanol mixtures ( 1:3 , 1:1 , 3:1 ) before washing for 5 min in PTx ( PBS with 0 . 1% Triton ) . Embryos were then blocked in PBTA ( PTx supplemented with 1% BSA and 0 . 2% Azide ) for 1 h at room temperature . Blocked embryos were then incubated with the primary antibody overnight at 4 °C . The following primary antibodies were used: rabbit anti-GFP at 1:500 ( Invitrogen A11122 ) and mouse anti-tubulin at 1:100 ( DSHB 12G10 , AA12 . 1-s , and AA4 . 3-s ) . Embryos were then washed with PTx 3 times for 15 min each and then incubated with the appropriate fluorescently labeled secondary antibody ( Molecular Probes ) at 1:300 for 1 h in the dark at room temperature . Embryos were then washed again with PTx 3 times for 15 min each . In order to detect total DNA , DAPI was added to the second wash . Finally , stained embryos were mounted on glass slides in Fluoromount . To detect both Rif1-EGFP and the AATAC satellite repeat , formaldehyde-fixed embryos were blocked in PBTA for 1 h , incubated with rabbit anti-GFP at 1:500 ( Invitrogen A11122 ) for 1 h at room temperature , washed 3 times for 15 min each in PTX , incubated with fluorescently labeled secondary antibody at 1:300 for 1 h at room temperature in the dark , and then washed 3 times for 15 min in PTX . Embryos were then post-fixed in 4% formaldehyde for 20 min . FISH was then performed as previously described [26] using a Cy5 labeled AATAC 30-mer oligo probe ( IDT ) . Protein extracts were prepared by homogenizing embryos in embryo lysis buffer ( 50 mM Tris-HCl pH 8 . 0 , 100 mM NaCl , 1% Triton X-100 , 1 mM EDTA ) supplemented with 1X protease inhibitor cocktail ( Pierce ) , PMSF , 100 mM Sodium Fluoride , 100 mM β-gylcerophosphate , and 10 mM sodium pyrophosphate . After lysis , 2X Sample Buffer was added to the extract , and samples were boiled for 5–10 min . For dephosphorylation reactions , protein extracts were prepared as above except for the omission of phosphatase inhibitors . Extracts were then supplemented with 1 mM MnCl2 and incubated with ƛ phosphatase for 30 min at 30 °C . The reaction was terminated by adding 2X Sample Buffer and boiling for 5–10 min . For immunoprecipitation of GFP-tagged Rif1 , dechorinated embryos were lysed using a dounce homogenizer in 500 μl of ice-cold RIPA buffer ( 50 mM Tris-HCl pH 8 . 0 , 150 mM NaCl , 1% Triton X-100 , 0 . 5% Sodium deoxycholate , 0 . 1% SDS , 1 mM DTT ) supplemented with 1X protease inhibitor cocktail ( Pierce , Waltham , MA ) , PMSF , 100 mM Sodium Fluoride , 100 mM β-gylcerophosphate , and 10 mM sodium pyrophosphate . The resulting extract was cleared by spinning twice at 12 , 000 rpm for 10 min each at 4 °C , after which the supernatant was incubated with 20 μl of GFP-TRAP Magnetic beads ( Chromotek , Martinsried , Germany ) for 1 h at 4 °C on a nutator . The beads were then washed 3 times with lysis buffer using a magnetic rack , and proteins were eluted by boiling in 30 μl of 2x Sample Buffer . For standard western blotting , protein extracts were separated by electrophoresis in precast 4%–15% polyacrylamide gels ( Biorad , Hercules , CA ) . To separate phosphorylated forms of Rif1 , protein extracts were run on a 0 . 5% agarose-strengthened 3% polyacrylamide gel containing 20 μM Mn2+-Phostag ( AAL-107 , Wako Chemicals , Japan ) . Proteins were then transferred to a PVDF membrane using a wet-transfer system . The membrane was blocked in TBST ( TBS with 0 . 1% Tween-20 ) supplemented with 2 . 5% BSA and then incubated in the appropriate primary antibody at a dilution of 1:1 , 000 overnight at 4 °C . The blot was then washed 3 times for 10 min each in TBST and then incubated in the appropriate secondary antibody at a dilution of 1:10 , 000 for 1 h at room temperature . The blot was then washed 3 times for 10 min each in TBST and then treated with Pierce SuperSignal West Pico ECL and used to expose autoradiography film . The following antibodies were used: rabbit anti-GFP ( ab290 , Abcam , Cambridge , United Kingdom ) , rabbit anti-PP1a ( 2582 , Cell Signaling , Danver , MA ) , and Goat anti-Rabbit HRP conjugated ( Biorad ) . Embryo microinjections were performed as previously described [31] . In vitro transcribed mRNA was prepared using the CellScript T7 mRNA production system ( CellScript , Madison , WI ) as previously described [31] and injected at a concentration of 600 ng/μl . The purified proteins used in this study were described in [30] . For live imaging , embryos were collected on grape agar plates and aged at 25 °C when appropriate . After dechorination in 50% bleach , embryos were aligned and glued to glass coverslips and then covered in halocarbon oil before imaging . Embryos were imaged using a spinning disk confocal microscope , and the data were analyzed using Volocity 6 ( Perkin Elmer , San Jose , CA ) . For most experiments , approximately 30 embryos were watched under the microscope , and only the embryos at the appropriate developmental stage were filmed . When comparing different conditions , all images acquired in a single experiment were acquired at the same time and with identical microscope settings . Choice of objective and z-stack size were determined by experimental need . Unless otherwise noted , all images shown are projections of a z-stack series . When imaging embryos following microinjection , the objective was centered in the portion of the embryo nearest the site of injection to record the area of maximum effect . The development of embryos is highly stereotyped , and the quality of the data is founded in the resolution of the imaging . Still images and movies presented in this paper are representative of multiple embryos filmed during a single experiment ( technical replicates ) and of identical experiments performed on embryos collected from independently sorted flies ( biological replicates ) . Choice of embryos for imaging was dictated by developmental stage and by embryo health ( unfertilized and clearly damaged embryos were excluded ) . Western blots reported in this paper were performed in 2 biological replicates ( separate protein extracts from independent embryo collections ) .
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Cells divide rapidly in the early embryos of most animals . However , during a conserved period of development known as the mid-blastula transition ( MBT ) , the cell cycle slows down dramatically . In Drosophila embryos , genome duplication abruptly slows to initiate this cell cycle prolongation . This is achieved through the onset of late replication , a well-recognized phenomenon in which specific sequences of the genome await replication until long after other sequences have finished . Even though this temporal program of replication is a major determinant of the duration of S phase , the factors involved in this process remain unknown . Here , we use genetics and real-time microscopy to visualize replication in developing fly embryos and show that the protein Rap1 interacting factor 1 ( Rif1 ) mediates the introduction of late replication at the MBT . We find that at this stage , Rif1 binds to and selectively delays the replication of large blocks of repetitive DNA known as satellite sequences . During the rapid cell cycles before the MBT , we show that the cyclin-dependent kinase 1 ( Cdk1 ) prevents Rif1 from slowing down DNA replication by driving its removal from the chromatin . The developmental down-regulation of Cdk1 at the MBT allows Rif1 to associate with the satellite sequences and initiate cell cycle slowing . Our work provides new insights into the temporal programming of S phase and into the embryonic origin of late replication .
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2018
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Rif1 prolongs the embryonic S phase at the Drosophila mid-blastula transition
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The rise in dengue fever cases and the absence of dengue vaccines will likely cause governments to consider various types of effective means for controlling the disease . Given strong public interests in potential dengue vaccines , it is essential to understand the private economic benefits of dengue vaccines for accelerated introduction of vaccines into the public sector program and private markets of high-risk countries . A contingent valuation study for a hypothetical dengue vaccine was administered to 400 households in a multi-country setting: Vietnam , Thailand , and Colombia . All respondents received a description of the hypothetical dengue vaccine scenarios of 70% or 95% effectiveness for 10 or 30 years with a three dose series . Five price points were determined after pilot tests in order to reflect different local situations such as household income levels and general perceptions towards dengue fever . We adopted either Poisson or negative binomial regression models to calculate average willingness-to-pay ( WTP ) , as well as median WTP . We found that there is a significant demand for dengue vaccines . The parametric median WTP is $26 . 4 ( $8 . 8 per dose ) in Vietnam , $70 . 3 ( $23 . 4 per dose ) in Thailand , and $23 ( $7 . 7 per dose ) in Colombia . Our study also suggests that respondents place more value on vaccinating young children than school age children and adults . Knowing that dengue vaccines are not yet available , our study provides critical information to both public and private sectors . The study results can be used to ensure broad coverage with an affordable price and incorporated into cost benefit analyses , which can inform prioritization of alternative health interventions at the national level .
Dengue fever is a major public health concern in South-East Asia and South America . Dengue virus is transmitted to humans by Aedes mosquitoes . Clinical presentation ranges from self-limited , mild febrile illness to classic dengue fever ( DF ) to the more severe form of illness , dengue hemorrhagic fever ( DHF ) . The global burden of dengue has increased dramatically in the past five years , and presently , DF and DHF are recognized as a major cause of mortality and morbidity in tropical and sub-tropical countries[1 , 2] . The recent study shows that there are 96 million apparent and 294 million inapparent dengue infections occurring yearly , and the total 390 million infections are more than three times the previous estimate of the World Health Organization ( WHO ) [3–6] . At present , there is no specific treatment for dengue infection . Mosquito control prevention efforts have not been sufficient to control the disease . Vaccine development is still in progress . The Dengue Vaccine Initiative ( DVI ) has conducted extensive multidisciplinary dengue fever studies for decision makers in three countries: Vietnam , Thailand , and Colombia . In Vietnam , annual disease incidence is reported to be 145/100 , 000 population according to the national surveillance system in 2010[7] . Because extensive studies in Vietnam are lacking , a better understanding of dengue and its impact is necessary for disease control , especially in making decisions in regard to future implementation of dengue vaccines . In Thailand , DF/DHF has steadily increased in both incidence and range of distribution despite mosquito control efforts . The dengue incidence rate in Thailand was estimated to be 177/100 , 000 population in 2010[8] . Dengue epidemiology in Thailand can be characterized by the circulation of all four dengue serotypes and the presence of a well-established national dengue surveillance system . Colombia has seen a significant increase in cases of DF/DHF during the last 10 years , with epidemic waves occurring every 3–4 years . In 2010 , Colombia experienced the largest recorded epidemic with the dengue incidence rate of 685/100 , 000 population[9] . All four dengue serotypes are found in Colombia , and in significant contrast to Asian countries , the disease occurs in people of all ages . The rising tide of the Dengue Fever and its associated morbidities underscore the need for vaccines against dengue[10–12] , but there continues to be a lack of economic assessment on dengue fever vaccines . Vaccines currently under development may significantly reduce the burden of disease . The three countries mentioned above are each candidates to become early adopters of future dengue vaccines . However , like many other low- and middle-income countries , these countries will face decisions on whether and how to incorporate new and potentially expensive vaccines within their budget-constrained national vaccination programs . Therefore , understanding the private economic benefits of potential dengue vaccines is necessary for accelerated introduction of vaccines into the public sector program and private markets of high-risk countries .
To estimate household demand and WTP for hypothetical vaccines against dengue infection , we administered a study questionnaire to 400 households in each of three countries ( Fig 1 ) . All respondents ( N = 400 ) at each site received a description of the hypothetical dengue vaccine scenarios of 70% or 95% efficacy for 10 or 30 years . Five pre-assigned prices were determined after performing pilot tests ( 40 pretest interviews ) and open-ended focus group discussions . In this analysis , the dichotomous choice method was adopted . Unlike other CV studies such as open-ended , bidding game , and payment card which have shown incentive compatibility problems , dichotomous choice eases the burden on the respondents , decreasing the number of protest answers[13] . Respondents were asked if they would be willing to buy a vaccine for their youngest child and other household members at randomly pre-assigned prices . Interviewers reminded respondents of their budget constraints and mentioned that there were no right or wrong answers . We adopted a time-to-think approach in Colombia and Vietnam , which gives respondents time to deliberate their decision on whether they would like to purchase a new vaccine . In previous split sample studies[14–17] , respondents tended to demand significantly fewer vaccines when provided with more time to think about their purchasing decision compared to respondents that completed interviews in one sitting . In Colombia and Vietnam , respondents received general information on dengue illness , risk factors and a hypothetical vaccine . They were instructed to consider their vaccine purchasing decision overnight . The time-to-think design was not implemented in Thailand because of cost and logistical issues . Instead , respondents completed the entire survey in one interview . The three sites were selected in support of multidisciplinary research goals of the Dengue Vaccine Initiative . In addition to economic studies , these sites were chosen to provide an in-depth picture of dengue epidemiology and transmission within high risk populations of the chosen countries . All three sites share several common characteristics—high levels of dengue virus transmission; stable population with low rates of migration and high rates of ethnic homogeneity; sites are easily accessible with good health services; and local dengue control officers and provincial public health officials are exceptionally motivated and committed to dengue research . Interviews were administered to the head /senior of selected households . The questionnaire consists of six sections . The first section collected demographic information about the respondent and members of the household . The second section asked about respondent’s perception and experience regarding dengue fever , including activities undertaken by the household to reduce their risk of dengue infection . The third section included information for the respondents on general conditions of dengue fever including how the disease is transmitted and dengue fever risk may be mitigated through community-wide efforts . This section also recorded previous vaccination history , and provided a description of the hypothetical dengue vaccine , including efficacy and duration of protection which can be found in S2 Text and S2 Fig . A series of questions were asked to ensure that respondents had understood how the vaccine works . In the fourth section , household demand was collected . For example , the first WTP question was framed as: “Suppose that the total cost for the dengue fever vaccine would be VND 450 , 000 for three dose needed for one person . Would you buy this vaccine for your youngest child ? ” To access household WTP , the additional question was followed: “Suppose that this dengue fever vaccine costs VND 450 , 000 for the 3-dose series required for each person ( same price for adults and children ) , how many people in your household ( not including your youngest child ) would you be willing to purchase vaccines for ? …Who would you buy this vaccine for ? ” The responses were recorded in a table which is linked to the demographic information in the first section . Respondents who said that they would not buy the vaccine at the specified price were asked if they would take the vaccine if it were provided free . For those who did not want to take a free vaccine or pay any positive price , an additional question was posed to see why they would not take the vaccine . The respondents refused to take the vaccine because they did not think that vaccines are safe or prevent the disease were determined as out-of-market respondents and did not proceed to the next step . In the fifth section , socioeconomic information was collected , such as education , occupation , income , and economic status . The sixth section included questions regarding the time-to-think approach . Pilot studies , focus group discussion and pre-final questionnaires , were conducted in each of the three studies to refine the survey instrument and to help determine an appropriate set of prices for each setting . Results from the pilot studies were not included in this analysis . Our underlying economic model assumes that respondents maximize their household utility , subject to their budget constraints . Vaccines are one of many purchases that can be used to build health capital and household health is one of many competing spending choices . Household vaccine demand is a non-negative integer value and the number of vaccines demanded ( dependent variable ) can be estimated as a function of vaccine price , efficacy , household perceptions of dengue severity and likelihood , as well as household socio-economic characteristics . Count models are suitable for our household demand analysis because the count model estimates non-negative integer values and specifies the quantity demanded with a mean that is dependent on exogenous variables[13 , 21] . The Poisson or its variants ( e . g . , negative binomial ) typically takes the exponential form for expected demand , and the Poisson probability density function can be written as Pr ( xi=n ) =e−λiλinn ! , n=0 , 1 , 2… where n is observed demand , and λi is the mean , λi = exp ( ziβ ) . For the Poisson model , the mean is equal to the variance of the distribution . If the variance is greater than the mean , the model is mis-specified due to overdispersion[22 , 23] ( S1 Text ) . Overdispersion may not affect the coefficient estimates significantly , but causes standard errors to be underestimated . For this reason , the Z-score test and the boundary likelihood ratio test were performed to test for overdispersion for each country[22] . The negative binomial technique relaxes the assumption of equality of the mean and variance by adding a gamma distributed error term[24] . A common version of the negative binomial model is as follows: E ( xi|ziβ ) =λi=exp ( ziβ ) log ( E ( xi ) ) =ziβ+θi where θi represents unobserved individual differences ( or unobserved heterogeneity ) . Pr ( xi ) =Γ ( xi+1α ) Γ ( xi+1α ) Γ ( 1α ) ( 1α1α+λi ) 1α ( λi1α+λi ) xi where λi = exp ( ziβ ) . The mean of the negative binomial distribution is E ( xi ) = λi = exp ( ziβ ) . However , now the variance of the dependent variable is V ( xi ) = λi ( 1 + αλi ) . The parameter α can be interpreted as the overdispersion parameter . When α is equal to zero , the variation becomes equal to the mean , and the distribution can be modelled by Poisson regression . However , if α is greater than zero , overdispersion exists , and the Poisson model is rejected in favor of the negative binomial model[13] ( S1 Fig ) . Standard errors were corrected for the cluster sampling procedure to improve the accuracy of the estimates . Model validation is critical to check whether a model is appropriate and useful . There are several statistics which estimate how well the model fit the data , how much error was in the model[25] . Mean Absolute Deviation ( MAD ) and Mean Squared Prediction Error ( MSPE ) were used to estimate how well the model fit the data [24–26] . MAD provides a measure of the average mis-prediction of the model , and MSPE is typically used to assess the error associated with a validation or external dataset[26] . MAD=∑i=1n|Y^i−Yi|nMSPE=∑i=1n ( Y^i−Yi ) 2n where n is validation data sample size , Y^iis the predicted value , and Yi is the observed value . 50% of the full dataset for each country were randomly selected as a validation dataset . The two statistics were used to measure how well the original models estimated on estimation data predict the validation data . The smaller the value of MAD and MSPE represents the more desirable model which fits the data as closely as possible[24] . The mean household WTP can be calculated by aggregating the area beneath the demand curve . WTP ( vaccine ) =∫0∞eβixi+βpPidP=−eβixiβp where βp is the estimated coefficient for price and βi is an array of the estimated coefficients for the other independent variables . The median WTP was also calculated by estimating the price at which an estimated 50% of the population would purchase vaccines . Parametric estimates of WTP are sensitive to the choice of distribution and functional forms of household demand . Non-parametric models , Turnbull lower bound and Kristrom’s midpoint models[13 , 27–29] , were also estimated . The advantages of non-parametric models are in their simplicity and transparency . The Turnbull estimator does not impose any statistical assumptions about how WTP is distributed[13] , and is considered to be a conservative measure . The Kristrom’s midpoint estimator assumes that the distribution between bid points is symmetrical[15] . Both models provide a useful comparison of mean and median WTP with the parametric WTP measures . The contingent valuation studies and survey questionnaires were approved by the ethical review committees in three countries ( National Institute of Hygiene and Epidemiology in Vietnam , Faculty of Tropical Medicine , Mahidol University in Thailand , Universidad de Antioquia in Colombia ) , as well as Ministry of Health in three countries and Institutional Review Board of the International Vaccine Institute . Written informed consent was obtained prior to conducting interviews and respondents were informed that they could terminate interviews at any time . Respondents received compensation for their time .
Table 1 shows household characteristics for each study site . Average respondent age is from 37 to 47 years , and average household size is around 5 members . Most of the respondents are females . In order to make sure that their responses reflect the decisions made at the household , the respondents were asked who would be primarily involved in making decision for their household members . Over 80% of the respondents confirmed that they would be primarily involved in making vaccine purchasing decisions . The respondents had 6~9 years of median school education in Vietnam and Colombia , and 1~5 years of median school education in Thailand . The self-reported mean household income per month is $351 , $788 , and $367 in Vietnam , Thailand , and Colombia , respectively . For all three countries , more respondents thought that dengue fever is serious for children than respondents who thought so for adults , although the differences are not significant . Approximately 35% , 60% , and 87% of the respondents in Vietnam , Thailand , and Colombia said that their children would likely contract dengue in the next five years . In Vietnam and Thailand , about 28% of the respondents reported that at least one member of their household had contracted dengue fever in the past , compared to 10% in Colombia . Around 52% , 47% , and 27% of the respondents in Vietnam , Thailand , and Colombia mentioned that they know someone who had dengue fever in their neighborhoods . In response to past vaccine purchase history , 68% and 13% of the respondents in Vietnam and Colombia answered that they had previously purchased other vaccines . This question was not asked in Thailand . Over 99% of the total respondents from all three countries correctly answered questions designed to test their understanding of vaccine duration and efficacy . Table 2 summarizes the raw data for average household vaccine demand as a function of price and efficacy . Vaccine demand decreases with price in all three countries . We did not find any significant difference in demand between the 70% and 95% efficacy scenarios . The regression results are shown in Table 3 . Type 2 includes all possible covariates , while type 1 is a parsimonious model which includes only non-attitudinal variables . As expected , the price variable is statistically significant at the 1% level and has a negative sign . Income per capita ( in log form ) is also highly significant across countries with positive signs indicating that vaccine demand increases with income . The respondent age variable is inversely related to the likelihood that a respondent would purchase the vaccine in Vietnam , but this variable is not significant in Thailand and Colombia . The relationship between education and demand was not consistent across countries . Compared to no education , respondents with some education had significantly greater demand in Vietnam , but lower demand in Colombia . The coefficient was positive , but not significant in Thailand . The interaction between earning and price is positive and significant , meaning that respondents with a higher income can afford a more expensive vaccine . Neither the perceived seriousness of dengue nor the likelihood of contracting the disease in the next 5 years was a statistically significant determinant except the perceived seriousness in Colombia . Respondents in Vietnam who knew a person who had contracted dengue were more likely to be willing to purchase a vaccine . There is some evidence that respondents who had purchased other vaccines tend to demand more for our hypothetical dengue vaccine than those without previous vaccine purchase experience . The overall robustness of the model was examined by the MAD and MSPE statistics . In the field of transportation and accident analyses where the negative binomial models are more commonly used , 1 . 8 of MAD and 7 . 2 of MSPE were considered to be relatively small values for a mean dependent variable of 2 . 85[24 , 30] . Given that the mean value of the dependent variable in this study ranges from 1 . 54 to 2 . 66 , the models for all three countries produced fairly satisfactory predictive performance . In particular , MSPE values are closer to 1 for both short and long models in Vietnam , meaning that the model fits the data better than the other countries . While the long model is preferred over the short model in Vietnam , the short models fit the data better for Thailand and Colombia . Fig 2 depicts the observed and predicted fractions of household members vaccinated by price . Table 4 shows parametric and non-parametric mean WTP estimates for the three-dose series described in the hypothetical scenario . The mean WTP per dose is included in parentheses . We did not generate separate estimates by vaccine efficacy/duration since the difference in vaccine demand was not statistically significant . The conservative Turnbull-lower bound mean WTP is $42 . 3 ( $14 . 1 per dose ) for a 3 dose-series vaccine in Vietnam , $68 . 8 ( $22 . 9 per dose ) in Thailand , and $48 ( $16 per dose ) in Colombia . The parametric mean WTP estimates lie in between Turnbull lower bound and Kristrom midpoint values except Colombia . The mean WTP in Thailand is higher than for the other two countries . Table 5 summarizes the median WTP estimates for both parametric and non-parametric models . The median WTP is calculated based on the price in which an estimated 50% of the population would purchase vaccines . Median estimates tend to be less sensitive to the unexpected responses and functional form assumptions than mean estimates , as long as the empirical 50th percentile value lies in between the lowest and the highest price points[13] . For all three countries , the observed median WTP estimates fall between the lowest price and the highest price offered in the surveys . In the case of non-parametric models , the point estimates were linearly interpolated . The parametric median WTP is $26 . 4 ( $8 . 8 per dose ) for a 3 dose-series vaccine in Vietnam , $70 ( $23 . 4 per dose ) in Thailand , and $23 ( $7 . 7 per dose ) in Colombia . The median WTP in Thailand is again higher than the other countries . It is also possible to create separate sub-models and estimate vaccine demand for different age groups . We divided households into three groups: young children ( age under 5 years ) , school age children ( age 5–18 years ) , and adults ( age over 19 years ) . Fig 3 shows the predicted coverage as a function of price for the three age groups . For all three countries , the predicted fractions of young children vaccinated are higher than those for the other age groups at any price , suggesting that respondents place more value on vaccinating young children than school age children and adults .
This study provides insight into the private economic benefits of potential dengue vaccine in three countries . The median WTP per household member was $26 . 1 ( $8 . 7 per dose ) in Nha Trang , Vietnam , $69 . 8 ( $23 . 3 per dose ) in Ratchaburi , Thailand , and $22 . 6 ( $7 . 5 per dose ) in Medellin , Colombia . Our models showed that household demand for the dengue vaccine is sensitive to price and income , suggesting that respondents took the hypothetical purchasing scenario seriously . These results suggest the possibility that a private market for dengue vaccines exists in these three countries and that sales may be robust if vaccine prices are lower than the median estimates from our study . Since respondents were not bound by their stated purchasing decisions , it is possible they may not act as they reported . There was a relatively large fraction of respondents who were willing to purchase vaccines at high price points in Thailand ( 11% ) compared to those in Vietnam ( 9% ) and Colombia ( 3% ) . One explanation for higher WTP in Thailand is that the mean reported household income in Thailand is almost two times greater than that in Vietnam and Colombia; therefore , Thai respondents had more purchasing power . In addition , we were not able to employ the time-to-think research design in Thailand due to budget and logistical constraints . Other researchers have found that people tend to report lower WTP when they have more time to think about a new vaccine product and their budget constraints[14–17] . It is worth noting that this study did not attempt to test the validity of the time-to-think approach . Rather , the study was designed based upon evidence from the time-to-think option used in the previous studies [17] . The time-to-think approach allowed respondents to think carefully about their budget constraints and may more accurately reflect their willingness-to-pay for the vaccine . While the absence of the time-to-think option in Thailand may contribute to higher WTP compared to Vietnam and Colombia , the exact magnitude could not be measured in this study . The detailed methodology and comparison for the time-to-think approach were extensively discussed by Cook J et al . [17] . It should be noted that two parameter estimates among the significant determinants differ in sign by country: education 1 and age group 2 . While it is common for regression coefficients to have the same direction towards the underlying concept in the similar circumstance , some of the socio-economic variables may behave differently across countries to explain variance of the dependent variable ( vaccine demand ) due to the diverse contexts of local specific situations . Ideally , our study samples would be more heterogeneous and more representative of the entire countries; however , we were limited to performing the studies in locations where epidemiologic studies were being conducted at the same time . As a result , these results may not be generalizable beyond the communities in which the studies were conducted . In comparison with previous studies , a study from Philippines suggests a median WTP of $60 for a 10 year efficacy scenario of dengue vaccine[31] , and a study from Indonesia shows a median WTP of $1 . 94 for a fully efficacious dengue vaccine[32] . The estimates may differ depending upon income levels of study populations and previous experience in receiving other vaccines in the study communities ( i . e . availability of free vaccines from local health centers , etc . ) . The rise in dengue fever cases and the absence of dengue vaccines will likely cause governments to consider various types of effective means for controlling the disease . The contingent valuation study proposed here provides important information—how much people are willing to pay for a dengue fever vaccine to avoid the risk of getting infected . The WTP estimates provide quantification of the private benefit of disease reduction . Results can be incorporated into cost benefit analyses , which can inform prioritization of different health interventions at the national level . The study can also assist decision makers to understand how much of population can be covered by subsidizing dengue vaccines when implementing the nationwide campaigns and can help inform how households would allocate vaccines across age groups given household budget constraints . Further , the WTP study provides vaccine manufacturers a better picture of people’s perceptions of dengue fever and dengue vaccines .
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Dengue is complicated . There are four serotypes of the dengue virus , and dengue infection occurs in almost all age groups . Infection with one serotype provides life-long immunity to that specific serotype but does not protect against the other three serotypes . Unlike other diseases which already have preventable vaccines developed , currently there are no commercially available vaccines for dengue fever . Even if the first vaccine becomes available , it is expected that there will be a limited number of vaccine doses available in the first few years . Due to the increase in dengue fever cases , there is already huge public and private interest in potential dengue vaccines . This study reports the household willingness-to-pay for a hypothetical dengue vaccine in three dengue endemic countries . We found that household demand is strongly related to price and income . It was also observed that more than half of the study populations are willing to pay for vaccines when price is lower than the median estimates reported here . This study may contribute to a more effective decision on dengue vaccine introduction .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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A Multi-country Study of the Household Willingness-to-Pay for Dengue Vaccines: Household Surveys in Vietnam, Thailand, and Colombia
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The corpus callosum ( CC ) is the main pathway responsible for interhemispheric communication . CC agenesis is associated with numerous human pathologies , suggesting that a range of developmental defects can result in abnormalities in this structure . Midline glial cells are known to play a role in CC development , but we here show that two transient populations of midline neurons also make major contributions to the formation of this commissure . We report that these two neuronal populations enter the CC midline prior to the arrival of callosal pioneer axons . Using a combination of mutant analysis and in vitro assays , we demonstrate that CC neurons are necessary for normal callosal axon navigation . They exert an attractive influence on callosal axons , in part via Semaphorin 3C and its receptor Neuropilin-1 . By revealing a novel and essential role for these neuronal populations in the pathfinding of a major cerebral commissure , our study brings new perspectives to pathophysiological mechanisms altering CC formation .
The largest commissural tract in the human brain is the corpus callosum ( CC ) , with over 200 million axons that act as a conduit for information between the two cerebral hemispheres . Callosally projecting neurons are Satb2-positive pyramidal projection neurons positioned , in rodents , in upper and lower cortical layers and that extend their axons through the CC [1]–[4] . More than 50 human syndromes result in agenesis of the CC ( AgCC ) and have an associated genetic etiology [5] , [6] . AgCC can result from defects during different steps of callosal development , including cell proliferation , migration , or a failure in axonal guidance within the CC [6] . Studies to date suggest that a specialized population of glia adjacent to the midline are central for the formation of the CC [7]–[13] . The primitive astroglial cells of the “glial” sling form a bridge-like structure at the midline between the two lateral ventricles and are required for the development of the CC [12] , [14] , [15] . Additional glial structures in the CC were described: radial glial cells in the glial wedge ( GW ) and astrocytes in the indusium griseum ( IG ) [6] , [7] , [10] . Recent observations in mice and humans showed that many neurons are also present within the “glial” sling [16] , [17] . Similarly , scattered neurons were observed within the cat CC during early postnatal life [18] , [19] . However , whether these populations have a specific function during development has not been investigated . In this paper , we characterize the embryonic midline cellular organization at times prior to and during the formation of the CC . Through this effort , we discovered that in mouse embryos , uncharacterized GABAergic neurons intermix with glutamatergic neurons within the entire CC white matter . Here , we explore the possibility that these populations act in conjunction with midline glial cells to mediate the formation of the CC . We first investigated the identity of these populations and their spatial organization relative to ingrowing callosal axons . To determine whether these populations are functionally important , we examined the consequences of genetic ablation of a subpopulation of neurons as well as testing whether neuronal cells of the CC contribute to axonal guidance there . We show that the two neuronal populations that transiently populate the CC form a complex cellular network and that CC GABAergic interneurons are required for the proper organization of this network . Furthermore , ex vivo and in vitro experiments indicate that GABAergic and glutamatergic neurons of the CC are able to attract callosal axons . With regards to the signaling pathways that contribute to the formation of the CC , a number of studies have demonstrated that midline glial cells are the principal CC guidepost cells and secrete guidance factors that channel the callosal axons into the correct path [7]–[13] . These guidance signaling factors include Netrin1/DCC , Slit2/Robo1 , ephrins/Eph , Semaphorin/Neuropilin-1 ( Npn-1 ) , and Wnt [5] , [6] , [20]–[28] . Mutant mice for these guidance cues and their receptors exhibit callosal defects that range from minor , with few axons leaving the callosal track , to severe , with complete AgCC . Although the Semaphorin/Npn-1 signaling had been shown to be essential for CC development , the specific semaphorin ligand involved in this process , its source within the midline , as well as its precise function , remained to be determined [26] , [29] . In this study , we show that the transient population of CR-positive glutamatergic neurons expresses Sema3C and that either the ectopic transplantation of glutamatergic neurons or the ectopic expression of this ligand is sufficient to attract callosal axons . The use of Sema3C knockout ( KO ) mice confirms a novel and essential role of this factor in the pathfinding of callosal axons . Taken together , these results reveal that transient GABAergic and glutamatergic neurons are required for the formation of the CC . The present work , therefore , gives new insights into the mechanisms involved in axon guidance and implicates that transient neuronal populations work in conjunction with their glial partners in the guidance of callosal axons .
Previous work has implicated the “glial” sling as central for the establishment of the CC [11] , [12] . Despite its name , the sling has been shown to contain at least one neuronal population whose function to date is undetermined [17] . As a starting point for investigating whether this neuronal population , and perhaps others , contribute to the formation of the CC , we undertook an immunological analysis of this region during embryonic and postnatal development . In addition to glial cells , upon immunostaining with antibodies against βIII-tubulin , MAP2A , and NeuN , we detected a large number of neurons , not only within the “glial” sling , but also within the entire white matter of the developing CC from embryonic day 12 . 5 ( E12 . 5 ) until postnatal day 14 ( P14 ) . In particular , our molecular analysis revealed two distinct neuronal subpopulations . One that includes the population previously described as “sling neurons” was comprised of a population of differentiated glutamatergic neurons ( Figure 1 ) . We found that this population expressed the homeobox transcription factor Emx1 and T-box transcription factor Tbr1 , which are known to promote glutamatergic fate [30]–[32] , the type 1 vesicular glutamate transporter ( VGLUT1 ) , and the calcium binding protein calretinin ( CR ) ( Figure 1Ai–1Aii to 1Bi–1Bii and unpublished data ) . Nearly all the CR-positive embryonic neurons of the CC intermediate zone ( IZ ) coexpressed the glutamatergic marker Tbr1 ( 91 . 7±1 . 3% at E16 . 5 , n = 1 , 415 ) ( Figure S1Ai ) . The other population was composed of GABAergic interneurons and was identified using either: i ) a GAD67-GFP mouse line in which the green fluorescent protein ( GFP ) is reliably expressed within GABAergic neurons [33] ( Figure 1Ci–1Cii to 1Fi–1Fii ) or ii ) a Mash1-GFP transgenic mouse line ( Ascl1 , Mammalian achaete-scute homolog ) ( GENSAT ) that labels telencephalic GABAergic interneurons derived from Mash1-expressing progenitors of the ventral telencephalon [34] , [35] ( Figure S1Ci–S1Cii , S1Di–S1Dii and Figure S4Ei ) . A careful analysis of the colocalization between CR and GAD67-GFP in the neurons of the CC IZ indicates that these two neuronal population are exclusive at embryonic ages ( 0 . 7±0 . 2% at E16 . 5 , n = 1 , 907; and 1 . 4±0 . 4% , n = 1 , 898 at E18 . 5 ) ( Figure 1Ci–1Cii to 1Ei–1Eii and Figure S1Bi ) . The two neuronal population identified by the expression of CR or GAD67-GFP included half of the CC IZ cells at embryonic ages ( 46% at E16 . 5 , n = 5 , 561; 53% at E18 . 5 , n = 6 , 495 ) . At E16 . 5 , the CR-positive glutamatergic neurons constitute 73 . 6±0 . 012% of these neurons , whereas the GAD67-GFP–positive GABAergic interneurons constitute 25 . 9±0 . 012% ( n = 2 , 580; Figure S1Bii ) . At E18 . 5 , the proportion of both neuronal cell types is even ( 51 . 0±0 . 026% for CR+ neurons , 48 . 3±0 . 025% for GAD67-GFP+ neurons , n = 3 , 442; Figure S1Biii ) . As expected , the CR-positive glutamatergic neurons and GABAergic interneurons did not express any of the glial markers nestin , GLAST , and GFAP ( Figure S1Ci–S1Cii to S1Ei–S1Evi and unpublished data ) previously found on early astroglial cells of the CC , IG , and GW [10] . We wished to determine whether CR-positive glutamatergic and GAD67/Mash1-GFP–positive GABAergic neurons are present at times and in a spatial distribution consistent with their contribution to the formation of CC axonal paths . As such , we undertook a longitudinal analysis of these populations during development to establish their relationship to callosal axons . Between E12 . 5 and E15 . 5 , the glutamatergic CR-positive neurons occupy a strategic midline position at the corticoseptal boundary ( CSB ) ( Figure 1Ci–1Cii , arrowheads ) . As such , they occupy this area prior to any callosal axons entering this region ( Figure S2Ai–S2Aiv ) . At this stage , the GAD67/Mash1-GFP–positive interneurons are still migrating within the marginal zone , subplate , IZ , and subventricular zone of the frontal cortical area ( Figure 1Ci ) . At E16 . 5 , GAD67/Mash1-GFP neurons intermix with the CR neurons at the midline and in the lateral part of the CC ( Figure 1Di–1Dii ) . At this age , CC pioneer callosal axons start to cross the midline [36] , [37] , whereas later-growing axons originating from the frontal cortex just approach the lateral border of the CC ( Figure S2Bi–S2Bii and S2Ci–S2Cii ) . All these axons expressing the transmembrane receptor Npn-1 come into contact with both the CR-positive glutamatergic neurons ( Figure 2Ai–2Aii and Figure 2Gi ) and GAD67/Mash1-GFP–positive interneurons ( Figure 2Di–2Dii and Figure 2Gi ) while growing through the CC . From E18 . 5 to P3 , CR-positive neurons are positioned topographically in three stripes within anatomically distinct regions of the main body of the CC ( Figure 1Ei–1Eii , open arrowheads ) . They were located: i ) at the border of the IG and of the cingulate cortex ( CCi ) , ii ) in the middle of the white matter of the CC , and iii ) in the “glial” sling at the border of the septum ( SEP ) and in the region of the GW . The three stripes of glutamatergic CR-positive neurons delineate both a ventral and a dorsal CC axonal path ( Figure 2Bi–2Bii , Figure 2Ci–2Cii , open arrows , and Figure 2Gii ) . Labeling using carbocyanine dyes showed that these dorsal and ventral axonal paths originate from distinct mediolateral cortical areas ( Figure 2Ei–2Eii , Figure 2Fi–2Fii , and Figure S2Di–S2Div ) . This dorsoventral organization was further delineated by the restricted expression pattern of receptors for axon guidance molecules such as Npn-1 ( Figure 2Bi–2Bii and Figure S2F ) and Deleted in Colorectal Cancer ( DCC ) ( Figure S2H ) dorsally , and ephrinA5 binding sites ventrally ( Figure 2Ci–2Cii and Figure S2G ) . By contrast , at this age , GAD67/Mash1-GFP–positive neurons are more diffusely distributed within the entire white matter of the CC and are seen surrounding the growing commissural axons ( Figure 1Ei–1Eii , Figure 2Ei–2Eii , and 2Fi–2Fii ) . Glutamatergic neurons of the CC expressing CR disappeared abruptly between P1 and P3 , whereas GAD67/Mash1-GFP GABAergic neurons disappeared progressively in a spatiotemporal gradient , from P7 at the midline , until P21 in the extreme lateral part of the CC ( Figure 1Fi–1Fii and Figure S3Ai–S3Aii to S3Di–S3Dii ) . Cleaved caspase 3 staining and ultrastructural changes showed that both neuronal populations of the CC died at early postnatal ages ( Figure S3 ) . Our ultrastructural study revealed that dying neurons adopt different morphological types: a non-lysosomal vesiculate type ( type IIIB ) for GAD67-GFP–positive GABAergic interneurons or an autophagic type ( type II ) for glutamatergic neurons [38] . Our results , therefore , demonstrate that the CC is more heterogeneous than previously thought . Specifically , the entire CC white matter contains transient CR-positive glutamatergic neurons and GABAergic interneurons that correspond to the organization of the callosal projections within this region . Furthermore , their location and the timing of their appearance raise the possibility that these neurons actively participate in the guidance of callosal axons . To study the spatial relationships between CC neurons and callosal axons , we used electron microscopy and 3-D analysis of high-resolution confocal image stacks . Electron microscopy and pre-embedding immunocytochemistry showed CC neurons apposed to one another , forming a complex cellular network ( stars ) around callosal axons ( arrowheads ) ( Figure S4A to S4Di–S4Dii and unpublished data ) . To determine how glutamatergic CR-positive and GABAergic GAD67/Mash1-GFP–positive neurons participate in this cellular network , we generated isosurface maps ( Figure S4Eii ) using immunostaining to label both neuronal populations and cell nuclei ( CR , GFP , Hoechst ) ( Figure S4Ei ) . Isosurface reconstructions allowed us to explore the geometry of this cellular organization using the navigator function of IMARIS 4 . 3 software ( Figure S4Eiii–S4Evii and Video S1 ) . The 3-D visualization showed that both CR-positive glutamatergic neurons and GAD67/Mash1-GFP interneurons contributed in forming the “walls” of a complex cellular network surrounding callosal axons inside the CC ( Figure S4Eiii–S4Evii and Video S1 ) . Our observations thus indicate that the two neuronal populations that transiently populate the CC form a dense cellular network that interacts intimately with the growing commissural axons . Given the density and complexity of the neuronal network that we identified , it is relatively difficult to unravel its function in CC formation . As a first step , we analyzed the brains of mutant mice defective for the production of GABAergic interneurons . Mash1 is a transcription factor expressed in GABAergic progenitors of the ventral telencephalon and its inactivation severely impairs the production of cortical interneurons [34] , [35] . Consistently , we found that the CC of Mash1 mutant embryos was nearly devoid of GABAergic interneurons ( GABA-positive neurons: 1 . 390±0 . 146 neurons/mm2 in CC of wild-type ( WT ) mice versus 0 . 167±0 . 055 neurons/mm2 in CC of Mash1−/− mice , p<0 . 001 ) ( compare Figure S5Ci–S5Cii with S5Di–S5Dii ) . To investigate how the lack of GABAergic interneurons affects CC formation , we also examined whether the other CC cell types are impaired by Mash1 inactivation . At E16 . 5 , the CC glial cells' localization , morphology , and expression of guidance factors ( ephrins , semaphorins , and Slit2 ) were not affected in Mash1 mutant embryos ( Figure S5Ei–S5Eii and S5Fi–S5Fii , and Figure S6 ) . By contrast , some glutamatergic CR-positive neurons were displaced ventrally at the midline ( compare Figure 3Ci–3Cii and 3Di–3Dii , arrowheads ) . Thus , in Mash1 mutants , although the glial scaffold appears normal , the CC neuronal network is severely affected , with a lack of GABAergic interneurons and a displacement of CR-positive glutamatergic neurons at the midline . Our analysis showed that Mash1 inactivation leads to major alterations of axonal paths in the CC ( compare Figure 3A with 3B , compare Figure 3Ci–3Cii with 3Di–3Dii , and see Figure S5Gi–S5Gv with S5Hi–S5Hv ) . From E16 . 5 to E18 . 5 , Mash1−/− embryos exhibited partial ( Figure 3Di–3Dii and Figure S6 ) to complete ( Figure 3B and Figure S5Hi–S5Hiv ) AgCC , with few axons , if any , crossing the midline . Although axons were impaired in midline crossing , they expressed normal levels of L1 , Npn-1 , and DCC guidance receptors ( unpublished data , Figure 3Di–3Dii , and Figure S6Gi–S6Gii and S6Hi–S6Hii ) . Instead , callosal axons entered the IG or the SEP and formed two large ectopic fascicles known as Probst bundles that are characteristic of acallosal mammalian forebrains ( Figure 3B and Figure 3Di–3Dii , open arrowheads ) . In addition , DiI-labeled axons that are normally located in the dorsal and ventral paths of the CC intermingle in Mash1−/− embryos before reaching the midline ( compare Figure S5Gi–S5Gv and S5Hi–S5Hv ) . On the other hand , in Mash1−/− , the area specification of the dorsal telencephalon [39] , and the laminar distribution of the Tbr1-positive cortical layers V–VI that contain pyramidal callosal neurons and of Sabtb2-positive callosally projecting neurons were normal ( unpublished data , and compare Figure S5Ai–S5Aii and S5Bi–S5Bii ) . To investigate whether this severe axon guidance phenotype was due to defects in the CC region rather than to altered development of other regions in the Mash1 mutants , we performed transplantations of the CC into E16 . 5 telencephalic slices , using different combinations of WT and Mash1−/− embryos ( Figure 3 and Figure S7 ) . In our slice assays , as in in vivo [36] , [37] , the callosal axons from dorsolateral neocortex develop later than pioneer axons , and after E16 . 5 , their growth cones enter the CC region in successive streams over a period of several days ( Figure S2Bi–S2Bii to S2Ci–S2Cii ) . When dorsal cortical explants from GFP-positive Mash1−/− mice were transplanted into WT slices ( n = 7 out of 7 ) , GFP-labeled callosal axons crossed the midline , whereas transplantations of dorsal cortex from GFP-positive WT mice into Mash1−/− slices ( n = 6 out of 6 ) lead to an impairment in axonal midline crossing ( Figure S7 ) . These experiments suggested that callosal axons mistargeting in Mash1 mutant embryos is due to defects in CC midline and surrounding structures . To further investigate this issue , we then performed reversion experiments ( Figure 3 ) . When dorsal cortical explants from GFP-positive WT mice and explants of the CC region from WT donors were transplanted into a WT brain slice , a majority of GFP-labeled callosal axons crossed the midline ( Figure 3Ei–3Eiii; n = 5 out of 6 ) , thereby reproducing the in vivo behavior of callosal axons . By contrast , with GFP-positive Mash1−/− cortical and Mash1−/− CC explants transplanted into Mash1−/− slices , GFP-positive callosal axons failed to cross the midline ( Figure 3Fi–3Fiii; n = 3 out of 3 ) . We then tested whether the transplantation of WT CC into Mash1−/− mutant slices could restore correct pathfinding of GFP-positive Mash1−/− callosal axons ( Figure 3Gi–3Giii ) . Remarkably , WT CC restored normal axonal guidance of the majority of Mash1−/− callosal axons , but only when the transplant comprised the medial and lateral parts of the CC that contain the GABAergic interneuron population we have identified ( Figure 3Gi–3Giii; n = 4 out of 6 ) . Transplantation experiments of GAD67-GFP–positive WT CC into WT slices confirmed that CC GABAergic interneurons remain through the CC transplant and maintained their initial organization after several days in vitro ( Figure 4Di–4Diii; n = 4 out of 4 ) . Therefore , callosal axons misrouting observed in Mash1 mutant embryos is largely due to defects in the CC region . Altogether , our experiments indicate that Mash1 inactivation does not impair callosal pyramidal neurons differentiation but leads to a severe modification of the CC neuronal network . These results suggest that CC GABAergic interneurons , which are lacking in Mash1−/− mice , may participate in callosal axons guidance and support the idea that the integrity of this neuronal CC network is important for normal callosal axons navigation . To further understand how CC neurons contribute to callosal axon navigation , we tested whether a CC region enriched in GABAergic and/or CR-positive glutamatergic neurons could promote the growth of callosal axons in coexplant and heterotopic graft experiments ( Figures 4 , 5 , and 6 ) . At first , we examined whether the CC region exerts an attractive influence on cortical axons by placing E16 . 5 lateral CC explants , comprising the two neuronal populations of interest , adjacent to explants of medial ( cingulate or frontal ) cortex ( Figure 4Ai–4Aii ) . At E16 . 5 , after 2 d in vitro , outgrowth in the quadrant closest to the CC aggregate was increased for axons originating from the cingulate and the frontal cortical area compared to that in the quadrant furthest away from the aggregate , indicating chemoattraction ( Figure 4Ai–4Aii and 4C ) . By contrast , the septal and the IG regions were found to exert a repulsive action on cortical axons ( Figure 4Bi–4Bii , 4C , and unpublished data ) . At E16 . 5 , after the cerebral hemispheres have fused , it was possible to ascertain the callosal identity of the axons , by using CC organotypic slices . DiI-labeled axons growing in E16 . 5 slice preparations from GAD67-GFP slices ( unpublished data , n = 17 out of 22 ) or in E16 . 5 WT slices grafted with a CC from a GAD67-GFP embryo ( Figure 4Di–4Diii; n = 4 out of 4 ) navigated across the midline as they normally do in vivo . In contrast , when small explants of E16 . 5 GAD67-GFP–positive lateral CC containing both neuronal populations were inserted into E16 . 5 heterotopic septal region of host slices , some DiI-labeled callosal axons were deflected from their normal trajectory , penetrated the SEP and innervated the transplants ( Figure 4Ei–4Eiii , arrowheads; n = 7 out of 8 ) . The enrichment of both types of CC neurons within small E16 . 5 lateral CC explants was confirmed by using GAD67-GFP–positive explants ( Figure 4Aii and Figure 4Di–4Diii to 4Fi–4Fiii ) and CR immunohistochemistry ( Figure 4Fi–4Fiii ) , whereas the lack of astroglial cells was demonstrated by GFAP immunohistochemistry ( unpublished data ) . Thus , these observations reveal the existence of an attractive activity for callosal axons located in the neuron-rich region of the CC . We next determined the respective contribution of GAD67-GFP–positive GABAergic interneurons and CR-positive glutamatergic neurons of the CC to this guidance activity . To directly test the involvement of CC GABAergic neurons , we grafted in the SEP , explants of E14 . 5 or E16 . 5 GAD67-GFP medial ganglionic eminence ( MGE ) ( Figure 5Ai–5Aiii ) , which generate the GABAergic interneurons of the CC ( unpublished data ) . Interestingly , numerous axons left the callosal track , penetrated the repulsive SEP , and grew through migrating GAD67-GFP–positive interneurons originating from the MGE transplant ( Figure 5Ai–5Aiii; n = 12 out of 15 for E14 . 5 MGE , and n = 17 out of 22 for E16 . 5 MGE ) . This attraction was specific for MGE-derived interneurons , since control explants of the lateral ganglionic eminence ( LGE ) did not attract callosal axons ( Figure 5Bi–5Biii; n = 5 out of 6 ) . These observations strongly support the idea that CC GABAergic neurons directly contribute to the attraction of callosal axons . To estimate whether CC GABAergic neurons are the sole contributors of this guidance activity , we compared in coexplant experiments the quantity of cortical axons that were attracted by WT or Mash1−/− E16 . 5 lateral CC explants ( Figure 5Ci–5Cii , 5Di–5Dii , and 5E ) . Mash1−/− explants of the lateral CC , that contained glutamatergic neurons but are devoid of GABAergic interneurons ( Figure S5Di and S5Fi ) , were found to exert a reduced chemoattraction on cortical axons compared to WT lateral CC explants that contain both neuronal populations ( Figure 5E; −40% , p<0 . 05 ) . The equal number of CR-positive neurons within small lateral CC explants of Mash1−/− compared to WT was confirmed by using CR immunohistochemistry ( unpublished data ) . These results show that CC GABAergic interneurons contribute to part of the attractive activity of the CC on cortical axons . To further test whether CR-positive glutamatergic neurons can also directly attract callosal axons , we took advantage of the fact that the E14 . 5 developing CC comprises CR-positive glutamatergic neurons and lacks GAD67-GFP–expressing GABAergic interneurons ( Figure 1Ci–1Cii ) . Coexplant experiments performed at E14 . 5 showed that cortical axons from the CCi were attracted by CC explants comprising only CR-positive neurons ( Figure 6Ai–6Aii and 6B ) . In addition , heterochronic transplantation of E14 . 5 developing CC into the SEP of a E16 . 5 WT slice revealed that regions enriched in CR-positive neurons ( Figure 6Ci–6Ciii ) provided an attractive environment for callosal axons ( Figure 6Di–6Diii , arrowheads; n = 11 out of 13 ) . Altogether , coexplant and transplantation experiments indicate that CC neuronal populations exert an attracting influence on callosal axons , which is mediated by both GABAergic and glutamatergic CR-positive neurons . In search for candidate molecular signals mediating the attractive activity on callosal axons , we found that Sema3C is strongly expressed only in the subcortical white matter and especially the CC region ( Figure 7Ai and Figure S6Ii–S6Iii ) , as previously observed [26] . In the CC , colabeling experiments revealed that Sema3C mRNA expression is restricted to CR-positive glutamatergic neurons ( Figure 7Aii–7Aiv ) . The Sema3C mRNAs were never detected in GAD67-GFP–positive interneurons ( Figure S8Ai–S8Aii ) or GFAP-positive astroglial cells ( Figure S8Bi–S8Bii ) . Since Sema3C has been described to act as an attractive factor for neocortical and cingulate axons in vitro [26] , [40] , [41] , CR-positive glutamatergic neurons of the CC might exert their attractive effect on callosal axons through the action of Sema3C . To test this possibility , aggregates of Sema3C-expressing HEK293T cells were placed in the repulsive septal region of E16 . 5 WT slices ( Figure 7Bi ) . Callosal axons were misrouted from their normal path and invaded cell aggregates expressing Sema3C ( Figure 7Biii–7Biv; arrowheads; n = 13 out of 16 ) , whereas control cell aggregates did not affect the growth of callosal axons ( Figure 7Bii; open arrowheads; n = 7 out of 8 ) . Thus , localized expression of Sema3C in slice cultures directs callosal axon outgrowth . In addition , experiments made with explants of E14 . 5 and E16 . 5 cingulate or frontal cortices and aggregates of Sema3C-expressing HEK293T cells indicate that pioneer cortical axons and later-growing callosal axons are chemo-attracted by Sema3C as early as E14 . 5 ( unpublished data ) . To determine the in vivo function of Sema3C in the developing CC , we examined the brains of mutant mice inactivated for the Sema3C gene ( Figure 7Di–7Dv and Figure S8Di–S8Dii ) . CR and GFAP immunohistochemistry at E16 . 5 and E18 . 5 indicated that the position and organization of the CR-positive glutamatergic neurons and glial cell populations within the CC is indistinguishable in WT and Sema3C−/− mice , suggesting that their development is not sensitive to the loss of Sema3C ( compare Figure S8Ci with S8Di and Figure S8Cii with Figure S8Dii , respectively ) . Sema3C−/− mice exhibited partial to severe AgCC . When the agenesis was partial , all dorsal Npn-1–positive axons failed to cross the midline , whereas part of ventral callosal axons labeled for NPY were able to cross ( compare Figure 7Ci–7Cv with Figure 7Di–7Dv ) . Misguided callosal axons formed Probst bundles within the IG ( Figure 7Di–7Div , arrowheads ) . In some cases , Sema3C−/− mice displayed severe AgCC characterized by midline fusion defects and a complete failure of any callosal axons to cross the midline at the level of the CC main body ( compare Figure S8Ci–S8Cii with Figure S8Di–S8Dii ) . Taken together , these results reveal that guidance mechanisms of callosal axons rely in part on Sema3C , which contributes to the chemoattractive effect of CR-positive glutamatergic neurons on callosal axons . The precise identity of the endogenous neuronal receptor for Sema3C remains unclear . In vitro , Sema3C binds with high affinity to both Npn-1 and its close homolog Npn-2 [42] . Since Npn-1 , but not Npn-2 , is expressed on callosal axons ( see Figure 2Ai–2Aii , 2Bi–2Bii , 2Di–2Dii , Figure 3Ci–3Cii , and 7Ci–7Civ; and unpublished data ) and Semaphorin/Npn-1 signaling is critical for CC development [26] , [29] , we examined whether Npn-1 was necessary to allow callosal axons to respond to Sema3C . We placed aggregates of Sema3C-expressing HEK293T cells adjacent to explants of E15 . 5 medial cortex ( Figure 8Ai–8Aii ) . After 2 d in vitro , axonal growth in the quadrant closest to the aggregate was increased by 70% at E15 . 5 compared to that in the quadrant farthest away from the aggregate ( p<0 . 01; Figure 8Ai–8Aii ) , indicating chemoattraction . Consistently , adding recombinant Sema3C ( 5 to 10 nM ) to dissociated neurons from medial cortex increased axon length by 35% compared to the control condition ( p<0 . 001; Figure 8Bi–8Bii ) . Npn-1 blocking antibodies abolished both the attractive and growth-promoting responses of cortical neurons to Sema3C ( Figure 8Ai–8Aii and 8Bi–8Bii ) and disturbed DiI-labeled callosal axons navigation in E16 . 5 brain slices ( unpublished data , n = 14 out of 19 ) . To exclude the possibility of nonspecific antibody binding , we knocked down endogenous Npn-1 in dissociated cortical neurons using two different small interfering RNA ( siRNA ) sequences that efficiently silenced expression of Npn-1 without affecting Npn-2 levels , as assessed by antibody staining ( unpublished data ) . Remarkably , both siRNAs completely abrogated the positive effect of Sema3C on axon growth ( Figure 8Ci–8Cii ) . Taken together , these results strongly suggest that Npn-1 is necessary for mediating the attractive response of callosal axons to Sema3C .
We have revealed the existence of two populations of glutamatergic and GABAergic neurons that although arising from distinct sources , converge on the interhemispheric fissure prior to the arrival of CC axons . The precise origins of these two CC neuronal populations have yet to be determined . Our observations suggest that CR-positive glutamatergic neurons invade the CC through a tangential subpial migration and may thus correspond to cortical pioneer neurons that originate from the retrobulbar ventricle [43] , [44] . In contrast , our fate-mapping and tracing experiments indicate that the GABAergic interneurons of the CC originate in the MGE ( unpublished data ) as described for a majority of cortical interneurons in mice [45]–[51] . A few studies have reported the presence of neurons within or around the CC , such as CR-positive neurons in the mouse and human “glial” sling [16] , [17] and scattered neurons in the cat CC during early postnatal life [18] , [19] . It was proposed that these neurons were migrating through the CC [19] or below the CC in the sling [10] . Our study provides an evaluation of the positioning , development , and character of these populations and demonstrates that their presence within the CC is transient . Moreover , our data strongly support a requirement for these neurons in the guidance of callosal axons . First , we identified a close structural association between the neurons of the CC and the callosal axons during embryonic development . The intimate relationship between these neurons and the incoming callosal afferents is further bolstered by our 3-D analysis showing that CR-positive glutamatergic neurons form a complex multicellular network with the transient GABAergic interneuron population we identified . The integrity of the CC multicellular network formed by GABAergic and glutamatergic neurons is required for normal CC axonal navigation , as shown by both our analysis of Mash1 mutant mice and our grafting experiments . Our present work reveals that the guidance of callosal axons is actively mediated through the chemotropic actions of the two novel neuronal populations of the CC that we examined . Moreover , our study demonstrates that CR-positive glutamatergic neurons exert a direct attractive influence on callosal axons via Sema3C expression . This function of the CC neurons fits well with the emerging notion that migrating neurons may have a role in axon pathfinding . It has recently been found that thalamocortical axon growth relies on the early tangential migration of a population of GABAergic neurons within the ventral telencephalon [52] . In addition , the lateral olfactory tract ( LOT ) projections are guided by early generated neurons , named “LOT neurons , ” that migrate tangentially [53] , [54] . Similar functions have been reported for CD44-positive neurons in the guidance of retinal axons at the optic chiasm [55] and Cajal-Retzius reelin/calretinin-positive neurons in the establishment of hippocampal projections [56] . Our work demonstrates that a neuronal-rich region of the CC attracts callosal axons , at least in part through the expression by glutamatergic CC neurons of the guidance cue Sema3C . Initially , the Sema3C gene is strongly expressed by guidepost CR-positive glutamatergic neurons adjacent to the midline prior to the entrance of callosal axons . In organotypic slices , Sema3C-expressing HEK293T cells attract callosal axons into heterotopic regions . These observations , using a specific guidance assay for CC axons , extend previous in vitro studies showing that Sema3C acts as an attractive guidance signal for neocortical and cingulate axons [26] , [40] , [41] . It was known that the Sema3C repulsive activity is mediated via Npn-1/Npn-2 heterodimers or Npn-2/Npn-2 homodimers [57] , but the nature of the receptor mediating the attractive effect was not yet characterized . Here , we show that inhibiting selectively the Npn-1 receptor abolished completely the attractive and outgrowth-promoting effects of Sema3C . Moreover , callosal axons are found to express Npn-1 , but not Npn-2 . Therefore , our results reveal that Npn-1 can serve as a Sema3C receptor to mediate chemoattraction . Neuropilins require a signaling coreceptor to mediate semaphorin function . For example , PlexinAs and L1-CAM are responsible for transducing Sema3A repulsive response via Npn-1 in cortical neurons [58] , [59] . Other transmembrane proteins , including the tyrosine kinase receptors Met , ERBB2 , OTK , and VEGFR2 , participate in semaphorin responses by regulating diverse intracellular signaling events and functional outcomes [60]–[62] . The transducer that mediates Sema3C attractive response remains so far undefined . It will be important to analyze whether the assembly of specific subunits combinations confers unique ligand-binding properties of semaphorin receptors , and whether different Npn-1 receptor complexes coexist on cortical axons , dictating either Sema3A-mediated repulsion or Sema3C-mediated attraction . Although it has long been recognized that Sema3C regulates the formation of the cardiovascular system [63] , its in vivo function in the central nervous system remains relatively unexplored . Here , we observed that the development of the CC path depends on Sema3C expression . Indeed , callosal axons fail to grow or navigate correctly through the CC of mutant mice lacking Sema3C gene function . These results shed new light on previous studies showing that mice in which Npn-1 is unable to bind Semas exhibit CC axonal pathfinding defects [26] , [29] . The similarity between the Npn-1Sema− mice and Sema3C−/− mice suggests that Sema3C is the ligand required for directing Npn-1–mediated callosal axon navigation . Taken together , these results reveal that CR-positive glutamatergic neurons within the dorsal midline territory control callosal axon navigation , at least in part , through a Sema3C-dependent mechanism . Therefore , transient CC guidepost neurons play a central role in mediating the guidance cues required for callosal axon pathway formation . Previous studies on CC development emphasized the role of glial cells . In Silver and Ogawa's study [11] , aberrant callosal axons maintained a potential to regrow upon the surface of a glia-covered scaffold after mouse embryos were made surgically acallosal at E16 . 5 . Other studies indicate that astroglial cells of the GW and IG direct callosal pathfinding at the midline by secreting guidance cues [7] , [8] . Our work demonstrates that , in addition , CC formation requires the presence of specific neuronal populations . What is the relative contribution of neurons and glia to CC formation ? Preliminary results indicate that neurons and astroglial cells of the CC intermingle to form a complex 3-D structure and that glutamatergic CR-positive neurons lie along the radial glial processes . Therefore , in addition to secreting guidance factors , glial cell populations may aid in the establishment of the CC neurons through more complex trophic or signaling interactions . Indeed , the interplay between the neuronal and glial cells within the midline will be intriguing to investigate in the future .
All animal research has been conducted according to relevant national and international guidelines . WT mice maintained in a C57Bl/6 genetic background were used for developmental analysis of the CC . We used heterozygous GAD67_GFP ( Δneo ) mice [33] , which will be referred to as GAD67-GFP mice in this work . Experimental animals were obtained by mating C57Bl/6 mice with heterozygous GAD67_GFP mice . GAD67_GFP embryos can be recognized by their GFP fluorescence . NINDS GENSAT BAC Transgenic mice for Ascl1 ( Ascl1-EGFP ) 1Gsat/Mmnc ( MMRC ) referred to as Mash1-GFP in this work were maintained in a C57Bl/6 background and were recognized by their GFP fluorescence . Mash1 KO heterozygous mice were maintained in a mixed C57Bl/6 and DBA background and crossed to produce homozygous embryos [64] . Mash1 heterozygous mice were also crossed with a transgenic mouse line expressing GFP ubiquitously [65] in order to produce GFP-positive Mash1−/− embryos . PCR genotyping of these lines was performed as described previously [52] . Heterozygous embryos did not show any phenotype and were used as controls . Sema3C heterozygous mice were maintained in a CD1 background and mated to obtain Sema3C−/− embryos . The genotype of the offspring was determined by PCR as described [63] . For staging of embryos , midday of the day of vaginal plug formation was considered as embryonic day 0 . 5 ( E0 . 5 ) . Embryos were collected by Caesarean section and killed by decapitation . Their brains were dissected and fixed by immersion overnight at 4°C in a solution containing 4% paraformaldehyde ( PFA ) in 0 . 1 M phosphate buffer ( pH 7 . 4 ) . Postnatal mice were deeply anaesthetized and perfused with the same fixative , and their brains postfixed 4 h . Brains were cryoprotected in 30% sucrose , and cut in coronal 50-µm-thick frozen sections for staining . AP-Sema3C was obtained by cloning cDNA encoding mouse Sema3C in pAPtag-5 vector ( GenHunter Corporation ) , which contains a sequence coding for secreted alkaline phosphatase . To produce AP-tagged proteins , HEK293T cells were transfected with the AP-Sema3C vector or empty pAPtag-5 vector as control , using lipofectamin plus ( Invitrogen ) or fugen ( Roche ) . After 3 d of culture in Opti-MEM serum-free medium , the supernatant was collected and concentrated using Centricon filters ( Millipore ) . AP activity was assessed as described [29] . We developed an in vitro model of CC organotypic slices adapted from a previously published telencephalic slice culture preparation [45] , [52] , [66]–[68] and CC preparation [7] . Embryos were placed in ice cold dissecting medium ( MEM Gibco ref 11012-044 with 15 mM glucose and 10 mM Tris [pH 7–9] ) . Brains were removed and embedded in 3% low-melting point agarose ( Invitrogen ) ; 250-µm-thick coronal sections were then cut using a vibratome filled with cold dissecting medium , and slices at the level of the CC were collected in the same medium . CC slices were cultured on nuclepore Track-Etch membrane ( 1-µm pore size; Whatman ) or PET cell inserts ( 1-µm pore size; Beckton-Dickinson ) in tissue dishes containing 1 ml of BME/HBSS ( Invitrogen ) supplemented with glutamine , 5% horse serum , and Pen/Strep [52] . For CC transplantation experimentation , slices from E16 . 5 embryos were selected since at this early stage of development , the CC contained its whole complement of guide post cells and only the pioneer CC axons of ventral cingulate origin [36] , [37] . It is critical that cultured hemispheres are already joined for the differentiation of the CC in vitro . In our slice assay , as in vivo , the callosal axons from dorsolateral neocortex develop later , and after E16 . 5 , their growth cones enter the CC region in successive streams over a period of several days . Our slice assay performed at E16 . 5 allowed us to study: ( 1 ) the function of both CC guidepost neuronal populations that have reached the CC midline at that stage , ( 2 ) the outgrowth properties of the majority of callosal axons that are growing through the CC after E16 . 5 , and ( 3 ) the effects of transplantations and pharmacological ( guidance factors , lesions ) manipulation on callosal axons navigations . To define the putative function of CC neurons in attracting callosal axons , the transplantation assay was performed at E16 . 5 to analyze the navigation of WT early callosal axons labeled for DiI after insertion of small DiI crystals into the frontal cortex of slices . Small explants of E14 . 5 corticoseptal boundary comprising only CR-positive glutamatergic neurons or E16 . 5 lateral CC IZ comprising both neuronal populations were excised using tungsten needles and transplanted into the SEP of E16 . 5 host slices . After incubation for 48–64 h , the slices were fixed , and axon trajectories through the various regions were analyzed by confocal analysis . In most of our transplantation experiments of CC ( >90% ) , we observed that axons grew without any difficulty through small or large transplants , and only cases with axons penetrating into the grafted explants were counted as positive results for attraction . We found that CC GABAergic interneurons are generated by the medial ganglionic eminence ( MGE ) from E14 . 5 to E16 . 5 ( unpublished data ) . To define the putative function of the CC GABAergic interneurons we transplanted small explants of E14 . 5 or E16 . 5 MGE into the SEP of an E16 . 5 slice as described above . As a control , we used small explants of E16 . 5 lateral ganglionic eminence ( LGE ) that do not generate CC GABAergic interneurons . In this assay , cases with axons growing along GAD67-GFP+ interneurons originating from the grafted explants were counted as positive results for attraction . For the Sema3C study , HEK293T cells were transfected with an AP-control plasmid or an AP-Sema3C plasmid ( see above ) . To highlight HEK293T transfected cells , a pEGFP plasmid was coexpressed . Aggregates of HEK293T transfected cells prepared by high-density culture within an inverted drop of medium were transplanted into the CCi , CC , or SEP of host slices as described before [68] . For the Npn-1 study , the Npn-1–blocking antibody ( R&D systems ) was added at the final concentration of 5 µg/ml . For the Mash1 study , the transplantation assay was performed at E16 . 5 to analyze the growth of WT ( Mash1+/+; Mash1+/− ) or Mash1−/− GFP-positive callosal axons within CC of WT ( Mash1+/+; Mash1+/− ) or Mash1−/− slices . Since heterozygous embryos did not show any phenotype , they were also used as controls . Portions of the frontal cortex with underlying white matter and CC from donor slices were excised using tungsten needles and transplanted into host slices from which the equivalent region had been removed . After incubation for 48–64 h , the slices were fixed and immunostained for GFP before confocal analysis . Cocultures were performed as described [52] , [69]–[71] . Explants of E14 . 5 , E16 . 5 CCi , explants of E16 . 5 frontal cortices , explants of E14 . 5 , E16 . 5 SEP , or explants of E16 . 5 IG were cocultured with CC explants of the corresponding ages . Explants of E14 . 5 and E15 . 5 CCi , or E14 . 5 , E15 , and E16 . 5 frontal cortex were cocultured with HEK293T cell aggregates secreting AP-Sema3C or control AP . For the Mash1 study , the coexplant assay was performed at E16 . 5 to analyze the growth of WT ( Mash1+/+; Mash1+/− ) or Mash1−/− cortical axons confronted with WT ( Mash1+/+; Mash1+/− ) or Mash1−/− CC . For dissociated cell cultures , neurons were dissociated and plated onto polylysine/laminin-coated four-well plates ( Nunc ) in Neurobasal medium supplemented with 1 mM glutamine , 1∶50 B27 ( GIBCO ) , and AP control or AP-Sema3C supernatants ( see above ) . In some experiments , neurons were cultured in the presence of anti–Npn-1 ( R&D Systems ) . Efficient knock-down of Npn-1 was obtained using the following siRNA sequences: 5′-AAUCAGAGUUCCCGACAUAUU-3′ ( Npn-1 siRNA1 ) and 5′-UGUCAAGACUUACAGAGUAUU-3′ ( Npn-1 siRNA2 ) . Neurons were coelectroporated with a pCAGGS-GFP vector and with different siRNAs ( 100 pmol ) as described [72] . Quantification of axonal growth and guidance was performed as described before [73] , or by using a measuring program built in MatLab software that allows to compare the density of immunolabeled axons in the proximal region facing the source of guidance cues and the distal region . Sema3C plasmid was linearized with EcoRI ( New England Biolabs ) for antisense RNA synthesis by T7 polymerase ( Promega ) and with XhoI ( New England Biolabs ) for sense RNA synthesis by T3 polymerase ( Promega ) . EphA4 , Npn-1 , EphB1 plasmids were linearized with SacI ( New England Biolabs ) for antisense RNA synthesis by T3 polymerase ( Promega ) . ephrinB2 plasmid was linearized with BamH1 ( New England Biolabs ) for antisense RNA synthesis by sp6 polymerase ( Promega ) . Slit2 plasmid was linearized with Xba1 ( New England Biolabs ) for antisense RNA synthesis by T7 polymerase ( Promega ) . For in situ hybridization , brains were dissected and fixed by immersion overnight at 4°C in a solution containing 4% paraformaldehyde ( PFA ) in PBS . Free-floating vibratome sections ( 100 µm ) were hybridized with digoxigenin-labeled cRNA probe as described before [74] . To combine in situ hybridization and immunofluorescence , Fast Red ( Roche ) was used as an alkaline phosphatase fluorescent substrate . Monoclonal antibodies were human DCC receptor and NeuN ( Chemicon ) ; Nestin ( Pharmingen ) ; and SNAP25 ( Stemberger Monoclonal ) . Rat monoclonal antibody was L1 ( Chemicon ) . Rabbit polyclonal antibodies were calbindin and calretinin ( Swant ) ; GABA ( Sigma ) ; GFAP ( DAKO ) ; GFP ( Molecular Probes ) ; GLAST , Tbr1 , and Tbr2 ( Chemicon ) , Satb2 ( gift from V . Tarabykin ) ; Emx1 ( gift from A . Trembleau ) ; and cleaved caspase 3 ( Cell Signaling ) . Goat polyclonal antibodies were calretinin ( Swant ) ; Npn-1 and Npn-2 ( R&D System ) ; and NPY ( gift from W . W . Blessing , Flinders University , Melbourne , Australia ) . Guinea pig polyclonal antibodies were VGLUT1 and VGLUT2 ( Chemicon ) . To label ephrin-A5 binding sites , we used the ephrinA5 chimera human Fc ( R&D Systems ) . After overnight fixation in 4% PFA at 4°C , fine glass needles covered with the fluorescent carbocyanide dye DiI ( 1 , 1′-dioctadecyl 3 , 3 , 3′ , 3′-tetramethylindocarbocyanine perchlorate or DiA ( 4-[4- ( dihexadecyl amino ) styryl]N-methyl-pyridinium iodide ( Molecular Probes ) were placed in single or multiple locations in the neocortex [75] . After 4–8 wk at 37°C in 4% PFA or PBS to allow dye diffusion , the samples were embedded in 5% agarose and cut into 100-µm-thick sections on a vibratome . Counterstaining was with Hoechst ( Molecular Probes ) . Fluorescent-stained sections were imaged with confocal microscopes ( Zeiss LSM 510 Meta or Leica SP5 ) equipped with 10× , 20× , 40× oil Plan-NEOFLUAR , and 63× oil , 100× oil Plan-Apochromat objectives . Fluorophore excitation and scanning were done with an Argon laser 458 , 488 , 514 nm ( blue excitation for GFP , Alexa488 , CY2 , and DiA ) , with a HeNe1 laser 543 nm ( green excitation for Alexa 594 , CY3 , and DiI ) and a Diode laser 405 nm ( for Hoechst staining ) . Z-stacks of 10–15 plans were acquired for each CC coronal section in a multitrack mode avoiding crosstalk artifacts of the fluorochromes . Z-stacks of 40–50 sections were acquired for each CC section for the creation of isosurfaces with Imaris4 . 3 software . E16 . 5 and E18 . 5 embryos were killed by decapitation . Brains were dissected and fixed by immersion for 24 h at 4°C in a solution containing 2% glutaraldehyde and 4% paraformaldehyde in 0 . 1 M phosphate buffer ( pH 7 . 4 ) with the addition of 2% sucrose . The brains were then rinsed in 0 . 1 M cacodylate buffer ( pH 7 . 4 ) , postfixed at room temperature for 2 h in 1% OsO4 , dehydrated in graded ethanols , and embedded in Epon . The regions containing the CC of the embedded brains were trimmed and mounted on blocks to cut semithin and ultrathin sections . The ultrathin sections were mounted on Formvar-coated single-slot grids and contrasted with 2% uranyl acetate and 0 . 2% lead citrate . For pre-embedding immunocytochemistry , embryonic brains were fixed by immersion in a solution containing 4% paraformaldehyde and 0 . 1% glutaraldehyde in 0 . 1 M phosphate buffer ( pH 7 . 4 ) supplemented with 2% sucrose for 24 h . Fifty-micrometer-thick sections were cut with a vibratome and immunoreacted . Endogenous peroxidase reaction was quenched with 0 . 5% hydrogen peroxide in methanol , and unspecific binding was blocked by adding 2% normal horse serum during preincubation and incubations in Tris-buffered solutions . The primary antibodies were detected with biotinylated secondary antibodies ( Jackson ImmunoResearch ) and the Vector-Elite ABC kit ( Vector Laboratories ) . Following the diaminobenzidene reaction , sections were dehydrated and embedded in Epon . The plastic-embedded specimens were prepared for ultrathin sectioning following the same protocol as above . In slices of WT mice , the CR+ , Tbr1+ , and GAD67-GFP+ neurons in the CC were counted at E16 . 5 and E18 . 5 as the number of cells in the CC region from at least five slices per condition . To study the total neuron number through the CC , the values were reported as a percentage of the total number of the cells encountered within the same region of the CC and labeled by Hoechst staining . To study the neuronal subpopulations repartition , the values were reported as a percentage of the total number of labeled neurons encountered within the same region of the CC . In slices of WT and Mash1−/− mice , the GABAergic interneurons in CC were counted as the number of neurons labeled for GABA per surface unit from at least five slices per condition . For all analyses , values from at least three separate experiments were at first tested for normality . Values that followed a normal distribution were compared using Student t-test or one-way ANOVA and Fisher t-tests . Values that did not follow a normal distribution were compared using Mann-Whitney and Kolmogorov-Smirnov nonparametric tests . The nomenclature for callosal development is based on the Atlas of the Prenatal Mouse Brain [76] . On the basis of our results , we considered that the CC is divided into two sectors: the medial part is bordered dorsally by the IG and the longitudinal fissure , and ventrally by the GW and the dorsal limit of the septal area . The lateral part comprises the white matter bordered by the CCi superficially , and by the ventricular zone between the GW and the mediodorsal angle of the lateral ventricle towards the ventricular side .
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The largest commissural tract in the human brain is the corpus callosum , with over 200 million callosal axons that channel information between the two cerebral hemispheres . Failure of the corpus callosum to form appropriately is observed in several human pathologies and can result from defects during different steps of development , including cell proliferation , cell migration , or axonal guidance . Studies to date suggest that glial cells are critical for the formation of the corpus callosum . In this study , we show that during embryonic development , the corpus callosum , which was considered a neuron-poor structure , is in fact transiently populated by numerous glutamatergic and GABAergic neurons . With the use of in vitro graft experiments and of various transgenic mice , we demonstrate that neurons of the corpus callosum are essential for the accurate navigation of callosal axons . Moreover , we discovered that the guidance factor Semaphorin 3C , which is expressed by corpus callosum neurons , acts through the neuropilin 1 receptor to orient axons crossing through the corpus callosum . The present work therefore gives new insights into the mechanisms involved in axon guidance and implies that transient neurons work together with their glial partners in guiding callosal axons .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology/neurodevelopment",
"developmental",
"biology/pattern",
"formation"
] |
2009
|
Transient Neuronal Populations Are Required to Guide Callosal Axons: A Role for Semaphorin 3C
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The TOR ( Target of Rapamycin ) pathway is a highly-conserved signaling pathway in eukaryotes that regulates cellular growth and stress responses . The cellular response to amino acids or carbon sources such as glucose requires anchoring of the TOR kinase complex to the lysosomal/vacuolar membrane by the Ragulator ( mammals ) or EGO ( yeast ) protein complex . Here we report a connection between the TOR pathway and circadian ( daily ) rhythmicity . The molecular mechanism of circadian rhythmicity in all eukaryotes has long been thought to be transcription/translation feedback loops ( TTFLs ) . In the model eukaryote Neurospora crassa , a TTFL including FRQ ( frequency ) and WCC ( white collar complex ) has been intensively studied . However , it is also well-known that rhythmicity can be seen in the absence of TTFL functioning . We previously isolated uv90 as a mutation that compromises FRQ-less rhythms and also damps the circadian oscillator when FRQ is present . We have now mapped the uv90 gene and identified it as NCU05950 , homologous to the TOR pathway proteins EGO1 ( yeast ) and LAMTOR1 ( mammals ) , and we have named the N . crassa protein VTA ( vacuolar TOR-associated protein ) . The protein is anchored to the outer vacuolar membrane and deletion of putative acylation sites destroys this localization as well as the protein’s function in rhythmicity . A deletion of VTA is compromised in its growth responses to amino acids and glucose . We conclude that a key protein in the complex that anchors TOR to the vacuole plays a role in maintaining circadian ( daily ) rhythmicity . Our results establish a connection between the TOR pathway and circadian rhythms and point towards a network integrating metabolism and the circadian system .
The TOR ( Target of Rapamycin ) pathway is a highly conserved cellular pathway in eukaryotes that monitors nutritional and stress signals from both extracellular and intracellular sources to regulate cellular growth , division , autophagy and stress responses . It has been extensively studied in mammals [1] and yeast [2] . In mammals , extracellular growth factors act through cell-surface receptors to activate the kinase AKT , which in turn activates the mammalian TOR complex 1 ( mTORC1 ) through inactivation of the inhibitory tuberous sclerosis complex ( TSC ) [3] . The mTORC1 complex is also activated by amino acids through pathways independent of cell-surface receptors and TSC [1] . Monomeric GTPases in the RAG family are localized to the lysosomal membrane by interaction with the membrane-bound RAGULATOR complex . RAGs are activated by amino acids through various mechanisms and recruit mTORC1 to the lysosome . This pathway converges with the growth factor pathway to help activate mTORC1 at the lysosome [3] . In yeast , which do not utilize growth factors and do not have TSC complexes , the primary signals are amino acids and other nutrients such as carbon and nitrogen sources . The RAG-family GTPases Gtr1 and Gtr2 are anchored at the vacuole ( homologous to the mammalian lysosome ) by binding to the membrane-localized EGO complex ( similar to the mammalian RAGULATOR complex ) . TORC1 is found at the yeast vacuolar membrane regardless of nutrient status , and is activated by amino acids through activation of Gtr1 and Gtr2 [3] . In yeast , there is evidence that other pathways related to amino acid availability also intersect with TORC1 signaling , including the GAAC ( general amino acid control ) pathway , which upregulates amino acid transport and metabolism in response to amino acid starvation , and the SPS ( Ssy1-Ptr3-Ssy5 ) pathway that upregulates amino acid transport in response to extracellular amino acids [3] . In both yeast and mammals , localization of the TOR complex to the lysosomal/vacuolar membrane is essential for its activation [4] . The key process that leads to increased cell growth is activation of ribosome biogenesis and increased protein translation , accomplished by the phosphorylation of key targets by the activated TORC1 kinase [2 , 5 , 6] . In mammals , the best-characterized targets are S6K , which in turn phosphorylates ribosomal protein S6 to increase ribosome biogenesis; and translation inhibitor 4E-BP , phosphorylation of which increases translation [2 , 5 , 6] . In yeast , Sch9 is the S6K homolog , activating ribosome biogenesis , and the second major target is Tap42 , a regulator of type 2A phosphatases ( PP2A ) . The two major proximal TORC1 effectors Tap42 and Sch9 together activate translation initiation factors . Disruptions in the TOR pathway have been associated with human pathologies such as metabolic disease , cancer , and age-related diseases [7 , 8] . Circadian ( daily ) rhythmicity is also common to all eukaryotes and some prokaryotes , and rhythmicity is found in many and possibly most intracellular functions including metabolism , stress responses , cell division and growth [9] . Circadian disruption has been linked to multiple disorders in mammals and humans including metabolic syndrome [9 , 10] . We have now identified a connection between circadian rhythmicity and the TOR pathway in the model eukaryote Neurospora crassa . The most popular model for the molecular mechanism of rhythmicity in all organisms has been a transcription/translation feedback loop ( TTFL ) involving the activation of transcription of a gene by a positive element , the translation of that gene into a protein that is the negative element , and the negative feedback of that protein onto the positive element to inhibit transcription . In N . crassa , the protein product FRQ of the frequency ( frq ) gene is the negative element and the White Collar Complex ( WCC ) is the positive element [11–13] . Many problems with this model have been noted , not least of which are examples of circadian rhythmicity in the absence of transcription that would be required for a TTFL mechanism [9 , 14 , 15] . In N . crassa , which has a long history as a model organism for investigating the molecular mechanisms of circadian rhythmicity , there are numerous examples of rhythmicity in the absence of a TTFL in mutant strains lacking functional FRQ or WCC genes [12] . FRQ-less rhythms of conidiation ( spore-formation ) have been reported in strains growing on agar medium for long periods of time [16] , in cultures exposed to temperature cycles [17–19] , in strains with defects in lipid metabolism [20] , in cultures supplemented with various chemicals [21 , 22] , and in a variety of mutant backgrounds [23–26] . FRQ-less rhythms at the molecular level have been reported in the level of diacylglycerol [27] , the level of ccg-16 mRNA [28 , 29] , the activity of nitrate reductase [30] , the level of WC-1 protein [29] , and the oxidation state of peroxiredoxin protein [31] . There is very little information about the molecular mechanisms of FRQ-less rhythmicity . A recent report [26] described a mutation , cog-1 , that allows the expression of rhythms in strains defective in the TTFL , and this rhythmicity required a functional blue light photoreceptor CRY ( Cryptochrome ) gene , suggesting a role for CRY in rhythmicity . In order to identify potential components of a FRQ-less circadian oscillator ( FLO ) [32] , we carried out a mutagenesis screen in a FRQ-less strain using UV light . We identified a mutation , named uv90 , that compromises FRQ-less rhythmicity of the conidiation ( spore-formation ) rhythm under two different assay systems [33]: rhythmic entrainment to short heat pulses , and free-running rhythmicity in chol-1 ( choline-requiring ) strains deprived of choline . Crucially , in the FRQ wild-type background , this mutation also dampens the rhythm of conidiation , dampens the amplitude of the FRQ protein rhythm , and dampens the amplitude of the entire circadian oscillator as measured by responses to phase-resetting by light or heat pulses [33] . The uv90 mutation therefore identifies a gene that is necessary for robust FRQ-less rhythmicity and also for maintaining the amplitude of the entire circadian system when FRQ is present . Our goal in the present work was to identify the gene affected by the uv90 mutation and uncover its functional role . We have mapped and identified the uv90 gene and have found that it codes for a protein in the TOR pathway that is homologous to p18/LAMTOR1 in mammals and EGO1 in yeast . In yeast and mammals , this protein is essential for the vacuolar/lysosomal localization of the TORC1 complex and participates in the transmission of nutritional status information . We demonstrate that the UV90 protein is localized to the vacuolar membrane , and is required for normal sensing of both amino acids and glucose in the growth medium . Our results contribute to understanding the close connection between metabolic status and circadian rhythmicity by identifying the function of a component of an oscillatory network that can drive rhythmicity independent of the standard TTFL .
To identify the gene affected by the uv90 mutation , we mapped the phenotype using the method of cleaved amplified polymorphic sequences ( CAPS ) [34] . We first crossed our lab-generated uv90 mutant strain in the Oak Ridge background to a wild-type Mauriceville strain that carries many DNA polymorphisms relative to Oak Ridge . Using PCR-based markers designed to detect these polymorphisms in the progeny of the cross , we mapped the uv90 mutation to a region on linkage group ( chromosome ) VI ( Fig 1A , S1 Table , S2 Table ) . We then carried out fine mapping with additional CAPS markers using only progeny that had a crossover event in that region ( Fig 1B ) . This defined the location of uv90 as a 75 kb region around marker 3317 . To identify the putative uv90 gene , we tested the growth phenotypes of a number of strains carrying deletions of genes in this region ( see S3 Table ) . Out of 21 ORFs identified in this region in the N . crassa genome , 16 were available as deletions from the Fungal Genetics Stock Center and the Neurospora Knockout Project , and one ( NCU05950 ) showed a growth phenotype similar to the uv90 mutant . To confirm the presence of a mutation in NCU05950 in our uv90 mutant , we attempted to sequence this gene in the mutant strain . Our initial attempts to obtain a PCR product from this region were unsuccessful in the mutant . Southern blots using a probe for the wild-type NCU05950 gene showed a loss of DNA fragments in this region in the mutant , suggesting a major chromosomal event such as a deletion ( Fig 1C ) . We carried out additional PCR in this region , walking in both directions from NCU05950 in approximately 1 kb increments . PCR failed to give products until we reached genes NCU05957 upstream and NCU05947 downstream ( S1 Fig , S2 Fig ) . Long-range PCR across this region produced products shorter than predicted in the mutant but none in the wild type , likely due to the extreme length of the predicted products ( S1 Fig ) . We sequenced a long-range PCR product from the mutant and found a deletion of 35 , 128 nt ( Fig 1D ) . This deletion removes 11 genes , including NCU05950 and two tRNAs , and partially deletes NCU05957 and NCU05947 ( Fig 1D , S2 Fig ) . We confirmed that deletion of NCU05950 , and only this gene , is responsible for the uv90 phenotype by using two strategies: assaying the circadian rhythm phenotype of an NCU05950 deletion strain , and rescuing the phenotype of the uv90 mutant by transformation with a wild-type copy of NCU05950 . We crossed the NCU05950 deletion into our laboratory strains to introduce a FRQ-null mutation and the chol-1 mutation . We assayed conidiation rhythmicity under free-running conditions and found that the phenotype of the NCU05950 deletion was very similar to the uv90 mutant , in both the choline-supplemented and choline-deficient conditions , both with and without the FRQ-null mutation ( Fig 2 ) . The entrained rhythm of the NCU05950 deletion in a FRQ-null background was also similar to the uv90 mutant and different from the UV90 wild-type strain ( Fig 3A ) . ( Note that the apparent troughs following the conidiation peaks do not represent entrainment , but are artifacts of the direct masking effects of heat on the development of conidiospores at the time of the heat pulse[19] . ) The phenotype of the deletion mutant is highlighted in Fig 3B where we have re-plotted the heat pulse profiles to compare the effects of different T-cycles within each strain . The conidiation peaks in wild-type occur at varying times after the heat pulse depending on the T-cycle , as expected from an entrained oscillator [17 , 19] . In contrast , the main peaks in the uv90 mutant and the deletion mutant occur earlier in the cycle than the wild type and at nearly the same time , demonstrating that the loss of UV90 function disables the oscillator that is revealed by the heat pulse entrainment . We then introduced a wild-type copy of NCU05950 into the original uv90 mutant strain , both with and without the FRQ-null mutation , and found that the rhythmic phenotype was similar to the uv90+ wild-type , in both assays ( Fig 2 & Fig 4 ) . These results confirmed that the phenotype of the uv90 mutant is due to a loss-of-function ( null ) mutation in the NCU05950 gene , and cannot be accounted for by disruption of neighboring genes . The NCU05950 gene was not annotated in the N . crassa genome database prior to our characterization of the uv90 mutant . Database searches using the protein sequence retrieved a number of similar proteins from other filamentous fungi; however , none of these had functional annotations ( see S5 Table ) . We performed a search for putative protein domains and identified a conserved domain in the LAMTOR family , which includes human p18/LAMTOR1 and yeast EGO1/Meh1p/Gse2p ( Fig 5 and Table 1 ) . In yeast , EGO1 is localized to the vacuolar membrane and serves as an anchor for the EGO complex [2 , 35] . Human p18/LAMTOR1 is localized to the surface of late endosomes/lysosomes to anchor the “Ragulator” complex [4] . These complexes function upstream of TORC1 and transmit nutritional signals , specifically amino acid sufficiency signals , to TORC1 . In addition to the LAMTOR domain , the predicted amino acid sequence of NCU05950 contains elements that support the identification of the protein product as a member of the LAMTOR family ( Fig 5 ) . The predicted protein is similar in size to the human and yeast proteins ( Table 1 ) . Both human p18/LAMTOR1 and yeast EGO1/Meh1p/Gse2p are predicted to be helix-rich [36] as is NCU05950 ( Table 1 ) . Similar to LAMTOR1 and EGO1 , the N-terminus of NCU05950 has two cysteines that may be sites for S-acylation ( palmitoylation ) and an N-terminal glycine that is a potential site for myristoylation ( Fig 5 ) . Dual acylations are known to localize some proteins to lipid rafts [37] . The human LAMTOR1 protein has been found in lipid rafts in late endosomes and these N-terminal putative acylation sites are essential for this localization [38] . The NCU05950 gene contains a sequence ( DEAQHL ) near the N-terminus that fits a localization signal [DE]XXXL[LI] for sorting proteins to the endosomal/lysosomal compartments in mammals , yeast , and many other organisms [39] . Both human LAMTOR1 and yeast EGO1 contain similar localization sequences ( Fig 5 ) . Pairwise protein sequence alignments identified similarities between these proteins from N . crassa and yeast , and N . crassa and human , in the N-terminal acylation sites , the lysosomal localization sequences , and the LAMTOR domains ( S3 Fig ) . To determine the intracellular location of the NCU05950 protein , we constructed a GFP fusion protein expressed from the high-expression ccg-1 promoter . This fusion protein was functional , as shown by rescue of the rhythmic phenotype in an NCU05950 deletion strain ( Fig 6 , row 3 ) . As a control , we constructed a strain carrying an RFP-tagged vacuolar marker , vam-3 ( NCU06777 ) [40] , which is a vacuolar-associated SNARE . As previously reported , [40] , the RFP-VAM-3 protein was found in filamentous structures behind the tip , and inside large spherical vacuoles in older hyphal regions that were filled with large vacuoles ( Fig 7A ) . Localization inside the vacuole may be the result of turnover of vacuolar membrane proteins and normal degradation processes [40] . The NCU05950-GFP protein co-localized with RFP-VAM-3 in hyphal tips ( Fig 7A , top row ) . In older hyphae , NCU05950-GFP was found on the vacuolar membrane ( Fig 7A , bottom row ) . These results localize the NCU05950 protein to the vacuole , and specifically the vacuolar membrane , in agreement with the known localization of the orthologous human and yeast proteins . The putative acylation sites at the N-terminus of the NCU05950 protein ( Fig 5 ) may be responsible for localizing the protein to membranes . We constructed a deletion mutant lacking the terminal glycine ( amino acid #2 ) and we also constructed a deletion mutant lacking 7 amino acids ( #2–8 ) , which would delete both putative acylation sites . However , the 7 amino acid deletion leaves two glycines near the N-terminus , which could potentially serve as new acylation sites , so we also constructed a deletion of 10 amino acids ( #2–11 ) . GFP-fusion proteins with these deletions expressed from the ccg-1 promoter were found to be diffusely localized in the cytosol ( Fig 7B ) , in contrast to the vacuolar localization of the wild-type protein . Similar results were found with deletion mutants expressed from the native NCU05950 promoter ( Fig 7C ) . S5 Fig demonstrates that the proteins with N-terminal 7- and 10-amino acid deletions were stably expressed . These results indicate that the NCU05950 gene product is a LAMTOR-like protein localized to the vacuolar membrane , probably by acyl group anchors . We also found that this vacuolar localization is required for the rhythm-related function of NCU05950: FLAG-tagged N-terminal deletion constructs expressed from the native NCU05950 promoter and missing 7 or 10 amino acids failed to rescue the defective phenotype of the NCU05950 gene deletion strain ( Fig 6 , rows 7 & 8 ) . In contrast , a deletion of only the N-terminal glycine at position #2 , the putative site for myristoylation , did not disrupt vacuolar localization of the protein ( Fig 7B ) and did not disrupt the rhythm-related function of the protein , as this deletion was able to rescue the phenotype of the gene deletion mutant ( Fig 6 , row 6 ) . Similar results were found for GFP-tagged N-terminal deletion constructs expressed from the native NCU05950 promoter ( S4 Fig ) . Quantitation of pixel brightness from confocal images ( S6 Fig ) confirmed that GFP-tagged proteins were concentrated at the vacuolar membranes in the control and Δ1 strains but not in the Δ7 and Δ10 strains , for both the ccg-1 and native promoters . Acylation at the N-terminal glycine is therefore not required for correct vacuolar localization and function . ( Note that the growth rate of the strain carrying Δ10-NCU05950::GFP was close to that of the strain carrying the full-length NCU05950::GFP ( S8 Table ) although the growth rate of the corresponding FLAG-tagged Δ10 mutant was slower than the full-length control ( S7 Table ) . ) To determine whether the NCU05950 protein product is regulated by the circadian system , we constructed a fusion protein with a FLAG epitope tag , driven by the native NCU05950 promoter , and introduced it into the NCU05950 deletion strain . This transformant was functional and restored the wild type phenotype , as assayed by rhythmicity on race tubes ( Fig 6 , row 5 ) . To assay a time-course of protein levels , cultures were grown in liquid medium in constant darkness and constant 22°C after synchronizing their clocks with a light-to-dark transition , and samples were collected at various times . The level of NCU05950 protein was assayed by immunoblotting and the protein was found at nearly constant levels across two circadian cycles ( Fig 8 ) . As a control , we assayed levels of FRQ protein in the same samples and found the expected rhythm of phosphorylation state , demonstrating that the clock in these cultures was functional ( Fig 8 ) . These experiments used samples harvested from cultures in low-glucose liquid medium in which growth is inhibited . Similar results ( S7 Fig ) were obtained from cultures growing rapidly on agar medium and expressing the rhythm of conidiation , using culture methods previously described [33] . We concluded that the function of NCU05950 does not require rhythmicity of the protein . We constructed GFP-tagged proteins using both the native NCU05950 promoter and the high expression ccg-1 promoter , and we found that both types of constructs can rescue the rhythmic phenotype in the NCU05950 deletion mutant background ( Fig 6 , rows 3 & 4 ) . This indicates that the native promoter is not required for the clock function of NCU05950 , in agreement with our finding that rhythmicity of the protein levels is not required for clock function . If the NCU05950 protein functions in the TOR pathway , as predicted , a null mutation might be expected to affect the growth response of the fungus to different nutritional states . We assayed the growth rate on solid agar in race tubes with various media and found differential responses of the NCU05950 wild type and the NCU05950 deletion mutant ( Fig 9A ) . On water agar with no added nutrition , NCU05950 wild type grew faster; on phytagel with no added nutrition , the mutant was faster; when yeast extract was added to agar , they grew at the same rate . This indicates that the mutant does not have a generalized growth defect that slows growth under all conditions , but rather it responds atypically to nutritional state . Using the standard Vogel’s minimal medium ( VM ) with agar and glucose , both strains could grow at the same rate without added nitrogen sources ( Fig 9A ) . The wild type increased its growth rate with added casein hydrolysate ( a source of amino acids ) or the standard ammonium nitrate source , while the mutant did not respond to these nitrogen sources ( Fig 9A ) . We repeated this analysis in a new set of strains , with the chol-1 mutation in the background but adding sufficient choline to repair the chol-1 defect . We included the original uv90 mutation and two transformants carrying wild-type copies of NCU05950 at the his-3 locus in either the NCU05950 deletion background or the uv90 mutant background . The results ( S8 Fig ) indicated that in most cases the uv90 mutant phenotype was similar to the NCU05950 deletion and the ectopic copy of the wild-type gene could reverse the growth phenotypes of the mutants . The presence of chol-1 did not alter the phenotypes as long as there was sufficient choline supplementation . To further refine this analysis , we grew a wild-type control and the NCU05950 deletion mutant in liquid VM medium without agar ( to avoid the unknown impurities that allow growth on water agar alone ) with or without ammonium nitrate , the standard nitrogen source . In mammals and yeast , nitrogen sources ( typically amino acids ) stimulate TORC1 activity and growth [1] . Both glutamine and leucine stimulate TOR activity in mammals and yeast [2] , with glutamine being the preferred nitrogen source for yeast [41] . In N . crassa , glutamine is also the preferred amino acid nitrogen source for growth [42] . N . crassa also stores large amounts of arginine in its vacuole , and releases this nitrogen when glutamine is depleted [43] . We therefore chose to assay the effects on growth of three amino acids: glutamine ( gln ) , arginine ( arg ) and leucine ( leu ) ( Fig 9B ) . Both gln and arg added to VM increased the growth of the NCU05950 wild-type but had no significant effect on the growth of the mutant ( Fig 9B ) . In media without ammonium nitrate , arg was significantly better than gln at supporting the growth of the wild-type , but there was no significant difference in the mutant ( Fig 9B ) . Leucine inhibited the wild type in VM but had little effect on the mutant , and leucine was a poor nitrogen source for growth of both strains in the absence of ammonium nitrate ( Fig 9B ) . Leucine and glutamine activate TORC1 through different pathways in both mammalian cells and yeast [3] . Activation of TORC1 by leucine depends on the EGO complex in yeast ( Gtr1 , Gtr2 , Ego1 and Ego3 ) or the functionally homologous Ragulator-Rag complex in mammalian cells ( RagA/B , RagC/D and Ragulator ) while glutamine activates TORC1 by other poorly-characterized pathways [41 , 44] . Our results may also indicate separate pathways for different amino acids in N . crassa . We next tested the effects on growth rate of varying glucose concentration . The NCU05950 deletion mutant grew at the same rate as the wild type at low glucose concentrations but grew more slowly than wild type at higher concentrations of glucose ( Fig 9C ) . Taken together , these results indicate that the NCU05950 deletion mutant is defective in its growth response to added nutrition , both nitrogen and carbon sources , and therefore the TOR pathway is implicated in growth responses in N . crassa .
Very little is known about the TOR pathway in N . crassa and other filamentous fungi . Rapamycin binding proteins ( FKBPs ) have been identified in the fungus [45 , 46] . A screen of Ser/Thr kinase gene deletions in N . crassa [47] identified a homolog of yeast TOR1/TOR2 by sequence similarity , but the deletion strain is not available as a homokaryon from the Fungal Genetics Stock Center [48] suggesting that the deletion may be lethal , although this has not been rigorously tested . The same screen identified a homolog of the yeast Sch9 gene ( homologous to the TOR kinase substrate S6K in mammals ) and found that the deletion strain had impaired growth and impaired osmoregulation [47] . Genes encoding components of the TOR pathway have been identified throughout the fungal kingdom and are ( with a few exceptions ) highly conserved [49] . In the fungal plant pathogen Fusarium graminearum , this pathway is involved in virulence and vegetative development [50] . Our work suggests that in N . crassa , the TOR pathway is important in nutrient sensing and growth control as in other eukaryotes , and in addition plays a role in regulating circadian rhythmicity . Because the uv90 gene is homologous in structure and function to the yeast EGO1 and mammalian LAMTOR1 , and the protein is found on the vacuolar membrane , we propose naming this gene “vta” , vacuolar TOR-associated protein . Connections between the TOR pathway and rhythmicity have been reported in other organisms . There are several reports that TOR pathway activity is rhythmic and most of these studies implicate the TOR pathway as an element of output pathways , communicating clock information to drive downstream rhythmic processes . In the chicken retina , phosphorylations of mTORC1 and S6K are rhythmic , and inhibition of mTORC1 dampens the amplitude of rhythmic ion channel activity [51] . In the brain of Drosophila , expression of the Tor gene shows a bimodal pattern in light/dark cycles , and rhythmic changes in neuron morphology depend on expression of Tor [52] . An important output of the clock is gene expression; the role of the circadian clock in regulating gene transcription is well known , and recent findings have shown that the clock is also able to regulate specific genes at the level of translation in several organisms [53 , 54] including Neurospora [55] . The TOR pathway can play a role in this translational regulation: in mouse cells , mTORC1 activity is rhythmic [56] , which drives rhythmic phosphorylation of 4E-BP1 and rhythmic translation of proteins [57] . Rhythmic activation of the mTORC1 target S6K in mice causes rhythmic phosphorylation of the canonical clock protein BMAL1 [58]; this clock protein has now been shown to be a translation factor that regulates rhythmic translation independently of its transcriptional function [58] . Evidence for a role for TOR in the clock mechanism itself is sparse . In Drosophila , TORC1 activity is rhythmic [59] . Overexpression of TOR or S6K lengthens the period [60] , while silencing the Tor gene decreases the period [52] . S6K appears to interface with the clock TTFL through phosphorylation of the kinase SGG , which in turn phosphorylates and regulates TIM protein [60] . In mice , knockout of the tuberous sclerosis complex gene Tsc2 ( an inhibitor of mTORC1 ) results in changes in free-running period and phase-shifting behavior of circadian outputs . These effects apparently result from an increase in BMAL1 levels due to effects of Tsc2 knockout on translation and protein turnover , since the clock effects can be reversed by decreasing BMAL1 levels [61] . Our results with the uv90 gene provide evidence that the TOR pathway and nutritional sensing play a role in the mechanism of rhythmicity in N . crassa , both in the presence and absence of a functional FRQ/WCC TTFL . We have previously identified the clock-affecting PRD-1 gene product as an RNA helicase located in the nucleus [62] . The localization of PRD-1 is responsive to glucose in the growth medium , and the prd-1 mutant is defective in nutritional compensation of the circadian period [63] . Mutations in both uv90 and prd-1 compromise rhythmicity in FRQ-less conditions [33 , 64] , implicating nutritional sensing and metabolism in this system . Because rhythmicity can be studied in this organism in the absence of the TTFL , N . crassa provides a model system for dissecting the role of the TOR pathway in rhythmicity and identifying the molecular mechanisms of the circadian metabolic network . The TOR pathway has been seen as a one-way signaling pathway to promote increased translation in response to extracellular signals of nutritional availability; however , there are indications that the TOR pathway also responds to internal nutritional status and translational rate in a negative feedback loop [5] . This suggests the intriguing possibility that this feedback loop might provide the substrate for the evolution of the oscillator that functions in the absence of the canonical TTFL .
The Oak Ridge ( OR ) and Mauriceville ( MV ) wild types used for mapping were FGSC 4200 and FGSC 2225 and were obtained from the Fungal Genetics Stock Center ( FGSC , Kansas State University , Manhattan , KS ) [48] . Strains carrying gene deletions produced by the Neurospora Functional Genomics Project [65] were also obtained from FGSC . Other strains were generated in our laboratory by standard crossing techniques as previously described [20] . The uv90 mutation was identified in a mutagenesis screen using UV light as previously described [33] . Strains carrying the uv90 mutation were identified by phenotype ( damped or arrhythmic conidiation , depending on genetic background ) , and by molecular genotype ( failure to produce PCR products from NCU05950-specific primers ) . Genotypes of multiple mutant strains were identified by various criteria as previously described [62] . The rasbd mutation renders conidiation resistant to inhibition by high CO2 levels and allows assay of rhythmicity in closed growth tubes . The chol-1 mutation impairs synthesis of the lipid phosphatidylcholine and is carried in most of our strains to allow assay of the FRQ-less rhythm in choline-depleted cultures . When chol-1 is supplemented with choline , the chol-1 defect is repaired and the cultures are indistinguishable from chol+ strains in our assay system . This allows us to assay FRQ-less rhythms that do not depend on choline depletion , such as heat pulse entrainment behavior , in the same genotypes . It should be noted that the csp-1 mutation is included in the genotype of most of the strains used in this work . The csp-1 mutation was identified [66] as a morphological mutation that prevents the separation of conidiospores from aerial hypha , hence the name “conidial separation” ( csp ) . This mutation was introduced a number of years ago into strains utilized for circadian rhythm work [67] as it greatly reduces the contamination of cultures with free-flying spores that can occur with csp-1 wild-type genotypes . The CSP-1 gene product has recently been identified as a transcriptional repressor that affects transcription of a number of genes in response to light [68] . ( Note that our experiments are all conducted in constant darkness , removing the complications of light regulation . ) CSP-1 also dampens the amplitude and shifts the phase of a number of rhythmically-transcribed genes [69] . The gene NCU05950 that we have characterized in this paper is reportedly not controlled by csp-1 [68] . The csp-1 mutation we have used inactivates the DNA binding domain of the CSP-1 protein and is likely to be a null mutation [70 , 71] . This mutation causes a small , 1 h decrease in the period of the circadian conidiation rhythm ( relative to wild type ) on maltose media [25] . A true deletion mutant of csp-1 decreases the period by about 2 hours ( relative to wild type ) on high glucose media but not on low glucose media [71] . This deletion similarly decreases the period of the rhythm of a frq-luc reporter gene by about 2 h but does not dampen the amplitude [71] , indicating that the CSP-1 gene product does not play a major role in the FRQ/WCC TTFL but does provide a small amount of feedback on nutritional state . The CSP-1 gene product therefore appears to primarily function in transcriptional control of output pathways . Our initial report of the phenotype of the uv90 mutation [33] demonstrated that the uv90 mutation dampens the amplitude of the circadian oscillator , as shown by increased responses to light and temperature phase-resetting and dampening of the rhythm of FRQ protein [33] , and therefore the uv90 mutation is not acting on output pathways but rather on the central clock mechanism . The work reported in this paper was initiated before the molecular characterization of csp-1 , and this lab has continued to use the genetic background in which the uv90 mutation was generated and characterized in order to maintain consistency between experiments . In every case in which the phenotype of uv90 or the NCU05950 knockout is assayed , the control strains carry the same genetic background , including csp-1 where indicated , allowing us to conclude that the effects we report are due to the NCU05950 gene and not a variable genetic background . The growth experiments in liquid media in Fig 9B & 9C used csp-1+ strains so that uniform conidial suspensions could be used for inoculation of liquid cultures , and the results using VM medium in race tubes with csp-1 ( Fig 9A ) and in liquid VM using csp-1+ ( Fig 9B ) are comparable . The phenotypes of the uv90 mutation and the NCU05950 knockout have not been assayed in genetic backgrounds other than those indicated in this paper , and therefore we do not have evidence one way or the other as to whether the phenotypes are dependent on a particular genetic background . For the purposes of this paper , the rhythm phenotypes have been used to map the position of the uv90 mutation and to demonstrate the repair of the mutant phenotype by a wild-type copy of the NCU05950 gene , confirming its identity . Therefore the question of whether or not the phenotypes are different in different genetic backgrounds is not relevant to the central findings reported in this paper . For assaying rhythmicity of conidiation , cultures were grown on solid agar medium in glass growth tubes ( “race tubes” ) on media containing 1x Vogel’s salts , 0 . 5% maltose , 0 . 01% arginine and 2% agar , as previously described [62] . Entrainment to heat pulses and data analysis were carried out as previously described [19 , 62 , 64] . For assaying growth rates on various media in race tubes ( Fig 9A ) , growth rates were calculated for each day of growth and it was found that growth rates increased until cultures reached maximum or steady growth rates at day 4 ( or 6 for Phytagel which grew more slowly ) . Therefore growth rates are reported for day 4 only , or day 6 for Phytagel . For S8 Fig , uneven growth patterns were observed for some media . Several days were averaged for some sets , as follows: agar , days 2 , 3 , 4 & 5; VM no N , days 2–3; VM no N + casein , day 1 only; and VM , days 4–5 . Means were compared using the unpaired two-tailed Student’s T-test . For assaying growth rates in liquid media , cultures were grown in 1 ml of appropriate media in 24 well microtiter plates . Strains used were the OR wild type or the NCU05950 deletion mutant with no additional mutations . For inoculation , spore suspensions were made in water and counted so that 500 spores in 0 . 1 ml were inoculated into 1 ml medium in each well . Cultures were grown at 25°C in a 12:12 LD ( light/dark ) cycle . Preliminary time-course experiments showed that the cultures were growing linearly at 48 hours so this was chosen as the time point at which the cultures were harvested . The mycelia were harvested over nylon net filters , washed with water , and dried for 48 hours at 80°C in microfuge tubes that had been pre-dried and weighed empty . The dried samples were weighed and the empty tube weights subtracted to give the net dry weights . Three replicates of each condition were averaged to give one value for each independent experiment , and means were calculated from three or four independent experiments . Means were compared using the unpaired two-tailed Student’s T-test . A cross was made between the original uv90 strain generated by mutagenesis , genotype csp-1; chol-1 rasbd; uv90; frq10 ( mat a ) in the Oak Ridge ( OR ) background , and a rasbd ( mat A ) strain , as previously reported [33] . From the progeny of this cross , a csp-1; rasbd; uv90 ( mat a ) strain was chosen as the parent in a further mapping cross to the Mauriceville ( mat A ) ( MV ) wild-type . Progeny from the second cross were phenotyped for csp-1 by failure of spore separation , and csp-1 progeny were inoculated onto race tubes to assay growth rate and conidial banding to determine rasbd and uv90 phenotypes . Single nucleotide polymorphisms ( SNPs ) between the OR and MV strains were used to map the location of the uv90 gene . The cleaved amplified polymorphic sequence ( CAPS ) marker method [34] uses specific SNPs that either remove or create an enzyme restriction site in either the OR or MV strain . PCR products are amplified from genomic DNA of progeny from a cross between the mutation of interest in the OR background , and the wild-type MV strain . PCR products are cleaved with the restriction enzyme of interest and run on gels; cleaved or uncleaved PCR products indicate which parent contributed that region of the genome , and the recombination frequency between that CAPS marker and the mutation of interest can be determined . Marker 6-68-MspI was from Jin et al . [34] . Marker F9-R9 was from Lambreghts et al [70] . Marker F6-R6 was developed using the method of Jin et al [34] modified as previously described [62] . Other markers were developed using locations of SNPs identified by Pomraning , Smith and Freitag , and posted on the website of the Fungal Genetics Stock Center [72] . CAPS markers were designed to be approximately 400–500 base pairs in length with single restriction sites for the enzyme affected by the SNP . Primers were designed to have GC contents of 50–55% , melting temperatures ( Tm ) of 58–65 oC , and lengths of 20–22 nucleotides . Southern analysis was carried out according to standard procedures [73] . For Fig 1C , genomic DNA was isolated from two uv90+ wild type strains of genotypes csp-1; chol-1 rasbd ( mat a ) and csp-1; chol-1 rasbd; frq10 ( mat a ) , and two uv90 mutant strains of genotypes csp-1; chol-1 rasbd; uv90 ( mat a ) and csp-1; chol-1 rasbd; uv90; frq10 ( mat a ) . Seven additional strains with the uv90 phenotype were also analyzed . DNA was digested with the appropriate restriction enzyme , separated by electrophoresis on 0 . 8% agarose gels , denatured and transferred to nylon membranes . The probe ( 2883bp ) consisted of the NCU05950 gene plus 1kb upstream and downstream sequence , amplified from pBM61-NCU05950 plasmid DNA using the following primers: TCCGGGCCCTCATCTTCCCTGTTGAACTCGTG and ATAAGAATGCGGCCGCCGAATGTTGCATGTCCTTCCA . The labeled probe was made using a digoxigenin labeling kit ( DIG High Prime DNA Labeling and Detection Starter Kit II , Roche ) according to the manufacturer’s instructions and was hybridized to the membrane . After washing the membrane , the signal was detected using an immunochemical method and chemiluminescence was recorded on film or by a CCD camera . The genomic sequence of NCU05950 along with 1kb upstream and downstream ( 2883bp in total ) was amplified from genomic DNA of a csp-1; chol-1 rasbd; frq10 ( mat a ) strain using the same primers as for Southern analysis . The PCR product was inserted into the ApaI-NotI site of the his-3 targeting plasmid pBM61 [74] . The presence of the NCU05950 gene on the recombinant plasmid ( named pBM61-NCU05950 ) was confirmed by PCR , restriction digestion and sequencing . Conidiospores of a csp-1 his-3; chol-1 rasbd; NCU05950KO ( mat a ) strain ( carrying the deletion of NCU05950 ) were transformed with the plasmid by electroporation and his-3+ transformants were selected . Successful integration at the his-3 locus was confirmed by PCR using combinations of plasmid-specific and gene-specific primers . Heterokaryotic transformants were purified by making uninucleate microconidia as previously described [62] . Homokaryotic transformants , genotype csp-1 his-3+::NCU05950; chol-1 rasbd; NCU05950KO ( mat a ) , were confirmed by using PCR primers specific for the his-3 locus . Positive identification of NCU05950 as uv90 required demonstrating that the NCU05950 wild type gene could rescue the defective phenotype of the uv90 mutant . The simplest method would be to transform a his-3; uv90 strain with the his-3 targeting pBM61-NCU05950 plasmid , as was done with the his-3; NCU05950KO strain . For unknown reasons , we were unable to construct a his-3; uv90 double mutant strain in spite of a number of attempts with various combinations of parental strains . Therefore , we adopted a different strategy . A strain of genotype chol-1 rasbd; uv90; frq9 ( mat A ) was constructed to act as female parent in a cross to a csp-1 his-3+::NCU05950; chol-1 rasbd; NCU05950KO ( mat a ) transformant in order to introduce the NCU05950 sequence into the uv90 mutant . The csp-1 mutation , which is carried in most of our laboratory strains , was omitted from the female parental strain because csp-1 makes a poor female parent . The null frq9 allele was introduced instead of the frq10 deletion to allow selection against the NCU05950KO allele by hygromycin sensitivity; both the frq10 and NCU05950KO alleles confer hygromycin resistance and this would complicate the analysis of progeny . All progeny from the cross carried chol-1 and rasbd ( present in both parents ) . Progeny were screened for the csp-1 phenotype and for hygromycin sensitivity . All csp-1 and uv90 mutant ( hygromycin sensitive ) progeny were tested for rhythm phenotypes on race tubes with or without 100μM choline and the four expected classes of progeny were obtained: with or w/o the frq9 mutant allele ( identified by absence or presence of rhythmicity with choline ) and with or w/o his-3+::NCU05950 ( identified by presence or absence of rhythmicity without choline ) . To construct a highly-expressed fusion of NCU05950 and GFP , the NCU05950 coding sequence ( 672bp ) was amplified by PCR from the previously constructed pBM61-NCU05950 plasmid using the following primer pair: GCTCTAGAATGGGCAACTTTTGCTCAACC and CCTTAATTAAACAGCGCATGGCGGCAGCG and inserted into the XbaI-PacI site of the his-3 targeting pCCG::C-Gly::GFP plasmid [75] between the highly-expressed ccg-1 promoter and the 10X Gly linker upstream of the GFP sequence . To construct a fusion protein expressed from the native NCU05950 promoter , the coding sequence with upstream region ( 1651bp total ) was amplified from pBM61-NCU05950 using the following primers: ATAAGAATGCGGCCGCTCGTGGTCCGTTCCTGATG and CCTTAATTAAACAGCGCATGGCGGCAGCG and inserted into the NotI-PacI site of the his-3 targeting pCCG::C-Gly-GFP plasmid , removing the pccg-1 sequence and inserting the NCU05950 sequence upstream of the 10X Gly linker and GFP sequence . Plasmids were transformed by electroporation into conidiospores of a csp-1 his-3; chol-1 rasbd; NCU05950KO ( mat a ) strain . Heterokaryotic transformants were purified by microconidia preparation and the presence of the cloned gene in the homokaryons was confirmed by PCR . Expression of the fusion proteins was confirmed by Western blotting using anti-GFP antibodies . Both the overexpressing and native promoter strains produced a band corresponding to 44 . 6kDa , the predicted size of the NCU05950-GFP fusion protein . The RFP-VAM-3 strain was constructed by transforming the pRFP-Vam-3 plasmid [40] into a csp-1 his-3; chol-1 rasbd ( mat a ) strain to construct a strain of genotype csp-1 his-3+::pCCG-1::tdimer2 ( 12 ) ::vam-3+; chol-1 rasbd ( mat a ) that expresses the RFP::VAM-3 fusion protein from the high expression ccg-1 promoter . Strains carrying deletions of 1 ( G ) , 7 ( GNFCSTC ) or 10 ( GNFCSTCFGG ) amino acids of NCU05950-GFP expressed from the ccg-1 promoter were constructed by replacing either the first 2 , first 8 or first 11 amino acid codons ( see Fig 5 ) with an initiator methionine codon . The pCCG::NCU05950::C-Gly::GFP plasmid was used as the template for PCR , and XbaI and PacI restriction sites were introduced at either end . The following forward primers were used: for 1-deletion , GCTCTAGAATGAACTTTTGCTCAACCTGCTTCGGC; for 7-deletion , GCTCTAGAATGTTCGGCGGTAGGAGGAGCGATGAC; for 10-deletion , GCTCTAGAATGAGGAGGAGCGATGACTACGATGAG . The reverse primer for all three constructs was CCTTAATTAAACAGCGCATGGCGGCAGCG GCATCGG . PCR products were inserted into the XbaI-PacI site of the pCCG::C-Gly::GFP plasmid . Strains carrying deletions of 1 , 7 or 10 amino acids of NCU05950-GFP expressed from the native promoter were constructed by utilizing a SanDI restriction site ( GGGACCC ) 261–267 nt upstream of the start codon , and a BglII restriction site ( AGATCT ) 328–333 nt downstream . Gene sequences between these two sites , but missing either 1 , 7 or 10 amino acid codons as described above , were commercially synthesized ( Integrated DNA Technologies , Inc . , Coralville , IA , USA ) and inserted between the SanDI and BglII sites on the GFP plasmid described above harbouring NCU05950-GFP expressed from its native promoter . Plasmids were transformed by electroporation into conidiospores of a csp-1 his-3; chol-1 rasbd; NCU05950KO ( mat a ) strain . Heterokaryotic transformants were purified by microconidia preparation and the presence of the cloned gene in the homokaryons was confirmed by PCR analysis . Expression of fluorescence from GFP- and RFP-tagged strains was observed in live-cell cultures by confocal microscopy . For Fig 7A , heterokaryons between the RFP-VAM-3 and NCU05950-GFP strains were made by co-inoculating both strains into one culture tube . Several heterokaryon cultures were screened by confocal microscopy to choose one with approximately equal fluorescence intensity in the green and red channels for observation of co-localization . Cultures were grown on agar-covered microscope slides and living hyphae were observed by confocal microscopy as previously described [76] . Young hyphae were imaged using a Bio-Rad MRC 600 confocal laser scanning microscope with a 60x oil-immersion objective . Image contrast was adjusted in Photoshop . Images of older hyphae were collected on a Leica DMI 3000 inverted microscope equipped with an oil immersion objective ( Leica , 100× , NA 1 . 40 ) with a piezo objective drive from Physik Instruments and attached to an Andor DSD2 confocal scanner . System was integrated and supplied by Quorum Technologies ( Guelph , Ontario ) . Images were processed with Volocity software . For Fig 7B , strains with deletions of 1 , 7 or 10 amino acids of the NCU05950 sequence were used . The strains were otherwise similar to the GFP fusion strain in Fig 7A . For Fig 7C , deletion strains were similar to 7B but the GFP fusion genes were expressed from the native NCU05950 promoter . Living hyphae were observed using a Zeiss LSM 700 confocal microscope under 40x oil immersion . Image contrast was adjusted in Photoshop . For S6 Fig , pixel brightness was quantitated to demonstrate localization of the NCU05950-GFP fusion protein at the vacuolar membrane . Three images for each strain were analyzed , and either one , two or three vacuoles per image were quantitated , for a total of six vacuoles per strain . For each vacuole , transects were constructed by drawing six lines of 5 pixels wide starting from the interior of the vacuole and extending across the membrane into the cytosol . Transects were approximately the length of the vacuole diameter and were distributed around the vacuolar circumference , avoiding nearby organelles in the cytosol . The Plot Profile function of ImageJ ( NIH ) was used to measure the mean gray value of the pixels and generate a profile of the pixel brightness of each transect . The profiles of the six transects for each vacuole were averaged . Each mean profile was normalized by dividing each pixel value by the average of the entire profile . The six normalized mean profiles from six vacuoles per strain were then averaged . Because vacuoles were different sizes and the transects were different lengths , it was necessary to align the six transects so the vacuolar membranes were coincident . This was done by aligning the normalized profiles so that the values closest to the average of 1 . 0 on the upward slope of the profile ( corresponding to the interior edge of the vacuolar membrane ) were aligned . The averages of the six normalized transects were then plotted for S6 Fig with the SEM calculated for N = 6 . For quantitation of NCU05950 protein levels by immunoblotting , a FLAG epitope tagged fusion protein expressed from the native promoter was constructed using the same primers and strategy as the GFP fusion protein , but the PCR product was inserted into the his-3 targeting pCCG::C-Gly-3XFLAG plasmid [75] . The plasmid was transformed into a csp-1 his-3; chol-1 rasbd; NCU05950KO ( mat a ) strain by electroporation and transformants were purified by preparation of microconidia . Strains carrying deletions of 1 , 7 or 10 amino acids of NCU05950-FLAG expressed from the native promoter were constructed by utilizing a SanDI restriction site 261–267 nt upstream of the start codon , and a BglII restriction site 328–333 nt downstream . Gene sequences between these two sites , but missing either 1 , 7 or 10 amino acid codons as described for the GFP fusion strains , were commercially synthesized ( Integrated DNA Technologies , Inc . , Coralville , IA , USA ) and inserted between the SanDI and BglII sites on the FLAG plasmid described above . Samples for immunoblotting were grown either in conditions of slow growth in low-glucose liquid media or growing rapidly on top of cellophane overlaid on solid agar . Liquid media cultures were grown using methods modified from Edgar et al . [31] . Conidiospores of the transformant were inoculated into 1 ml high-glucose liquid medium ( VM plus 2% glucose , 0 . 5% arginine , 10 ng/ml biotin , 0 . 2% Tween 80 , 100 μm choline ) in wells of 24-well microtiter plates and allowed to grow at 25°C in constant light ( LL ) for 2 days . The resulting hyphal mats were transferred to 50 ml of low-glucose medium ( VM plus 0 . 03% glucose , 0 . 05% arginine , 10 ng/ml biotin , 100 μm choline ) in 100 ml flasks and shaken at 150 rpm on an orbital shaker . Cultures were transferred to constant dark ( DD ) at various times to set the circadian clock at different phases , from 0 to 48 hours in DD . Samples were harvested by vacuum filtration after 48–56 hours of growth in flasks , frozen in liquid N2 and stored at -80°C . Cultures on sold agar were grown and harvested as described previously [33] . Cultures were grown in 150 mm Petri plates at 22°C on top of cellophane overlaid on the same medium used in race tubes , containing 1x Vogel’s salts , 0 . 5% maltose , 0 . 01% arginine and 2% agar . Cultures were initiated in constant light , transferred to DD at various times , and harvested after 72 hours of total growth . The times of transfer to DD were varied so that the time in darkness at harvest varied from 0 to 48 h . Cultures were harvested by scraping off the final 1 cm of growth at the colony edge , and samples were frozen in liquid N2 . For electrophoresis , samples were ground in liquid N2 and total protein was extracted in boiling SDS buffer ( 50 mM tris pH 6 . 8 , 2% SDS , 10% glycerol , 5 mM EDTA , 1 mM PMSF ) . Protein concentration was assayed by Bio-Rad DC Protein Assay and 0 . 1 M DTT and 0 . 1% bromphenol blue were added before electrophoresis . 20 μg protein was run on 15% acrylamide gels in Tris-glycine-SDS buffers , blotted to Immobilon-P PVDF membranes , and immunodetected using a monoclonal anti-FLAG M2 antibody ( Sigma-Aldrich ) and HRP-conjugated goat anti-mouse secondary antibody ( Origene ) . For quantitation of FRQ protein , 50 μg protein samples prepared as above were run on a 7 . 5% gel , blotted to Immobilon-P and detected using anti-FRQ monoclonal primary antibody and HRP-conjugated goat anti-mouse secondary antibody . The FRQ antibody was generously supplied by M . Merrow [77] and M . Brunner . Chemiluminescence was detected with a CCD camera and quantitated with ImageJ software . UV90 protein was normalized against total protein by staining the membrane with Coomassie Blue after immunodetection . FRQ phosphorylation state was quantitated by calculating the ratio between the density of the upper band of FRQ protein ( highly phosphorylated ) to the density of the lower FRQ band ( relatively dephosphorylated ) . N . crassa sequences were retrieved from the FungiDB database ( http://fungidb . org/fungidb/ ) [78] . Database searches for homologs were carried out using NCBI BLAST software ( https://blast . ncbi . nlm . nih . gov/Blast . cgi ) [79] . Protein domains were identified using the NCBI Conserved Domain search tool ( https://www . ncbi . nlm . nih . gov/Structure/cdd/cdd . shtml ) [80] . Pairwise alignments of protein sequences were made using EMBOSS Needle software ( http://www . ebi . ac . uk/Tools/psa/ ) [81] . Protein secondary structure predictions were made using SPIDER2 software ( http://sparks-lab . org/server/SPIDER2/ ) [82] .
|
Circadian clocks drive 24-hour rhythms in living things at all levels of organization , from single cells to whole organisms . In spite of the importance of daily clocks for organizing the activities and internal functions of organisms , there are still many unsolved problems concerning the molecular mechanisms . In eukaryotes , a set of “clock proteins” turns on and off specific genes in a 24-hour feedback loop . This “clock gene feedback loop” has been the dominant idea about how clocks work for many years . However , some rhythms can still be seen when these feedback loops are not functioning . Using the fungus Neurospora crassa as a model organism , we have discovered a gene that is important for maintaining rhythms that continue without the known feedback loop . We have found that this gene codes for a protein that was already known to be important in helping cells to adjust their growth rate to adapt to varying availability of nutrients . Because the same gene is found in all eukaryotes , including mammals , this finding may point towards a universal clock mechanism that integrates nutritional needs with daily rhythms .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
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"vacuoles",
"tor",
"signaling",
"fungi",
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"organisms",
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"organism",
"systems",
"chronobiology",
"molecular",
"biology",
"techniques",
"mutagenesis",
"and",
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"circadian",
"rhythms",
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"transduction",
"eukaryota",
"cell",
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"crassa",
"phenotypes",
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] |
2018
|
A component of the TOR (Target Of Rapamycin) nutrient-sensing pathway plays a role in circadian rhythmicity in Neurospora crassa
|
Francisella tularensis , the etiological agent of the inhalation tularemia , multiplies in a variety of cultured mammalian cells . Nevertheless , evidence for its in vivo intracellular residence is less conclusive . Dendritic cells ( DC ) that are adapted for engulfing bacteria and migration towards lymphatic organs could serve as potential targets for bacterial residence and trafficking . Here , we focus on the in vivo interactions of F . tularensis with DC following airway infection of mice . Lethal airway infection of mice with the live vaccine strain ( LVS ) results in trafficking of a CD11bhigh/CD11cmed/autofluorescencelow DC subset from the respiratory tract to the draining mediastinal lymph node ( MdLN ) . Simultaneously , a rapid , massive bacterial colonization of the MdLN occurs , characterized by large bacterial foci formation . Analysis of bacteria in the MdLN revealed a major population of extracellular bacteria , which co-exists with a substantial fraction of intracellular bacteria . The intracellular bacteria are viable and reside in cells sorted for DC marker expression . Moreover , in vivo vital staining experiments indicate that most of these intracellular bacteria ( ∼75% ) reside in cells that have migrated from the airways to the MdLN after infection . The correlation between DC and bacteria accumulation in the MdLN was further demonstrated by manipulating DC migration to the MdLN through two independent pathways . Impairment of DC migration to the MdLN , either by a sphingosine-1-phosphate receptor agonist ( FTY720 ) or by the D prostanoid receptor 1 agonist ( BW245C ) , resulted in reduced bacterial colonization of MdLN . Moreover , BW245C treatment delayed the onset of morbidity and the time to death of the infected mice . Taken together , these results suggest that DC can serve as an inhabitation niche for F . tularensis in the early stages of infection , and that DC trafficking plays a role in pathogen dissemination . This underscores the therapeutic potential of DC migration impairing drugs in tularemia treatment .
Dendritic cells ( DC ) are a heterogeneous group of antigen presenting cells ( APC ) , which reside in peripheral tissues , and serve as sentinels for invading microorganisms . Most often , contact of DC with microorganisms results in engulfment of the microorganism , and triggers a series of programmed events ( maturation ) . These include surface expression of MHC class II and of co-stimulatory molecules , induction of cytokine secretion , and degradation of the internalized pathogen , allowing for surface-presentation of its antigens to naïve T cells [1] . The encounter between DC and T cells is facilitated by the induced trafficking of activated DC from the periphery to the vicinal draining lymph nodes . The mechanisms that control DC trafficking appear to be complex . Modulation of the surface display of chemokine receptors ( up regulation of CCR7 expression and down regulation of other receptors ) plays a key role in this process [2] , [3] , [4] . In addition , other effectors including prostaglandins [5] and sphingosine-1-phosphate [6] also play a critical role in DC migration . F . tularensis , the etiological agent of tularemia , is a zoonotic pathogen with a broad host range . Disease manifestations depend upon the route of infection and include ulceroglandular infection , respiratory infection and a typhoidal disease [7] . The high infectivity of certain F . tularensis strains via inhalation led to their classification as a Category-A threat agent . Two subspecies of F . tularensis , F . tularensis subsp . tularensis ( type A ) and F . tularensis subsp . holoarctica ( type B ) are highly infectious to humans yet only the type A bacterium is life-threatening [7] , [8] . Most research on the pathogenesis of F . tularensis has been performed on mice using the live vaccine strain ( LVS ) derived from F . tularensis subsp . holoarctica . This organism shows attenuated virulence in humans but is lethal to mice following pulmonary infection [9] . F . tularensis strains are capable of infecting and multiplying in a variety of cultured cells ( reviewed in [10] ) . The mechanisms used by the pathogen to escape the phagocytic pathway and grow inside cells have been the subject of intense research [11] , [12] , and specific proteins required for intra-macrophage growth were identified . These include members of the iglABCD operon [13] , [14] and the pdpA and pdpD genes contained within a Francisella pathogenicity island ( reviewed in [15] , [16] ) . In many cases mutant strains that are impaired in intra-macrophage growth were also identified as attenuated in murine infection models [12] , [17] . All this led to the accepted notion that intracellular growth is a key mechanism used by F . tularensis to escape host defense . Nevertheless , the direct body of evidence for intracellular growth in vivo is rather meager . Intracellular LVS bacteria were identified by immunostaining in lungs of infected mice [18] and PCR analyses suggest that practically all F . tularensis LVS organisms of bacteremic mice are cell-associated [19] . Nevertheless , the association between LVS and blood cells was recently contested by showing that the majority of F . tularensis recovered from blood of infected mice reside in the plasma [20] . Thus , in spite of the increased efforts in this direction , the various manifestations of the interaction of F . tularensis with host cells , and the role of these interactions in tularemia pathogenesis are far from being resolved . In the present study we have focused on the interactions of F . tularensis LVS with DC in vivo . We show that airway infection by LVS is followed by bacterial colonization of the mediastinal lymph node ( MdLN ) , which occurs in parallel to recruitment of respiratory tract DC ( RTDC ) from the airways to this draining lymph node . Moreover , administration of two different DC migration inhibitors impairs bacteria accumulation in the MdLN , and not less importantly , affects the course of disease . Finally , we show that cells with characteristic DC phenotype that have immigrated to the MdLN from the respiratory tract carry viable intracellular F . tularensis .
Several aspects of bacteria/DC interactions can affect the dynamics of dissemination in the infected host . Among the most relevant ones are cell inhabitation by bacteria and the ability to trigger DC trafficking . These two features were examined in an in vitro LVS-infection system , using bone marrow DC ( BMDC ) as target cells . In accordance with a previous report [21] LVS was found to replicate in BMDC as efficiently as in the macrophage-like J774A . 1 cells ( Figure 1A ) . Pulsing of host cells with bacteria ( even at an MOI as high as 200 ) led to an inefficient cell uptake ( ∼5×104 bacteria were taken up by 106 cells ) . Yet , once bacteria are taken-up by J774A . 1 cells or BMDC , intracellular propagation appeared to be very efficient , resulting in increase of more than two orders of magnitude within 24 hrs . Induction of maturation responses by F . tularensis in APC was examined previously , revealing complex interactions , involving activating as well as inhibitory effects [21] , [22] , [23] . Acquisition of migratory properties is one of the aspects of bacteria-triggered DC maturation and could , in principal , be also subjected to inhibitory effects by LVS . As a first step in examining the effect of LVS/DC interactions on cell migration we have examined surface expression of CCR7 , a receptor involved in DC trafficking from the periphery to lymph nodes [4] , [24] . Flow cytometry analysis of pulsed BMDC revealed a notable increase of CCR7 display ( Figure 1B and 1C ) . As expected , LPS of E . coli , which served as positive control , led to an effective CCR7 induction . Killed LVS bacteria were also found to be effective , though to a lesser extent , in inducing surface display of CCR7 , attesting to the stimulatory potential of LVS pathogen associated molecular patterns ( PAMP ) . Most importantly , live bacteria were as effective as killed bacteria in promoting CCR7 display , arguing against potential abrogating effects exerted by the live pathogen . This is in contrast to the effect of LVS on other markers of DC activation such as TNF-α secretion , where induction occurs with killed bacteria and is abrogated by live bacteria ( not shown ) . It is also interesting to note that display of certain co-stimulatory surface molecules , such as CD83 and CD40 is affected by the viability of LVS ( Figure 1C ) . However , display of other molecules ( e . g . , CD86 ) appears to be efficient following pulsing by live as well as killed bacteria . As an additional step in evaluating DC migratory properties , we have used an in vitro transmembrane chemotaxis assay . BMDC were exposed to various stimulants for 24 hrs and then allowed to migrate through a nylon mesh towards the CCR7-ligand CCL19 ( Figure 1D ) . As controls , we have used non-treated cells and cells exposed to E . coli LPS . Pulsing DC with E . coli LPS led to effective induction of migration towards CCL19 ( 6 folds increase over background ) . Pulsing with LVS bacteria resulted also in induction of cell migration ( about 4 . 5 folds over background ) . Migration appears to be , at least partly , CCR7-dependent since migration in presence of CCL19 is higher than in its absence ( Figure 1D ) . Again , no differences were found between the effects of killed and live bacteria , suggesting that LVS does not exert adverse effects on DC movement induction . Taken together , the in vitro analyses suggest that DC have the potential to serve as replication niches , as well as transport vehicles for LVS . This prompted us to examine these functions in vivo . The interrelationship between F . tularensis and DC in vivo was examined by using a mouse model for respiratory tularemia . As a first step , we have examined the kinetics of LVS dissemination from the respiratory tract to host organs . Mice were infected by intranasal administration of 105 CFU of LVS , which is equivalent to ∼100 LD50 ( LD50 = ∼1000 CFU , our results as well as those of others [9] ) leading to death within 5–6 days . Intranasal administration of LVS resulted in robust proliferation of the bacterium in the airways ( Figure 2A ) , confirming earlier reports [25] , [26] . Bacterial counts in lungs increased by at least three orders of magnitude within 2 days and remained constant as long as mice were alive ( Figure 2A ) . As expected , immediately after infection , bacteria were localized in the broncholaveolar lavage fluid ( BALF ) . In the following days bacterial counts in the lung were divided equally between BALF and lung tissue , and during the late days of infection the relative amount of BALF bacteria was somewhat lower ( Figure 2A ) . Monitoring mediastinal lymph node ( MdLN ) colonization , 24 hrs pot infection revealed viable bacteria , at levels as high as 104 CFU/MdLN ( Figure 2A ) . This number increased to about 106 CFU/MdLN on the second day and then remained unchanged . The accumulation of bacteria in the spleen and liver lagged behind their accumulation in the MdLN . Levels comparable to those found in MdLN at 24 hrs were reached in these organs 48 hrs post infection ( Figure 2A ) . Taken together , these results underline the role of the draining lymph nodes in respiratory LVS infection . MdLN colonization begins very early post airway infection . It occurs immediately after colonization in the primary infection site ( lung ) , and precedes the spreading of the pathogen to distant organs such as spleen and liver ( Figure 2A ) . The rate of LVS accumulation in the lymph node is very rapid , close to two orders of magnitude within 24 hours , resembling LVS propagation in tissue cultures at optimized conditions ( compare Figure 1A and Figure 2A ) . It is interesting to note that the maximal number of organ-associated bacteria in MdLN is 106 CFU/organ , compared to 107CFU/organ in spleens and livers , which are about 100 folds larger in size . To better characterize the robust colonization of the draining lymph nodes by LVS , we searched by light microscopy for bacterial localization in cryo-sections of MdLNs 72 hrs post airway infection . This led to identification of distinct bacteria-containing infection foci in LVS infected MdLNs . Most notable are rare ( 1–2 per cross section ) , yet very expanded foci carrying a large number of bacteria ( Figure 2B ) . The average number of LVS per cross section of such a focus was found to be 100–200 ( such large clusters could not be revealed 24 hrs post infection ) . Simple geometrical calculations suggest the presence of more than 103 bacteria per one global focus . This morphological feature implies an in-situ clonal expansion of bacteria that have entered the lymph node at an early stage . Thus , bacterial accumulation in the MdLN is not a mere reflection of bacterial influx from other organs . It should be noted that at the same time point ( 72 hrs post infection ) , one could find also much smaller foci ( not shown ) that could have been formed by bacteria entering the MdLN at a later stage . Taken together , our observations suggest that colonization of the draining lymph node is a major step in bacterial dissemination , following airway infection with LVS . Once the kinetics of bacterial spreading was defined , we have examined the cellular events related to respiratory infection of mice by LVS . We have focused on phagocytic cells of the monocytic lineage , and restricted the study to the early infection sites: the respiratory tract and the MdLN . In general , the respiratory tract monocytic phagocytes can be defined by surface display of two markers , CD11c and CD11b [4] , [27] and can be differentiated into alveolar macrophages and pulmonary DC by virtue of their autofluorescence ( AF ) level . Macrophages are defined by high AF , whereas pulmonary DC exhibit low AF [28] . Analysis of single cell suspensions derived from the MdLN , two days post intranasal infection revealed the presence of cells that are CD11cmed/CD11bhigh ( Figure 3A , top ) , of cells that are CD11cmed/AFlow ( Figure 3A , center ) , as well as of cells that are CD11bhigh/AFlow ( Figure 3A , bottom ) . These three populations are represented at comparable levels ( ∼7% ) , attesting to the presence of a CD11cmed/CD11bhigh/AFlow cell population in the MdLN . The appearance of such cells in the MdLN is infection-dependent , since background levels of this population are ∼10 times lower in non-infected animals ( Figure 3A , left panels ) , as well as in mock infected mice ( PBS instillation , not shown ) . The phenotype of the CD11cmed/CD11bhigh/AFlow cell identified in the MdLN matches accurately the phenotype of an identical population , identified in lung tissue ( plotting of CD11b vs . AF is shown in Figure 3B ) . The appearance of this population in the lung is not dependent on infection . Analysis of cells derived from the BALF revealed this same population , but also revealed a distinct population of CD11bmed/AFhigh cells ( Figure 3C ) which happens to be also CD11chigh ( not shown ) . The phenotype of these CD11chigh/CD11bmed/AFhigh cells and their presence in the BALF prompted us to define them as alveolar macrophages ( AMΦ ) . The CD11cmed/CD11bhigh/AFlow population , on the other hand , was defined as a subset of respiratory tract DC ( RTDC ) , relying on previous characterizations of such populations [4] , [28] . The definition of these cells as DC is further supported by surface expression of MHC class II ( not shown ) . The kinetics of RTDC recruitment to the MdLN following infection with 105 CFU of LVS is marked by a burst in cell influx on day 2 ( Figure 4 ) reaching levels close to 105 RTDC per lymph node . This is followed by a decline at later days . The representation of RTDC cells on the first day post infection with 105 CFU was not higher than background levels measured in non-infected mice ( Figure 4 ) . Nevertheless , when infection dose was increased from 105 to 107 CFU , one could clearly detect recruitments of RTDC , as early as 24 hours post infection ( not shown ) . In order to define the origin of the DC imported to the MdLN , we have labeled the respiratory tract cells by vital staining [29] . The orange cell tracer CMTMR was administered to mice by intranasal instillation , five hours prior to intranasal infection by LVS . MdLN cells were isolated on the next day , and examined for presence of CMTMR and for DC-marker expression . In this protocol we have used an infection dose of 107 CFU , which allowed early monitoring of cell trafficking . Flow cytometry analysis revealed MdLN cells carying CMTMR , which also express CD11c ( Figure 5A and 5B ) . One such cell population which is CMTMR+/CD11cmed exhibits a ∼4 fold increase following infection , indicating migration of CD11cmed cells from the respiratory tract to the draining lymph node ( Figure 5A and 5B ) . This migration is substantiated by another set of experiments indicating that the CD11cmed cells accumulating in the infected MdLN display on their surface CCR7 ( not shown ) . To further characterize the immigrating cells we have fractionated MdLN cells by magnetic sorting ( MACS ) , using beads coated with anti-CD11b antibodies . Bound and non-bound cell fractions were then analyzed for presence of CMTMR and for surface display of CD11b or CD11c ( Figure 5C–5F ) . Sorting by anti CD11b-coated beads resulted in the expected enrichment for cells expressing CD11b but at the same time in enrichment for cells stained by CMTMR ( Figure 5C ) . Actually 27% of the cells in the CD11b-sorted population were highly positive for both CMTMR and CD11b , as opposed to ∼2% in the non-bound fraction ( Compare Figure 5C and 5E ) . Sorting by CD11b also resulted in a comparable enrichment for cells that were CD11c positive ( Figure 5D and 5F ) , leading to 23% representation of CMTMR+/CD11c+ cells ( Figure 5D ) . Moreover , closer examination of the sorted cells reveals a correlation between high uptake of the viable dye and intermediate expression of CD11c . The viable staining experiments provide indication to the trafficking of cells expressing both CD11c and CD11b from the respiratory tract to the draining lymph node in the infected animal . This result together with the observed accumulation of RTDC in the infected MdLNs attests to an LVS-induced trafficking of DC in vivo . The in vivo trafficking of both viable LVS ( Figure 2 ) and of DC to the MdLN ( Figure 5 ) as well as the in vitro infection results ( Figure 1 ) , led us to search for association between host cells and LVS in the infected lymph node . As a first step in evaluating the localization of bacteria in the MdLN cells , we have subjected single-cell suspensions , obtained 48 hours post intranasal infection , to a gentamicin protection test . About 10% of the bacteria found in the cell suspensions survived gentamicin treatment ( Figure 6A ) , suggesting that this bacterial population is localized within cells and is therefore not accessible to the antibiotic . The other approach used to identify cell-associated bacteria was based on differential centrifugation and provided similar results . Mild spinning ( 200 g , 10 min ) resulted in a supernatant containing ∼90% of the MdLN bacteria and a cell pellet containing ∼10% of the bacterial content ( Figure 6A ) . To characterize the cells that carry LVS , we have subjected washed MdLN cell suspensions to magnetic cell sorting by beads conjugated to anti-CD11b antibodies ( Figure 6B , top panel ) . Fractionated cells were then analyzed for association with LVS . The amount of viable bacteria , per a given number of anti-CD11b bound cells was found to be 1000 folds higher than that in the unbound fraction ( Figure 6B , top ) . Moreover , the actual amount of bacteria in the unbound fraction is in good agreement with the residual amount of ∼0 . 5% CD11b+ cells found in this fraction ( data not shown ) . Altogether this suggests a specific association between LVS and CD11b+ cells in the infected lymph node . Flow cytometry analysis of the CD11b-MACS sorted cells revealed that , as expected ( Figure 3 and Figure 5 ) , bound cells display on their surface CD11c in addition to CD11b . This led us to sort infected MdLN cells by anti-CD11c microbeads as well ( Figure 6B , bottom panel ) . Results of this fractionation were very similar to those obtained by CD11b MACS sorting ( compare top and bottom panels of Figure 6B ) . The amount of viable bacteria , per a given number of anti-CD11c bound cells was found to be ∼500 folds higher than that in the unbound fraction ( Figure 6B , bottom ) . Thus , LVS appears to associate with CD11b+ as well as CD11c+ cells . In order to determine if the observed bacteria/cell association reflects intracellular residence of LVS , CD11b sorted cells from infected MdLNs were subjected to gentamicin protection tests ( Figure 6C ) . The number of viable bacteria was not affected by pretreatment with gentamicin , indicating that LVS indeed resides inside CD11b+ cells . Moreover , when gentamicin-treated cells were lysed with saponin , the number of measurable viable counts was higher by ∼4 folds , indicating presence of several bacteria within one cell . As expected , lysis of cells prior to antibiotic treatment , relieved cell protection , and rendered all bacteria sensitive to gentamicin . To substantiate the intracellular localization of bacteria in DC of infected lymph nodes , the CD11b sorted cells , as well as CDb11c sorted cells were stained with antibodies specific to LVS . Microscopic analysis revealed cells carrying LVS ( Figure 6B , insets ) . These cells were not very abundant; nevertheless , in almost all cases more than one bacterium was associated with a single cell . Taken together , the results presented in Figure 6 reveal that viable LVS bacteria reside within MdLN cells that exhibit an RTDC phenotype . To examine the origin of the CD11b-sorted , LVS-carrying cells , we have resorted to in vivo vital staining . Cells lining the respiratory tract were stained with CMTMR , as described above ( Figure 5 ) , animals were sacrificed 2 days later , and single cell suspensions derived from the infected MdLNs were first subjected to flow cytometric analysis ( Figure 7A ) . The bound fraction contained , as expected , a substantial amount of fluorescent cells , about 20% of which exhibited fluorescence levels higher then background autofluorescence . These and were therefore defined as CMTMR stained cells ( Figure 7A ) . Only trace amounts of this population were present in the non-bound fraction . Sorted cells were mounted on chamber slides , and were screened by fluorescence microscopy for the presence of the intracellular orange CMTMR staining , as well as presence of cell-associated bacteria . This resulted in identification of CMTMR+/LVS+ cells , CMTMR+/LVS− cells , and CMTMR−/LVS+ cells ( representative cells are shown in Figure 7B ) . The relative distribution of these cell types ( Figure 7C ) revealed a strong linkage between CMTMR staining and presence of intracellular bacteria . Screening of 1000 cells which were not bound to CD11b , failed to reveal any CMTMR+ cells , and revealed only two CMTMR− LVS-carrying cells . Screening of 2200 CD11b-bound cells revealed 220 cells that carried CMTMR at levels sufficient to allow microscopic detection . Of these CMTMR+ cells , as much as 38% were found to carry bacteria . In contrast , only 2 . 5% of the CD11b-bound cells , which were not stained by CMTMR were found to carry bacteria ( Figure 7C ) . To further define the intra-cellular residence of LVS , we counted the number of bacteria in the individual cells . The average number of bacteria in the CMTMR+ cells was found to be 5 . 2±3 . 5 , and that in the CMTMR− cells 2 . 8±1 . 9 . When the total number of bacteria residing in these two cell populations is calculated ( 440 in CMTMR+ cells and 140 in CMTMR− cells ) , it becomes evident that as much as 75% of the bacteria associated with CD11b-sorted cells reside within newly imported cells . While the actual number of bacteria per cell in the CMTMR− population does not seem to be very different from that in the CMTMR+ population ( 2 . 8 vs 5 . 2 ) , the statistical significance of the difference is very impressive ( P<10−5 , Figure 7C ) . This implies that the events leading to bacterial residence in these two cell populations are different . Taken together , these results attest to preferential bacterial residence in cells that have recently immigrated from the airways to the MdLN . These results also imply that two cell-infection mechanisms take place during airway infection; one occurs in the airway at the early stages of infection , and the other occurring later on , either in the airways or in the lymph node . The residence of intracellular bacteria in RTDC , and more specifically in newly-immigrated MdLN cells suggests that DC play a role in F . tularensis trafficking . To further examine this point , the effect of RTDC migration-impairment on bacterial dissemination was tested using FTY720 ( fingolimod ) , a sphingosine analogue . FTY720 counteracts the functions of the sphingosine-1-phosphate ( S1P ) , and thereby impairs cell migration [30] . FTY720 inhibits lymphocyte egress from lymphoid tissue , and was also found to inhibit migration of lung DC to the MdLN [6] . FTY720 in its carrier solution , or carrier solution alone were administered intranasally to mice , concomitantly to infection . MdLNs were analyzed two days later by flow cytometry . The MdLN of infected , mock-treated , animals carried the distinct CD11bhigh/autofluorescencelow cell population ( Figure 8A ) , which defines RTDC recruitment ( Figure 3 ) . In mice treated with FTY720 , this population was brought down to background levels ( Figure 8B and 8C ) , indicating that FTY720 impairs very effectively the LVS-triggered RTDC migration to the MdLN . The FTY720 treatment resulted also in a substantial reduction in the LVS counts in the MdLN ( Figure 8D ) . Mock-treated mice carried 1 . 3×106±0 . 9×106 live LVS in the MdLN . This number was reduced by two orders of magnitude in FTY720 treated mice , reaching values of 1 . 1×104±0 . 5×104 . Thus , administration of a S1P analogue to the airways of LVS infected mice impairs effectively recruitment of RTDC to the MdLN , as well as colonization of this organ , implying that these two events are linked . To substantiate the observed correlation between DC and LVS trafficking , we examined the effects of an additional inhibitor of DC-migration , which is known to act through a different mechanism . We have chosen BW245C , a D prostanoid receptor 1 ( DP1 ) agonist , known to inhibit in vivo migration of Langerhans cells [31] , [32] as well as airway DC [5] . BW245C was administered by two intranasal instillations , one immediately prior to LVS inoculation , and the other 24 hours later . The effect of agonist administration on recruitment of DC and bacteria to the MdLN was examined 48 hours post infection . The BW245C treatment resulted in a marked reduction in the representation of RTDC in the infected lymph node ( Figure 9A ) . While ∼7×104 of the MdLN cells exhibited the RTDC phenotype in LVS infected mice , DC representation in infected mice , treated with BW245C was reduced to ∼2×104 . It should be noted that background levels in non-infected mice , either treated or not treated with the agonist , remained ∼0 . 6×104 . The effect of BW245C on the infection-dependent DC recruitment was accompanied by a significant impairment of MdLN colonization by LVS ( Figure 9B ) . The average number of viable bacteria in the draining lymph nodes 48 hours post airway infection was 480 . 000±180 . 000 . This number was reduced to 75 . 000±21 . 000 upon treatment with BW245C . It should be noted that treatment had no effect on the number of bacteria or of DC in the lung , excluding possible bacteriostatic/bacteriocidic or cytotoxic effects of the drug in vivo . Taken together , these results provide additional evidence to the linkage between the accumulation of RTDC and of viable bacteria in the draining lymph nodes following infection . To examine the effect of the DP1 agonist on the course of experimental respiratory tularemia , infected mice were subjected to a short treatment by intranasal instillation of BW245C as described above . Animals were monitored for survival in comparison to infected , sham-treated ( instillation of carrier only ) animals . Results presented in Figure 9C indicate that the short treatment ( day 0 and day 1 ) resulted in a delay of one day in the time to death of mice . Mean time to death without treatment was 6 . 4 , as compared to 7 . 5 following treatment . This difference appears to result from a treatment-dependent delay in the onset of the disease manifestations . Monitoring of animal morbidity revealed significant differences ( Figure 9D ) in the kinetics of weight loss in treated vs . non-treated mice . The first day is marked by a moderate weight loss in all animals , which stems from the instillation procedure itself , as the same loss is also observed in treated non-infected mice . Nevertheless the disease-induced weight loss starts after day 1 in infected non-treated animals and after day 2–3 in treated animal ( Figure 9D ) . Similar experiments , conducted with FTY720 were marred by the intrinsic long-term pleotropic effects of this agonist on lymphocyte mobilization [30] . A single FTY720 instillation into infected animals resulted in a somewhat prolonged mean time to death , but did not alleviate weight loss ( not shown ) . In summary , treatment with a DP 1 agonist , like treatment with an S1P analogue has a marked effect on DC recruitment to the draining lymph node and on bacterial colonization of the lymph node . This treatment also delays the time point at which disease becomes apparent , and the time of death of the infected animals .
DC play a key role in surveillance for pathogen invasion through skin and mucosal epithelium . DC are highly adapted for sampling , killing and processing microbes , and for trafficking the processed material to regional lymph nodes for antigen presentation . Impairment of certain DC functions by pathogens has been addressed by numerous studies during the last years ( reviewed in [33] ) , yet much less is known about the specific interplay between DC migration and microbial infection . One can envision two ways by which manipulation of DC migration could enhance microbial invasiveness . DC/pathogen interaction could impair DC migration to the draining lymph node [34] , [35] , and thereby interfere with the onset of immune responses . Alternatively , hijacking of the DC migration process by intracellular pathogens and its adaptation for dissemination of live microbes [36] , [37] could provide an advantageous mechanism for subverting the immune system , and at the same time facilitate the progress of infection . In the present study we examined the dynamics of DC trafficking in mice infected with F . tularensis LVS . It is widely accepted that bacterial PAMP trigger migration of DC through TLR-mediated induction of surface display of the chemokine receptor CCR7 . The ability of live LVS to trigger this process is not self-evident . LVS carries on its surface an atypical LPS which is limited in its capacity to interact with cellular TLRs [38] , [39] , [40] , and could therefore be handicapped in triggering signal transudation involved in cell trafficking . Moreover , LVS can actively abrogate activation processes within immune cells , as indicated by the observed effect of live LVS on expression of certain co-stimulatory DC markers ( Figure 1C ) , as well as on expression of pro-inflammatory cytokines ( our unpublished results and those of others [22] , [23] ) . In spite of all this , pulsing of BMDC in vitro with LVS resulted in induction of notable , surface expression of functional CCR7 ( Figure 1B and 1D ) . To examine manifestations of these migratory properties in vivo , a mouse model based on airway infection of mice by LVS was employed , and migration of DC from the infection site to the draining lymph node was analysed . Identification of such DC is complicated by the unique features of respiratory tract APC . Several populations of monocytic phagocytes were identified in the different anatomical compartments of lung [27] , [41] , and moreover , APC in the pulmonary tract exhibit unusual phenotypes . On one hand , CD11b which is considered to be a typical marker for macrophages , is low in alveolar macrophages yet appears on certain pulmonary DC . On the other hand , CD11c which is routinely used as marker to identify DC in peripheral lymphoid organs is also present on pulmonary macrophages ( reviewed in [42] , [43] , [44] ) . In an attempt to define RTDC populations affected by LVS we have examined lungs of infected mice for expression of CD11c and CD11b and identified two major integrin-expressing populations . One population that is present only in the BALF is characterized by high expression of CD11c , low expression of CD11b and high autofluorescence ( Figure 3B ) and thus exhibits the characteristics of alveolar macrophages . The other major population can be defined as a RTDC subset ( Figure 3A and 3B ) , as it exhibits low autofluorescence [28] , [45] , high CD11b expression [4] , [46] , [47] , intermediate level of CD11c [48] , [49] and also high surface expression of MHC class II ( not shown ) [50] . The phenotypic definition of the relevant cell populations ( Figure 3 ) , prompted us to search for cell trafficking to the MdLN . This led to the identification ( Figure 4 ) of infection-dependent recruitment of RTDC to the draining lymph node , with no apparent recruitment of AMΦ . Moreover , our experiments suggest that cells have been imported from the infected respiratory tract . The phenotype of the cells matches accurately the phenotype of DC identified in lung tissue and BALF ( Figure 3 ) , and cells were shown to carry a vital dye ( CMTMR ) , instilled into the respiratory tract prior to infection ( Figure 5 ) . Taken together our findings indicate that in vivo interactions between F . tularensis and DC can induce the signaling process leading to cell migration from the infection site to the draining lymph node . This observation substantiates the prevailing notion that DC but not macrophages are the primary migratory APC following invasion of the airways . We show that such a migration is induced not only by soluble antigens [50] and inert particles and spores [4] , [51] , but also by viable respiratory pathogens . Moreover , the DC that take part in this process are identified as a specific subset of CD11cmed/CD11bhigh RTDC . The CD11bhigh DC-subset was recently distinguished functionally from the CD11blow subset , and was associated with directing leukocyte trafficking during lung inflammation [37] , [46] , [52] . Another part of this study was dedicated to bacterial spreading following airway infection with LVS ( Figure 2A ) . We show that infiltration of MdLN by bacteria is a very early event ( occurring during the first day of infection ) , resulting in a massive load of bacteria accumulating in the lymph node , at a very high rate ( Figure 2A ) . These results , which characterize infection by LVS as well as by the Schu4 strain [22] suggest that colonization of draining lymph nodes is an important stage in bacterial spreading . Moreover , microscopic analysis of MdLN from LVS infected mice at the late stages of infection reveal large foci of infection carrying tens of bacteria , suggesting in situ replication of a clonal nature , i . e . single bacteria infiltrating the tissue at early stages have replicated in the lymph node to generate a large condensed focus . All this underlines the major role played by tropism for lymphatic organs in F . tularensis pathogenesis . It is tempting to speculate that the invading bacteria are carried into the MdLN by immigrating RTDC . The rate of bacterial spreading from the infected airways actually supports such a model . Bacteria can be detected in MdLNs at substantial amounts , as early as 24 hrs post infection , and this correlates well with short time frames reported for transport of soluble or particulate antigen from the airways to the draining lymph nodes in mice [4] , [50] , [51] , [53] . Nevertheless , comparison of the kinetics of bacterial inhabitation of the MdLN to those of DC recruitment reveals that bacteria are detected in the lymph node at least one day prior to a notable increase in DC numbers ( compare results of infection with 105CFU in Figure 2A and Figure 4 ) . One should note , however , that the sensitivity of detecting bacterial import is much higher than that for detecting DC import . One can easily detect the presence of several CFU in the MdLN , whereas detection of newly immigrating DC over a background of ∼1% representation is difficult ( Figure 3A and Figure 4 ) . Actually , one cannot preclude the possibility that LVS infection triggered the immigration of ∼103 DC ( ∼10% of the observed background ) on the first day of infection and that these cells are instrumental in spreading the infection . Indeed when intranasal infection dose was increased from 105 to 107 CFU newly immigrating DC were identified 24 hrs post infection ( Figure 5 ) , indicating that early recruitment does occur , and suggesting that the extent of recruitment is dependent on the bacterial load in the respiratory tract . As a first step in defining the correlation between LVS and DC accumulation in the draining lymph node , we have identified intracellular inhabitation of LVS in MdLN cells . LVS-carrying cells could be enriched by magnetic sorting for expression of CD11c as well as CD11b . The similar efficiency of the two sorting processes ( Figure 6B and 6C ) in retrieving cell-associated bacteria suggests that LVS-containing cells express CD11c as well as CD11b on the same cell . CD11c and CD11b expression , which characterizes monocytic phagocytes is not exclusive to DC , yet presence of such cells in MdLNs following airway infection would argue for their definition as RTDC [4] . The cell-associated bacteria were found to be viable , as indicated by their ability to form colonies and are located within the cells , as indicated by their resistance to antibiotics ( Figure 6C ) . These observations provide one of the more solid indications to the localization of live F . tularensis in cells of the infected host , and identify the RTDC as an in vivo niche for pathogen residence . The fact that most cells carry several intracellular bacteria probably reflects intracellular replication of LVS , rather than simultaneous uptake of several bacteria by an individual cell . While MdLN DC appear to carry LVS , one cannot overlook the presence of a large extracellular bacterial load in the infected MdLN ( Figure 6A ) . This finding underlines the long and unresolved debate on the interrelationship between the intracellular and the extracellular life styles of F . tularensis , and their relevance to pathogenesis . While extracellular bacterial trafficking per se cannot be excluded , one can envision an infection mechanism that involves uptake of LVS by DC in the airways [18] , [21] and import of bacteria-harboring DC into the MdLN followed by apoptosis-mediated ( our unpublished results and those of others [14] ) release of bacteria from the cells . Such a model would imply an initial stage of intra-DC residence required to overcome early host defense mechanisms , which is then followed by an extracellular colonization process , and possibly re-infection of more cells A major support for the function of RTDC as transporters of LVS comes from the in vivo viable staining experiments ( Figure 7 ) . Staining of infected airway cells with CMTMR allowed us to determine that a major fraction of the CD11b-sorted , LVS-carrying cells are newly-immigrating cells , recruited from the respiratory tract to the MdLN after infection ( Figure 7 ) . Moreover enumeration of intracellular bacteria revealed that the about 75% of the bacteria carried by CD11b-sorted cells actually reside in the newly-immigrated cells . The preferential presence of intracellular LVS in newly-immigrating RTDC ( Figure 7C ) provides very strong support to DC-mediated , LVS trafficking . In order to address the less-likely possibility of preference in LVS uptake by the newly-immigrating within the MdLN , we have treated mice with inhibitors of DC migration . Trafficking of DC from the infection site is governed by a variety of mechanisms . The most characterized mechanisms relate to controlled change of the surface-displayed chemokine receptors repertoires . Other mechanisms involve sphingosine-1-phosphate [6] , [54] , scavenger receptor A [55] , osteopontin [56] and prostaglandins [5] , [42] . It should be noted however that these mechanisms do not act exclusively on DC migration , and often exhibit pleotropic effects . This led us to examine two independent experimental systems . One system is based on FTY720 , which desensitizes the S1P receptor , and thereby inhibits lymphocyte migration [30] . The other system is based on BW254C , a prostaglandin D1 analogue which interacts with the cognate DP1 receptor to inhibition of DC migration [5] , [42] . Choosing these two effectors allowed us to use a drug that hampers positive migration signals , as well as an agonist that activates a physiological migration-impairing signal . In spite of the major difference in their mode of action , treatment with either FTY720 or BW245C at the early stages of infection resulted in similar effects , impairment of both RTDC recruitment and LVS colonization of the MdLN ( Figure 8 and Figure 9 ) . Interestingly , the effect of FTY720 treatment on RTDC migration-impairment was more pronounced than that of BW245C ( Compare Figure 8A and 8B and Figure 9A ) . This was translated into a more effective inhibition of bacterial dissemination by FTY720 than by BW245C ( Compare Figure 8D and Figure 9B ) , providing additional support to the linkage between RTDC and LVS trafficking . Instillation of each one of the migration-impairing agents to airways of infected mice prolonged disease progression . We chose , however , to concentrate on BW254C which is a drug of short-residence , and not on FTY720 which has long term effects , and therefore could influence later stages of disease . Instillation of the BW254C on days 0 and 1 of infection delayed the onset of morbidity by two days , and delayed the time of death by one day ( Figure 9C and 9D ) . This again argues for a DC-driven bacterial spreading . Taken together , all the observations presented here suggest that F . tularensis can inhabit DC in vivo , and DC migration can play a role in enhancing the invasiveness of the pathogen . In addition , this study provides guidelines to the development of a novel potential therapeutic strategy against respiratory tularemia . A treatment , based on impairment of DC trafficking could delay the onset of disease and provide an adequate window for the identification and the application of a suitable antibiotic treatment .
Francisella tularensis live vaccine strain ( ATCC 29684 ) stocks were plated on GCHI agar ( GC Medium base , Difco , supplemented with 1% hemoglobin and 1% Iso-Vitalex BD , France ) . Working stocks were prepared from single individual colonies exhibiting the large-light phenotype [57] . For cell and animal infection experiments , bacteria were grown at 37°C to mid log phase ( optical density of 0 . 1–0 . 2 at 660 nm ) in TSBC ( TSB Difco , supplemented with 0 . 1% cysteine ) in a gyrostatory shaker . Bacteria were washed and then re-suspended at the desired concentration in either PBS for animal infection experiments , or RPMI 1640 medium ( see below ) , devoid of antibiotics , for cell infection experiments . Killed bacterial suspension were generated by incubating growth cultures , overnight , at room temperature in the presence of 0 . 4% formaldehyde , followed by extensive washing with PBS . BMDC were generated essentially according to the method developed by Lutz et al . [58] as described in detail previously [34] . More than 95% of the cells were CD11c positive as assessed by flow cytometry , indicating effective differentiation into DC . BMDC as well as the J774A . 1 macrophage–like cells were grown in RPMI 1640 medium supplemented with 10% FCS , 2 mM L-glutamine , 1 mM sodium pyruvate , 1% v/v MEM-EAGLE non-essential amino acid solution , 100 U/ml penicillin , 100 µg/ml streptomycin and 50 µM β-mercaptoethanol; all these components were supplied by Biological Industries ( Beit Haemek , Israel ) . BMDC ( 106 cells/well in 24 well plates in supplemented RPMI devoid of antibiotics ) were infected by pulsing with bacteria at an MOI ( multiplicity of infection ) of 200 . Infection was initiated by spinning ( 140 g , 5 min ) bacteria onto plated cells ( this is referred to as time point 0 of infection ) . Pulsed cells were incubated at 37°C , 5%CO2 for 1 h before adding gentamicin ( Sigma ) at a concentration of 2 µg/ml . Incubation was then continued for additional 23 hours prior to analysis . In an alternative protocol , gentamicin-containing medium was replaced by fresh gentamicin-free medium after 2 hrs . This had no effect on bacteria counting . It should be pointed out that extracellular LVS did not propagate in the eukaryotic-cell growth medium , as noted by others as well [13] , [59] . Infected cells were resuspended in RPMI containing 1% FCS to a concentration of 107 cells/ml and were placed ( 106 cells/well ) in the upper compartments of Transwell migration chambers ( Costar 3421 , Corning , NY ) . CCL19 ( R&D Systems ) diluted to concentrations of 200 ng/ml in RPMI+1% FCS was placed in the lower compartments to induce CCR7-dependent chemotaxis . Medium alone served to evaluate CCR7-independent migration . DC were allowed to migrate through a polycarbonate ( 5 µm pore size mesh ) at 37°C for 2 h , and cells migrating to the lower compartment were counted under light microscope . The experiments were performed in triplicates and migration was determined by calculating the percentage of migrating cells relative to input . Lipopolysaccharide ( LPS ) pulsing was conducted by application of 1 µg/ml of Escherichia coli LPS ( Sigma ) . C57BL female mice ( 8–10 weeks old ) were used in most infection experiments . Some experiments were repeated using BALB/c mice as indicated . Mice anesthetized with ketamine/xylazine were infected intranasally by careful application of 25 µl LVS suspension at the desired concentration . Bronchoalveolar lavages were performed on anesthetized mice through a 23-gauge catheter inserted into the trachea . Doses of 1 ml cold PBS were infused into each mouse and then aspirated from the airways . Animals were sacrificed by cervical dislocation and the desired organs were collected . Isolated organs were minced and treated with Liberase Blendzyme 3 ( Roche ) at final concentration of 2 µg/ml for 30–60 minutes at 37°C , followed by five minute treatment with 100 U/ml of Dnase I ( Boehringer Mannheim ) . This was followed by passage through a cell strainer to obtain single cell suspension . All experiments reported here were conducted in compliance with the guidelines of the animal use committee at the Israel Institute for Biological Research and are in accordance with the Animal Welfare Act . FTY720 and BW245C were both purchased from Cayman chemicals ( Ann Arbor , MI ) . FTY720 was diluted to a concentration of 40 µg/ml in PBS containing 10% ethanol . Twenty-five µl of the FTY720 solution ( final amount of 1 µg ) were administered to anesthetized mice by intranasal instillation at day zero ( 15 min prior to bacterial infection ) BW245C was diluted to a concentration of 0 . 4 mM in 0 . 3% DMSO in water , immediately prior to use . Twenty-five µl of the agonist solution ( final amount of 10 nmol ) were administered to anesthetized mice by intranasal instillation on day zero and on day 1 post infection . Carriers alone were distillated into mock treated animals Infected cell suspensions were submitted to centrifugation ( 140 g , 10 min ) , followed by two washes with PBS , in order to remove non-associated bacteria . When indicated , cells were incubated at 37°C for 30 min in the presence of 20 µg/ml gentamicin , followed by centrifugation and washes for gentamicin removal . Cells were lysed with either 0 . 1% deoxycholate ( DOC ) for 2 minutes or alternatively with 0 . 1% saponin for 30 minutes at 37°C . Bacterial suspensions were submitted to intensive mixing prior to serial dilution and plating on GCHI agar . Washed DC were incubated with PE or APC conjugated antibodies against CD11c ( Clone N418 ) , CD11b ( clone M1/70 ) , CD40 ( clone 1C10 ) , CD83 ( clone Mitchel-17 ) and CD86 ( clone GL1 ) , as well as with the appropriate isotype-matched control antibodies . Reagents were purchased from eBioscience ( San Diego CA ) . Staining was performed using standard incubation protocols ( 30 min at 4°C ) except for CCR7 staining which was conducted at 37°C as indicated by the manufacturer . In all staining protocols , FcR was blocked prior to staining with FCR Block Reagent ( Miltenyi Biotech , Germany ) , according to the manufacturer's protocol . Cells were collected on a FACSCalibur cytometry ( Becton & Dickinson ) , excluding events smaller than 200 on the FSC . Target cells were separated from the lymph node single cell suspension by magnetic microbeads carrying either anti-CD11c or anti CD11b antibodies ( Miltenyi Biotech , Germany ) , using the manufacturer's instructions . Prior to separation , cell suspensions were treated with the FcR Block Reagent ( see above ) . About 108 cells ( pool of 8–10 lymph nodes ) were then incubated with 100 µl of the microbead suspension for 15 min on ice , and washed to remove excess of free beads . Cells were passed through a column attached to a magnet and washed to separate bound and unbound cells . Out of 108 cells submitted to sorting , about 106 cells were bound to either anti-CD11c or anti-CD11b microbeads Migration of cells from the airways to the peripheral lymph node was evaluated by tracking cells labeled by viable staining [29] , [34] . Briefly , the orange cell tracer CMTMR ( Molecular Probes , OR ) was diluted in RPMI to a concentration of 8 mM and 30 µl/mouse were administered intranasally to mice anesthetized with ketamine/xylazine . Five hours later mice were instilled with 5×106 bacteria per mouse ( 25 µl of bacterial suspension in PBS ) . At the indicated time post addition of bacteria , MdLNs were isolated , shredded and treated with 2 µg/ml Collagenase-D ( Roche ) for 30 min at 37°C . Cells were then passed through a 70 µm nylon mesh to yield a single-cell suspension , and analyzed by FACS . Tissues or cells infected by LVS were examined for the presence of bacteria by fluorescent staining . J774A . 1 cells were cultivated and infected in chamber slides and fixed with 3 . 7% formaldehyde . DC suspensions derived from bone marrow or from lymph nodes were placed in LabTekII chambered glass slides which are capable of binding semi-adherent cells ( Nunc , Roskilde , Denmark ) . Cells were incubated for 20 minute at 37°C to allow binding . The bound cells were fixed with 3 . 7% formaldehyde in PBS for 30 min , followed by washing with PBS . Dissected MdLNs were infiltrated with OCT ( Sakura , The Netherlands ) , snap frozen in liquid nitrogen and transferred to storage at −70°C . Eight-micrometer cryostatic sections were cut and mounted on SuperFrost Plus slides ( Menzel-Galaser , Germany ) . Slides were then fixed by dipping in cold acetone ( −20°C ) for 1 min . Fixed slides were blocked with either 0 . 5% BSA in PBS in the case of infected cell preparations , or with Rodent Block M ( Biocare Medical , CA ) , for infected tissue . Hyper-immune antiserum of rabbits immunized with formalin killed LVS diluted 1/300 served as primary antibody , while normal rabbit serum served as negative control . Texas-Red or FITC-conjugated goat anti rabbit antibodies ( Molecular Probes , OR ) served as second antibody . Stained specimen were examined with an Axiovert 200 inverted microscope ( Zeiss ) equipped with an AxioCAM MRc5 digital camera ( Zeiss ) .
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The high infectivity of Francisella tularensis via inhalation led to its classification as a Category-A bio-threat agent and renewed the interest in this pathogen . Here , we characterize early events in respiratory tularemia , which could be instrumental in designing new therapeutic approaches . We focus on the interaction of F . tularensis with dendritic cells , which serve as first-line sentinels for invading bacteria and are expected to be pivotal in initiation of host protective response . In this study , we show that lethal airway infection of mice with F . tularensis results in accumulation of both bacteria and dendritic cells in the draining lymph node , and that viable bacteria can be detected in dendritic cells that have been recently imported from the airways . The correlation between trafficking of dendritic cell and bacteria is further substantiated by demonstrating that impairment of dendritic cell migration to the draining lymph node through two independent pathways results in decreased bacterial accumulation in the lymph node . Taken together , our observations suggest that F . tularensis actually harnesses dendritic cells to facilitate bacterial dissemination and to enhance host invasion . These findings call for examination of the therapeutic potential of drugs that impair dendritic cell migration as countermeasures for tularemia .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"microbiology/cellular",
"microbiology",
"and",
"pathogenesis",
"microbiology/innate",
"immunity",
"immunology/leukocyte",
"activation"
] |
2008
|
Interrelationship between Dendritic Cell Trafficking and Francisella tularensis Dissemination following Airway Infection
|
Epstein-Barr virus ( EBV ) latently infects most of the human population and is strongly associated with lymphoproliferative disorders . EBV encodes several latency proteins affecting B cell proliferation and survival , including latent membrane protein 2A ( LMP2A ) and the EBV oncoprotein LMP1 . LMP1 and LMP2A signaling mimics CD40 and BCR signaling , respectively , and has been proposed to alter B cell functions including the ability of latently-infected B cells to access and transit the germinal center . In addition , several studies suggested a role for LMP2A modulation of LMP1 signaling in cell lines by alteration of TRAFs , signaling molecules used by LMP1 . In this study , we investigated whether LMP1 and LMP2A co-expression in a transgenic mouse model alters B cell maturation and the response to antigen , and whether LMP2A modulates LMP1 function . Naïve LMP1/2A mice had similar lymphocyte populations and antibody production by flow cytometry and ELISA compared to controls . In the response to antigen , LMP2A expression in LMP1/2A animals rescued the impairment in germinal center generation promoted by LMP1 . LMP1/2A animals produced high-affinity , class-switched antibody and plasma cells at levels similar to controls . In vitro , LMP1 upregulated activation markers and promoted B cell hyperproliferation , and co-expression of LMP2A restored a wild-type phenotype . By RT-PCR and immunoblot , LMP1 B cells demonstrated TRAF2 levels four-fold higher than non-transgenic controls , and co-expression of LMP2A restored TRAF2 levels to wild-type levels . No difference in TRAF3 levels was detected . While modulation of other TRAF family members remains to be assessed , normalization of the LMP1-induced B cell phenotype through LMP2A modulation of TRAF2 may be a pathway by which LMP2A controls B cell function . These findings identify an advance in the understanding of how Epstein-Barr virus can access the germinal center in vivo , a site critical for both the genesis of immunological memory and of virus-associated tumors .
Epstein-Barr virus ( EBV ) is a B-lymphotropic gammaherpesvirus that establishes latent infection in over 90% of the world's population [1] , [2] . Initial infection is usually asymptomatic if the virus is acquired during childhood . Following infection , EBV may persist for the life of the host in resting memory B cells where a limited number of viral genes are expressed [3] . EBV is also associated with a number of B cell malignancies , including Hodgkin's lymphoma , Burkitt's lymphoma , and post-transplant lymphoproliferative disorder , as well as epithelial malignancies such as nasopharyngeal carcinoma . In vitro , EBV has the unique ability of transforming primary human B cells into lymphoblastoid cell lines ( LCLs ) expressing the latency III program of gene products [4] , including six EBV nuclear antigens ( EBNA1 , -2 , -3A , -3B , -3C and -LP ) as well as three latent membrane proteins ( LMP1 , -2A , and -2B ) , and multiple non-coding RNAs ( EBERs and miRNAs ) . LMP1 is a transmembrane protein with a cytoplasmic C-terminal tail that is transforming in vitro [5] and tumorigenic in vivo [6] . LMP1 signaling resembles that of the tumor necrosis factor superfamily member CD40 , expressed on B cells; however , LMP1 signaling is constitutive and amplified [7] . LMP1 and CD40 signaling activate the B cell through downstream kinases and NF-κB , resulting in upregulation of surface costimulatory and adhesion molecules [8]–[10] . LMP1 signaling also plays a role in B cell survival by upregulating Bcl-2 , A20 and Mcl-1 in human B cell lines and murine transgenic lymphomas [6] , [11]–[13] . When expressed under the control of the immunoglobulin heavy chain ( IgH ) promoter and enhancer , LMP1 lineage 3 mice have normal lymphocyte populations , yet LMP1 predisposes to lymphoma development when aged [6] , [14] , [15] . Several transgenic models have demonstrated the immunomodulatory capacity of LMP1 . LMP1 has been shown to block germinal center formation [10] , [16] , and to synergize with CD40 signaling to enhance proliferation and immunoglobulin production [16] . CD40 and LMP1 both utilize the tumor necrosis factor receptor-associated factor ( TRAF ) adaptor proteins for signaling [17] , [18] , but often in opposing ways in different experimental systems [7] , [19] , [20] . In knockout mouse embryonic fibroblasts , TRAF6 , but not TRAF2 and TRAF5 , was required for LMP1 signaling [21] . Compared to CD40 , TRAF3 was shown to be preferentially used by LMP1 in murine B cells , and LMP1 could still signal in TRAF2 null cells while CD40 could not [7] . Conversely , a study using LCLs found that TRAF3 negatively modulated LMP1 activation of NF-κB [8] . Another study showed that TRAF2 was required by LMP1 in LCLs , and TRAF2 expression was controlled by LMP2A [22] . TRAF2 is critical for germinal center functions such as B cell proliferation , class switch recombination , and immunoglobulin secretion [23] , yet findings from TRAF3 null mice suggest that TRAF3 prevents or delays germinal center entry [24] . Based on these arguments , we would hypothesize that LMP1 alters TRAF2 and TRAF3 regulation in vivo and that LMP2A might also affect TRAF regulation to indirectly modulate LMP1 . LMP2A is also capable of eliciting profound effects on B cell function in vivo . LMP2A is a functional homologue of the B cell receptor , and constitutively associates with Src family kinases through its N-terminal cytoplasmic tail to activate Ras/PI3K/Akt [25] and mTOR [26] to signal to NF-κB [22] , [27] . LMP2A is not essential for LCL generation [28] nor B cell proliferation [29] , but appears to promotes survival through upregulation of Bcl-XL and survivin [30] , [31] . Expression of LMP2A under the control of the immunoglobulin heavy chain ( IgH ) promoter and enhancer in the Tg6 lineage produces phenotypically normal B cells which express a BCR , and does not predispose to tumor development [31] , [32] . In certain models , LMP2A overcomes the requirement for BCR expression [31]–[33] , enhances antibody production and plasma cell frequencies [34] , and alters tolerogenic signals induced through the BCR on the transgenic BCRHEL background [27] . The patterns of LMP1 and LMP2A expression in humans can vary depending on the type of cell , tissue , or pathology analyzed . For example , EBNA1 , EBNA2 , LMP2A and the EBERs can be found in germinal center B cells , with varying detection of LMP1 [35] , [36] . In some cases , LMP1 expression is restricted to B cells outside of germinal centers in the extrafollicular space [37] , similar to observations in LMP1 transgenic mice [10] , [16] . The bulk of EBV genomes in peripheral B cells are detected in class-switched memory B cells where latent gene expression is limited to EBNA1 [35] , [38]–[40] . These findings have suggested a model whereby LMP1 and LMP2A promote terminal differentiation to a memory B cell in which EBV genomes can quiescently persist [3] . Therefore , we hypothesize that LMP2A could modify LMP1 signaling to allow the B cell to enter germinal centers . Our hypothesis is supported by studies of LMP1 and LMP2A co-expression that indicated a role for LMP2A in altering LMP1 signaling through the TRAFs . In an early study , LMP2A expression reduced signaling through several receptors in EBV-negative Burkitt's lymphoma ( BL ) B cell line transfected with LMP1 and LMP2A [41] . Also , LMP2A decreased signaling from LMP1 by modulating the levels of TRAF2 and TRAF3 in BL cell lines [22] . However , these findings differ from studies with epithelial cell lines , where LMP2A appeared to stabilize LMP1 , enhancing NF-κB activation [42] . These differential results in transformed epithelial and B cell lines , and the difficulties with studying latently EBV-infected B cells in humans warrants the study the effects of co-expression of LMP1 and LMP2A on TRAF levels in vivo using transgenic models . To address whether LMP1 and LMP2A co-expression alters B cell maturation and function and to identify a role for LMP2A in modulation of LMP1 , we generated double LMP1/2A B cell transgenic mice . Instead of LMP1 and LMP2A signals synergizing to enhance B cell proliferation , activation , and immunoglobulin secretion , we have identified that LMP2A modulates the LMP1-induced phenotype of the B cell following stimulation . The decrease in TRAF2 , but not TRAF3 , levels detected upon co-expression of LMP1 and LMP2A recapitulates in vitro findings with B cells lines in an animal model . Our results suggest a role for LMP2A in modulating the effect of LMP1 on B cell function in vivo , and have larger implications for the ability of Epstein-Barr virus in the subversion of normal B cell behavior before disease develops .
To investigate the significance of expression of LMP1 and LMP2A in B cells , we crossed LMP1 and LMP2A single transgenic mice . Both lines express the transgene under the control of the IgH promoter and enhancer region , rendering transgene expression B cell-specific . The well-described LMP2A Tg6 line has no gross defect in B cell numbers , B cell development , or BCR expression [31] , [32] , [43] . In LMP1 lineage 3 mice , modest alterations have been described in B cell maturation in the periphery , as well as the ablation of germinal center ( GC ) formation in response to antigen [16] . We crossed LMP2A and LMP1 heterozygotes to obtain LMP1/2A transgenic mice , and used these mice and the LMP1 , LMP2A or non-transgenic littermate controls ( wild-type , WT ) in each subsequent experiment . We first examined the expression of LMP1 and LMP2A protein in splenic B cells from the relevant genotypes as well as WT mice . Splenic cryosections from 8 week old mice were stained with antibodies to LMP1 and LMP2A and the B cell marker IgM . IgM staining was specific , as shown by the follicle border in the WT IgM panel ( Top Left , Figure 1 ) . IgM-positive B cells were also positive for LMP1 and/or LMP2A , and staining was specific , as shown by the lack of LMP1 or LMP2A staining in WT spleen ( Figure 1 ) . In all transgenic spleens , LMP1 or LMP2A-positive cells were located in IgM-positive B cell follicles at low power magnification ( data not shown ) . These data confirm that LMP1 and LMP2A protein were expressed in B cells of LMP1/2A transgenic mice . We examined whether co-expression of LMP1 and LMP2A in B cells resulted in perturbation of normal splenic architecture , which has previously been described in LMP1 transgenic animals [6] , [44] . We isolated spleens and axillary and brachial lymph nodes of mice at 8 weeks of age , weighed these organs , and stained spleen sections with H&E . In all genotypes , the splenic red and white pulp were well organized and follicles were clearly present with no spontaneous germinal centers observed ( Figure 2A ) . The mass of lymph nodes and spleens of LMP1/2A animals was similar to WT , LMP1 and LMP2A animals ( Figure 2B ) . Thus , in peripheral lymphoid organs , LMP1/2A co-expression did not alter follicle formation nor elicit spontaneous germinal center formation . Since LMP1 and LMP2A act as constitutive signaling mimics of normal B cell signaling and LMP2A Tg6 mice have previously been described as having normal bone marrow B cell development [31] , [32] , we next examined whether expression of LMP1 and LMP1/2A altered B cell development in bone marrow . Bone marrow was flushed from tibia and femurs of 4 , 6 , or 8 week old mice , stained with fluorescent antibodies against B cell maturation markers , and analyzed by flow cytometry . Data from 8 week old mice is shown in Figure 2 , although similar B cell populations were detected at 4 and 6 weeks ( data not shown ) . Similar frequencies of immature B cells expressing a BCR of the IgM isotype ( B220+/IgM− ) were observed in mice of all genotypes ( Figure 2D ) . Expression of LMP1 and/or LMP2A did not alter B cell maturation from pro-B to large and small pre-B , as shown by B220 , CD43 and GL7 expression ( Figure 2E ) . In addition , the frequencies of recirculating , mature B220+/IgM+/IgD+ B cells detected in bone marrow were similar across genotypes , suggesting that LMP1/2A co-expression does not alter mature B cell recirculation ( Supp . Figure S1A ) . Taken together , these data suggest that LMP1/2A co-expression does not alter B cell ontogeny . We next examined whether expression of LMP1 and LMP2A alters maturation of B cells by examining B cell populations in peripheral lymphoid organs . Upon exiting the bone marrow , immature bone marrow B cells home to the spleen via the blood , differentiating into mature follicular B cells which recirculate , or marginal zone B cells , which remain in the spleen . Spleen and axillary and brachial lymph nodes from mice at 8 weeks of age were isolated and single cell suspensions were prepared . Cells were stained with fluorescent antibodies against B cell maturation markers and analyzed by flow cytometry . In spleen , significantly fewer total B220+/IgM+ B cells were detected in LMP1/2A spleen compared to LMP1 , LMP2A and WT spleen ( Figure 2F ) . Lower , but not statistically significant , frequencies of mature follicular ( FO ) B cells ( B220+/IgM+/IgD+ ) were observed in LMP1 spleen ( Figure 2F ) , and this was consistent with a slight increase in marginal zone ( MZ ) B cells ( B220+/IgM+/IgD− ) in LMP1 spleen , while LMP2A and LMP1/2A B cell populations appeared more similar to WT ( Figure 2G ) . The frequency of splenic B1 B cells ( Figure S1B ) and T cells ( Figure S1C ) was not altered by expression of LMP1 and/or LMP2A when compared to WT . Next , we assessed frequencies of total ( B220+/IgM+ ) , FO B cells ( B220+/IgM+/IgD+ ) and MZ B cells ( B220+/IgM+/IgD− ) in axillary and brachial lymph nodes . The expression of LMP1 and/or LMP2A did not alter the frequencies of total lymph node B cells ( Figure S1D ) , MZ or FO B cells ( Figure S1E ) , or CD4+ and CD8+ T cells ( Figure S1F ) . Because LMP1/2A animals did not demonstrate gross alteration of B cell maturation , we postulated that the levels of natural immunoglobulin in LMP1/2A animals would be similar to controls . We assessed the levels of immunoglobulin in serum from 8 week old naïve animals by isotype-specific ELISA . Levels of IgM in LMP1/2A serum were significantly increased ( p<0 . 05 ) over LMP1 , LMP2A and WT animals , whereas levels of IgG1 , IgG2a and IgG2b were similar across all genotypes ( Figure 2C ) . To assess whether LMP2A alters the ability of LMP1-expressing LMP1/2A B cells to enter GC in response to antigen , we immunized mice with the hapten TNP24-KLH and isolated spleen at Day 7 , as the GC response peaks between Days 7 and 10 . Splenic cryosections were stained for the GC B cell markers PNA and IgM , as well as CD4 for T helper cells to demarcate follicles ( Figure 3A ) . The location of GC in follicles was confirmed by staining separate sections for the germinal center marker GL7 ( data not shown ) . PNA+/IgM+ GC were observed in spleens of WT mice , surrounded by a network of CD4+ T helper cells ( Figure 3A ) . PNA-positive GC per follicle were counted and the percentage of follicles containing GC was enumerated ( Figure 3B ) . As previously shown [16] , GC were rarely detected in LMP1 spleen ( Figure 3A ) , and the frequency of GC per follicle was significantly decreased in LMP1 spleen to less than half that of WT ( p<0 . 05 ) ( Figure 3B ) . Similar to WT , LMP2A-expressing B cells were able to enter GC . Intriguingly , LMP1/2A-expressing B cells were able to form GC at a similar frequency per follicle compared to LMP2A or WT animals , suggesting that the LMP2A signal restores normal GC development and allows LMP1-expressing B cells to enter GC . Previously , it was shown that despite the inability of LMP1 B cells to participate in the GC reaction , LMP1 expression maintains the production of high-affinity class switched antibody at levels similar to WT animals [16] . We assessed the kinetics of TNP-specific IgG1 production in serum of immunized LMP1/2A mice compared to single LMP1 , LMP2A , and WT animals during the primary response . Between Day 7 and Day 35 following immunization , the levels of TNP-specific IgG1 increased with similar kinetics among all genotypes and was maximal by Day 35 ( Figure 4A ) . The germinal center response is also critical for affinity maturation . TNP-specific antibodies were tested by ELISA for high or low affinity for TNP by binding to low-density or high-density hapten , respectively . Serum isolated at Days 7 , 21 and 35 following immunization was assayed for high and low affinity IgG1 . The ratio of TNP2∶TNP11-binding IgG1 increased with similar kinetics over time for each genotype , and was not altered by expression of LMP1 or LMP2A either alone or in combination ( Figure 4B ) . We also explored the possibility that LMP1 and LMP2A co-expression in B cells responding to antigen might enhance signals for class switching to IgG and IgE , as has been shown in LMP1-expressing cell lines [45] . By ELISA , we compared serum levels of TNP-specific immunoglobulin at Day 35 of the primary response . IgM , IgG1 and IgE levels were similar in LMP-expressing mice compared to WT . TNP-specific IgG2a levels in LMP1 , LMP2A , and LMP1/2A mice were elevated compared to WT ( Figure 4C ) . Conversely , the expression of LMP1 and LMP1/2A decreased TNP-specific IgG2b levels in serum; for LMP1 and LMP1/2A mice , this decrease was significant when compared to WT ( p<0 . 05 ) . The physiological significance of the decrease in IgG2b in LMP1 and LMP1/2A animals is unclear at present . It has been proposed that co-expression of LMP1 and LMP2A during the GC reaction may drive antigen-specific B cells to become memory B cells by augmenting BCR and CD40 signals [3] . If higher percentages of memory B cells were present in LMP1/2A transgenic mice , an increased frequency of antigen-specific plasma cells may be detected following secondary immunization . Thus , the ability of LMP1 , LMP2A , and LMP1/2A to alter plasma cell generation during the secondary immune response was investigated using TNP24-KLH . Mice were boosted with TNP24-KLH at Day 50 following primary immunization , and TNP-specific IgG1 antibody-secreting cells ( ASCs ) were enumerated in bone marrow and spleen by ELIspot on Day 7 after boost . A representative experiment is shown ( Figure 4D–E ) . As expected , levels of bone marrow plasma cells were tenfold higher in bone marrow than spleen among all genotypes , reflecting the ability of plasma cells to home to bone marrow following generation in secondary lymphoid tissues ( Figure 4D ) . The frequencies of TNP-specific IgG1+ ASCs in LMP1/2A mice were comparable to controls in both bone marrow ( Figure 4D ) and spleen ( Figure 4E ) , suggesting that LMP1 , LMP2A , and LMP1/2A do not alter the frequency of IgG1+ ASC nor the ability of plasma cells to home from spleen to bone marrow during the secondary response . Next , we tested whether co-expression of LMP2A altered the expression of B cell surface activation and co-stimulation markers in vitro on LMP1-expressing cells . Following antigen exposure , B cells upregulate the co-stimulatory molecules CD80 and CD86 , which interact with T cell ligands to elicit secondary activation signals critical for GC formation [46] , [47] . Once B cells enter the GC , they upregulate Fas and bind PNA at higher levels than non-GC B cells [48] , [49] . Splenic B cells were purified by negative selection using CD43+ microbeads to generate a >95% pure population of resting naive B cells . B cells were stimulated with anti-IgM to crosslink B cell receptors for 72 hours , due to maximal upregulation of all markers by this time [50]–[52] . B cells were surface stained for expression of CD80 , CD86 , and Fas , and with PNA-FITC , and were analyzed by flow cytometry by gating on live B220+ cells . Resting B cells from all genotypes appeared similar in expression levels of all markers , although LMP1 B cells expressed slightly higher surface levels of Fas ( Figure 5 ) , confirming previous observations with this transgenic line [16] . Upon BCR cross-linking , all genotypes upregulated expression of all markers but to different levels . LMP1 and LMP1/2A further upregulated CD80 and Fas upon BCR crosslinking compared to WT and LMP2A alone . The intensity of PNA staining on LMP1 B cells was decreased compared to WT , LMP2A and LMP1/2A controls . In sum , LMP1 expression alone or with LMP2A appears to enhance cell surface expression of CD80 and CD86 following B cell stimulation , but decreases levels of PNA following IgM stimulation compared to WT and LMP2A alone . Next , we wanted to assess whether LMP1/2A co-expression influenced in vitro B cell proliferation in response to BCR and T cell signals , as both LMP1 and LMP2A have been shown to influence proliferation in the presence of antigens , mitogens , or oncogene overexpression [16] , [34] , [53]–[55] . Purified resting CD43− B cells were stimulated with optimized concentrations of anti-IgM , anti-CD40 and/or recombinant murine IL-4 . LPS was used as a BCR and CD40-independent positive control . Proliferation of B cells was assessed by incorporation of 3[H]-thymidine at 72 hours of culture . Under all stimuli , LMP1 promoted B cell hyperproliferation and recapitulated the ability to proliferate with the T helper cell cytokine IL-4 that has been observed elsewhere [16] , while LMP2A and LMP1/2A did not synergize with IL-4 ( Figure 6A ) . B cells from all genotypes proliferated in response to LPS , but there was no significant difference in proliferation level ( Figure 6A ) . In the presence of a BCR agonist , LMP1/2A B cells proliferated at the same level as LMP1 B cells ( Figure 6B ) , indicating that the LMP2A signal did not synergize with nor impair BCR-induced proliferation , similar to previous results with LMP2A transgenic mice [25] , [27] . However , when stimulated with a BCR agonist in the presence of IL-4 , LMP1/2A B cells exhibited a lower level of proliferation compared to LMP1 alone ( Figure 6B ) . We also observed the dampening effect of LMP2A and intensification of this effect by IL-4 when LMP1/2A B cells were stimulated with signals mimicked by LMP1 and LMP2A ( i . e . the BCR and CD40 ) ( Figure 6C ) . These data suggest that LMP2A co-expression decreased the hyperproliferation driven by LMP1 , and that this normalizing phenotype in LMP1/2A B cells is more strongly promoted in the presence of IL-4 stimulation . The cytoplasmic C terminal activating domain-1 ( CTAR1 ) of LMP1 directly recruits TRAF2 and TRAF3 to elicit proliferative effects on B cells , [8] , [9] , [17] , [44] and LMP2A has been shown to decrease TRAF2 and TRAF3 expression in B cell lines expressing LMP1 [22] . To examine mRNA levels of TRAF2 and TRAF3 in resting CD43− splenic B cells , we prepared cDNA from isolated CD43− splenic B cells and amplified TRAF2 and TRAF3 message by RT-PCR . In resting LMP1 B cells , TRAF2 was upregulated to approximately four-fold compared to WT ( Figure 6D ) . LMP2A expression decreased TRAF2 mRNA by half compared to WT , which was also observed in LMP1/2A-expressing B cells . The levels of TRAF3 were not significantly altered by either single or co-expression of LMP1 and LMP2A . To assess whether the effects on TRAF2 and TRAF3 at the mRNA level were recapitulated at the protein level , we carried out TRAF2 and TRAF3 immunoblots on lysates prepared from purified B cells and CHO-K1/hTRAF2 cells using the housekeeping protein GAPDH as a loading control ( Figure 6E ) . The low levels of expression of TRAF2 in purified B cells have been seen in other murine models [56] , [57] . To confirm TRAF2 levels , we used an additional anti-TRAF2 antibody that gave similar results ( Figure S2 ) . Quantitation revealed that TRAF2 levels were increased up to twofold in LMP1 B cells ( Figure 6F ) while TRAF2 levels in LMP2A and LMP1/2A B cells were similar to WT . Expression of LMP1 , LMP2A , and LMP1/2A did not appear to significantly alter TRAF3 protein levels . [56] , [57] . In sum , LMP1 appears to increase mRNA and protein levels of TRAF2 , but not TRAF3 , and this increase is reversed when LMP2A is co-expressed with LMP1 . Hence , in resting B cells , LMP2A expression appears to regulate levels of TRAF2 , a molecule critical for LMP1 signaling .
Our results describe LMP2A as a regulator of LMP1-induced B cell hyperactivation during LMP1/2A co-expression in B cells in an animal model of EBV latency . Specifically , we found that in LMP1/2A animals: ( 1 ) LMP2A dampened LMP1-mediated hyperproliferation in response to mitogenic stimuli; ( 2 ) LMP2A expression allowed LMP1-expressing B cells to enter germinal centers consistent with decreased proliferation; ( 3 ) LMP2A decreased levels of TRAF2 , required by LMP1 for signaling to NF-κB . The finding that B cell maturation is not perturbed in naïve LMP1/2A animals in the absence of a strong antigenic signal supports this conclusion . Many studies of LMP1 and LMP2A expression in cell lines and transgenic mouse models of disease have indicated that these viral proteins can elicit profound effects on B cell function . Our study is the first to explore the effect of co-expressing both LMP1 and LMP2A in the same naïve B cell from early stages of development , and indicates that LMP1/2A-expressing B cells develop and function normally in naïve mice without driving spontaneous B cell proliferation in the absence of antigen . Once stimulated by antigen , LMP1/2A normalized responses in terms of germinal center physiology and antibody production , as well as production of normal plasma cell frequencies during the secondary response . Whether LMP1/2A can alter plasma cell numbers during the primary response remains to be determined , although antibody titers in LMP1/2A animals were similar to control animals during the primary response . Cooperation of LMP1 and LMP2A signaling has been reported in vitro [42] , however , we did not detect evidence of synergistic activity of LMP1 and LMP2A in our model , as demonstrated by no acceleration of mortality ( data not shown ) , the dampening effect on B cell proliferation in LMP1/2A B cells , and the downmodulatory effect of LMP2A on TRAF2 levels . Our findings are the first description of LMP2A alteration of LMP1 signaling by TRAF2 modulation in an animal model , and support similar findings in EBV-positive nasopharyngeal carcinoma and Burkitt's lymphoma cell lines [22] , [41] , [58] . Previous studies of EBV-positive or LMP1-transfected tumor cell lines proposed that LMP1 perturbs TRAF regulation in order to enhance NF-κB activity [8] , [9] , [21] . One study identified that protein levels of TRAF2 were increased in transformed B cell lines when LMP1 was expressed , but that co-expression of LMP2A decreased TRAF2 levels to normal [22] . These data are consistent with our findings that LMP2A decreases TRAF2 transcript and protein levels in resting LMP1/2A B cells in vivo . The in vivo effect of the two-fold increase in TRAF2 detected in LMP1 mice is currently unclear . While TRAF2 transmits signals from TNF family receptors to AP-1 and NF-κB , studies from TRAF2 deficient mice have revealed potentially conflicting roles in activation of the canonical and noncanonical NF-κB pathways [56] , [57] , [59] , [60] . Future studies of TRAF2 requirement for NF-κB activation and the effect on the B cell phenotype are warranted , especially with regards to the ability of TRAF2 to promote synergy between BCR and CD40 signals , and to degrade TRAF3 during CD40 signaling [61] . In addition , the effects on LMP1 localization and turnover when LMP2A is co-expressed necessitate additional investigation , as previous data suggested that LMP1 turnover could be altered by LMP2A co-expression in epithelial cell lines [42] , which may alter TRAF2 recruitment by LMP1 . The most striking finding during the T cell-dependent immune response in LMP1/2A mice is the restoration of germinal center frequencies similar to LMP2A and WT mice , suggesting that LMP1 signals impeding GC formation may be overcome in the presence of LMP2A . Signals from activated CD40 through TRAF2 and NF-κB are critical for GC-associated functions , including B cell proliferation , class switch recombination , and immunoglobulin secretion [23] . Although the two-fold increase in TRAF2 message in LMP1 B cells is difficult to reconcile with the finding that LMP1 B cells are impaired in GC entry , a possible explanation may be that an overly strong CD40 signal prevents B cells from entering germinal centers . In support of this hypothesis , one study suggested that overly strong CD40 signaling downregulated the master germinal center regulator , BCL-6 [62] , while another study found that overexpression of CD40 drives B cells to exit the germinal center to memory [63] . While BCL-6 levels and activity have not been assessed in this study , several lines of evidence support LMP1 repression of BCL-6 expression in EBV-positive Hodgkin's lymphoma cells [64] , [65] . While LMP2A appears to have a more variable effect on BCL-6 in human B cell lines and primary transgenic murine B cells [30] , [33] , other evidence supports a role for LMP2A in promoting a germinal center-like cellular environment in LMP1/2A B cells . Microarray analysis of LMP2A transgenic B cells and LMP2A-positive LCLs indicated that LMP2A induces a gene expression pattern that resembles that detected in GC centroblasts [30] . Thus , it is possible that during the response to antigen , LMP1 and CD40 signaling together provide an overly strong CD40 signal , downregulating BCL-6 and diverting B cells from entering the germinal center , which may be rescued by the ability of LMP2A to induce a GC-like gene expression program . Evidence suggests that LMP1 and LMP2A also alter B cell cytokine profiles , which may have global effects on gene transcription , warranting future study of the alteration in cytokines and global gene expression induced during LMP1/2A-co-expression . Taken together , our findings suggest a model whereby LMP1/2A co-expression does not provide a synergistic signal for B cell activation , but instead normalizes B cell function by allowing B cells to enter the germinal center in a manner that may be advantageous to the virus . As LMP1 and LMP2A confer survival and proliferative functions to latently EBV-infected B cells in vitro , several groups have suggested that these characteristics may allow latently infected human B cells to survive the germinal center reaction in order to enter the memory pool [3] , [35] , [39] . However , conflicting reports exist on the detection of LMP1 and LMP2A in human GC B cells [36] , [37] . The entry of LMP1/2A-expressing B cells into germinal centers described herein is notable , as it is the first time that detection of LMP1/2A-expressing B cells in germinal centers of latently infected humans can be recapitulated in a mouse model . Similar to findings with latently-infected humans and LMP1 transgenic mice , we have confirmed that LMP1 B cells are defective in the ability to enter GC [16] , [37] , although the location of LMP1 B cells during an immune response and the nature of the signals received that generate high-affinity antibody , memory and plasma B cells are not well-defined . Our findings suggest that LMP2A expression in LMP1/2A B cells alters B cell biology by allowing LMP1-expressing B cells to transit the germinal center and successfully become memory cells , based on the finding that LMP1/2A B cells differentiate into plasma cells at the same frequency as wild-type animals during a secondary immune response . As highly-proliferative LMP1-expressing B cells responding to antigen are more at risk of recognition by CD8+ T cells , the expression of LMP2A with LMP1 could be a viral strategy to normalize B cell physiology during the response to antigen . If this were the case , the latently-infected GC B cell could potentially access the memory compartment . The presence of LMP1/2A-expressing B cells in the germinal center has other implications for germinal center-derived neoplasms that express LMP1 and LMP2A , such as Hodgkin's lymphoma . It is plausible that a B cell that would normally apoptose due to a selection defect during GC transit might be rescued by LMP1/2A co-expression , allowing aberrant B cell activation , proliferation , and survival , which are hallmarks of EBV-associated germinal center-derived tumors . As such , our findings underscore the utility of the LMP1/2A model in providing novel insights as to the behavior of LMP1/2A-expressing B cells in vivo before the development of overt disease .
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by and all experimental procedures were in compliance with the Institutional Animal Care and Use Committee of Northwestern University . Where indicated , procedures were performed under isoflurane anesthesia and all efforts were made to minimize suffering . LMP1 lineage 3 heterozygotes ( LMP1 ) [6] were backcrossed to C57BL/6 mice and crossed with LMP2A Tg6 heterozygotes [32] to generate double transgenic LMP1/2A mice . Both transgenes are driven by an IgH promoter and enhancer region . Expression of transgenes was confirmed by multiplex PCR on genomic DNA isolated from tail snips [27] . Primers used were OL106 ( TACCCTGAGCTTCAGTTCTGCACC ) and OL107 ( TGACTGTGGGAACTGCTGAACTTT ) ( RAG control , 560 bp ) , LMP2A-RC-F2 ( TCTTCTGTTTGCATTGCTGG ) and LMP2A-RC-R2 ( TCCAGAAAACATGTGGCAAA ) ( LMP2A , 404 bp ) , LMP1-AA-F1 ( ATGGCCAGAATCATCGGTAG ) and LMP1-AA-R1 ( CACACCCCCTTTCCCTTACT ) ( LMP1 , 490 bp ) . LMP1 and LMP2A expression in transgenic B cells was confirmed by immunofluorescence on spleen sections . All non-transgenic littermates are referred to as wildtype ( WT ) mice . Antibodies against LMP1 and LMP2A included rat 14B7 ( LMP2A ) and rabbit Lympa-1 ( LMP1; gift of Dr . K . Izumi , UT Health Center , San Antonio ) . Monoclonal antibodies against mouse IgM , IgD , IgG1 , IgG2b , IgG2a , B220 , CD19 , GL7 , CD21 , CD23 , CD43 , CD138 , CD38 , CD4 , and CD8 were purchased from BD Biosciences ( San Jose , CA ) . Antibodies used in immunoblotting included TRAF2 C-20 ( Santa Cruz , Santa Cruz , CA ) , TRAF2 #4712 , TRAF3 #4729 ( Cell Signaling , Danvers , MA ) and GAPDH ab8245 ( Abcam , Cambridge , MA ) . Germinal center staining was carried out with PNA-biotin ( Vector , Burlingame , CA ) . Viability reagents included Live/Dead Fixable Violet ( Invitrogen , Carlsbad , CA ) . Secondary reagents included streptavidin-HRP ( GE Healthcare , Piscataway , NJ ) , streptavidin-AP ( Vector , Burlingame , CA ) , streptavidin-Alexa 488 ( Invitrogen , Carlsbad , CA ) , goat anti-rat Cy3 , anti-rabbit Cy5 ( Jackson ImmunoResearch , West Grove , PA ) and goat anti-mouse IRDye 800 and goat anti-rabbit IRDye 680 ( LiCor , Lincoln , NE ) . Single cell suspensions of bone marrow , spleen and lymph node cells were prepared as previously described [27] , [32] . For flow cytometry , cells were washed in cold FACS buffer ( 1% fetal bovine serum [FBS] in 1× phosphate buffered saline [PBS] ) . For plating primary cells , cells were washed in cold complete medium ( RPMI 1640 with L-glutamine and 10% FBS , 50 U/mL penicillin , 50 µg/mL streptomycin ) . One million bone marrow and spleen cells were resuspended in 50 µL antibody cocktail in cold FACS buffer and stained in the dark for 30 min on ice . Following three washes in FACS buffer , secondary streptavidin staining took place in PBS for 20 min in the dark on ice . Following three washes in FACS buffer , cells were either analyzed immediately using a BD FACSCanto , or fixed in 3% PFA and analyzed within 24 hours . Positive and negative gates were set using unstained or single-stained BD CompBeads ( BD Biosciences , San Jose , CA ) . Mice were immunized with 100 µg TNP24-KLH ( Biosearch Technologies , Novato , CA ) in CFA s . c . For germinal center analysis , spleen was isolated at Days 7 post-immunization . For serum ELISA , blood was drawn from anesthetized mice at Day 0 , 7 , 14 and 35 following immunization and sera separated by centrifugation . Mice were boosted after Day 50 with 50 ug of TNP24-KLH in sterile 1× PBS i . p . For hematoxylin and eosin ( H&E ) staining , spleen was isolated and processed as described [34] . For immunofluorescence , tissue was cryopreserved in Tissue-Tek OCT Compound ( Redding , CA ) , snap frozen in a bath of ethanol and dry ice and stored at −80°C . Sections 5–6 µm thick were air dried for 10 min then fixed in ice cold acetone for 10 min . Sections were allowed to dry and rehydrated in a humid chamber for 20 min . Sections were blocked for 60 min with 10% goat serum , 5% bovine serum albumin ( BSA ) in 1× PBS , followed by washes with PBS . Incubations with primary antibody diluted in blocking buffer for 60 min were followed by washes in 1× PBS . Sections were incubated with secondary antibody diluted in blocking buffer for 30 min , washed twice and mounted with Fluoromount-G ( Southern Biotech , Birmingham , AL ) . To quantitate total serum immunoglobulin , plates were coated with isotype-specific purified antibodies . To quantitate TNP-specific IgG1 , plates were coated with 50 µg/mL TNP11-BSA ( Biosearch Technologies , Novato , CA ) . For IgG1 affinity , plates were coated with TNP2-BSA and TNP11-BSA . Following blocking with 3% BSA in PBS , serial dilutions of serum or an anti-TNP IgG1 standard ( BD Biosciences ) in blocking buffer in triplicate were incubated overnight at 4°C . Plates were washed multiple times with 1× TBST , and incubated with a biotinylated isotype-specific Ig , followed by washing and incubation with a streptavidin-conjugated HRP . Plates were developed with TMB ( BioFX , Eden Prairie , MN ) and stopped with StopSolution ( BioFX , Eden Prairie , MN ) and read at 450 nm on a Wallac Victor2 counter . IgG1 titers were calculated from the line generated from standards of a known calculation . Background subtracted ( corrected ) OD values were used to calculate the ratio of TNP2 ( high affinity ) to TNP11 ( total ) binding IgG1 . For isotypes , corrected OD is shown as a percentage of the wildtype corrected OD . For plasma cell ELIspots , immunized mice were boosted at Day 50 or later with 50 µg TNP-KLH i . p . , and splenocytes and bone marrow isolated at day 7 . Cells were treated with erythrocyte lysis buffer , washed and plated in B cell medium ( RPMI 1640 with L-glutamine and 10% FBS , 50 U/mL penicillin , 50 µg/mL streptomycin , 50 µM β-mercaptoethanol ) in serial dilutions ( starting with 4×105/well ) on plates previously coated with 50 µg TNP11-BSA , and incubated for 18 hours at 37°C . IgG1-expressing ASC were revealed with streptavidin-AP and spots were counted using an ImmunoSpot ( Cellular Technology LTD ) . Resting splenic CD43− B cells were isolated from single cell suspensions by magnetic column ( Miltenyi Biotec , Auburn , CA ) . Cells were incubated in B cell medium and stimulated with recombinant mouse IL-4 at 5 ng/mL ( eBioscience , San Diego , CA ) , anti-CD40 at 10 µg/mL ( eBioscience , San Diego , CA ) , goat anti-mouse anti-IgM F ( ab′ ) 2 at 10 µg/mL ( Southern Biotech , Birmingham , AL ) or LPS ( Sigma-Aldrich ) . The concentrations of these reagents and the timepoint used had been previously optimized . Cells were incubated for 48 hours at 37°C , and 1 µCi 3[H]-thymidine was added for the last 18 hours of culture before the cells were harvested for analysis of thymidine uptake . Total RNA was extracted from resting CD43− splenic B cells using the RNeasy RNA Extraction kit ( Qiagen ) and cDNA was prepared with the High Capacity cDNA Reverse Transcription Kit ( Applied Biosystems ) . Real-time PCR was performed and data analyzes as described previously [53] . Primer sequences for TRAF2 , TRAF3 and HPRT are available at http://mouseprimerdepot . nci . nih . gov . The difference between the gene expression in transgenic compared to WT mice backgrounded to HPRT expression ( ΔΔCT ) was used to determine the relative gene expression in transgenic B cells compared with wildtype B cells , and fold change was calculated by 2−ΔΔCT [66] . Purified B cells were lysed in modified RIPA buffer ( 0 . 1 M Tris-HCl pH 8 . 2 , 0 . 15 M NaCl , 2% SDS , 1% NP40 alternate , 0 . 5% Na-deoxycholate , 0 . 01 M NaF , 0 . 002 M Na3VO4 , 0 . 002 M phenylmethylsulfonyl floride , 0 . 01 M DTT ) with protease and phosphatase inhibitor cocktails ( Roche Diagnostics ) . Control lysates included CHO-K1 cells and CHO-K1/hTRAF2 ( CHO-K1 cells transfected with hTRAF2 plasmid from Addgene , #20229 ) . DNA and nucleic acid were digested with Benzonase nuclease ( Sigma-Aldrich ) . Lysates were cleared and heated for 10 minutes at 72°C and then electrophoretically separated by 10% SDS-PAGE . Protein was transferred to Immobilon-P membrane ( Millipore ) , blocked with 5% BSA in 1× TBST , and probed for TRAF2 , TRAF3 and GAPDH . Membranes were incubated with IRDye secondary antibodies in blocking buffer for 1 h at room temperature , and imaged using a LiCor Odyssey Fc scanner and LiCor Image Studio Software ( v2 . 0 , Lincoln , NE ) . Boxes were manually placed around each band of interest , which returned near-infrared fluorescent values of raw intensity with intra-lane background subtracted [67] . TRAF2 and TRAF3 signal was normalized to GAPDH for each sample . The relative expression of TRAF2 and TRAF3 for each sample relative to wildtype was calculated by ( normalized signalsample/normalized signalwildtype ) *1 .
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As a ubiquitous human pathogen , Epstein-Barr virus ( EBV ) infection is associated with several human B cell diseases characterized by inappropriate B cell activation and function , including infectious mononucleosis and certain cancers . EBV latent membrane protein 1 ( LMP1 ) and 2A ( LMP2A ) hijack cell signaling pathways to alter B cell activation and function , and are detected in EBV-associated diseases . Defining the effect on B cell function when LMP1 and LMP2A are expressed together in the same cell is critical to understanding how EBV subverts normal B cell behavior before disease develops . Using transgenic mice , we have demonstrated that LMP2A dampens cellular proliferation and activation induced by LMP1 , which may be due to the LMP2A-associated decrease in the levels of TRAF2 , a signaling protein used by LMP1 . LMP2A also allows B cells carrying LMP1 to enter the germinal center during an immune response , a site that gives rise to EBV-associated tumors in humans . In sum , this study highlights the biological outcomes of LMP1 and LMP2A co-expression in B cells and contributes to the knowledge of how EBV subverts normal B cell behavior before disease develops .
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2012
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Epstein-Barr Virus LMP2A Reduces Hyperactivation Induced by LMP1 to Restore Normal B Cell Phenotype in Transgenic Mice
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The Caenorhabditis elegans dosage compensation complex ( DCC ) equalizes X-chromosome gene dosage between XO males and XX hermaphrodites by two-fold repression of X-linked gene expression in hermaphrodites . The DCC localizes to the X chromosomes in hermaphrodites but not in males , and some subunits form a complex homologous to condensin . The mechanism by which the DCC downregulates gene expression remains unclear . Here we show that the DCC controls the methylation state of lysine 20 of histone H4 , leading to higher H4K20me1 and lower H4K20me3 levels on the X chromosomes of XX hermaphrodites relative to autosomes . We identify the PR-SET7 ortholog SET-1 and the Suv4-20 ortholog SET-4 as the major histone methyltransferases for monomethylation and di/trimethylation of H4K20 , respectively , and provide evidence that X-chromosome enrichment of H4K20me1 involves inhibition of SET-4 activity on the X . RNAi knockdown of set-1 results in synthetic lethality with dosage compensation mutants and upregulation of X-linked gene expression , supporting a model whereby H4K20me1 functions with the condensin-like C . elegans DCC to repress transcription of X-linked genes . H4K20me1 is important for mitotic chromosome condensation in mammals , suggesting that increased H4K20me1 on the X may restrict access of the transcription machinery to X-linked genes via chromatin compaction .
In many animals , males and females have a different number of X chromosomes . Dosage compensation is a chromosome-wide process of gene regulation that equalizes gene expression between the sexes despite the difference in X-linked gene dosage , and is achieved by a variety of mechanisms [1] , [2] . In humans , one X chromosome is inactivated in females . In Drosophila , expression from the single X chromosome in males is upregulated two-fold to match expression from the two X chromosomes in females . In C . elegans , the two X chromosomes in hermaphrodites are downregulated two-fold to match expression from the single X chromosome in males . In each of these cases , regulation of gene expression involves the targeting of specialized protein complexes specifically to the X chromosome . Studies of different dosage compensation mechanisms have uncovered chromatin-mediated mechanisms of gene regulation . In C . elegans , dosage compensation is achieved by the dosage compensation complex ( DCC ) ( reviewed in [3] ) . The core of the DCC consists of a five-subunit condensin complex named condensin IDC . Condensin complexes mediate chromosome condensation and resolution in mitosis and meiosis , and participate in crossover control during meiosis [4] . Four subunits ( MIX-1 , DPY-26 , DPY-28 , and CAPG-1 ) are shared with canonical condensin I , while DPY-27 is specific to condensin IDC [5] . The central role of a condensin-like complex in dosage compensation suggests that the mechanism of dosage compensation involves regulation of chromatin structure . Five other components of the DCC ( SDC-1 , SDC-2 , SDC-3 , DPY-21 and DPY-30 ) physically interact with different subunits of condensin IDC , and all examined components of the DCC are enriched on hermaphrodite X chromosomes relative to autosomes [3] . The DCC is targeted to the X chromosome through specific sequence elements , called rex ( recruitment elements on X ) sites ( reviewed in [3] ) . After recruitment , the DCC spreads to dox ( dependent on X ) sites , which consist mostly of active promoters . The zinc finger protein SDC-2 is the primary X-chromosome recruitment factor for the DCC . The DCC also binds to some autosomal sites at lower levels , but the functional significance of autosomal binding is not yet known [6] , [7] . SDC-3 requires SDC-2 for X-chromosome binding , and all of the other DCC components require SDC-2 and SDC-3 for recruitment . Loss of DCC proteins impairs dosage compensation , resulting in upregulation of X-linked genes and death of XX animals . DPY-21 and SDC-1 null mutants have milder dosage compensation defects and are viable , with apparently normal DCC protein localization on X [8] , [9] , [10] , [11] , [12] . A current model is that SDC proteins recruit condensin IDC to the X chromosome , leading to changes in chromatin structure that result in reduction of gene expression . In XX animals , not all genes on X are dosage compensated , and DCC association with genes correlates with gene expression level but not with the degree of repression [7] . The mechanism of repression is not understood , but DCC mutants have increased levels of RNA polymerase II on X-linked genes , indicating regulation at the level of transcription [13] . Here we show that the DCC is required for enrichment of the histone modification H4K20me1 on the X chromosomes of hermaphrodites and that the responsible histone methyltransferase SET-1 is important for downregulation of dosage-compensated genes . Our study implicates the histone modification H4K20me1 in the process of dosage compensation .
In C . elegans , dosage compensation downregulates genes on the X chromosome . We therefore examined the pattern of H4K20me1 with respect to gene features . As seen previously in early embryos and L3 larvae [15] , H4K20me1 is enriched across active gene regions at all developmental stages examined , with high enrichment on X-linked genes and lower enrichment on autosomal genes ( Figure 1C ) . H4K20me1 levels are positively correlated with transcript levels for both X-linked and autosomal genes ( rs = 0 . 66 and rs = 0 . 56 , respectively ) . Notably , inactive X-linked genes have higher levels of H4K20me1 than active autosomal genes ( Figure 1C ) . On autosomes H4K20me1 is primarily confined to transcribed regions , while on the X , H4K20me1 is elevated across the chromosome , including regions that are more than 5 kb from any annotated gene feature ( Figure 1D ) . This widespread distribution of H4K20me1 on the X chromosome suggests a role in chromosome-wide regulation of gene expression . Our ChIP experiments from early and late stage embryos , L3s , and young adults showed that the timing of H4K20me1 enrichment on the X chromosome is consistent with a role in dosage compensation . To determine more precisely when H4K20me1 becomes enriched on the X chromosome , we performed immunofluorescence experiments using two different antibodies specific for H4K20me1 . In embryos prior to the 30-cell stage , neither DPY-27 nor H4K20me1 was concentrated in any subnuclear region ( Figure 2A ) . However , we observed that nuclear staining of H4K20me1 increased dramatically during mitosis ( Figure 2A and Figure S1 ) . This is consistent with reports showing that in other organisms , H4K20me1 is present at high levels in mitosis and has a role in chromosome condensation [16] . At around the 30-cell stage , DPY-27 became localized to subregions of each nucleus that have been shown to be the X chromosomes [14] ( Figure 2B , 2F ) . At this time , H4K20me1 was still distributed uniformly in the nucleus ( Figure 2B , 2F ) . In embryos beginning the differentiation stage , H4K20me1 staining began to concentrate on the X chromosomes , as evidenced by colocalization with DPY-27 , and this pattern became widespread in somatic cells throughout hermaphrodite development ( Figure 2D , 2E , 2G; Figure S2A ) . Therefore , localization of the DCC to the X chromosome precedes enrichment of H4K20me1 . In the germ line , the DCC does not localize to the X chromosome [10] . The X chromosome is largely silent , and the silent state is mediated by a mechanism independent from somatic dosage compensation [10] , [17] , [18] , [19] . We observed a distinct and dynamic pattern of H4K20me1 staining in the adult germ line . H4K20me1 levels were highest in the distal mitotic region , and decreased as nuclei entered meiosis ( Figure S3A ) . Early meiotic nuclei entering the transition zone showed similar H4K20me1 levels on X and autosomes ( Figure S3B ) . As nuclei progressed through the transition zone into early pachytene , H4K20me1 levels were much lower on the X chromosome than on autosomes ( Figure S3B ) . The X chromosome is silent during early and mid-pachytene [18] . Later in meiotic prophase , H4K20me1 levels increased on the X , coincident with activation of X-linked gene expression ( Figure S3B; [18] ) . In contrast to the enrichment of H4K20me1 on the X chromosome in somatic nuclei , levels of H4K20me1 in late meiotic prophase were similar on the X chromosome and autosomes ( Figure S3B ) . To summarize , H4K20me1 shows a dynamic localization pattern on germline chromatin , with two characteristics of localization shared with somatic chromatin . First , enrichment of H4K20me1 is observed on mitotic chromosomes . Second , in meiotic nuclei , H4K20me1 is associated with chromatin that has active gene expression . To test whether H4K20me1 enrichment on the X chromosome depends on the DCC , we carried out H4K20me1 ChIP-chip experiments using extracts from dpy-21 mutant L3 larvae , which are deficient in dosage compensation [12] . Strikingly , H4K20me1 enrichment on the X relative to autosomes was abolished in dpy-21 mutants ( Figure 1B–1F ) , indicating that the DCC facilitates enrichment of H4K20me1 on the X . To further investigate this link , we asked whether the DCC could increase H4K20me1 levels at ectopic sites . Previous studies showed that DCC proteins bind recruiting elements on the X and then spread to neighboring regions that lack recruiting sites [6] , [20] . Spreading is observed in chromosomal fusions between the X chromosome ( which contains recruiting sites ) and an autosome ( which lacks recruiting sites; Figure 3 ) . Using this assay , we observed spreading of H4K20me1 into the autosomal region flanking the site of the fusion , similar to that seen for the DCC component DPY-27 ( Figure 3 ) . This is consistent with a direct role for the DCC in generating enrichment of H4K20me1 on the X . To better define the timing and requirement for dosage compensation in H4K20me1 enrichment on the X , we performed immunofluorescence experiments on dosage compensation mutant embryos . H4K20me1 was not enriched on the X chromosome in any dosage compensation mutant tested ( dpy-21 , dpy-26 , dpy-28 , and dpy-30; Figure 4 and Figure S4 ) . Instead , H4K20me1 was evenly distributed on all chromosomes . We next analyzed XO males , which do not undergo dosage compensation and found no H4K20me1 enrichment on the single X of XO embryos or XO adult somatic nuclei ( Figure 4B , Figures S2B and S4B ) . We also observed no H4K20me1 enrichment to X in adult gut nuclei of DCC mutants , similar to [21] ( Figure S2 ) . These results indicate that the DCC is required for the X-chromosome enrichment of H4K20me1 . To determine whether H4K20me1 functions in dosage compensation , we sought to identify the enzymes responsible for methylation of H4K20 . In other organisms , PR-Set7/SETD8 catalyzes monomethylation of H4K20 and Suv4-20 catalyzes di- and trimethylation of H4K20 [22] , [23] , [24] . The C . elegans orthologs of these proteins are SET-1 ( PR-Set7/SETD8 ) and SET-4 ( Suv4-20 ) . Deletion mutants for both genes are available: set-1 ( tm1821 ) homozygotes develop into sterile adults ( S . Mitani , pers . comm . ) , whereas set-4 ( n4600 ) homozygotes are viable and fertile [25] . Among embryos from fertile set-1/balancer mothers , heterozygous set-1/balancer embryos contain robust H4K20me1 while set-1 homozygous mutant embryos lack detectable H4K20me1 staining ( Figure 5A ) . Furthermore , by western blot analysis , set-1 mutant adult extracts lack detectable H4K20me1 , as well as H4K20me2 and H4K20me3 ( Figure 5B ) . We conclude that SET-1 is the major histone methyltransferase required for generation of H4K20me1 . C . elegans SET-4 appears to be the major histone methyltransferase for converting H4K20me1 to H4K20me2 and H4K20me3 . In set-4 ( n4600 ) homozygotes , we observed strongly reduced levels of H4K20me2 and H4K20me3 and increased levels of H4K20me1 compared to wild type , both by western blot and immunofluorescence analyses ( Figure 6 ) . In summary , our results show that SET-1 generates H4K20me1 and SET-4 converts H4K20me1 to H4K20me2 and H4K20me3 , consistent with a recent report [21] . We note that DPY-27 localization appears normal in set-1 and set-4 mutants ( Figure 5A and Figure 6B ) , suggesting that H4K20 methylations are not important for DCC recruitment . In contrast to H4K20me1 , the nuclear distributions of H4K20me2 and H4K20me3 are relatively uniform . To examine the levels of H4K20me2 and H4K20me3 more closely , we . co-stained late stage embryos for DPY-27 to mark the X chromosome . We observed that H4K20me2 and H4K20me3 were depleted on the X chromosome relative to autosomes ( Figure S5 ) . These differences were not observed in the DCC mutant dpy-21 ( Figure S5 ) . We investigated the distribution of H4K20me3 at higher resolution using ChIP . Similar to other organisms ( e . g . [26] ) , H4K20me3 is found at higher levels on inactive genes ( bottom 20% ) than on active genes ( top 20% ) ( Figure 1C ) . However , overall levels are lower on the X chromosome compared to the autosomes , consistent with immunofluorescence results ( Figure 1C–1E and Figure S5 ) . We conclude that in hermaphrodites , the X chromosome has higher levels of H4K20me1 and lower levels of H4K20me2 and H4K20me3 relative to autosomes . In principle , these patterns could be generated through differential activity of SET-1 or SET-4 on X versus autosomes . For example , SET-1 might be more active in generating H4K20me1 on the X chromosome compared to autosomes , or SET-4 could be more active in converting H4K20me1 to H4K20me2 or H4K20me3 on autosomes compared to the X . To distinguish between these possibilities , we investigated H4K20me1 patterns in set-4 mutant embryos . We observed that H4K20me1 levels in set-4 mutant embryos were elevated and uniformly distributed in all nuclear regions , with no detectable X-chromosome enrichment ( Figure 6B , 6C; similar to [21] ) . Similarly , ChIP experiments show that H4K20me1 is present at similar levels on the X chromosome and autosomes in set-4 L3 mutant extracts ( Figure S6 ) . We conclude that the higher level of H4K20me1 on the X chromosome compared to the autosomes in wild type is achieved at least in part through higher SET-4 directed conversion of H4K20me1 to H4K20me2/3 on the autosomes . If dosage compensation inhibits SET-4 from acting on the X chromosome , then dosage compensation mutants would be expected to have increased activity of SET-4 on the X , and as a result , reduced H4H20me1 and increased H4K20me3 levels compared to wild-type . To test this hypothesis , we carried out western blot analyses using dosage compensation mutant dpy-21 and sdc-1 L3 extracts . We found that the level of H4K20me1 is reduced in these mutants compared to wild type ( Figure 6D and data not shown ) . Reduced H4K20me1 is due to inappropriate SET-4 activity , because levels are greatly increased in dpy-21; set-4 ( RNAi ) or sdc-1; set-4 ( RNAi ) animals ( Figure 6D and data not shown ) . Furthermore , we found that the reduction in H4K20me1 in dpy-21 mutants is accompanied by an increase in the level of H4K20me3 , as expected if SET-4 has increased activity ( Figure 6E ) . These results support the hypothesis that dosage compensation inhibits SET-4 activity on the X chromosome , leading to relatively high H4K20me1 levels and relatively low H4K20me3 levels on X . We reasoned that if H4K20me1 is important for dosage compensation , then reducing H4K20me1 levels should impair this process . To test this hypothesis , we depleted SET-1 in two mutant backgrounds partially compromised for dosage compensation: null dpy-21 ( e428 ) mutants , which are viable , and a weak temperature-sensitive allele of dpy-28 ( y1ts ) , which shows low embryonic lethality at the permissive temperature [12] , [27] . A complete lack of dosage compensation in XX hermaphrodites results in 100% embryonic lethality [28] . Therefore , further perturbing the dosage compensation process in the sensitized backgrounds should cause an increase in embryonic lethality . We first validated the assay by testing whether knockdown of three different DCC subunits causes synthetic lethality in the two dosage compensation mutant backgrounds described above . As expected , RNAi of sdc-2 , dpy-27 , or dpy-30 resulted in greatly increased lethality in dpy-21 and dpy-28 ( ts ) mutant backgrounds compared to wild type ( Figure 5C and data not shown ) . Using this assay we found that RNAi of set-1 induced synthetic lethality in dpy-21 and dpy-28 ( ts ) mutant backgrounds , elevating embryonic lethality from 2% in a wild-type background to 46% and 44% in dpy-21 and dpy-28 ( ts ) , respectively ( Figure 5C ) . RNAi of set-4 or of three other histone methyltransferases ( met-1 , met-2 , set-2 ) had no effect ( Figure 5C ) . The specific synthetic genetic interactions between set-1 and dosage compensation mutants support the view that H4K20me1 is important for dosage compensation . In C . elegans , the DCC represses dosage-compensated genes on the X by approximately 2-fold . To test directly the role of H4K20me1 in this repression , we compared the expression of X-linked dosage-compensated genes to non-compensated autosomal genes in wild-type and set-1 mutant animals . Because set-1 homozygous mutants are sterile and the X chromosome is not dosage compensated in the germ line , we focused on genes expressed in the soma . In order to control for possible germline effects , we performed analyses in glp-1 mutant animals , which lack a germ line . Finally , as some X-linked genes are not dosage compensated , we chose X-linked genes that are upregulated in dosage compensation mutants dpy-21 or dpy-28 . As expected , we found that the expression of three X-linked genes ( aco-1 , ajm-1 , and apl-1 ) relative to two autosomal genes ( W07G4 . 4 and act-1 ) is unchanged in glp-1 mutants and significantly increased in dpy-21 and/or dpy-28 mutants ( Figure 5D ) . Similar to the DCC mutants , we observed a significant increase in the expression of dosage compensated X-linked genes relative to autosomal genes in the set-1 mutant ( Figure 5D ) . These results show that H4K20 monomethylation mediated by SET-1 has a role in repression of dosage-compensated X-linked genes .
Downregulation of X-linked gene expression during C . elegans dosage compensation allows study of gene expression mechanisms that act over large chromosomal regions . Previous studies have identified a condensin-like complex and other chromatin-associated proteins required for this process , but the mechanism by which these proteins lower X-linked gene transcription is not known . Here we show that the DCC generates X-linked enrichment of the post-transcriptional histone modification H4K20me1 and that this modification is important for dosage compensation . As we observed here for C . elegans , H4K20me1 in other organisms is enriched on gene regions and its level is positively correlated with gene expression [29] . Although H4K20me1 levels are highest on actively transcribed genes , functional experiments in vertebrates and Drosophila point to a repressive role in gene expression . Knockdown of the H4K20me1 methyltransferase Pr-Set7 in human cells caused a two-fold upregulation of genes normally harbouring H4K20me1 [29] , and mutation of Pr-Set7 in Drosophila leads to position effect variegation , a hallmark of genes required for heterochromatic gene repression [30] . H4K20me1 is also associated with the inactive X chromosome during X inactivation in vertebrates [31] . Therefore , the high levels of H4K20me1 we observed on the C . elegans X chromosome are consistent with a role in dosage compensation-mediated repression of gene expression . What is the mechanism that leads to higher H4K20me1 levels and lower H4K20me3 levels on the hermaphrodite X chromosomes relative to autosomes ? Our results suggest that this is achieved at least in part through DCC inhibition of SET-4 activity on X . Lower conversion of H4K20me1 to H4K20me2/3 by SET-4 on the X chromosome would lead to relatively higher H4K20me1 levels and lower H4K20me2/3 levels there . Several observations support this model . First , dosage compensation mutants show lower overall H4K20me1 levels and higher H4K20me3 levels compared to wild type . Second , the lower overall H4K20me1 level in DCC mutants is due to inappropriate SET-4 activity , supporting the idea that active dosage compensation inhibits SET-4 activity . Third , the difference in H4K20me1 levels on the X versus the autosomes is abolished in set-4 mutants , indicating a role for SET-4 in generating the asymmetry . We propose that a component of the DCC prevents SET-4 from acting on the X chromosome , leading to maintenance of H4K20me1 on X , whereas H4K20me1 is preferentially converted to H4K20me2/3 on the autosomes . Because H4K20me1 levels are similar on X and autosomes in set-4 mutants , SET-1 might be equally active in generating H4K20me1 on all chromosomes . Our results suggest that of the three H4K20 methylation states , H4K20me1 is the key modification for dosage compensation . Whereas loss of dosage compensation leads to lethality of XX embryos , set-4 null mutants , which have strongly reduced levels of H4K20me2 and H4K20me3 , are viable , and RNAi of set-4 does not enhance lethality of DCC mutants . This suggests that these modifications are not necessary for dosage compensation . In contrast , RNAi depletion of maternal and zygotic set-1 leads to loss of H4K20me1 and embryonic lethality , set-1 genetically interacts with dosage compensation mutants , and set-1 mutants show upregulation of X-linked gene expression . When does H4K20me1 function in dosage compensation ? The DCC is recruited to the X chromosome around the 30-cell stage whereas X-chromosome enrichment of H4K20me1 occurs several hours later . This difference in timing suggests that there might be two separable aspects of dosage compensation during embryogenesis , for example initiation and maintenance . Although the DCC is recruited to the X in early embryogenesis , it is not yet known when repression of X-linked gene expression is initiated . The DCC might be active immediately after recruitment or might become active later in embryogenesis . Furthermore , although H4K20me1 becomes highly enriched on X in late embryogenesis , it is possible that a basal level on the X chromosome is functional earlier . Because the DCC component DPY-27 shows apparently normal localization to the X chromosome in the absence of SET-1 or SET-4 , H4K20me1 does not appear to be a recruitment signal for the DCC . Instead , H4K20me1 may be important for the function of the DCC in downregulating gene expression . Key future questions to address are when during embryogenesis X-linked gene expression is initially downregulated , and when H4K20me1 function is necessary . Regulation of histone modification levels also occurs during dosage compensation in other organisms . For example , in Drosophila , where gene expression on the single X chromosome in males is upregulated two-fold to match that of the two X chromosomes in females , dosage compensation acts to increase H4K16ac levels on the single male X . In addition , the inactive X chromosome of female mammals displays high levels of several histone modifications , including H4K20me1 [31] . H4K20me1 enrichment correlates with Xist expression , is independent of transcriptional silencing , and marks the early steps of X inactivation [31] . In addition to the strong enrichment of H4K20me1 on the X chromosome in C . elegans , Liu et al . showed that several marks of gene activity , including H4K16ac , were lower on X linked genes than on autosomal genes [15] . Using immunofluorescence assays on gut nuclei , a recent report by Wells et al . showed that the X/A difference in H4K16ac levels depends on dosage compensation and on sir-2 . 1 , a putative H4K16 deacetylase [21] . It is not clear if H4K16Ac plays a role in dosage compensation as depletion of sir-2 . 1 did not genetically interact with a DC mutant . The enzyme that generates H4K16Ac is not yet known . Using immunofluorescence assays , Wells et al . also observed that H4K20me1 enrichment on X is dependent on dosage compensation , and on SET-1 and SET-4 [21] . Our immunofluorescence results are broadly similar , and our ChIP experiments give a higher resolution view , strengthening these conclusions . In support of a role for methylation of H4K20 in dosage compensation , Wells et al . observed that simultaneous reduction of set-1 and set-4 by RNAi could rescue mutant males that normally die due to active dosage compensation . However , the H4K20 methylation state was not determined after simultaneous depletion of set-1 and set-4 , so the specific alteration of methylation of H4K20 that caused rescue is not known . The reported X/A differences in H4K16ac levels also depended on set-1 and set-4 , suggesting that H4K16Ac might be regulated by H4K20 methylation state . Although the exact mechanisms of dosage compensation vary , studies in different organisms suggest that global regulation of H4K16ac and H4K20me1 levels might be a conserved feature of these chromosome-wide gene regulation mechanisms . Our results indicate that H4K20me1 is important for repression of X-linked gene expression . How might H4K20me1 function in transcriptional repression ? Several links in the literature suggest roles for H4K20me1 in chromatin compaction . For example , the Malignant-Brain-Tumor ( MBT ) domains of human L3MBTL1 compact nucleosomal arrays by recognizing mono and dimethylation of H4K20 and H1bK26 [32] . Furthermore , L3MBTL1 has transcription repressor activity that is enhanced by Pr-Set7 , and its chromatin association depends on H4K20me1 [33] , [34] . It is not yet known whether C . elegans MBT repeat proteins LIN-61 or MBTR-1 are involved in dosage compensation or bind H4K20me1 . H4K20me1 has also been shown to be important during mitosis . H4K20me1 levels are high on mitotic chromatin ( [35] , [36] and this study ) , and in mammalian cells inhibition of Pr-Set7 leads to defects in cell cycle progression [36] , [37] , [38] , [39] . Although the function of H420me1 in cell cycle progression is not yet understood , a key aspect of the loss of function phenotype is reduced chromosome compaction . Furthermore , a recent study demonstrated that two components of condensin II , N-CAPD3 and N-CAPG2 , can directly bind H4K20me1 [35] . This raises the exciting possibility that condensin IDC might function to compact chromatin through binding H4K20me1 . Increased compaction of the X chromosome relative to the autosomes might reduce access by RNA polymerase , leading to lower X-linked gene expression . Consistent with this idea , DCC mutants were recently shown to have increased RNA polymerase II levels on the X [13] . We propose that condensin complexes and H4K20me1 might be intimately linked in diverse chromatin-regulating events .
The following strains were used and cultured using standard methods ( Brenner , 1974 ) : TY0621 [yDp1 ( IV , V:f ) ; dpy-26 ( n199 ) unc-30 ( e191 ) IV] , DR1410 [dpy-27 ( y56 ) /qC1 III] , TY1621 [unc-49 ( e382 ) dpy-28 ( y1ts ) III] , TY148 [dpy-28 ( y1ts ) III] , CB428 [dpy-21 ( e428 ) V] , KK0423 [dpy-21 ( e428 ) par-4 ( it57ts ) V] , TY1936 [dpy-30 ( y228 ) V/nT1[unc- ? ( n754 ) let- ? ] ( IV;V ) ] , SS1075 [set-1 ( tm1821 ) /hT2G ( qIs48 ) I;III] , JA1574 [set-1 ( tm1821 ) /hT2G ( qIs48 ) I;III] , MT14911 [set-4 ( n4600] , YPT41 [X;II] . Late embryo ( LE ) extracts were prepared by growing wild-type N2 adult worms from synchronized L1s in standard S-basal medium with shaking . Worms were fed HB101 E . coli and grown at 20°C until they were gravid , approximately 70 hours . Embryos were obtained by dissolving adult worms with bleach , and then the embryos were aged by incubating in M9 media for 3 . 5 hrs at 20°C with gentle rocking . The embryos were washed once with PBS and flash frozen in liquid nitrogen , then processed for ChIP as in [40] . Wild-type , dpy-21 ( e428 ) , and set-4 ( n4600 ) L3 and fem-2 YA animals were grown and ChIPs performed as in [41] except that DNA was sonicated to a size range of 200–400 bp . EE and L3 in Figure 1 are from [15] ( Abcam ab9051; lot 104513 ) . H4K20me1 ChIP conditions were: LE ( 1 mg extract and 5 ul Diagenode SN-147 ) , fem-2 young adults ( 1 . 25 mg extract and 3 ug Abcam ab9051 lot 104513 ) , dpy-21 L3s ( 500 ug extract and 2 ug Abcam ab9051 lot 104513 ) , WT and set-4 L3s in Figure S6 ( 500 ug extract and 2 ug Abcam ab9051 lot 602259 ) , WT L3 in Figure S7 ( 500 ug extract and 5 ul Diagenode SN-147 ) . The Diagenode SN-147 and Abcam ab9051 antibodies give concordant patterns by ChIP in L3 extracts ( Figure S7A , S7B ) . H4K20me3 ChIP conditions: 500 ug L3 extract and XX Abcam 78517 lot 827718 . Antibodies used for ChIP , western blot , or immunofluorescence were tested for specificity to histone peptide tails using dot blots ( [42] and http://compbio . med . harvard . edu/antibodies/ ) . Early Embryo , Late Embryo , L3 , and dpy-21 L3 H4K20me1 ChIPs and L3 H4K20me3 ChIPs were hybridized to a C . elegans full-genome tiled microarray ( NimbleGen 2 . 1 , Roche ) . For H4K20me1 ChIPs , log2 ratios of IP/Input were obtained and standardized so the autosomal signal had mean 0 and standard deviation 1 . The H4K20me3 L3 ChIP dataset was processed similarly except that all chromosome regions were used . fem-2 young adult ( Figure 1 ) and WT and set-4 L3 H4k20me1 ChIPs in Figure S6 were sequenced on the Illumina platform , aligned using BWA with default settings [43] , normalized using BEADS [44] , then converted to log2 ratios of BEADS scores ( enrichment relative to input ) and standardized so the mean of the autosomal signal was 0 and the standard deviation 1 . Biological ChIP-chip and ChIP-seq replicates were averaged after standardization . Gene profile plots ( Figure 1 and Figure S6 ) were generated by aligning genes at their TSS and TES ( WS190/ce6 ) . The genomic regions 1 kb upstream to 1 kb downstream from TSS and 1 . 5 kb upstream to 1 kb downstream from TES were divided into 50-bp bins . Genes were grouped into top 20% and bottom 20% expressed and autosomal and X-linked genes . Mean signals for each group of genes and each bin were plotted as well as the 95% confidence intervals of the mean ( as error bars ) . Profile plots of intergenic regions were obtained by first identifying regions of at least 10 kb length without any annotation ( WS190/ce6 ) ( 491 such regions on autosomes , 193 on chromosome X ) . The regions were aligned at their center and the genomic regions from 5 kb upstream to 5 kb downstream from the center were divided into 50 bp bins . Mean signals for the autosomal and X intergenic regions were plotted as well as the 95% confidence intervals of the means . Boxplots ( Figure 1 and Figure S7 ) were obtained after 1 kb median smoothing along the chromosomes of the respective standardized log2 ratios . Each box indicates the median with the center line and extends from the 25th to the 75th percentile of the standardized log2 ratios; whiskers extending from the box indicate the 2 . 5th and 97 . 5th percentiles . Transcript data for the EE , LE , L3 and YA stages were obtained from the modENCODE DCC ( http://intermine . modencode . org ) . The platform was a single color 4-plex Nimblegen expression array with 72 , 000 probes ( three 60-mer oligo probes per gene ) . Quantile normalization [45] and the Robust Multichip Average ( RMA ) algorithm [46] were used to normalize and summarize the multiple probe values per gene to obtain one expression value per gene and sample . Sample buffer was added directly to worms , samples heated to 65°C for 10 minutes , sonicated for 15 minutes ( 30 sec in/30 sec out ) , incubated at 65°C for 5 min and finally boiled at 95°C for 5 min . Proteins were separated on 4–12% NuPage SDS pre-cast gels ( Invitrogen ) . The following antibodies were used: anti-H4K20me1 ( Abcam ab9051 at 1∶2000 ) , anti-H4K20me2 ( H . Kimura monoclonal antibody 2E2 at 1∶20 , 000 ) , anti-H4K20me3 ( Abcam ab78517 at 1∶500 ) , anti-H3 ( Active Motif 39163 at 1∶8000 ) , and anti-SET-1 ( SDI SDQ3895 ) . JA1574 was used to obtain set-1 homozygotes in Figure 5B . Immunostaining of embryos and dissected intestines was done using methanol/acetone fixation as in [47] ( Figure 2; Figure 5; Figure S1 , S2 , and S4 ) or using methanol fixation as in [48] ( Figure 4 , Figure 6 , Figure S5 ) . Germline immunofluorescence experiments ( Figure S3 ) were carried out after dissecting worms in egg buffer containing 0 . 1% Tween 20 and fixation in 1% formaldehyde in egg buffer [49] . SS1075 was used for the IF experiment in Figure 5A . Primary antibodies used are indicated in the figure legends . Antibody concentrations used were: anti-H4K20me1 Kimura 1F11 ( 1∶40 , 000 ) , anti-H4K20me1 Diagenode SN-147 ( 1∶100 , 000 ) , anti-H4K20me1 Abcam ab9051 ( 1∶400 for Figure S1; 1∶5000 for Figure S3 ) , anti-H4K20me2 Kimura 2E2 ( 1∶25 , 000 ) , anti-H4K20me3 ab78517 ( 1∶200 ) , anti-DPY-27 SDI SDQ3995 ( 1∶4000 ) , anti-GFP Abcam ab290 ( 1∶6000 ) , anti-H3S10p Kimura 10H12 ( 1∶1000 ) , anti-HIM-8 ( 1∶250 ) . Secondary antibodies were purchased from Jackson ImmunoResearch or Molecular Probes . Total RNA was extracted from N2 ( wild type ) , dpy-21 ( e428 ) , dpy-28 ( y1 ) , or set-1 ( tm1821 ) L3 worms grown at 25°C using TriPure ( Roche ) . RNA was further purified using an RNeasy column ( Qiagen ) . Reverse transcription was carried out using the Invitrogen SuperScript III First-Strand Synthesis System . Quantitative PCR was performed using primers specific to the target genes: Chromosome V: W07G4 . 4 F: GCAATCGCTCCAGCCGTTAACAAT; R: TCGTCCAGATGGAACGACAGATGA act-1 F: TGCAGAAGGAAATCACCGCTCTTG; R: AAGCACTTGCGGTGAACGATGGAT Chromosome X: apl-1 F: ACGACGACGATGAGGATGATGCTT; R: TGAACTTCTCGGCTCCCTTTGGAT aco-1 F: CAAGATCAACCCAGTATGCCCAGT; R: ACCTGATGGACGATTCCAGATCCT ajm-1 F: TCGTCTTGATGAGATGGAACGCGA; R: AAGTTCTGCGTTACGTTGGGCTTG Gene expression levels in each strain were normalized to the levels of the autosomal gene W07G4 . 4 . Expression of each gene in wild-type N2 was then set to 1 and mutant expression levels expressed relative to N2 . RNAi by feeding was performed on N2 ( wild type ) , dpy-21 ( e428 ) and dpy-28 ( y1 ) animals as follows: 3–5 L3 larvae were placed on RNAi bacteria for three days at 15°C , transferred to new RNAi plates for 24 hours , transferred again after 24 hours , then removed . The progeny on the latter two plates were scored for embryonic lethality . We note that RNAi of set-1 leads to embryonic lethality in the N2 ( wild-type ) background in embryos produced in the next 24 hours of RNAi feeding , or if RNAi is performed by injection ( not shown ) . RNAi plates were prepared as in [50] . The following RNAi clones were used from [51] , [52]: sdc-2 ( C35C5 . 1 ) , set-1 ( T26A5 . 7 ) , set-2 ( C26E6 . 9 ) , met-1 ( C43E11 . 3 ) , and met-2 ( R05D3 . 11 ) . The set-4 RNAi clone was made by PCR amplifying and cloning a portion of the set-4 gene into RNAi feeding vector L4440 . The primers used were: atacgaattcacaggtcggc and tgctactacgcttgtcgtcg . RNAi plasmids were in the HT115 ( DE3 ) bacterial strain , which was used as the control . All RNAi clones were verified by sequencing . H4K20me1 ChIPs were performed in mixed stage embryos from wild-type N2 normal karyotype strain ( 2 replicates ) and in YPT41 X;II fusion strain ( 2 replicates ) using methods described previously [53] . 1 mg of total embryo extract and 2 ug of H4K20me1 antibody ( Abcam ab9051 ) were used per ChIP . The ChIP DNA was prepared for Illumina multiplex sequencing with slight modifications to the manufacturers protocol [54] . Briefly , sequencing libraries were prepared from half of the ChIP DNA and 10 ng of corresponding input DNA . NEB Klenow , T4 DNA polymerase and T4 PNK were used to repair ends at 20°C for 30 min . Exo ( - ) Klenow fragment and dATP was used to add adenosine at the 3′ ends for 1 hour at 37°C . DNA was ligated to multiplex adaptors ( Illumina ) and amplified by PCR , introducing the following indices: N2 H4K20me1 ChIP index #6 ( GCCAAT ) , N2 Input index #12 ( CTTGTA ) , YTP41 H4K20me1 ChIP replicate 1 index #2 ( CGATGT ) , input index #3 ( TTAGGC ) , and H4K20me1 ChIP replicate 2 index #1 ( ATCACG ) , input index #5 ( ACAGTG ) . DNA between 200–500 bp in size was gel purified . Multiplexed single-end sequencing was performed by GAIIx at the UNC high-throughput sequencing facility . The sequencing reads , obtained from the Illumina pipeline in fastq format , were aligned to the ce6 ( WS190 ) version of the C . elegans genome with Bowtie [55] , using default parameters . Each sequence read was extended to calculate coverage per base pair using MACS [56] . The coverage from the input data was subtracted from that of the ChIP data , and ChIP enrichment was standardized by z score transformation . Accession numbers for datasets generated in this paper are listed in Table S1 .
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In many animals , males have one X chromosome and females have two . However , the same amount of gene expression from X chromosomes is needed in the two sexes . The process of dosage compensation ( DC ) globally regulates X-chromosome gene expression to make it equal between the sexes , and it occurs in different ways in different animals . In mammals , one X chromosome in females is randomly inactivated , leaving one active X chromosome . In contrast , in the nematode worm C . elegans , the two X chromosomes in hermaphrodites are repressed two-fold to match gene expression to the single X chromosome in males . Previous work in C . elegans identified proteins required for DC that bind to the X chromosome , but their mode of action is not known . Here we show that DC proteins lead to higher levels of histone H4 lysine 20 monomethylation ( H4K20me1 ) on hermaphrodite X chromosomes and that H4K20me1 functions in repressing X-chromosome gene expression . This shows that histone modification is an important aspect of the mechanism of dosage compensation . Together with previous work linking H4K20me1 to chromatin structure regulation , our results suggest that dosage compensation might lower gene expression on hermaphrodite X chromosomes by compacting them .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"biology"
] |
2012
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H4K20me1 Contributes to Downregulation of X-Linked Genes for C. elegans Dosage Compensation
|
Dengue virus ( DENV ) causes more human infections than any other mosquito-borne virus . The current lack of antiviral strategies has prompted genome-wide screens for host genes that are required for DENV infectivity . Earlier transcriptomic studies that identified DENV host factors in the primary vector Aedes aegypti used inbred laboratory colonies and/or pools of mosquitoes that erase individual variation . Here , we performed transcriptome sequencing on individual midguts in a field-derived Ae . aegypti population to identify new candidate host factors modulating DENV replication . We analyzed the transcriptomic data using an approach that accounts for individual co-variation between viral RNA load and gene expression . This approach generates a prediction about the agonist or antagonist effect of candidate genes on DENV replication based on the sign of the correlation between gene expression and viral RNA load . Using this method , we identified 39 candidate genes that went undetected by conventional pairwise comparison of gene expression levels between DENV-infected midguts and uninfected controls . Only four candidate genes were detected by both methods , emphasizing their complementarity . We demonstrated the value of our approach by functional validation of a candidate agonist gene encoding a sterol regulatory element-binding protein ( SREBP ) , which was identified by correlation analysis but not by pairwise comparison . We confirmed that SREBP promotes DENV infection in the midgut by RNAi-mediated gene knockdown in vivo . We suggest that our approach for transcriptomic analysis can empower genome-wide screens for potential agonist or antagonist factors by leveraging inter-individual variation in gene expression . More generally , this method is applicable to a wide range of phenotypic traits displaying inter-individual variation .
Dengue virus ( DENV ) is a mosquito-borne RNA virus of the Flavivirus genus ( family Flaviviridae ) that causes an estimated 390 million human infections annually [1] . Although the first dengue vaccine was recently approved in a few countries [2 , 3] , its potential impact is still uncertain [4] . In the absence of specific therapeutics , dengue prevention is limited to vector control , which can be effective but is difficult to sustain in the long term [5] . DENV exists as four serotypes ( DENV-1 , -2 , -3 and -4 ) that are phylogenetically related and loosely antigenically distinct [6] . DENV has a positive-sense , single-stranded RNA genome that encodes only three structural proteins and seven non-structural proteins . Due to this minimal genetic material , DENV depends on numerous host cellular factors to complete its lifecycle that represent promising targets for the development of antiviral strategies [7 , 8] . Accordingly , recent genome-wide screens identified multiple human and insect factors required for DENV infectivity [9–12] . For example , several endoplasmic reticulum-associated proteins are necessary for Flavivirus infection in both human and insect cells [9 , 12] . Functional validation in vivo in Aedes mosquitoes is an important step of such genome-wide screens because candidate host factors identified in model systems are not necessarily confirmed in more biologically relevant organisms . For instance , when the orthologues of three candidate host factors identified in Drosophila cells were tested in the main DENV vector Aedes aegypti , only one had a conserved function in mosquitoes in vivo [11] . One difficulty associated with in vivo experiments is that multiple tissues can become infected and may display tissue-specific responses [13 , 14] . In the field , mosquitoes acquire DENV infection after feeding on a viremic host . Following the infectious blood meal , DENV infection is initially established in the mosquito midgut before the virus spreads systemically to infect the salivary glands and is eventually released in the saliva , through which it is transmitted to the next host [15] . Anatomical barriers to DENV propagation in Ae . aegypti have been described , namely a midgut infection barrier and a midgut escape barrier [16] . These tissue barriers are quantitative genetic traits controlled by the mosquito genotype [17–19] and specific interactions between mosquito and virus genotypes [20] . Viral genetic determinants [21] , the mosquito RNA interference ( RNAi ) pathway [22 , 23] , and putative receptors [24] have been suggested to mediate these barriers , but overall their molecular nature is still poorly understood [25] . With a few exceptions [26–28] , the specific mosquito genes that modulate DENV infection in the midgut of Ae . aegypti remain to be identified . Earlier functional genomics studies of DENV infection in the Ae . aegypti midgut focused on mosquito innate antiviral immunity [26 , 29–31] , or documented transcriptome-wide patterns of gene expression upon DENV exposure [13 , 14 , 32 , 33] . It is worth noting that all these studies used either reference laboratory strains of Ae . aegypti , such as the Rockefeller and the Liverpool strains , or mosquito lines artificially selected for DENV resistance or susceptibility . Although transcriptomic responses may substantially vary between different Ae . aegypti strains [13 , 34] , laboratory strains are experimentally powerful because their usually high level of inbreeding minimizes inter-individual variation . To further reduce inter-individual variation , most of these earlier studies examined differential gene expression based on pools of mosquitoes . Here , we used an alternative functional genomics approach that takes advantage of inter-individual variation in a field-derived Ae . aegypti population . Using mosquitoes and a DENV isolate originating from Kamphaeng Phet Province in Thailand , we simultaneously examined the transcriptome of 45 individual midguts by RNA sequencing ( RNA-Seq ) following oral DENV exposure . In addition to a conventional pairwise comparison of DENV-infected versus uninfected control midguts , we examined the correlation between individual midgut viral RNA load and gene expression level among DENV-infected midguts . The aim of the correlation analysis was to identify genes modulating midgut infection without being differentially expressed between DENV-infected and uninfected individuals . For instance , a transcript whose average expression is not significantly different between DENV-infected mosquitoes and uninfected controls would go undetected by pairwise comparison . However , the expression level of this transcript could be significantly correlated with viral RNA load within DENV-infected individuals . Our correlation analysis thus identifies this transcript as a candidate . We demonstrated that this approach has two main advantages . First , it led us to the identification of a set of candidate genes that was not detected by pairwise comparison . Second , the sign of the correlation ( i . e . , positive or negative association with viral RNA load ) was used to make a prediction about the agonist or antagonist effect of the gene product on virus infection . Agonist refers to a gene promoting virus replication whereas antagonist refers to a gene impairing virus replication . We used Pearson’s determination coefficient as a simple measure of the linear co-variation between viral RNA load and gene expression . We confirmed the validity of our approach with a candidate gene encoding a sterol regulatory element-binding protein ( SREBP ) . SREBPs are transcriptional regulatory proteins conserved among metazoans that modulate lipid biosynthesis [35] . SREBP was identified by our correlation analysis but not by conventional pairwise comparison . Positive correlation between SREBP expression and DENV RNA load in the midgut was consistent with an agonist effect of this gene . As predicted , SREBP knockdown in vivo resulted in reduced viral RNA load , revealing a previously unknown agonist role of this mosquito gene during early DENV infection of the Ae . aegypti midgut .
We sampled Ae . aegypti mosquitoes from a natural population in Thailand and conducted our experiments within the first ten generations of laboratory colonization . In order to preserve its genetic diversity , the colony was maintained as an outbreeding population with several hundreds of reproducing adults at each generation . To examine the temporal dynamics of midgut infection in individual mosquitoes , we monitored DENV genomic RNA concentration in individual midguts of Ae . aegypti females following exposure to an infectious blood meal containing 1 . 08 x 107 focus-forming units per mL ( FFU/mL ) of blood . This infectious dose was chosen to maximize midgut infection prevalence . During a 10-day time-course experiment , 137 out of 138 tested midguts were positive for DENV RNA ( Fig 1 ) . Based on the presence of undigested blood observed during midgut dissection , blood digestion took up to 4 days ( Fig 1 ) . Lack of significant variation in the midgut viral RNA load measured immediately after blood feeding indicated that female Ae . aegypti ingested similar amounts of DENV ( Fig 1 , 0 hour post virus exposure ) . Viral RNA load in the midgut dropped during the first 6 hours post exposure , then increased exponentially for 3 days before reaching a plateau from 7 to 10 days post exposure . Statistical significance of differences across time points is shown in Fig 1 . Within each time point , midguts displayed inter-individual variation in viral RNA load as early as 6 hours post exposure . For instance , we observed up to 1 , 000-fold and 10 , 000-fold differences in DENV load among individual mosquito midguts on day 1 and day 4 , respectively ( Fig 1 ) . Viral RNA load can be several orders of magnitude higher than infectious titer [36] but we chose to focus on viral RNA load rather than infectious titers for two reasons . First , we were primarily interested in host factors influencing viral replication and viral RNA load is a better proxy for viral replication efficiency than infectious titer . The latter is a composite phenotype that can be influenced by several other steps than viral replication such as viral particle assembly and maturation . Second , the first few days of mosquito infection by arboviruses are characterized by a so-called eclipse phase during which infectious particles are undetectable [37] . Therefore , our results show that midgut viral RNA load varied significantly not only over the time course but also among individual mosquitoes at a given time point . We next investigated whether this individual variation in viral RNA load could be leveraged to identify novel host factors that modulate midgut infection . To identify mosquito genes contributing to natural inter-individual variation in midgut viral RNA load , we used a non-conventional approach for transcriptome analysis . We reasoned that correlating viral RNA load with gene expression at the inter-individual level among DENV-infected mosquitoes could provide information that would be missed by pairwise comparison between DENV-infected and uninfected individuals . To validate our method , we focused on the exponential growth phase of DENV midgut infection ( Fig 1 ) . Although successful infection of the midgut is essential for subsequent virus dissemination and transmission , DENV host factors during midgut infection remain largely unknown . Viral dissemination from the midgut to other tissues typically begins around 4 days post exposure [38] and it was confirmed in this mosquito population . We focused on day 1 and day 4 post exposure because they displayed the largest inter-individual variation in viral RNA load ( Fig 1 ) . Forty-five individual midguts collected either 1 or 4 days after virus exposure were used for transcriptome analysis by RNA-Seq . They consisted of 16 DENV-infected midguts collected 1 day post exposure , 17 DENV-infected midguts collected 4 days post exposure and 6 control midguts collected at each time point from individuals fed on uninfected blood . The mean number of raw sequencing reads per library that mapped to Ae . aegypti transcripts was significantly higher on day 1 than on day 4 post exposure ( ANOVA: P < 0 . 01 ) , presumably because the digestion process was on-going on day 1 but not on day 4 ( S1 Fig ) . Therefore , we analyzed day 1 and day 4 midgut transcriptomes separately in all subsequent statistical analyses . However , the total number of mapped raw reads per library did not vary significantly between DENV-infected and control midguts ( ANOVA: P = 0 . 9 ) . A total of 13 , 843 unique mosquito transcripts were detected considering both time points together . To correct for multiple testing , we calculated a false discovery rate ( FDR ) according to the Benjamini-Hochberg procedure [39] . Based on an FDR threshold of 0 . 1 , we identified 273 Ae . aegypti candidate transcripts by either pairwise comparison or correlation analysis ( S2–S5 Tables ) . Only four transcripts were detected by both methods across all time points ( Fig 2A ) . By pairwise comparison , 230 transcripts were differentially expressed between DENV-infected and control midguts ( Fig 2A ) . All of these transcripts were identified 1 day post exposure ( Fig 2B , blue and yellow dots ) . The correlation analysis identified 43 candidate transcripts whose expression was correlated with midgut viral RNA load ( Fig 2A ) . The majority of those transcripts were identified 4 days post exposure ( Fig 2B , red dots ) . Among the four transcripts in common between the two methods , two ( AAEL010168 and AAEL010169 ) were both correlated to viral RNA load and differentially expressed at the same time point ( day 1 ) whereas the two others ( AAEL000293 and AAEL017516 ) were detected by the pairwise comparison on day 1 and by the correlation analysis on day 4 ( Fig 2B , yellow dots ) . According to gene ontology ( GO ) classification at the biological process level , most of the candidate transcripts belong to metabolism , transcription/translation , oxidation-reduction and proteolysis categories , irrespective of the time point and analysis strategy . Candidates identified by pairwise comparison include transcripts encoding several zinc-finger proteins and immune-related transcripts previously associated with DENV infection in Ae . aegypti such as the transcription factor REL1A [30] and the Complement-related factor AaMCR [31] ( S2 Table ) . Several candidates identified by pairwise analysis are genes involved in lipid metabolism , such as the 85-kda calcium-independent phospholipase A2 ( AAEL012835 ) , a ceramidase ( AAEL007030 ) , a lipase ( AAEL001837 ) , a Niemann-Pick-type C2 protein ( AAEL009953 ) [27] and a regulator of the Wnt pathway ( AAEL004858 ) ( S2 Table ) . The correlation analysis identified 43 candidate transcripts , of which 39 were not differentially expressed between DENV-infected and uninfected control midguts at any of the time points . The expression level of these genes was linearly associated with midgut viral RNA load , either positively ( n = 18 ) or negatively ( n = 21 ) . Because of the statistical association between viral RNA load and gene expression , we hypothesized that the sign of the correlation ( i . e . , positive or negative ) could predict the effect of the candidate transcript on DENV infection ( i . e . , agonist or antagonist ) . The correlation analysis detected several immune-related genes encoding , for instance , a serine protease inhibitor ( AAEL008364 ) , a thioester-containing protein 3 ( AAEL008607 ) or a leucine-rich immune protein ( AAEL008658 ) . Expression of immune-related genes was most often negatively correlated with viral RNA load 4 days post virus exposure ( S4 Table ) . Conversely , the expression of two genes involved in lipid homeostasis was positively correlated with viral RNA load 4 days post exposure . One encodes a fatty acid synthase ( AAEL001194 ) and the other a sterol regulatory element-binding protein ( SREBP , AAEL010555 ) . To demonstrate the value of our correlation analysis and to provide the proof of concept that the sign of the correlation could be used to make a functional prediction relative to virus infection , we chose gene AAEL010555 ( SREBP ) for functional validation in vivo because of its known role in other viral infections [40–44] . SREBP was not differentially expressed between DENV-infected and control midguts at any of the two time points ( Fig 3A ) . However , midgut viral RNA load and SREBP expression were positively correlated on day 4 based on our FDR significance threshold of 0 . 1 ( Fig 3B ) . The correlation was stronger ( r = 0 . 70; P = 0 . 004 ) when the three individual midguts with viral loads >107 RNA copies were excluded , consistent with a differential relationship at low versus high viral loads . We predicted that the positive correlation observed for this gene 4 days post exposure indicated an agonist role during midgut infection , and therefore that SREBP knockdown during DENV midgut infection would result in reduced viral RNA load . To test the putative agonist role of SREBP during midgut infection by DENV , we used RNAi-mediated gene knockdown assays in vivo ( Fig 4A ) . Double-stranded RNA ( dsRNA ) targeting SREBP ( dsSREBP ) was injected into the thorax of Ae . aegypti females to reduce SREBP expression . Control mosquitoes were injected with the same amount of dsRNA targeting green fluorescent protein ( dsGFP ) . Three days later , we offered mosquitoes a DENV infectious blood meal and quantified viral RNA load in individual midguts by quantitative RT-PCR 1 and 4 days post exposure . SREBP knockdown efficiency was 99 . 7% , 79 . 3% and 47 . 0% on day 0 , day 4 and day 7 post DENV exposure , respectively ( S3A Fig ) . We observed a significant drop in midgut viral RNA load following SREBP knockdown on day 4 post DENV exposure ( Fig 4B ) . There was a 50% reduction in midgut viral RNA load in mosquitoes injected with dsSREBP relative to mosquitoes injected with dsGFP . To further confirm the role of SREBP as a DENV agonist , we performed RNAi-mediated gene knockdown assays in vivo in a different mosquito population . The field-derived Ae . aegypti population used for the transcriptomic analysis was originally collected in Thailand . We repeated the experiment in another field-derived mosquito population from Cambodia and also observed a statistically significant reduction of viral RNA load in the midgut following SREBP silencing ( S2 Fig ) . In the control groups , the mosquito population from Cambodia had significantly higher prevalence ( P = 0 . 0465 ) but lower viral RNA load ( P < 0 . 0001 ) at day 4 than the population from Thailand . This result is consistent with the agonist role of SREBP in DENV replication regardless of the mosquito geographical origin or intrinsic level of susceptibility . In addition to SREBP , RNAi-mediated knockdown was performed against two control genes already known to modulate DENV midgut infection in Ae . aegypti , Argonaute-2 ( AAEL017251 , Ago2 ) , and Cactus ( AAEL000709 ) [29 , 30] . For all target genes ( SREBP , Ago2 , Cactus ) , a significant decrease in gene expression was measured on the day of DENV exposure although knockdown efficiency varied between target genes at later time points ( S3 Fig ) . Knockdown of all target genes did not consistently affect the blood-feeding rate , which varied according to the interaction between treatment and experiment ( S4 Fig ) . As expected , Ago2 knockdown resulted in a statistically significant 42% increase of midgut viral RNA load 4 days post exposure . Note this could be an underestimation , due to the negative feedback loop of using a RNAi-mediated gene silencing assay to knockdown a gene involved in the RNAi pathway . Likewise , Cactus knockdown was associated with a statistically significant 81% decrease of DENV load in the midgut 4 days post exposure ( Fig 4B ) . These results were repeatable in at least two separate experiments , thereby validating our gene knockdown assay . Mosquitoes injected with dsRNA against Ago2 or Cactus died faster than dsGFP-injected controls ( Cox model: P < 0 . 0001 ) , whereas no significant difference was detected in the survival of mosquitoes injected with dsSREBP or dsGFP until day 7 post injection ( Cox model: P = 0 . 3 ) ( Fig 4C ) . Unlike viral RNA load , the proportion of DENV-infected midguts 4 days post exposure was not influenced by the knockdown of any of the three target genes ( Fig 4D ) .
We used a non-conventional analysis of transcriptomic data to identify new DENV host factors during early midgut infection in a field-derived mosquito population . We observed substantial variation in the individual midgut viral RNA load following oral exposure to the same infectious dose of DENV . This variation presumably results primarily from genetic differences because the viral RNA load measured in midguts on day 0 was almost equal among individuals and all environmental conditions were standardized . Instead of erasing this variation by pooling individual samples prior to transcriptomic analysis , we hypothesized that this variation contained valuable information that could be leveraged . Our approach is expected to identify genes whose expression does not necessarily differ between DENV-infected and uninfected mosquitoes ( i . e . , that go undetected by conventional pairwise comparison ) but is linearly correlated with viral RNA load . It is worth noting that we used viral RNA load as a proxy for viral replication efficiency in the midgut , which does not directly translate into the level of vector competence . Indeed , viral RNA load in the midgut may not correlate with the probability of virus transmission ( e . g . , [45] ) . As a consequence , the candidate genes that we identified do not necessarily meet the requirements to be considered as potential effectors in genetic-based vector control strategies but mainly as host factors agonist or antagonist of viral replication at early time points following infection . The 230 candidate genes identified by pairwise comparison between DENV-infected and control midguts were detected 1 day post exposure . This indicates that the strongest modulation of midgut gene expression occurs early upon infection . This reinforces observations from previous transcriptomic studies that detected the highest number of differentially expressed genes from 18 to 24 hours post DENV exposure [14 , 32] . The absence of differentially expressed genes detected 4 days post exposure in our study could result from the use of individual transcriptomes , which reduces the potential bias due to outliers ( i . e . , genes with extreme expression levels ) that may often exist in mosquito pools . The use of individual midgut transcriptomes allowed identification of 39 genes whose expression was correlated with viral RNA load , in the absence of differential expression between DENV-infected and control individuals . Although this is less than the 226 candidate genes only identified by conventional pairwise comparison , the sign of the correlation allows a strong prediction to be made about the effect of these additional candidates on DENV infection . Only four candidates were detected by both methods , indicating limited overlap between the two analyses and emphasizing their complementarity . GO classification did not reveal cellular or molecular functions specific to one type of analysis , but numerous genes in the current annotation of the Ae . aegypti reference genome remain anonymous and lack a predicted function . Improved genome annotations in the future may help to determine whether our correlation analysis and conventional pairwise comparison identify fundamentally different classes of genes . Based on the available annotations , numerous candidate genes were related to lipid metabolism regardless of the analysis . Identification of candidate genes involved in lipid metabolism is consistent with previous studies [13 , 14 , 27 , 46] . To confirm the validity of our correlation approach and to test our hypothesis that the sign of the correlation was predictive of the agonist or antagonist effect of the gene , we focused on a gene encoding a sterol regulatory element-binding protein ( SREBP ) . SREBP was only detected by the correlation analysis and its expression was positively correlated to viral RNA load , suggesting that this gene promotes virus infection . We confirmed this prediction by RNAi-mediated gene knockdown assays in vivo . SREBP genes are conserved among metazoans . Humans harbor three SREBP isoforms whereas only one SREBP homologue was identified in Drosophila melanogaster ( HLH106 ) and in Ae . aegypti [47 , 48] . SREBPs are membrane-bound transcription factors regulating cholesterol and fatty acid synthesis [49] . In our field-derived Ae . aegypti population , SREBP was not differentially expressed between DENV-infected and uninfected control midguts , in contrast with an earlier study that reported down-regulation of this gene after DENV exposure in pools of mosquitoes from a laboratory strain of Ae . aegypti [14] . Whether this discrepancy results from differences between mosquito strains , sampling strategy ( pooling versus individual transcriptomes ) , or other differences in the experimental strategy ( virus strain , midgut versus whole body , etc . ) is unknown . Studies in mice and flies indicate that SREBP is likely an essential gene during early development . SREBP knockout increased embryonic lethality in mice , and Drosophila SREBP mutants died at the larval stage while dietary supplementation with fatty acids rescued mutants to adulthood [35 , 50 , 51] . An earlier transcriptomic study in Ae . aegypti reported that SREBP expression was up regulated following blood uptake [52] , which is in line with the fact that lipids from the blood meal are required for oocyte maturation [53] . In our two Ae . aegypti population , SREBP knockdown did not significantly impact short-term adult survival . Conversely , we observed a 35% reduction in mosquito survival within 24 hours following Ago2 knockdown , and a 15% reduction in mosquito survival associated with Cactus knockdown following blood feeding . The fitness cost observed in both control treatments could have resulted from immune impairment or from disruption of other processes regulated by the RNAi and Toll pathways . Our results demonstrated that SREBP is an agonist factor during early DENV infection of the Ae . aegypti midgut . Although the underlying mechanism remains to be elucidated , SREBP knockdown was associated with a 53 . 8% decrease of DENV RNA load in the midgut of our Ae . aegypti population from Thailand ( and 26 . 9% in the population from Cambodia; S2A Fig ) . Knocking down Ago2 , a critical component of the mosquito antiviral response , resulted in a similar effect size ( a 42% increase ) in midgut viral RNA load . However , the relatively weak correlation between SREBP expression and viral RNA load indicates that other host factors determine the efficiency of viral replication . Our finding is consistent with the central role of lipid homeostasis during viral infections . Lipids are required for efficient replication of numerous viruses in mammalian cells including DENV [54 , 55] . SREBP proteins are transcription factors that regulate a variety of genes involved in lipid synthesis [56] . Hepatitis C virus , a member of the Flaviviridae family , increases the amount of lipid droplets through a DDX3X-IKK-α-SREBP pathway that allows assembly of viral particles in human cells [57] . DENV infection also increases the number of lipid droplets in mammalian cells [58] and recently lipid droplets were suggested to play a role during DENV infection in Ae . aegypti [46] . Human cytomegalovirus , hepatitis B virus and hepatitis C virus have been shown to activate SREBP , which can result in an increase in lipid synthesis to promote viral infection [40–44] . In insects , Drosophila C virus replication is attenuated in SREBP null mutant flies [59] . Thus , our finding that SREBP is a host factor promoting DENV infection in Ae . aegypti adds to the accumulating evidence for a widespread agonist role of this gene during viral infections . Our results illustrate how transcriptomic data obtained at the individual level can enhance functional genomics studies and improve our understanding of host-pathogen interactions . Based on transcriptome sequencing of individual mosquito midguts , we took advantage of inter-individual variation in gene expression and midgut viral RNA load by using their co-variation as an indication of a functional relationship . The candidate genes that we identified by this method should be useful for other investigators in the field . Identification of DENV host factors in vivo paves the way for future mechanistic studies and may ultimately contribute to the development of novel antiviral strategies . More generally , our transcriptomic approach should be of interest in other organisms because it is applicable to virtually any continuous trait with inter-individual variation .
The Institut Pasteur animal facility has received accreditation from the French Ministry of Agriculture to perform experiments on live animals in compliance with the French and European regulations on care and protection of laboratory animals . This study was approved by the Institutional Animal Care and Use Committee at Institut Pasteur under protocol number 2015–0032 . Mosquito cells ( Ae . albopictus C6/36 ) were maintained in Leibovitz's L-15 medium ( Life Technologies ) supplemented with 10% foetal bovine serum ( FBS , Life Technologies ) , 1% non-essential amino acids ( Life Technologies ) and 0 . 1% Penicillin-Streptomycin ( Life Technologies ) at 28°C . DENV-1 isolate KDH0030A was originally derived in 2010 from the serum of a dengue patient attending Kamphaeng Phet Provincial Hospital , Thailand [20] . Informed consent of the patient was not necessary because the virus isolated in laboratory cell culture was no longer considered a human sample . DENV-1 isolate was passaged three times in C6/36 cells prior to its use in this study and full-length consensus genome sequence is available from GenBank under accession number HG316482 . Virus stock was prepared in C6/36 cells as previously described [60] and a mock-inoculated flask was prepared simultaneously as a negative control . DENV-1 infectious titer was measured in C6/36 cells using a standard focus-forming assay ( FFA ) as previously described [60] . Most experiments were carried out with Aedes aegypti mosquitoes derived from a wild population originally sampled in 2013 in Thep Na Korn , Thailand and took place within 10 generations of laboratory colonization . One experiment was carried out with Ae . aegypti mosquitoes derived from a wild population originally sampled in 2015 in Phnom Penh City , Cambodia and took place 8 generations after laboratory colonization . Experimental infections were carried out as previously described [60] . Briefly , four- to seven-day-old females were offered a washed rabbit erythrocyte suspension mixed 2:1 with pre-diluted DENV-1 KDH0030A viral stock and supplemented with 10 mM ATP ( Sigma ) , to reach an expected titer of 107 FFU/mL . A control blood meal was prepared with the supernatant of mock-inoculated C6/36 cells . Mosquitoes were allowed to blood feed for 30 min through a pig-intestine membrane using an artificial feeder ( Hemotek Ltd , Blackburn , UK ) set at 37°C . Samples of the blood meals were saved and stored at -80°C for further titration . Fully engorged females were incubated at 28°C , 70% relative humidity and under a 12-hour light-dark cycle in 1-pint cardboard cups ( 20–30 females per cup , at least 2 cups/condition ) with permanent access to 10% sucrose . Upon harvest , females were freeze-killed at -80°C and transferred on ice . Midguts were dissected in 1X phosphate-buffered saline ( PBS ) under 10X magnification . Forceps were decontaminated between each individual using Surfa’Safe ( Anios ) to prevent cross contamination . Individual midguts were immediately homogenized for 30 sec at 6 , 000 rpm in tubes ( VWR ) containing ~20 1-mm glass beads ( BioSpec ) in 800 μL of TRIzol ( Life Technologies ) and stored at -80°C . Samples were thawed at room temperature ( 20–25°C ) and 150 μL of chloroform ( Sigma-Aldrich ) were added followed by vortexing for 30 sec . After a 5-min incubation at 4°C , samples were centrifuged at 4°C for 15 min at 14 , 000 rpm . The upper aqueous phase was harvested and transferred to a cold tube containing 400 μL of 2-propanol ( Sigma-Aldrich ) supplemented with 1 μL GlycoBLUE ( Ambion , Life Technologies ) . Samples were incubated at -20°C overnight and centrifuged at 4°C for 15 min at 14 , 000 rpm to pellet RNA . The pellet was washed with 800 μL of 70% ice-cold ethanol ( Sigma-Aldrich ) at 4°C for 10 min at 14 , 000 rpm , and allowed to dry for 10 min at 37°C . Total RNA was resuspended in 6 μL , of which 1 μl was diluted into 9 μl of RNase-free water for DENV quantification by RT-qPCR , while the remaining 5 μl were used for transcriptome sequencing . All the samples were stored at -80°C until use . DENV RNA was quantified using NS5-specific primers and TaqMan probe ( S1 Table ) with SuperScript III Platinum One-Step RT-qPCR kit ( Life Technologies ) and serial dilutions of total DENV RNA of known concentration ( from 109 to 101 DENV RNA copies/μL ) as a standard , as previously detailed [60] . Each RT-qPCR plate included negative controls derived from uninfected samples and a no template control . The RT-qPCR results were validated if the slope of the standard curve was between -3 . 33 and -3 . 65 , corresponding to 90–100% efficiency . Individual midgut libraries were prepared from total RNA extracts from individual midguts after quality control with a Bioanalyzer RNA 6000 kit ( Agilent ) . Purification and fragmentation of mRNA , cDNA synthesis , end-repair , A-tailing , Illumina indexes ligation and PCR amplification were performed using TruSeq RNA Sample Prep v2 ( Illumina ) followed by cDNA quality check by Bioanalyzer DNA 1000 kit ( Agilent ) . Libraries were diluted to 10 pM after Qubit quantification ( ThermoFisher ) , loaded onto a flow cell , clustered with cBOT ( Illumina ) . Single-end reads of 51 nucleotides in length were generated on a HiSeq2000 sequencing platform ( Illumina ) . Sequencing reads with a quality score <30 were trimmed using Cutadapt [61] . Passing-filter reads were mapped to Ae . aegypti transcripts ( AaegL3 . 1 , http://vectorbase . org ) using Bowtie2 [59] with the “sensitive” option . They were processed with the Samtools suite [62] to create of a matrix of raw counts used for gene expression analysis . The RNA-Seq data were deposited to SRA under accession number PRJNA386455 ( https://www . ncbi . nlm . nih . gov/bioproject/386455 ) . All analyses of midgut transcript expression were performed in R ( v . 3 . 2 . 3 , http://www . r-project . org/ ) using the DESeq2 package v . 1 . 8 . 0 [63] . Following normalization of raw read counts by the relative log expression method implemented in DESeq2 [64] , normalized read counts were considered separately according to time post DENV exposure . Two complementary analyses were run for each time point . First , a pairwise comparison was used to identify genes differentially expressed between DENV and control conditions . Differential expression was evaluated using the DESeq2 generalized linear model with its default parameters ( activated outlier detection and independent filtering ) . Statistical significance of differential expression was determined based on a 10% false discovery rate ( FDR ) . Second , a correlation analysis in DESeq2 measured the strength of the linear relationship between log2-transformed normalized read counts and the log10-transformed viral RNA load per midgut in DENV-1 samples only . Statistical significance of the linear relationship was determined based on a 10% FDR threshold . Genes with no detectable or very low expression ( i . e . , median < 50 normalized read counts ) were filtered out after the statistical analysis . DNase-treated RNA purified from a pool of Ae . aegypti midguts was used to produce a PCR template for dsRNA synthesis . Briefly , gene-specific PCR primers for dsRNA preparation were designed ( S1 Table ) using E-RNAi web-service v . 3 . 2 [65] with 21-bp length for siRNA specificity prediction and default parameters otherwise . A 500-bp fragment of the GFP gene was amplified with specific primers ( S1 Table ) and cloned into pCRII TOPO vector ( Life Technologies ) . A T7 promoter was incorporated into the PCR amplicon with tagged primers ( S1 Table ) . PCR was conducted in a 25-μL reaction containing 2 μL of template cDNA , 5 μM of each T7 primer , 1 . 5 mM MgCl2 , 200 μM of dNTP mix and 0 . 5 unit of native Taq polymerase ( ThermoFisher ) as follows: 3 min at 95°C , 40 cycles of 1 min at 94°C , 1 min at 58°C , 1 min at 72°C , and a final step of 10 min at 72°C . Synthesis of dsRNA was performed overnight at 37°C using MEGAscript RNAi kit ( Life Technologies ) with 1 μg of PCR product purified by MinElute Kit ( Qiagen ) . After column purification , 1:10 ( vol/vol ) 3M sodium acetate pH 5 . 5 ( Life Technologies ) and 1:2 . 5 ( vol/vol ) 100% ethanol ( Sigma-Aldrich ) were added , followed by overnight precipitation at -80°C . After centrifugation for 30 min at 14 , 000 rpm , the dsRNA pellet was washed with 800 μL of 100% ethanol , followed by 15 min centrifugation at 14 , 000 rpm . The dsRNA pellet was air-dried , resuspended in RNase-free water , adjusted to a concentration of 7 μg/μL with a Nanodrop spectrophotometer , and stored at -20°C until use . Four- to 7-day-old females were ice-chilled and intrathoracically injected with 2 x 69 nL of a 7 μg/μL dsRNA ( ~1 μg dsRNA ) from the gene of interest using a Nanoject-II device ( Drummond ) . Control mosquitoes were injected with dsGFP . Mosquitoes were allowed to recover from injection for 2 days before being offered an artificial DENV-1 blood meal as described above . Both dsCACTUS and dsAGO2 were used as controls for DENV-1 load modulation in the midgut . Total RNA from individual midguts was reverse transcribed into cDNA in a reaction mixture containing 5 nM random hexamers , 0 . 2 mM of dNTP mix , 10 μL of template and RNase-free water up to 14 . 5 μL . After incubation at 65°C for 10 min , samples were chilled on ice for 5 min . For each reaction , 4 μL of 5X First-Strand buffer , 1 μL of 0 . 1 mM Dithiothreitol , 40 units of RNase-OUT and 100 units of MML-V reverse transcriptase ( Life Technologies ) were added to a final volume of 20 μL . After 10 min at 25°C , cDNA synthesis was conducted at 37°C for 50 min and terminated at 70°C for 15 min . cDNA samples were stored at -20°C until use . Gene expression was assayed by relative quantitative PCR ( qPCR ) using a LightCycler96 machine ( Roche ) . The qPCR mix contained 200 nM of each primer , 10 μL of 2X SYBR-green I Master Mix ( Roche ) and PCR grade water to 18 μL , with 2 μL of cDNA template to a final volume of 20 μL . Settings were an initial denaturation step of 5 min at 95°C , followed by 40 cycles of 10 sec at 95°C , 20 sec at 60°C and 10 sec at 72°C . Melting curve were used to confirm the absence of non-specific PCR amplicons using the following program: 5 sec at 95°C , 60 sec at 65°C and continuous fluorescence acquisition up to 97°C with a ramp rate 0 . 2°C/sec . Relative expression was calculated as 2 - ( Cqgene-Cqrp49 ) , using the Ae . aegypti ribosomal protein-coding gene rp49 ( AAEL003396 ) for normalization . Infection prevalence was analyzed as a binary response variable ( 0 = absence , 1 = presence ) using logistic regression . Continuous response variables were analyzed using analysis of variance ( ANOVA ) . Explanatory variables included time point ( ordinal ) , experimental condition ( nominal ) and experiment ( nominal ) . Viral RNA load was log10-transformed and RNA-Seq normalized read counts were log2-transformed prior to analysis . Midgut gene expression normalized by rp49 ( referred to as expression ) was analyzed without log-transformation . Models including interactions were analyzed with type-III ANOVA , whereas models without interactions were analyzed with type-II ANOVA . Interactions terms were removed from the final model if they were not statistically significant ( P > 0 . 05 ) . When the ANOVA assumption of normal error distribution could not be met , a non-parametric Wilcoxon test was performed for pairwise comparisons . Multiple pairwise comparisons were performed with t-tests followed by Holm correction for multiple testing [66] . A Cox regression model including dsRNA injection and DENV exposure as covariates was used to compare mosquito survival across treatments [67] . This model is appropriate to analyze the effect of several variables on the time it takes for an event to happen . Statistical analyses were computed in the R environment and plotted with the R package ggplot2 ( v . 2 . 2 . 0 ) [68] .
|
Dengue virus ( DENV ) is transmitted among humans by mosquitoes , primarily Aedes aegypti . Despite their potential as targets to interrupt DENV transmission , mosquito genes that modulate infection in Ae . aegypti remain largely unknown . Using a field-derived Ae . aegypti population , we observed substantial variation in DENV load in the mosquito midgut . We hypothesized that this inter-individual variation contained valuable information to identify host factors modulating viral infection . We analyzed single-midgut transcriptomes using an approach that takes advantage of inter-individual variation among infected mosquitoes . We demonstrated the added value of this method by identifying novel host factors during early DENV infection of Ae . aegypti that went undetected by conventional pairwise comparison between DENV-infected and control groups . We confirmed the agonist role of a candidate gene encoding a sterol regulatory element-binding protein , which underlines the importance of lipid metabolism during DENV infection of the mosquito midgut . Our method for transcriptomic analysis can enhance genome-wide screens for host factors by taking advantage of inter-individual variation . It is also applicable to a wide range of phenotypic traits displaying inter-individual variation .
|
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"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
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] |
2017
|
Individual co-variation between viral RNA load and gene expression reveals novel host factors during early dengue virus infection of the Aedes aegypti midgut
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During recent years , comparative genomic analysis has allowed the identification of Mycobacterium leprae-specific genes with potential application for the diagnosis of leprosy . In a previous study , 58 synthetic peptides derived from these sequences were tested for their ability to induce production of IFN-γ in PBMC from endemic controls ( EC ) with unknown exposure to M . leprae , household contacts of leprosy patients and patients , indicating the potential of these synthetic peptides for the diagnosis of sub- or preclinical forms of leprosy . In the present study , the patterns of IFN-γ release of the individuals exposed or non-exposed to M . leprae were compared using an Artificial Neural Network algorithm , and the most promising M . leprae peptides for the identification of exposed people were selected . This subset of M . leprae-specific peptides allowed the differentiation of groups of individuals from sites hyperendemic for leprosy versus those from areas with lower level detection rates . A progressive reduction in the IFN-γ levels in response to the peptides was seen when contacts of multibacillary ( MB ) patients were compared to other less exposed groups , suggesting a down modulation of IFN-γ production with an increase in bacillary load or exposure to M . leprae . The data generated indicate that an IFN-γ assay based on these peptides applied individually or as a pool can be used as a new tool for predicting the magnitude of M . leprae transmission in a given population .
Leprosy is a chronic infectious disease caused by the obligate intracellular pathogen Mycobacterium leprae . Multidrug therapy ( MDT ) , a combination of antibiotics very effective in curing this mycobacterial infection , was introduced by WHO in the early eighties . With the success of MDT , in 1991 the World Health Assembly set a target of eliminating leprosy as a public health problem by the year 2000 . Elimination was defined as reaching prevalence levels of <10 case per 100 , 000 individuals . The elimination program has been successful in delivering MDT worldwide , decreasing globally the number of registered cases . More than 13 million cases were detected and treated with MDT from 1982 to 2002 [1] . However , the disease is still considered a public health problem in several countries ( www . who . int/lep ) . Particularly in Brazil , the new-case detection rate remains high and stable at approximately 40 , 000 new cases annually ( http://portal . saude . gov . br ) indicating that transmission has not been adequately interrupted in Brazil by treating leprosy patients with MDT alone . Therefore new strategies and approaches need to be developed in order to definitively eradicate leprosy as a public health problem . This conclusion is supported by recent mathematical modeling of leprosy indicators suggesting that leprosy is slowly declining but the rate of decline is uncertain , requiring sustained leprosy control efforts [2] . Leprosy manifests itself as a spectrum of clinical forms , but which for treatment purposes has been simply divided into multibacillary ( MB ) and paucibacillary ( PB ) leprosy . In Brazil , the detection rate among children under 15 years of age is stable and considered high ( approximately 8% of the new cases detected yearly ) indicating that despite a high level of MDT coverage by the National Leprosy Control Program ( PNCH ) , active transmission persists ( http://portal . saude . gov . br ) . Leprosy transmission is still poorly understood . The major sources of the bacteria are considered to be the multibacillary patients , carrying a high bacterial load in their skin and being able to shed large numbers of bacteria from their nasal passages; 107 viable M . leprae per day on average [3] . Two major pitfalls have contributed to our poor understanding of leprosy transmission: the long incubation period of the disease estimated to be between 2 and 10 years; and the absence of a test that could specifically measure exposure to M . leprae , since the magnitude of the M . leprae-infected population is much higher than that of individuals with actual leprosy . A serological test based on the detection of antibodies specific for the phenolic glycolipid-I ( PGL-I ) antigen , a unique molecule of the M . leprae cell wall , is positive in most MB patients but not in PB individuals , showing a positive correlation with the bacterial load [4] . New tools that could detect infected/exposed individuals are desperately needed to measure the level and dynamics of leprosy transmission . Moreover , most of the infected individuals will never develop the disease [5] . Thus , a test that could distinguish between exposed/infected individuals and those evolving to active disease , should allow for early diagnosis and subsequent prevention of disabilities as well as stoppage of the transmission chain . Mycobacteria are intracellular pathogens and as such elicit in the host a specific cell-mediated immune response that controls the infection . CD4+ T helper 1 ( Th1 ) lymphocytes play a central role in this response , producing IFN-γ that will activate the microbicidal mechanisms of macrophages leading to the killing of intracellular microorganisms ( for a review see [6] ) . The protective role of IFN-γ has been emphasized in several reports that describe the deleterious effects on mycobacterial infections of mutations/deletions in the IFN-γ gene and its receptor [7] . Thus , assessment of T cell functions provides a good alternative approach for the diagnosis of mycobacterial infections . In most endemic countries for leprosy , such as Brazil , tuberculosis is also endemic with 71 , 641 new cases detected in 2009 ( http://portal . saude . gov . br ) . Moreover , in Brazil , BCG vaccination is prescribed . Thus , the development of an immunologic test that could specifically detect M . leprae-infected individuals has to take these facts into account . In this context , a new scenario was introduced by the genomic era , with the knowledge of whole chromosome sequences of mycobacterial species , particularly M . leprae , M . tuberculosis and M . bovis BCG , providing unique opportunities to identify M . leprae specific antigens . We have used comparative genome analysis to identify M . leprae-specific genes , and tested both recombinant proteins and synthetic peptides derived from a subset of these proteins to test for immunological reactivity [8]–[13] . In a previous study performed with individuals living in Rio de Janeiro , a panel of 58 peptides ( 15 mers and 9 mers ) was tested for induction of IFN-γ responses in PBMCs of leprosy patients , healthy household contacts ( HHC ) of leprosy patients , TB patients , and endemic and non-endemic healthy controls [13] . Encouraging results were generated indicating that synthetic peptides induce specific responses in individuals exposed to M . leprae and could potentially be developed into a rapid test for the detection of M . leprae infection . In the present study , the 17 peptides with the best performance were selected and evaluated in individuals with different histories of exposure to M . leprae living in another endemic region of Brazil and in areas that are non-endemic for leprosy . The data generated indicate that an IFN-γ assay based on these peptides applied individually or as a pool can be used as a tool for predicting the magnitude of M . leprae transmission level in a given population .
The tests and procedures described in this work were approved by the Oswaldo Cruz Foundation and D . Libania Ethics Committees . All subjects provided informed written consent . For the analysis of IFN-γ levels induced by M . leprae-derived peptides , a total of 127 volunteer subjects living in the city of Fortaleza , Ceará State , Brazil were enrolled . Untreated paucibacillary ( PB ) ( three tuberculoid ( TT ) and 18 borderline tuberculoid patients [BT] ) , and multibacillary ( MB ) ( eight lepromatous [LL] and thirteen borderline lepromatous patients [BL] ) leprosy patients , household contacts of multibacillary patients ( HCMB , n = 37 ) , and household contacts of paucibacillary patients ( HCPB , n = 27 ) were recruited from the Dona Libânia Reference Center , Fortaleza , Ceará , Brazil . Healthy individuals with no history of exposure to leprosy and/or tuberculosis were recruited from Bom Jardim ( endemic controls high burden , EChigh , n = 20 ) and Meireles ( endemic controls medium burden , EClow , n = 18 ) , Fortaleza districts with , respectively , hyperendemic ( 162 cases per 100 000 inhabitants ) and medium ( 9 cases per 100 000 inhabitants ) annual new case detection rates for the disease . Twenty one healthy blood donors recruited from the Blood Bank of the Fundação Estadual de Pesquisa e Produção em Saúde , Porto Alegre , Rio Grande do Sul State , Brazil ( non-endemic controls , Brazil; NECBrazil ) , and with no history of exposure to leprosy or tuberculosis were also included . Rio Grande do Sul was the first Brazilian State to achieve the WHO leprosy elimination goal in 2001 ( a prevalence rate lower than 10 cases per 100 , 000 inhabitants ) . The 2009 new case detection rate in this State was 1 . 44/100 , 000 . This State is , however , endemic for tuberculosis; with a detection rate of 46 . 14/100 , 000 in 2009 ( http://portal . saude . gov . br ) . The baseline characteristics of each group of individuals included in the study are shown in Table 1 . Two additional control groups , pulmonary tuberculosis patients who had received more than three months of treatment ( tuberculosis , Netherlands; TB; n = 8 ) and healthy donors recruited at the Blood Bank Sanquin , Leiden , The Netherlands ( non-endemic controls , Netherlands; NECNetherlands; n = 8 ) , all residents of the Netherlands , a non-endemic country for leprosy , were also included in the study . Irradiated armadillo-derived M . leprae whole cells were probe sonicated with a Sanyo sonicator to >95% breakage . This material was provided through the NIH/NIAID “Leprosy Research Support” Contract N01 AI-25469 from Colorado State University ( these reagents are now available through the Biodefense and Emerging Infections Research Resources Repository listed at http://www . beiresources . org/TBVTRMResearch Materials/tabid/1431/Default . aspx ) . Blood was drawn by venipuncture , heparinized , and PBMC were isolated using Lymphoprep ( Pharmacia Biotech , Uppsala , Sweden ) by density gradient centrifugation , washed in PBS and resuspended in AIMV medium ( Invitrogen , Grand Island , NY , USA ) supplemented with 100 U/ml penicillin , 100 µg/ml streptomycin and 2 mM L-glutamine ( Sigma Chemical , St . Louis , MO ) . PBMC from each individual were seeded at 2×105 cells per well in 96-well round-bottomed plates in duplicate ( BD Biosciences , San Jose , CA ) and stimulated in vitro with armadillo-derived M . leprae whole cells ( 20 µg/ml ) , PPD ( 10 µg/ml ) individual peptides ( 10 µg/ml ) , Pool 1[p52 , p61 , p68 , p69] ( 0 , 1; 1 , 0 and 10 µg/ml ) , Pool 2 [p38 , p51 , p56 , p59 , p65 , p67 , p70 , p71 , p88 , p91 , p92] ( 0 , 1; 1 , 0 and 10 µg/ml ) or staphylococcal enterotoxinB ( SEB , 1 µg/ml ) ( Sigma ) . Cultures were incubated at 37°C in humidified 5% CO2 atmosphere . Supernatants were harvested at day-five of incubation and stored immediately at −70°C . IFN-γ levels were determined in duplicate by ELISA ( U-CyTech , Utrecht , The Netherlands ) . The cut-off value to define positive responses was set beforehand at 100 pg/ml . The assay sensitivity level was 40 pg/ml . Values for unstimulated cell cultures were typically <20 pg/ml [10] . ELISA for detection of anti-PGL-I IgM was done as previously described [15] . The antigen used in ELISA was NT-P-BSA ( synthetic native trisaccharide of PGL-I coupled to BSA through a 3-phenylpropanoyl ) [14] , and a cutoff value of 0 . 25 , at an optical density at 450 nm ( OD450 ) was set for positive responses [15] . Artificial Neural Networks ( ANN ) modeling ( Statistica Neural Networks 7 , Statsoft , Tulsa , OK , USA ) was used for the selection of peptides with the best performance in discriminating individuals with M leprae infection/disease based on its capacity to induce IFN-γ production in PBMC . The ANN model used for evaluating the peptides had 3 layers of neurons ( Feedforward neural network ) . In the first or input layer , each node receives the IFN-γ level values in response to a given peptide . Each neuron of the first layer is connected to all the neurons of the second or hidden layer . The IFN-γ levels are multiplied by the weights or synaptic strengths before entering the neurons of the second layer . The second layer neurons integrate these processed values and if the resulting number is above an established threshold , this activates the delivery of a value to a synapse connecting the second layer neuron to the single neuron in the output layer . If the sum of the weighted numbers coming from the hidden layer is below the threshold of the output neuron , a “0” output is obtained , or if the value is above the threshold a “1” output is the result . The “0” was associated to one group ( Ex . Non-exposed individuals ) and the “1” to a second and expectedly different group ( Ex . Individuals exposed/infected with M . leprae ) . The software trains the ANN by adjusting the synaptic values using the IFN-γ levels of individuals with known exposure/infection status . The ANN training is validated by analyzing a second group with no information made available to the ANN regarding infection status , and finally the ANN is used for testing with the complete groups to be differentiated . The performance of each peptide in discriminating different groups is evaluated by using the performance ratio ( PR ) of that peptide , a ratio between the mean square error ( MSE ) of the ANN with exclusion of the responses to the peptide ( MSEex ) and the MSE of the ANN including the peptide ( MSEcomp; PR = MSEex/MSEcomp ) . Peptides with the PR values of less than “1” in a given ANN configuration were preferentially removed , and the performances of the ANN with and without those peptides compared in order to reach the best set of peptides for the discrimination of individuals exposed/infected with M . leprae , or with active disease . Levels of IFN-γ responses to M . leprae peptides were compared among groups by Kruskal-Wallys test . Multiple tests were used to compute post-hoc comparisons for all the pairs of groups . A p value of 5% or less was considered significant . The analyses were performed with the STATISTICA software ( Statsoft ) . Box plot graphs were done using the SPSS software ( SPSS Inc , Clicago , IL , USA ) .
In order to identify people infected with M . leprae using an interferon-γ release assay , M . leprae-specific epitopes were required for ex vivo stimulation of the memory T cells of the individuals infected with this bacillus . The set of peptides had to be promiscuous , ideally binding to all the HLAs expressed in the population to be evaluated , to make sure that absence of IFN-γ detection would happen only in non-exposed people . The in silico analysis of genomes allowed the selection of M . leprae-specific genes and derived proteins . Previously we applied algorithms for identifying HLA-binding regions to these specific protein sequences . The chosen regions or epitopes were selected for binding to class I ( 9 mers ) and class II ( 15 mers ) HLA molecules [13] . Seventeen peptides were selected for this study from the original panel of 58 M . leprae-specific peptides . These peptides were previously tested for induction of IFN-γ release by PBMC from leprosy patients and contacts , endemic and non-endemic controls [13] . The IFN-γ levels induced by the peptides in non-exposed ( EClow ) and exposed individuals ( HCMB ) were used for selecting the best set of peptides allowing discrimination of the M . leprae-exposed from the non-exposed group , by applying an ANN algorithm ( Figure 1 ) . When the peptides with PRs below 0 . 96 were removed , a final step of selection by ANN ranked the 12 best peptides in terms of potential for discriminating M leprae infection/disease ( Table 2 ) . The final 12 peptides made the right choice in 96% of the tested individuals in defining the individual status regarding infection with M . leprae ( Figure 1; Table S1 ) . Five additional peptides from the original panel of 58 [13] but with PRs below 0 . 96 ( Table 2 ) were included in the subsequent analysis . The study population consisted of individuals living in the city of Fortaleza , Ceará State , located in the Northeast region of Brazil . Fortaleza is a city with 2 . 5 million inhabitants ( Brazilian Institute of Geography and Statistics , 2009 ) , and divided administratively in 114 districts . Besides the leprosy patients and their household contacts recruited from the Dona Libânia Reference Center , two groups of healthy individuals with no history of previous contact with leprosy were enrolled in the study . These individuals had residential addresses in Meireles or Bom Jardim , two districts of Fortaleza with , respectively , medium ( 9 cases per 100 , 000 inhabitants ) and hyperendemic leprosy new case detection rates ( 160 cases per 100 , 000 inhabitants ) . PBMC from leprosy patient groups ( PB and MB ) , leprosy household contacts of PB ( HCPB ) and MB ( HCMB ) patients , healthy endemic controls from Meireles ( EClow ) and from Bom Jardim ( EChigh ) , healthy controls from Porto Alegre ( NECBrazil ) , Dutch tuberculosis patients ( TB ) and Dutch healthy , non-endemic controls ( NECNetherlands ) were stimulated with peptides and control antigens , and IFN-γ was measured in culture supernatants on day 5 of incubation . The IFN-γ levels in the PBMC cultures of the different groups stimulated with the seventeen individual peptides are shown in the Figures 2 , 3 , 4 . IFN-γ responses were below or , in a few cases , just above the detection limit , in all unstimulated cultures ( medium alone ) for all groups . All individuals responded well when their cells were cultured in the presence of the superantigen SEB ( data not shown ) . Figure 2 A–E shows the responses of PBMC from groups of healthy individuals living in areas with different and increasing new case detection rates for leprosy ( from zero to 162/100 , 000 ) . Most of the Dutch individuals ( TB and NECNetherlands groups ) were responsive to PPD , but IFN-γ was below or , in a few cases , just above the detection limit in response to all M . leprae peptides , indicating absence of cross reactivity of the M . leprae-specific peptides in patients infected with M . tuberculosis or in BCG-vaccinated individuals ( Figure 2A , 2E ) . The other control group enrolled in the study consisted of people living in Rio Grande do Sul , the first Brazilian State to achieve the WHO leprosy elimination goal ( defined as a prevalence rate of lower than 10 cases per 100 , 000 inhabitants ) in 2001 . As shown in Figure 2B , most of the members of this group ( NECBrazil ) produced undetectable levels of IFN-γ for all the peptides . A few outliers responded to the peptides , but the pattern of the group was clearly different from the observed in groups from endemic areas . However , evaluation of the IFN-γ responses of individuals living in Meireles ( EClow ) and Bom Jardim ( EChigh ) , districts of Fortaleza with medium and hyperendemic leprosy new case detection rates , 9 and 162 per 100 , 000 inhabitants , respectively , showed a marked contrast . Most members of the EClow group displayed a reduced frequency of positive responses to the peptides . In contrast , members of the EChigh group showed good responses to all the peptides; the detection rate for leprosy is 18 times higher in the Bom Jardim district than in the Meireles district of Fortaleza . The groups of volunteers from these two sites had no history of known contact with leprosy patients; so , the levels of IFN-γ observed in the Bom Jardim individuals are consistent with the hypothesis that above a certain frequency of cases in the population , exposure to infection reaches the whole population , and history of contact with a leprosy patient is less relevant as an indicator of exposure to infection with M . leprae . Figure 3 A–D shows the IFN-γ levels observed in response to the peptides in groups of household contacts of leprosy patients ( HCPB and HCMB ) . In general , lower levels of IFN-γ were observed in the HCMB group when compared to the HCPB . As expected , most of the PB patients responded to all the peptides ( Figure 4 A ) . The same set of peptides , except for p85 , also elicited IFN-γ production in MB leprosy patients although at a lower level ( Figure 4 B ) . The serum levels of anti-PGL-I IgM were measured in all of the Brazilian individuals enrolled in the study ( Figure 5E ) . Assuming a cut off of 0 . 25 , positivity to anti-PGL-I IgM was observed in 80% MB , 60% PB , 40% HCMB , 25% HCPB , 30% EChigh , 10% EClow and 10% NECBrazil . An analysis of IFN-γ responses in positive vs . negative individuals showed significant differences in the HCPB group , with higher levels of IFN-γ produced by individuals who were anti-PGL-I negative ( Figure 3C , 3D; differences were significant at a p<0 . 05 except for p59 and p85 . Kruskal-Wallys test ) . No differences of the same kind were observed when PGL-I-positive and –negative HCMB were compared ( Figure S2 ) . In order to link responses of the Brazilian groups of individuals with increasing exposure to M . leprae and increasing bacillary loads among the patients , the medians for the IFN-γ levels in response to the M . leprae-specific peptides were plotted simultaneously , and the resulting graphic shows an initial increase in the IFN-γ levels to all the peptides starting at baseline with the Brazilian non-endemic group ( NECBrazil ) and the endemic controls in area of medium leprosy detection rate ( EClow ) . IFN-γ levels peaked in the controls for hyperendemic areas ( EChigh ) and contacts of paucibacillary leprosy patients ( HCPB ) . The remaining groups show a progressive decline in IFN-γ levels that can be associated with continuous exposure to live M . leprae ( HCMB ) or increasing bacillary load for the two groups of patients ( PB , MB ) ( Figure 5A ) . This observation was replicated when ex vivo levels of IFN-γ of the same groups to unfractionated M . leprae were evaluated ( Figure 5B ) . This initial elevation and subsequent decline of IFN-γ levels in response to M . leprae was also observed when responses to only HLA class I- and HLA class II-restricted peptides were plotted ( Figure 5C , 5D ) . This reduction in IFN-γ levels for M . leprae and M . leprae-derived peptides was not seen in the responses of the same groups to PPD and SEB ( Figure S1; Table S2 ) . The down modulation of M . leprae-specific IFN-γ in the groups followed an inverse path when compared to the levels of PGL-I-specific IgM in the same groups ( Figure 5E ) . The evaluation of statistically significant differences between the groups can be summarized as follows: No difference was found when responses to the peptides of the NECBrazil and EClow were compared . Nine to 16 peptides out of 17 induced markedly higher levels of response in exposed asymptomatic individuals ( EChigh , HCPB , HCMB ) in comparison to the low-exposure or non-exposed individuals ( NECBrazil , EClow ) . In comparison to the exposed asymptomatic groups , the patients were responsive to a reduced number of peptides , but even the MB patients had responses that could be differentiated from the NECBrazil and/or EC low to 4 peptides ( p56 , p69 , p71 , p91 ) . Another aspect that called the attention was the large number of peptides with reduced response in the MB patients in comparison to the exposed asymptomatic individuals ( Kruskal-Wallys test , Table S2 ) . The use of pools of class I and class II-restricted M . leprae-specific peptides is a necessary step towards a more simplified test . For evaluating the responses to the pools , groups expected to display different levels of response to M . leprae were tested: healthy controls from the hyperendemic area ( Bom Jardim; EChigh ) , the medium leprosy detection rate area ( Meireles; EClow ) , household contacts of MB patients ( HCMB ) , and PB patients ( Figure 6 ) . A second aspect evaluated with the use of peptide pools was the use of 3 peptide concentrations , in a 0 . 1 to 10 µg/mL range . The responses to the class I-restricted peptides ( 9 mers ) were markedly higher and applied to more individuals when the EClow were compared to the EChigh . The highest level of stimulation was required for inducing IFN-γ responses in some HCMB and PB patients . The class II-restricted stimulation induced responsiveness and peak levels of IFN-γ in all the evaluated groups at lower concentrations than the class I-restricted stimulus . The two pools of peptides induced responsiveness in more individuals and at lower doses in the EClow and EChigh than in the HCMB and PB groups . Taken together the IFN-γ responses induced by peptide pools suggest that the threshold for M . leprae-specific production of IFN-γ increases with increased exposure to M . leprae , providing a potential explanation for the decline in M . leprae-specific IFN production observed with increased exposure to M . leprae ( HCMB ) or active disease ( PB ) .
Humans constitute the only known reservoir of M . leprae , except in those select areas with zoonotic leprosy in armadillo populations [16] . It is generally assumed that all diseased individuals must have contracted leprosy directly or indirectly from another infected person . However , the inability to recognize subclinical or latent infections in association with the long incubation time have hampered our knowledge about the mode and source of M . leprae transmission and the risk factors associated with disease manifestation among infected individuals . In the previous [13] and present study , we showed that a set of M . leprae MHC class I and class II-restricted peptides can specifically identify individuals exposed to M . leprae infection and with active disease . The set of M . leprae-specific peptides clearly differentiated individuals from an endemic area ( Fortaleza ) from those living in a non-endemic site for leprosy in Brazil , but with endemic tuberculosis ( Porto Alegre ) . Our previous [13] and present studies were conducted in distinct endemic sites of Brazil ( Rio de Janeiro and Fortaleza ) , suggesting that despite differences in genetic background , a very similar combination of peptides could efficiently discriminate between exposed and unexposed individuals in other endemic countries . We propose as a major application for this test its use as an epidemiological tool by National Leprosy Control Programs , to define the magnitude of the infected population and consequently of transmission in an endemic area for leprosy . Currently a calibration curve of leprosy new case detection rate versus IFN-γ levels is under construction by evaluating sites with increasing annual leprosy new case detection rates . In addition these peptides are also being analyzed in other leprosy endemic areas in Ethiopia and Asia in order to estimate their use on a worldwide basis . As a positive response to PGL-I , a specific marker of M . leprae is an indicator of bacillary load , the combination of these two observations pointed to a role for M . leprae or M . leprae components in negatively modulating IFN-γ production in infected individuals , and perhaps contributing to the evolution from infection to active disease in M . leprae-exposed individuals . These observations were combined to elaborate a model relating IFN-γ production with the initially asymptomatic M . leprae infection , and as the infection progresses to disease , a down regulation of M . leprae-specific IFN-γ production ( Figure 7 ) . The relative IFN-γ levels of the different groups were derived from the median values shown in Figure 5A . This observation suggested a new role for the continuous exposure to live M . leprae seen in contacts of multibacillary leprosy patients , not only allowing M . leprae infection of the HCMB , but also negatively modulating the immune response to this bacillus , available from an exogenous source in the HCMB , or an endogenous source for the PB and MB patients . The distribution of groups in Figure 7 also raised the possibility that if we want to evaluate immune response in the asymptomatic phase of M . leprae infection , patients are not the best option for positive responses . Of note , a similar graph was generated based on the production of IFN-γ in response to the whole bacteria ( Figure 4B; except for groups living in sites with low/medium prevalence rates in which a higher background is seen with whole bacteria probably due to cross reactivity ) , indicating that the immune response to the peptides follows a similar trend as to the whole bacterium . The proposed model associated the NECBrazil and EClow groups as the individuals with no or reduced exposure to M . leprae infection . A second group can include healthy controls from high endemicity areas ( EChigh ) and contacts of PB patients ( HCPB ) . The HCMB group already had intermediate values for IFN-γ , and the patients were at the lower end among the groups of infected individuals . So we tested by ANN the possibility of discriminating infected individuals from patients . The group combining EChigh and HCBP was evaluated against MB and PB patients and the decline in IFN-γ levels allowed the correct discrimination of patients in 84 . 21% of the cases . A very interesting observation among the groups of non-contact healthy individuals was the correlation between the levels of IFN-γ produced by each group and the degree of exposure to M . leprae . While the IFN-γ levels were ( almost ) absent in individuals living in areas with low/medium prevalence rates ( NECBrazil and EClow groups ) , in residents of high-prevalence neighborhoods of Fortaleza ( EChigh group ) , levels were comparable to those seen in household contacts of leprosy patients . These data indicate that in areas with high prevalence rates , the exposure to M . leprae is independent of a previous history of contact with leprosy patients . These results are in agreement with previous studies indicating widespread M . leprae nasal carriage as determined by PCR among the general population in an area in which leprosy is endemic [17] . Moreover , they support the view that prolonged intimate contact with a leprosy patient is not required for transmission as has been shown in studies on medical personnel [5] , and may explain why a good proportion of incident cases arise among individuals with no previous history of contact with leprosy [18] , [19] . Our data also support the general view that M . leprae is highly infectious but poorly pathogenic and that most individuals exposed to M . leprae present a subclinical infection and develop a protective immune response against this bacillus . Although close contact is not critical for infection , it seems to play a key role in leprosy manifestation . The critical role of IFN-γ in controlling M . leprae infection was first described by Nogueira et al . [20] who demonstrated that lepromatous leprosy and borderline lepromatous patients , in deep contrast to tuberculoid patients , failed to release this cytokine in response to specific antigen . In our study , as shown in Figure 5 and 6 , the peak of IFN-γ median production was observed in household contacts of paucibacillary patients ( HCPB ) . Starting from this group , the IFN-γ levels in response to M . leprae or M . leprae-specific peptides is progressively reduced when groups of increasing levels of exposure to M . leprae are compared ( HCMB ) , and are further diminished in leprosy patients . The relatively lower response of contacts of multibacillary patients in comparison to contacts of paucibacillary patients suggests that the evolution of latent infection to active disease is associated with progressive reduction in pathogen-specific IFN-γ production , perhaps in parallel with increase in bacillary load . This down modulation of effector response to M . leprae ( Ex . IFN-γ levels ) in consequence of long-term and constant stimulation of the immune system by the exogenous bacillus released by the index case is a possible explanation for the well-known increased risk of household contacts of multibacillary leprosy patients to develop leprosy [18] , [21] . Indeed , the observation that “super exposure” to M . leprae can lead to a decrease in host resistance was first described in 1973 [5] . In this study , the authors used a lymphocyte transformation test to show that contacts of lepromatous patients with active disease displayed lower in vitro responses to M . leprae when compared with contacts of lepromatous patients treated for more than six months . Interestingly , HCPB with positive serology to PGL-I produced significantly lower levels of IFN-γ in response to M . leprae-specific peptides when compared to PGL-I negative individuals . No similar influence of levels of anti-PGL-I antibody was observed among HCMB , may be because in this case the IFN-γ levels were already down modulated due to the high bacterial exposure . The level of anti-PGL-1 antibody has been considered as a reliable marker of bacterial load in leprosy patients; anti-PGL-1 levels are associated with the disease spectrum and decline upon treatment ( for a review see Oskam et al . [4] , 2003 ) . Moreover , a higher risk of developing leprosy has been found among household contacts seropositive to anti-PGL1 [22] . Thus , PGL-I serology in association with IFN-γ levels in response to the peptides may constitute a robust test for detecting infected individuals with higher bacterial loads and more risk of developing leprosy . The combination of tests for PGL-I specific antibodies and IFN-γ in response to M . leprae-specific peptides may require a follow-up study for evaluating patterns of response associated with evolution to active disease or protection . This is currently under investigation at various endemic sites ( Geluk et al . , for IDEAL consortium ) . The studies on the immune response and models of leprosy pathogenesis have been concentrated in active cases that constitute less than 1% of the infected population . Some observations point to the inhibition of dendritic cell maturation and the low frequency of DC s in the lepromatous leprosy lesions as examples of the negative modulation of M . leprae-specific immune response in leprosy [23] . But , as seen in our observations in contacts of MB patients and endemic controls of hyperendemic areas , prior to active disease , PBMC from M . leprae-exposed individuals respond to M . leprae-specific stimuli with high IFN-γ levels . So , at least initially , priming to M . leprae and differentiation of a Th1 T cell response takes place . But , failure of DCs in inducing priming and Th1 differentiation of M . leprae can be a possible mechanism for lower levels of response in HCMB and patients , especially if components of M . leprae such as PGL-I are the culprits [24] . In the course of the chronic stimulation of Th1 and other T cell subsets seen in human and murine diseases such as visceral leishmaniasis , there is induction of IL-10 production by the IFN-γ producing T cell and subsequent down regulation of Th1 differentiation [25] , [26] . This is a mechanism that could be relevant for the modulation of response in M . leprae latent infection , with potential relevance for the development of a prognostic test and/or vaccines for leprosy .
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Despite the efforts to treat registered leprosy patients , the number of new cases reported globally remains stable and high ( about 200 , 000/year ) . As the treatment of multibacillary leprosy patients , the major recognized source for new infections , did not allow the expected reduction in new leprosy cases , additional sources must be considered . Following exposure to M . leprae infection , the evolution to active disease is estimated to take from 2 to 10 years , and it is conceivable that some of these asymptomatic individuals could be a yet unrecognized source of infection . Previously , the use of computational tools allowed us to select M . leprae-specific genes or gene regions , and derive M . leprae-specific synthetic peptides from the M . leprae genome . Ex vivo stimulation of the blood leukocytes with a subset of these peptides induced IFN-γ production that allowed the differentiation of individuals exposed to M . leprae from unexposed ones . Individuals with no known history of exposure to M . leprae , but living in an area with high frequency of leprosy cases had high-level positive responses to the peptides . This last observation raised the possibility of using this test as a tool for evaluating the level of transmission of M . leprae infection in areas of interest .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"immunology",
"biology",
"microbiology"
] |
2012
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Pathogen-Specific Epitopes as Epidemiological Tools for Defining the Magnitude of Mycobacterium leprae Transmission in Areas Endemic for Leprosy
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An important NK-cell inhibition with reduced TNF-α , IFN-γ and TLR2 expression had previously been identified in patients with diffuse cutaneous leishmaniasis ( DCL ) infected with Leishmania mexicana . In an attempt to pinpoint alterations in the signaling pathways responsible for the NK-cell dysfunction in patients with DCL , this study aimed at identifying differences in the NK-cell response towards Leishmania mexicana lipophosphoglycan ( LPG ) between patients with localized and diffuse cutaneous leishmaniasis through gene expression profiling . Our results indicate that important genes involved in the innate immune response to Leishmania are down-regulated in NK cells from DCL patients , particularly TLR and JAK/STAT signaling pathways . This down-regulation showed to be independent of LPG stimulation . The study sheds new light for understanding the mechanisms that undermine the correct effector functions of NK cells in patients with diffuse cutaneous leishmaniasis contributing to a better understanding of the pathobiology of leishmaniasis .
Leishmania mexicana can cause two forms of clinical diseases: a benign localized cutaneous leishmaniasis ( LCL ) characterized by ulcers at sites of parasite inoculation , and the highly destructive and invasive form , diffuse cutaneous leishmaniasis ( DCL ) characterized by intensely parasitized macrophages within nodules that spread uncontrolledly throughout the skin . This aggressive form also invades the oropharyngeal and nasal mucosae of patients in an advanced stage of the disease . Although the cause of disease progression in DCL patients remains unknown , early immune events during disease development may establish conditions that determine the outcome of the infection . A cell type capable of initial immunomodulation is the NK cell since it is an early producer of IFN-γ and TNF-α , two cytokines needed to potentiate the leishmanicidal activities of phagocytic cells . It is also known that NK cells are among the first cells to produce the protective cytokines that enable macrophages to cope with the intracellular pathogen . Previous work in our lab showed that NK cells are activated by Leishmania lipophosphoglycan ( LPG ) through TLR2 receptors inducing IFN-γ and TNF-α production [1] . Another approach considered by our group was to analyze whether the cause of disease progression in DCL patients was related to an altered NK-cell response . On activation through TLRs , NK cells initiate a signaling cascade that includes adaptor proteins such as MyD88 or TRIF . These in turn produce the recruitment and association of IRAK-1/IRAK4/TRAF-6 complex , leading to nuclear translocation of transcription factors such as IRF-3 and NF-κB as well as the production of inflammatory cytokines ( IL-6 , TNF-α , IL-1 and IFNs ) [2 , 3] . NK cells can also be activated by cytokines such as IL-2 , IFN-α/β , IL-12 , IL-18 , IL-4 , TNF-α and IL-1β , alone or in a synergistic combination by binding to different receptors and activating signaling pathways such as JAK/STAT in the case of IFN-γ [4 , 5] . Results from our study show that DCL patients not only suffered from reduced numbers of NK cells in blood and tissue lesions , but also , that their functional capacity was markedly diminished showing a reduced production of IFN-γ and TNF-α when stimulated with Leishmania LPG [6] . These data strongly indicated that NK cells play a role in disease resolution of LCL patients . It became important then , to comparatively analyze genes related to the innate immune response of NK cells upon stimulation with Leishmania LPG in both , LCL and DCL patients . The aim of this study was to compare , at a molecular level , the response of NK cells from patients with LCL and DCL upon stimulation with Leishmania mexicana LPG and , to analyze whether those differences could explain the cause of disease susceptibility and/or severity in DCL patients . It was found that important genes related to immune protection against leishmaniasis , particularly those involved in the TLR and JAK/STAT signaling pathways , were down-regulated in NK cells from DCL patients . We propose that this down-regulation is possibly implicated in the susceptibility of DCL patients to Leishmania mexicana infections .
This study was conducted according to the principles expressed in the Declaration of Helsinki . The study was approved by the Institutional Ethics Committee of the Medical Faculty of the National Autonomous University of Mexico ( FMED/CI/RGG/013/01/2008 ) . Guidelines established by the Mexican Health Authorities were strictly followed . All patients and healthy controls signed a written informed consent for the collection of samples and subsequent analysis . All patients were clinically diagnosed as either LCL or DCL . This was later corroborated with laboratory tests including Giemsa-stained smears and/or immunohistochemistry of tissue lesions tested for Leishmania mexicana . Montenegro skin hypersensitivity tests were made at the sanitary jurisdiction office of the Cunduacan Municipality in Tabasco State , located in Southeastern Mexico , before patients began their treatment . The diagnosis was confirmed by sandwich ELISA test using total Leishmania mexicana antigen . All patients were from “La Chontalpa” , a region in the state of Tabasco in Mexico , which is endemic for leishmaniasis . Control samples for microarrays were obtained from donors with no history of the disease and who tested negative in the ELISA test for Leishmania . An ancestry analysis was included that used an additionally group of controls , these were individuals of the same geographic region that had either tested positive or negative in the ELISA test for Leishmania , but showed no evidence of disease . All blood samples of LCL patients were taken before they began their first treatment with Glucantime ( 20 mg/kg/day ) . DCL patients had taken their last treatment at least 3 months prior to the date that blood samples were taken for this study . Genomic DNA was isolated from PBMC . Cells were suspended in 1 mL TRIZOL ( Invitrogen Carlsbad , CA , USA ) , mixed and incubated for 5 min at room temperature ( RT ) , after which 200 μL cold chloroform ( Sigma ) were added . The solution was mixed and centrifuged for 15 min at 4°C and 19 , 357 x g . The aqueous phase was eliminated , and the interphase and the organic phase were washed with 0 . 1 M sodium citrate/10% ethanol solution for 30 min under continuous mixing . The solution was centrifuged at 2 , 151 x g for 5 min at 4°C , the supernatant was discarded and the pellet was washed twice with sodium citrate , as described . One mL ethanol 75% ( Sigma ) was added , the solution was mixed during 10 s and centrifuged at 2 , 151 x g for 5 min at 4°C . The pellet was dried at RT , suspended in RNase free water and incubated for 15 min at 60°C . The DNA concentration was assessed using ND-1000 Spectrophotometer ( NanoDrop Technologies , Wilmington , DE , USA ) . DNA integrity was analyzed on 1% agarose gel . All patients were identified as Mexican-mestizo through a Principal Component Analysis ( S1 Fig ) using autosomal genome-wide data ( 299 , 411 SNPs ) , genotyped with Affymetrix Genome-Wide Human SNP Array 6 . 0 and analyzed with EIGENSTRAT Software [7 , 8] . Three principal ancestral references were used , two from the HapMap International project [9] European ( 56 samples ) and African ( 53 samples ) , and Native Mexican ( 71 samples ) from the Mexican Genome Diversity Project ( MGDP ) [10 , 11] . The MGDP includes 21 Zapotecas from Oaxaca , 27 Mayas from Campeche and 23 Tepehuanes from Durango . The ancestry individual proportions were estimated with ADMIXTURE , V1 . 23 [12] . Promastigotes of Leishmania mexicana were grown in RPMI-1640 medium ( Life Technologies Laboratories , Gaithersburg , MA , USA ) supplemented with 5% heat-inactivated FBS ( Fetal Bovine Serum ) at 28°C . For LPG extraction , promastigotes were harvested from stationary-phase cultures . Parasites were sub-cultured every 4–5 days and grown to a density of 1x106/mL , centrifuged at 350 x g for 10 min , washed three times with cold PBS , and counted after immobilization with 0 . 1% glutaraldehyde . LPG was extracted from 1010 promastigotes , as described by McConville et al . [13] , with some modifications . Briefly , the supernatant was removed and the pellet was extracted with chloroform/methanol/water ( 1:2:0 . 5 , v/v ) for 2 h at RT . The insoluble material was used for LPG extraction with 9% 1-butanol in water ( 2 x 500 μL ) and the pooled supernatants were vacuum dried . LPG was purified from this fraction by octylsepharose chromatography in HPLC , using a 1-propanol gradient ( 5−60% ) in 0 . 1 M ammonium acetate . To optimize LPG purity , two octylsepharose columns were used instead of one . The preparations tested negative for endotoxin using the Limulus sp . amebocyte lysate assay ( E- Toxate Kit; Sigma , St . Louis , MO , USA ) . Polymyxin B ( 5 μg/mL ) was also used to confirm the absence of contaminating LPS . A sample was analyzed for protein contaminants by SDS-PAGE with silver staining . The preparation was devoid of protein contaminants . Quantification of LPG was made by the Anthrone method [14] . Peripheral blood samples of all patients and healthy volunteers was taken and kept at 4°C during 18 h before purification . Human NK cells were purified using Ficoll-Hypaque ( Sigma ) density gradient centrifugation at 300 x g for 20 min at 20°C . Cells were suspended in pyrogen-free and sterile RPMI-1640 medium ( Life Technologies ) , supplemented with 10% heat-inactivated fetal bovine serum ( FBS ) , 2 mM L-glutamine , 10 mM HEPES buffer , 100 μg/mL penicillin , 160 μg/mL gentamicin and 17 mM NaHCO3 . PBMC were adhered for 18 h and non-adherent cells were removed , washed in PBS and thereafter purified with an NK-cell isolation Kit II , followed by magnetic sorting with MACS Microbeads ( NK cell isolation kit by immunomagnetic cell sorting , Miltenyi Biotec; Bergisch Gladbach , Germany ) . NK cells were washed and plated in 24-well culture-plates for 18 h before assays . The purity of the enriched NK cells was assessed by flow cytometry using anti-CD56-PE and anti-CD3-FITC ( Coulter Immunotech ) antibodies , achieving 97% purity . NK cells were defined as CD3- CD56+ . NK cells were stimulated during 6 h with Leishmania mexicana LPG ( 20 μg/mL ) at 37°C and 5% CO2 . ( The stimulation time of 6 h was based on data reviewed in the literature [15–18] ) . Stimulated and non-stimulated NK cells were washed twice with PBS and centrifuged at 453 x g for 10 min at 4°C . Approximately 1x106 stimulated and non-stimulated NK cells were suspended in 0 . 5 mL TRIZOL Reagent ( Invitrogen Carlsbad , CA , USA ) , mixed and incubated for 5 min at RT , after which 100 μL cold chloroform were added ( Sigma ) . This solution was mixed and centrifuged at 19 , 357 x g for 15 min at 4°C . The aqueous phase was recovered and 250 μL of cold isopropanol were added ( Sigma ) . The resulting solution was mixed for 15 s and incubated overnight at -20°C . Thereafter , the solution was centrifuged at 19 , 357 x g for 10 min at 4°C . The supernatant was discarded and 500 μL ethanol 75% ( Sigma ) were added , the solution was mixed during 10 s and centrifuged at 19 , 357 x g for 10 min at 4°C . The pellet was washed with 500 μL cold absolute ethanol and centrifuged at 19 , 357 x g for 10 min at 4°C . The ethanol was discarded , the excess was air-dried at RT and the pellet was suspended in RNase free water . The RNA concentration was assessed using ND-1000 Spectrophotometer ( NanoDrop Technologies , Wilmington , DE , USA ) . The quality of each RNA sample was validated on an Agilent BioAnalyzer 2100 ( Agilent , Germany ) and 150 ng of the best quality samples were processed using Affymetrix Whole Transcript Sense Target Labeling Kit ( Affymetrix , Santa Clara , USA ) . Fragmented and labeled cDNA was hybridized onto Human Gene 1 . 0 ST array ( Affymetrix ) . The arrays were washed , stained for biotinylated cDNA and scanned according to the manufacturer’s recommendations . Samples were classified into three main groups ( all males ) : ( 1 ) healthy controls , that were negative in anti-Leishmania ELISA test ( n = 4 ) , ( 2 ) samples from patients with LCL ( n = 2 ) , and ( 3 ) samples from patients with DCL ( n = 3 ) . Approximately 8 , 500 NK cells were isolated from all the samples . NK-cell mRNA of non-stimulated and LPG-stimulated groups was profiled , using Affymetrix Human Gene ST 1 . 0 oligo microarrays . All possible pairwise comparisons between the three groups were analyzed creating nine contrasts of interest . Three contrasts aimed at identifying genes responding to LPG stimulus: LCL_LPG versus LCL_NS , LCD_LPG versus LCD_NS , and Ctrl_LPG versus Ctrl_NS ( NS = non-stimulated ) . Three more interrogate changes in expression between the non-stimulated groups and the other three between LPG-stimulated groups . Raw data were background-corrected using Robust Multiarray Average ( RMA ) [19] and normalized using Quantile Normalization [20] . Differential expression was determined using statistical linear models with arbitrary coefficients , contrasts of interest were analyzed using the bioconductor library limma [21 , 22] . Correction for multiple hypotheses was applied using false discovery rate ( FDR ) [23] . Genes were selected based on a Fold-change > 2 ( Fold-Ch ) and a p-value ≤ 0 . 05 . The complete microarray analysis pipeline was conducted using Abraxas Biosystems Gene Expression Microarray Analysis Suite . Samples used for microarray analysis were also used for qRT-PCR validation except for the LCL group that used 4 additional samples . Total RNA ( 20 ng ) from NK cells of 4 healthy controls , 6 LCL and 3 DCL patients ( all males ) were retro-transcribed using High-Capacity cDNA Archive kit ( Applied Biosystems ) , according to manufacturer’s instructions . Relative quantification using Taqman PCR analysis was performed with the ABI PRISM 7900HT Sequence Detection System ( Applied Biosystem ) in a reaction volume of 20 μL containing 1X Taqman Universal Master Mix ( Applied Biosystems ) , 1X probes and the sets of primers: Hs00765730-m1 ( NF-κB1 ) , Hs00174517-m1 ( NF-κB2 ) , Hs00936103 ( IRAK-3 ) , Hs00610101-m1 ( TLR2 ) , Hs00174128-m1 ( TNF ) , Hs00989291-m1 ( IFN-γ ) , Hs01013989-m1 ( STAT-1 ) , Hs00194264 ( IFN-γR2 ) , Hs01548202 ( IL-12Rβ-2 ) and Hs01113602 ( TNFAIP6 ) ( all were Taqman Gene Expression assays , Applied Biosystems ) . The thermal profile was as follows: 95°C during 10 min and 40 cycles at 95°C for 15 s and 60°C for 1 min . All amplification reactions were done in duplicate and the relative quantification of gene expression was calculated using the comparative Ct method ( ΔΔCt ) [24] . Levels of mRNA expression were reported after normalization using GAPDH as endogenous control . GAPDH was chosen after verification that efficiencies of targets and reference gene had negligible differences . Statistically significant changes between groups were assessed using the Mann-Whitney U test . Data presented as mean +/- SEM , p< 0 . 05 were considered statistically significant . The analysis was done using the Prism 5 software ( GraphPad Software , San Diego , CA , USA ) . TLR2: Gene ID: 7097; UniProtKB: O60603 . IRAK3: Gene ID: 11213; UniProtKB: Q9Y616 . NF-κB p50: Gene ID: 4790; UniProtKB: P19838 . NF-κB p52: Gene ID: 4791; UniProtKB: Q00653 . TNF-α: Gene ID: 7124; UniProtKB: Q9UBM5 . IFN-γ: Gene ID: 3458; UniProtKB: P01579 . IFN-γR2: Gene ID: 3460; UniProtKB: P38484 . IL-12Rβ2: Gene ID: 3595; UniProtKB: Q99665 . STAT1: Gene ID: 6272; UniProtKB: P42224 . TNFAIP6: Gene ID: 7130; UniProtKB: P98066 .
The structure of our study , presents nine pairwise comparisons between the three groups . The numbers of differentially expressed genes per contrast are shown in Fig 2 . It has been reported that L . major LPG induces NF-κB nuclear translocation as well as TNF-α and IFN-γ cytokine production in healthy controls [1] . In order to verify if this phenomenon was also present at gene expression level , LPG-stimulated ( LPG ) versus non-stimulated ( NS ) NK cells from: healthy controls , LCL and DCL samples were analyzed . Results show that in the Control group ( C ) , no genes were found to be significantly down-regulated , whereas 8 genes were significantly up-regulated ( p < 0 . 05 ) , 7 of which , were related to the immune response ( Table 1 ) . The activation of NK cells stimulated with Leishmania LPG in the control group suggests that NK cells represent a first line of innate defense against the parasite , since they respond directly to a pathogen molecule . These results are consistent with a previous report showing that LPG-stimulated NK cells from healthy controls have an increased TNF-α production as well as nuclear translocation of NF-κB [1] . In the case of LCL patients , the analysis of LPG-stimulated vs non-stimulated NK cells showed that only one gene TCEB3CL , associated with transcription , was down-regulated ( p = 0 . 0007 , Fold-Ch = 2 . 05 ) . On the other hand , the same contrast but for DCL patients showed that two genes , both associated with mitochondrial biogenesis , were up-regulated . One of these ( MT1 ) also had multiple up-regulated isoforms ( Table 2 ) . Taken together , these results suggest that stimulation of NK cells with 20 μg of LPG during 6h up-regulates some genes associated to immune response but only in healthy controls . The other 6 contrasts: LCL vs C; DCL vs C; LCL vs DCL in non-stimulated as well as LPG-stimulated present a larger number of differentially expressed genes . The comparative analysis of gene expression of LCL vs C showed 108 differentially expressed genes: 71 up-regulated ( 66% ) and 37 down-regulated ( 34% ) ( Fig 2 , bars 1 and 2 ) . In contrast , for DCL vs C , 185 genes were found to be differentially expressed but only 31 of these were up-regulated ( 17% ) , whereas the remaining 154 genes were down-regulated ( 83% ) ( Fig 2 , bars 3 and 4 ) . A similar pattern was observed when comparing the expression of genes of DCL vs LCL , showing 149 differentially expressed genes: only 22 genes were up-regulated ( 15% ) and 127 were down-regulated in DCL samples ( 85% ) ( Fig 2 , bars 5 and 6 ) . This suggests that down-regulation patterns in DCL patients may play a role in disease susceptibility . A similar pattern of differential gene expression was evidenced in LPG-stimulated samples , although some of the genes differed from those of non-stimulated samples . For the case of LCL vs C , a total of 105 genes were found to be differentially expressed: 64 up-regulated ( 61% ) and 41 down-regulated ( 39% ) ( Fig 2 , bars 7 and 8 ) . In contrast , for DCL vs C a total of 218 genes were found to be differentially expressed , of which only 31 were up-regulated ( 14% ) and 187 down-regulated ( 86% ) ( Fig 2 , bars 9 and 10 ) . Similarly , for the analysis of DCL vs LCL , 194 out of the 216 differentially expressed genes were down-regulated ( 90% ) , ( Fig 2 , bars 11 and 12 ) . Gene set enrichment analysis per contrast using KEGG ( Kyoto Encyclopedia of Genes and Genomes ) showed mainly pathways associated to immune response including Toll-like receptors , JAK/STAT , MAPK signaling pathways and cytokine-cytokine receptor interaction ( All lists of differentially expressed genes and Venn diagrams are in supplementary file S1 File and KEGG enrichment analysis in S1 Table ) . An additional analysis of statistically significant enriched pathways ( p-value ≤ 0 . 05 ) using DAVID v6 . 7 ( The Database for Annotation , Visualization and Integrated Discovery ) was performed . Again , most of the enriched pathways were those associated to the immune system . The differentially expressed genes of the different contrasts are shown in supplementary file S2 File ) . The contrasts include: C_LPG vs C_NS; LCL_LPG vs LCL_NS; DCL_LPG vs DCL_NS in addition to LPG-stimulated and non-stimulated: LCL vs Controls , DCL vs Controls and DCL vs LCL . To further examine these findings , genes involved in the immune response were classified using non-supervised hierarchical clustering ( Fig 3 ) . The data show that gene expression profiles are consistent for DCL patients ( labeled green top horizontal bar ) but at the same time , show some opposite patterns in control ( black ) and LCL ( magenta ) samples . Note that some of the genes associated with immune response are down-regulated in DCL patients including IRAK-3 , NF-κB2 , IL-12Rβ-2 , STAT-1 and TNF-α . It is noteworthy , that these genes have also been reported as key players in the control of Leishmania infections [1 , 6 , 25 , 26] . In contrast , genes encoding IRAK-3 and TNF-α appear up-regulated in LCL patients possibly contributing in promoting a protective immune response . In order to validate the results from the microarray approach and using the same contrasts , ten genes important in the immune response against Leishmania were selected for relative quantification using qRT-PCR ( Table 3 ) . The list includes TLR2 , IRAK-3 , NFκ-B1 , NF-κB2 , IFN-γR2 , IL-12Rβ-2 , STAT-1 , TNF-α and IFN-γ . Additionally , we validated TNFAIP6 because it was the gene with the largest fold change for all contrasts . Rows represent genes encoding proteins that were clustered according to the signaling pathway in which they participate as well as to their location within the cell . Columns represent our main six contrasts each arranged in two sub-columns one for differential expression in fold change and the second for qRT-PCR differential values in ΔΔCt . Two blocks represent non-stimulated , and LPG-stimulated on the far right . Up-regulation is marked in italics and down-regulation is marked in bold black . It is observed that the down-regulation pattern for qRT-PCR is closely similar to that for microarray data . According to results in Table 3 , most values were validated through qRT-PCR except for IFN-γ that shows a persistent inconsistency . A possible explanation for this could be the reduced sample size .
Leishmania mexicana can cause two clinical forms of cutaneous leishmaniasis with contrasting severity . Patients with less severe clinical form , LCL , present ulcers at the sites of the sand fly bite that contain relatively low numbers of parasites . In contrast , patients with DCL have nodules containing highly parasitized macrophages that spread uncontrollably throughout the skin . Whilst LCL patients are able to contain the spread of the parasite , DCL patients are unable to control parasite reproduction inside macrophages , which eventually burst , releasing infective amastigotes . These are taken up by other phagocytic cells such as neutrophils , macrophages and dendritic cells , thereby protecting the parasites from the deleterious effect of complement activation . Their “Trojan horse” strategy , originally described by Wilson et al . , permits parasites an early escape from the infection site . Once inside phagocytic cells , they can inhibit microbicidal mechanisms such as the generation of NO and reactive oxygen metabolites , both of which , are highly toxic for the parasite [27 , 28] . Phagocytic cells need to be activated in order to cope with intracellular Leishmania infections . Cytokines such as IFN-γ and TNF-α are crucial for inducing leishmanicidal mechanisms in phagocytic cells . In addition to activating the infected cells , these two cytokines also favor the formation of granulomas in the infected tissues in an effort to contain parasite spread [29] . This could be evidenced in lesions of LCL patients , where well-organized granulomas have been reported . In contrast , lesions of DCL patients show diffusely scattered cells consisting mainly of heavily vacuolated macrophages harboring abundant amastigotes [2 , 30] . Taken together , these evidences highlight the importance of IFN-γ and TNF-α for Leishmania control and their lack of presence in DCL patients that could ultimately be responsible for the uncontrolled parasite spread . The protective effect of IFN-γ is achieved through various mechanisms: 1 ) by induction of the expression of NO synthase 2 ( NOS2 ) gene; 2 ) favoring a Th1 polarization of CD4+ T cells ( thereby guaranteeing further IFN-γ production ) ; and 3 ) by inducing maturation of dendritic cells and their migration to lymph nodes [6 , 31 , 32] . NK cells are among the first to produce IFN-γ and TNF-α in response to pathogen presence and in leishmaniasis , these cells can become activated after the binding of TLR2 to Leishmania LPG [1] . The possible role of NK cells in defining disease outcome in patients infected with L . mexicana was reported in previous work of our group [2] . We were able to show that effector functions in NK cells differ between LCL and DCL patients . For instance , NK cells of DCL patients showed an important reduction in IFN-γ and TNF-α production and reduced expression of TLR2 , TLR1 and TLR6 , as compared to NK cells of LCL patients , which showed an enhanced production of both cytokines and TLR expressions after stimulation with LPG . Moreover , we observed a reduced number of NK cells in peripheral blood and tissue lesions as well as down-regulation of IFN-γ in DCL patients by qRT-PCR . This evidence on impaired NK-cell function in DCL patients and the possible correlation to the disease severity , called for a precise analysis of the mechanisms involved . We therefore used NK cells of the same LCL and DCL patients to analyze the expression of the genes involved in innate cytokine production and TLR signaling pathways . We now show that disease severity correlates with the down-regulation of important genes involved in the early immune response of DCL patients . We were also able to validate most of the genes associated to innate immune response by qRT-PCR , finding a robust consistency with the gene expression patterns obtained from the microarray analysis , some of which were statistically significant in both platforms . The down-regulation of genes encoding IRAK-3 , NF-κB2 , IL-12Rβ2 , STAT-1 and TNF-α in DCL patients intervenes at different levels in the pathway needed for the activation of NK cells and their IFN-γ and TNF-α production . The process begins with IL-12 production mediated by activation of the TLR2 signaling pathway , which in turn is required for NK-cell stimulation and for a CD4+ Th1 development [33] . Previous studies have associated IL-12 with protection against L . major infections [6 , 34] . Our data now show that NK cells of DCL patients have reduced expression levels for IL-12Rβ2 , hindering an early NK response to IL-12 stimulation . Furthermore , down-regulation of TLR2 in these patients also impairs binding of Leishmania LPG , which can affect NK-cell activation at two levels . First , it hampers nuclear translocation of NF-κB and next it interferes with JAK/STAT activation that is initiated by the crosstalk between TLR/IL-1 and JAK/STAT signaling pathways . This is in accordance with Luu et al . , who recently described that STAT-1 interacts with TRAF6 following TLR activation and that the phosphorylation of STAT-1 has a critical role in augmenting TLR-induced NF-κB activation [4] . Our data also show that in addition to reduced TLR2 and STAT-1 , the expression levels of genes encoding NF-κB1 and NF-κB2 are also down-regulated in DCL patients . This suggests that the blockage of the TLR and STAT signaling pathways may be critical in activation and regulation of the pro-inflammatory responses following pathogen challenge . The inhibition of the immune response is further augmented by the low expression of IFN-γR2 in NK cells of DCL patients . Since IFN-γ is one of the key cytokines needed for the protective immune response against Leishmania , and its biological functions are mediated by activation of JAK/STAT kinases [35] , the down-regulation of IFN-γR2 and STAT-1 genes possibly render NK cells of DCL patients unresponsive to this cytokine . The importance of TLR receptors in the protection against Leishmania has also been shown in mouse models . Results indicate that resistance to L . major infections is induced by IL-12 and associated with the MyD-88-dependent pathway on TLR activation leading to a Th1 response . This contrasts with the disease susceptibility and the Th2 response observed in MyD-88−/− mice [3] . It is noteworthy that LPG stimulation led to a transient up-regulation of IFN-γ gene expression in NK cells of both groups of patients , as seen in Table 3 . Yet , the biological implications of the elevated gene expression in DCL patients are not evident since these patients showed down-regulation of the receptor IFN-γR2 . Hence , only LCL patients seem to be able to benefit from this cytokine . Interestingly , in vitro stimulation of NK cells with LPG further down-regulated the expression of the IFN-γR2 gene in DCL patients , although it did not modify the expression of STAT-1 and IL-12Rβ2 genes . With these results we are tempted to speculate that IFN-γR2 in NK cells of DCL patients is more susceptible to modulation by L . mexicana LPG , as compared to STAT-1 and IL-12Rβ2 . Our evidence is in accordance with the literature , where C57BL/6 STAT-1-/- mice , infected with L . major , showed a reduction of IL-12 , IFN-γ and nitric oxide ( NO ) production , and developed larger lesions containing significantly more parasites as compared to WT C57BL/6 mice [5] . All points to the idea that strong reduction in gene expression of TLR2 , IRAK-3 , NF-κB1 , NF-κB2 , IFN-γR2 , IL-12Rβ2 , STAT-1 and TNF-α may block NK-cell activation and effector mechanisms in DCL patients through various mechanisms: 1 ) reduced expression of IL-12Rβ2 limits IL-12 stimulation; 2 ) down-regulation of STAT-1 gene interferes with IFN-γ production; 3 ) down-regulation of IFN-γR2 interferes with autocrine activation of NK cells as well as of other immune cells . Thus , several of the critical early protective molecules , receptors and mechanisms needed for protection against Leishmania are likely to be shut down , leaving DCL patients unprotected against parasite replication . The cause of down-regulation of genes in DCL patients remains unknown , though one may speculate that DNA methylation or other epigenetic modulation could play a role . It has been shown that the response of immune cells to invading pathogens can lead to genomic instability and DNA damage . Furthermore , intracellular pathogens can alter the epigenome integrity of the host , possibly through DNA methylation or regulation of microRNA ( miRNA ) [36 , 37] . MicroRNAs are post-transcriptional regulators that belong to a molecular regulation system known as RNA interference and immune responses can be regulated by pathogen-encoded miRNAs [38] . MicroRNAs have been detected in macrophages and dendritic cells infected with L . donovani and L . major , respectively , and have been proposed to be responsible for epigenetic changes in DNA methylation [39 , 40] . Even though and to the best of our knowledge , Leishmania mexicana infections have not been related to microRNAs capable of regulating NK cells , it remains to be analyzed whether microRNAs can be associated with impaired NK effector functions and disease development , as has been demonstrated for other infectious diseases [41] . It would be interesting to establish whether these parasites possibly modify the host immune response at a molecular level through microRNAs , thereby modifying immune cell molecules and mechanisms as part of their evasion strategies . This has been shown for L . donovani that causes abnormal nuclear translocation of STAT-1 leading to: ( 1 ) its rapid proteosomal degradation , ( 2 ) diminished levels of the IFN-γ receptor α-chain and ( 3 ) the induction of SOCS3 , a negative regulator of IFN-γ signaling [42] . Evidence that the parasite can attenuate IFN-γ-induced tyrosine phosphorylation , inhibition of the alpha subunit of IFN-γR expression and a transient induction of SOCS3 has been presented [25 , 26] . In accordance , L . mexicana has been shown to block IFN-γ mediated NO production in infected macrophages and to increase protein-tyrosine phosphatase activity , particularly of SHP-1 . Additionally , this parasite causes elimination of the p65-containing subunit of NF-κB , cleaving p65 into a p35-containing subunit and promoting total protein degradation . It also inhibits STAT-1 and AP-1 activity [43] . Moreover , Leishmania LPG binding to TLR2 can induce the expression and activation of the serine/threonine phosphatase PP2A that inactivates TLR cytoplasmic adaptor proteins ( IRAK-1 , MAPKs , and IκB ) , thereby leading to tolerance [31] . All , indicating that the parasite has developed complex evasion strategies that can inhibit critical effector mechanisms of the immune response , the impact of which requires to be analyzed in the human host . Another remark is that in LCL patients , TLR2 , IRAK-3 and NF-κB1 genes were up regulated , both in non-stimulated and LPG-stimulated samples . These findings could explain why NK cells in LCL patients produce IFN-γ and TNF-α and over-express membrane TLR2 when these cells are stimulated with LPG [2] . Interestingly , Leishmania infections in LCL patients achieved maximal up-regulation for TLR2 , IRAK-3 and NF-κB1 , which was not modified by further in vitro stimulation with LPG . In summary , results of this study validate our earlier observations on the important role of NK cells in conferring an early protective response . We are able to show for the first time in samples from patients infected with L . mexicana , that important innate immune-related genes are down-regulated in DCL patients beginning at the early stages of the infection , which possibly interferes with an adequate protective response against Leishmania . TNFAIP6 ( TSG-6 ) , the gene with largest fold-change was down-regulated in DCL patients ( -54 . 19 in NS and -59 . 3 in LPG-stimulated NK cells ) , is expressed by many different cell types in response to pro-inflammatory cytokines and encodes a protein that is secreted at inflammation sites , playing an important role in the protection of tissues from the damage of acute inflammation [44] . Also , this protein interacts with CD44R on resident macrophages . The fact that TNFAIP6 ( TSG-6 ) has not been previously reported in leishmaniasis , and due to the important level of down-regulation found in DCL patients , its role still needs to be analyzed at the functional level . In conclusion , the down-regulation of genes that contribute in the immune response regulation of both TLR and JAK/STAT signaling pathways affect different molecules of NK cells: transcription factors ( NF-κB and STAT-1 ) , cytokine receptors ( IFN-γR2 and IL-12Rβ2 ) and cytokines ( TNF-α ) . These findings seem to correlate with the more severe clinical form of cutaneous leishmaniasis ( DCL ) . The clear pattern of a large number of down-regulated genes in DCL samples before and after being stimulated with Leishmania LPG suggests a possible association between gene regulation and disease susceptibility and/or severity . Thus , development of the clinical form of LCL or DCL may be associated to down-regulation gene patterns in NK cells . However , it remains to be demonstrated whether and how these down-regulated genes favor dissemination of Leishmania mexicana in these patients .
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Leishmaniasis , caused by protozoan parasites is considered a neglected disease . Leishmania mexicana can cause localized or diffuse cutaneous leishmaniasis . Patients with localized cutaneous leishmaniasis contain the parasite within granulomas , whereas patients with diffuse cutaneous leishmaniasis show uncontrolled parasite spread . The cause of this progression remains unknown . However , NK cells have been shown to play an important role since they are among the first to produce cytokines ( IFN-γ and TNF-α ) that help phagocytic cells to eliminate the intracellular parasite . Previous studies had shown that NK cells of patients with diffuse cutaneous leishmaniasis are unresponsive to Leishmania , yet underlying mechanisms were unknown . The current work aims at understanding how the parasite modulates NK-cell responses through gene expression profiling between patients with localized and diffuse cutaneous leishmaniasis . A highlight of our results is that NK cells of patients with the uncontrolled form of leishmaniasis show down-regulation patterns for genes that regulate the innate immune response through TLR receptors and JAK/STAT signaling pathways at different levels: transcription factors ( NF-κB and STAT-1 ) , cytokine receptors ( IFN-γR2 and IL-12Rβ2 ) and cytokines ( TNF-α ) . The alteration of expression levels for genes in immune response signaling pathways could predispose to DCL development and/or be associated with disease severity .
|
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2016
|
Down-Regulation of TLR and JAK/STAT Pathway Genes Is Associated with Diffuse Cutaneous Leishmaniasis: A Gene Expression Analysis in NK Cells from Patients Infected with Leishmania mexicana
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For more than half a century , genotoxic agents have been used to induce mutations in the genome of model organisms to establish genotype-phenotype relationships . While inaccurate replication across damaged bases can explain the formation of single nucleotide variants , it remained unknown how DNA damage induces more severe genomic alterations . Here , we demonstrate for two of the most widely used mutagens , i . e . ethyl methanesulfonate ( EMS ) and photo-activated trimethylpsoralen ( UV/TMP ) , that deletion mutagenesis is the result of polymerase Theta ( POLQ ) -mediated end joining ( TMEJ ) of double strand breaks ( DSBs ) . This discovery allowed us to survey many thousands of available C . elegans deletion alleles to address the biology of this alternative end-joining repair mechanism . Analysis of ~7 , 000 deletion breakpoints and their cognate junctions reveals a distinct order of events . We found that nascent strands blocked at sites of DNA damage can engage in one or more cycles of primer extension using a more downstream located break end as a template . Resolution is accomplished when 3’ overhangs have matching ends . Our study provides a step-wise and versatile model for the in vivo mechanism of POLQ action , which explains the molecular nature of mutagen-induced deletion alleles .
DNA mutations fuel evolution of organisms giving rise to speciation , and of cells within an organisms giving rise to cancer . Two replication-associated mechanisms are responsible for most if not all single nucleotide variants ( SNVs ) as well as small insertions/deletions ( indels ) at repetitive sequences: i ) copying errors made by the replicative polymerases delta and epsilon , which are mostly undone by DNA mismatch repair , and ii ) replication of damaged DNA by specialized so-called translesion synthesis ( TLS ) polymerases . TLS polymerases , in contrast to the replicative polymerases , have the ability to extend nascent DNA strands across non- or poorly coding damaged bases , often leading to mutation . It is , however , less well understood which mechanisms are responsible for other types of genomic alterations , such as deletions that are larger than a few bases . A recent study that involved whole genome analysis of C . elegans animals that were propagated for many generations revealed that vast majority of accumulating deletions larger than 1 bp required the activity of the A-family polymerase Theta ( POLQ ) . Upon unperturbed growth , wild-type C . elegans genomes accumulate SNVs as well as deletions but the latter class was strikingly absent in strains that were defective for POLQ [1] . Instead , much more dramatic chromosomal rearrangements were noticed indicating that POLQ action protects the genome against deterioration but at the cost of a small genomic scar . A similar profile of mutagenesis was observed resulting from DNA double-strand break repair , which hinted towards DSBs as being a very prominent source of genome diversification during evolution , and towards error-prone DSB repair as the mechanism responsible for this type of genome alterations [1] . The first demonstration of POLQ acting on DSBs was made in Drosophila: in vivo processing of artificially-induced DSBs in POLQ-mutant flies deviated from that in wild-type flies [2] . POLQ deficiency did not increase sensitivity to ionizing radiation , yet it did greatly exacerbate hypersensitivity in flies impaired in homologous recombination . Apparently , a POLQ-dependent DSB-repair pathway can act as a backup in HR-compromised circumstances . Indeed , recent work on human POLQ revealed a strong synergistic relationship between the HR pathway and POLQ-mediated DSB repair [3 , 4] . The synthetic lethal nature of this genetic interaction may be of great clinical importance as it identifies POLQ as a druggable target for tumours carrying mutations in HR genes . Another indication that POLQ repairs DSBs in contexts where HR is compromised came from genetic studies performed in C . elegans . Here it was shown that POLQ-mediated repair is the only pathway ( also in HR-proficient conditions ) capable of repairing replication-associated DSBs that are induced when persistent DNA damage or stable secondary structures cause a permanent block to DNA replication [5 , 6] . It was subsequently shown that these DSBs result from inheritable ssDNA gaps opposite to the strand containing the damage , which could thus not serve as a template for HR [7] . Extensive analyses of repair products in both flies and worms provided a clear signature of POLQ-mediated DSB repair with two prominent features: i ) the notion of microhomology at the repair junctions , a feature previously ascribed to non-canonical end-joining also called alternative end-joining [8 , 9] , and ii ) the occasional presence of so-called template inserts: deletions that contain , at the deletion junction , the inclusion of a DNA insert ( hereafter called delins ) . These inserts are of variable length but their origin can be mapped to DNA regions that lie in very close proximity to the DSBs ends that produced the delins . Similar hallmarks can be found for POLQ-mediated DSB repair in human and mouse cells [4 , 10] . A recent in vitro study provided a molecular explanation for the prominent presence of microhomology at the DSB repair junctions: repair reactions with purified protein showed that two base pairs of complementarity is enough for human POLQ to pair and extend 3’ overhangs of partially double-stranded oligonucleotides [11] . Although it is now becoming increasingly clear that POLQ plays an evolutionarily conserved role in DSB repair , how POLQ acts in vivo to explain all the observed consequences remains to be elucidated . Over the last four decades , the C . elegans community has used EMS and UV/TMP to generate many thousands of deletion alleles , but the underlying mechanism has remained unknown . Here , we demonstrate that mutagen-induced replication breaks in C . elegans germ cells are exclusively repaired by POLQ . This publically available allele collection , reflecting ~7 , 000 in vivo POLQ-mediated end joining reactions , allows us to analyse and describe the POLQ-mediated repair mechanism in great detail .
To investigate whether POLQ plays a general role in the processing of mutagen-induced DNA damage , we assayed embryonic survival in animals that were exposed to two of the most widely used mutagens in C . elegans: EMS , which causes alkylating damage , and TMP , which , upon exposure to UVA light , results in monoadducts and crosslinks . We found polq-1-deficient animals to produce more unviable embryos than wild-type animals when exposed to EMS ( Fig 1A and S1 Fig ) , but not to the extent observed in animals that are defective for polymerase eta ( polh-1 ) , a translesion synthesis ( TLS ) polymerase that is involved in replicative bypass of DNA damage [12] . A similar mild hypersensitivity was observed when polq-1-mutant animals were incubated with TMP and subsequently exposed to UVA ( Fig 1B and S1 Fig ) , in agreement with previously published work [13] . In addition to monitoring the survival of embryos , we monitored their ability to produce functional gametes . Complete or partial sterility of daughters from exposed mothers is another phenotype that is related to genotoxic stress , likely because germ cells , or their progenitors , are more susceptible to DNA damage-induced arrest , apoptosis , and mitotic catastrophe [14] . Indeed , at EMS or UV/TMP doses where the brood size of exposed mothers were only moderately affected in both wild-type and polq-1-mutant animals ( Fig 1C and 1D ) dramatic sterility was observed in polq-1 but not in wild-type progeny animals ( Fig 1E and 1F ) : 99% versus 16% median reduction , in brood for EMS-treated animals , and 65% versus 5% for UV/TMP-treated animals . These data establish a prominent role for POLQ in protecting germ cells against EMS and UV/TMP-induced toxicity . EMS and UV/TMP are widely used mutagens in C . elegans to create loss-of-function alleles [15] . Given the sensitivity of polq-1 animals towards these agents we wanted to investigate whether POLQ functionality is relevant for generating these alleles . EMS predominantly alkylates guanine which can be bypassed , leading predominantly to GC>AT transitions [15–17] . Deletions also result from EMS treatment through yet unknown biology [17] . UV/TMP treatment results in a different spectrum of mutations: for this mutagen , deletions dominate base pair substitutions [17 , 18] , but also here , the underlying mechanism of deletion formation is unknown . To address the candidate role of POLQ in producing deletion alleles , we created libraries of mutagenized wild-type and polq-1-mutant animals and screened them for deletions . We used standard protocols that were previously used by numerous laboratories and consortia leading to the ~10 , 000 C . elegans deletion alleles that are currently available [19–21] . The general concept of these protocols is to find by PCR a smaller than wild-type product for a target of interest in pooled broods of mutagenized animals; then use a sib-selection strategy to isolate the mutant allele ( S2 Fig and Methods section ) . Because the progeny of mutagenized polq-1-animals have a reduced brood size ( Fig 1E and 1F ) , we screened the F1 generation , and not the F2 , which allowed us to inspect the same number of animals for polq-1-mutant and wild-type genotypes . We screened the libraries for deletions using eight different amplicons , all ~1 kb in size . Positive pools were chased by PCR of less-complex pools and individual library addresses ( in duplicate ) to exclude false positives ( See Methods for details ) . This strategy proved to be robust and specific as deletion alleles were readily detected in wild-type animals exposed to either EMS or UV/TMP , but not in mock-treated animals ( Fig 2A and 2B and S2B and S2C Fig ) . In contrast , we did not find a single deletion allele in libraries of either EMS- or UV/TMP-mutagenized polq-1 animals ( Fig 2A and 2B ) . From this data we conclude that EMS- and UV/TMP-induced deletion mutagenesis , in the size range of 50 bp up to ~1 kb , requires functional POLQ . To further validate this conclusion we investigated UV/TMP-induced mutagenesis in a more unbiased fashion by catching loss-of-function mutations in an endogenous genomic target , unc-93 . A dominant mutation in the transmembrane protein UNC-93 , unc-93 ( e1500 ) , causes worms to move uncoordinatedly . Loss of UNC-93 expression , or of one of its cofactors SUP-9 and SUP-10 results in a reversion to wild-type movement , which provides an easy phenotypic manner to monitor loss of function mutagenesis . We exposed POLQ-proficient and -deficient animals , carrying the unc-93 ( e1500 ) allele to TMP with or without UVA irradiation to introduce crosslinks . Wild-type-moving animals were isolated from the brood of exposed animals and subsequently inspected for deletions in unc-93 , sup-9 and sup-10 . The mutants that did not , by DNA gel electrophoresis , reveal a deletion in any of the three genes are likely the result of single nucleotide variations ( SNVs ) and were not further analysed . In treated wild-type animals , we observed an increase in two distinct categories of deletions ( Fig 2C and 2D ) : one class , comprising of small , 50 bp to 1 kb , deletions with median size of ~100 bp ( S2D Fig ) , and another class in which deletions are substantially larger , being >5 kb in size ( Fig 2D ) . No deletions were found in the size range 1–5 kb . UV/TMP-treated polq-1-deficient animals were , however , devoid of small deletions , while the ratio of very large deletions further increased ( Fig 2C and 2D ) . Based on these data and the PCR-based screenings of UV/TMP-treated mutant libraries , we conclude that the vast majority ( if not all ) of small deletions in the range of 50 bp up to at least 1 kb are the result of POLQ action . In its absence large deletions manifest , which , in agreement with our previous work , argue that POLQ prevents large genomic alterations at replication blocking DNA lesions at the expense of relatively small deletions [1 , 5 , 6] . Above , we demonstrate that deletion alleles isolated from libraries of EMS- and UV/TMP-treated populations are the result of POLQ action . This notion allows us to systematically analyse a uniquely rich collection of ~2 , 000 EMS- and ~8 , 000 UV/TMP-induced deletion alleles that were generated by the C . elegans community to elucidate the in vivo mechanism of POLQ action . Fig 2E displays the sizes for all ~10 , 000 alleles , for which the sequence information was retrieved from WormBase [22] . The majority of alleles are between 50 bp and 1kb and can be categorized into two groups: i ) simple deletions , which make up the majority of events ( ~70–75% ) in both the EMS and in the UV/TMP dataset , and ii ) deletions that are accompanied by an insertion of a small segment ( median: 5 bp for both sets ) of novel DNA; we refer to this class ( ~25–30% ) of alleles as delins ( Fig 2F–2H ) . We set out to characterize the ~5 , 000 deletions and ~1 , 800 delins , filtered to size ( 50–1 , 000 bp ) , into great detail . First , we investigated the base composition of deletion junctions to further examine an earlier reported relationship in POLQ-mediated mutagenesis between the position of a deletion breakpoint and the position of a replicating blocking lesion: we previously found for deletions resulting from replication blocking G-quadruplexes that one of the breakpoints maps close to the replication impediment [6] . This led to a model where deletions result from processing the 3’ hydroxyl ends of blocked nascent strands . DNA lesions induced by EMS and UV/TMP also have the potential to block replication , and we thus questioned whether cognate deletions close to their breakpoints carry the signature of EMS- or UV/TMP-inflicted base damage . More precisely , if one of both breakpoints results from processing a stable but reactive nascent strand that was extended up to the damaged base , then the first nucleotide immediately downstream of the breakpoint ( the -1 position ) might reveal the nature of the replication impediment ( see Fig 3A for a graphical illustration of this concept ) . Indeed , we found a clear non-random base composition at position -1: for EMS we found an overrepresentation of cytosine ( Fig 3B and S3 Fig ) , which perfectly fits the damage spectrum of EMS predominantly ethylating guanines [16 , 17] . Blocked DNA synthesis , incapable of extending across a damaged guanine , would result in a 3’ hydroxyl end immediately upstream of a cytosine . Also for deletions induced by UV/TMP we found at the -1 position a clear mutagen-specific overrepresentation of a particular base , in this case an adenine ( Fig 3C ) , which reflect TMPs reactivity towards thymines [23] . Strikingly , and in contrast to the EMS spectrum , we here also observed a non-random distribution at the +1 position , being a thymine . This outcome suggests that UV/TMP-induced deletions are preferentially induced at sites where replication is blocked by a thymine that is preceded by an adenine , a conclusion that is further supported by probing the datasets with pairs of nucleotides ( S3 Fig ) . This prevalent signature is in perfect agreement with the preference of psoralens to intercalate into and react with 5’TA in duplexed DNA [24 , 25] . Without further genetic dissection , however , it is impossible to discriminate between interstrand crosslinks at 5’TA sites or monoadducts ( or DNA-protein complexes ) formed at sites of preferred intercalation , being responsible for POLQ-dependent deletion formation . Irrespective which lesion , our data indicates that replication can proceed right up to the base that is damaged by the psoralen moiety . Our analysis of ~7 , 000 mutagen-induced deletion alleles reveals a clear lesion-specific signature in POLQ-mediated deletion formation . Importantly , a single replication fork block triggers such a deletion , as we observed a damage signature at only one of both breakpoints ( S4 Fig ) . The position of the damage with respect to the deletion junction supports a mechanistic model where the nascent strand blocked at the site of base damage is not subjected to extensive trimming but instead is reactive towards a POLQ-mediated end-joining reaction that has small sized deletions as an end-product . The putative mechanism responsible for generating the other reactive end at a 50–1 , 000 bp distance will be discussed later , but we will provide evidence that , with respect to reactivity , it is indistinguishable from the blocked nascent strand . We reveal above that the terminal nucleotide of the nascent strand , blocked at the site of base damage , is retained in the repair product , it is the base immediately flanking the deletion , but does it also guide repair ? To address this question we compiled all simple deletions from the UV/TMP dataset that had the signature T+1 , A-1 composition at one of both breakpoints , because only for this subclass ( n = 1 , 248 ) the identity of the terminal nucleotide of the nascent strand is known , i . e . a thymine . We then tested the following prediction: if this 3’ thymine is guiding repair of the break , by providing a minimal primer for POLQ , a thymine should be overrepresented at the -1 position of the opposite flank ( Fig 4A for a graphical illustration ) . This is indeed what we found: Fig 4B shows that the composition of the donor sequence opposite to the blocked nascent strand is completely random apart from position -1 , which is dominated by a thymine . A similar conclusion results if we use an approach that is blind to the replication-obstructing base and does not restrict the analysis to a single nucleotide . For each of the ~5 , 000 alleles we established the degree of homology between both breakpoints by scoring the degree of sequence identity in a 16-nt window , encompassing the 8 outermost nucleotide of the flanking sequence and the 8 nucleotides of the adjacent but deleted sequence ( see Fig 4C for a schematic illustration of the approach ) . These plots were subsequently compiled to generate heat maps for the different category of alleles . In both the UV/TMP-induced ( n = 4 , 461 ) and the EMS-induced deletions ( n = 662 ) crosstalk between both breakpoints is observed , but only for the nucleotide at the -1 position of the deletion and the +1 position of the opposing flank ( Fig 4D ) . This outcome lends further support to the hypothesis that the terminal base of one end , upon minimal pairing with the opposing template , is guiding POLQ-mediated repair . Once priming has been established and extension has commenced there are two possible fates: i ) continuation and further processing; in which case the outcome will be a deletion with single nucleotide identity at the junction , or ii ) discontinuation . If , in the latter case , the extended end serves as a new nucleation site for yet another round of POLQ-mediated repair , templated inserts will result ( Fig 5A ) . If so , delins are suspected to have some features identical to those described above for simple deletions . To address this , and to further dissect the in vivo mechanism of POLQ-dependent mutagenesis , we characterized the ~25–30% of mutagen-induced deletion alleles that are accompanied by small insertions in great detail . First we placed them , based on their size and suspected origin , in different categories ( Fig 5B ) : ~47–50% are so small ( <5 bp ) that their origin is untraceable , and another 5–10% are larger in size but their sequence does not provide enough certainty as to their origin . However , ~40–45% of delins ( ~700 ) have inserts with sufficient sequence information to reveal their source: apart from a small percentage ( ~3% ) that comprise of sequences mapping to distant sites at the same chromosome or to other chromosomes ( S5 Fig ) , the majority ( ~37–44% ) maps very close to the deletion . These insertions are either completely or partially identical to parts of the flanking sequences and have been designated ‘templated inserts’ because of a presumed role for the flanking DNA to serve as a template for a repair reaction . Because the majority of templated inserts map a few bases away from the deletion junction ( the template is located within the flank ) a number of parameters can be investigated centred around the questions: i ) what defines the start of POLQ-mediated DNA synthesis , ii ) what defines the end , and iii ) how accurate is it ? With respect to the start , we focused on templated inserts that are 100% identical to sequences in their flanks to avoid possible ambiguity in interpretation . For both UV/TMP and EMS-induced alleles ( n = 227 and 41 , respectively ) we found that templated inserts , similar to simple deletions , are primed by a single base pair . This priming becomes apparent when the base composition of one breakpoint is plotted to the base pairs that are neighbouring the sequence that served as a template for extension ( Fig 5C and 5D ) . Overrepresentation of sequence identity is confined to one position , the +1 base of one breakpoint ( the reactive end ) and the base flanking the origin of the insert in the opposite breakpoint ( the template ) , providing further confirmation that a single base pair is sufficient to drive POLQ-mediated repair . We found that ~85% of inserts originate from priming within 10 base pairs of the breakpoints ( Fig 5E ) , which could point to homology search close to the end of the available sequence . The observed similarities in the initiation steps of deletions that are simple and those that include a templated insert means that the difference between both outcomes is the consequence of a downstream step , for instance , discontinuity of POLQ action . The determinants influencing discontinuity in the repair reaction are currently unknown but it is a remarkable frequent event as ~25% of all alleles have insertions . From plotting the size of all inserts ( Fig 5B ) , we infer that templated inserts do not have a minimal length: although it is impossible to reliably map inserts of only one or a few bases to the flanking sequences , we observe that the percentage of inserts that can be mapped is constant , yet high , over the complete range of small insert size . This notion argues that also the very small , unmappable , insertions are flank-derived . Fig 5B also shows that while template inserts are overall rather small ( <25 bp ) , they do not have a preferred size . Instead , a gradual decline in length is observed which may suggest that comprehensive extension prevents discontinuity . Still , we also found inserts where stretches of more than 20 consecutive bases have been templated , indicating that substantial base pairing can still be disrupted before the two opposite ends are irreversibly connected . Whether POLQ dissociates from the template in this process or whether POLQ facilitates template switching is an interesting question as the latter option could serve to broaden the resolving potential of POLQ-mediated repair . Some delins have complex combinatorial inserts with two or more mostly overlapping templated inserts , arguing for reiterative steps of priming , extension and dissociation . In most of these cases ( 16 out of 17 ) only one flank provided the template , which hints towards directionality in POLQ-mediated resolution . To complete repair of aborted reactions , it seems plausible that another round of priming and extension is required , analogous to the biology leading to simple deletions , only in this case , one end has been extended using the other end as a template . To test this hypothesis , we again created heat maps , but here compared the terminal bases of the origin of the template inserts as well as their flanking bases ( as this constitutes the new reactive end ) , to the border of the same flank , which in this scenario is considered the opposing end ( Fig 6A ) . We indeed found support for a single base pair priming reaction as also here a clear overrepresentation of single nucleotide identity is observed ( Fig 6B and 6C ) . Our combined analysis thus supports a model , where simple deletions and template inserts result from the same chemistry , displaying the same features , the only difference being an aborted POLQ-mediated extension of a single base paired-primed intermediate . Probing the entire collection of ~10 , 000 EMS- and UV/TMP-induced C . elegans deletion alleles for single nucleotide identity at break junctions and the presence of template inserts suggest that POLQ-mediated end joining is responsible for the majority of deletions in a 50–3 , 000bp range ( S6 Fig ) . At present it is unknown what underlies the discontinuity in POLQ-mediated repair that leads to delins instead of simple deletions . One possibility is polymerase errors . POLQ is a relatively error-prone polymerase generating single base errors at rates 10- to more than 100-fold higher than other polymerase A family members [26] . Mismatches resulting from wrongly incorporated nucleotides may reduce POLQ’s processivity and promote dissociation and/or template switching . One observation provides strong support for such a scenario: the frequency of errors observed in templated inserts is extremely high as compared to mutations in the flanks of the simple deletions , while for both repair products the flank has served as a template for POLQ action . Although ~30% of all templated inserts are perfect , in the sense that they do not show mismatches , another 15% can be matched to the flank through a single run of consecutive bases if one mismatch or one slippage event is allowed ( Fig 7A ) . It can thus be argued that at least 1 in 3 templated inserts suffers from a mutation which translates to an error rate of ~1 in 30 base pairs during templated extension ( average insert size = ~10bp ) . In sharp contrast , we found only few mutations in the flanks of ~4 , 500 UV/TMP- induced simple deletions . Assuming that here POLQ is required to extend the reactive end with at least 10 bp , we calculate an error rate of <1 in 3 , 000 bp for simple deletions . To explain the >100 fold higher mutation frequency in extension leading to templated inserts , we propose that POLQ errors in fact provoke template switching , thus are causal to the formation of delins . A supporting observation is that mismatches are more frequently found closer to where the reaction is abrogated ( Fig 7B ) . POLQ replication errors could result from replicating non-damaged or damaged DNA . The in vitro demonstrated bypass activity of POLQ may help to extend past base damage or abasic sites . We mostly found incorrect incorporation of adenines opposite to any nucleotide other than a thymine ( Fig 7C ) , making up for half of all mismatches , which fits with the preferential incorporation of adenine that has been observed for POLQ in vitro [27] . Finally , using this unique dataset of ~7 , 000 in vivo POLQ reactions we re-evaluated the assumption that POLQ acts to protect against mutagen-induced damage by acting on replication-associated DSBs . Despite having demonstrated that POLQ-mediated end joining is a stand-alone DSB-repair pathway that is able to process bona fide DSBs [1] , it remained difficult to formally prove that a DSB is an intermediate in a repair reaction that produces simple deletions and templated inserts that were previously also found to accumulate in mutants defective for TLS polymerases . Through combining the features that characterize POLQ-mediated deletions , a mutagen , i . e . UV/TMP , that leaves a signature in the final product , and the sheer size of the collection analysed here , we are now able to establish that replication-associated deletion mutagenesis results from the processing of two opposing 3’ extendable ends , hence a DSB . Above , we have shown that a nascent strand blocked at a site of base damage can serve as a single nucleotide primer to be extended , using a donor sequence , located 50–1 , 000 bp away , as a template . In Fig 8 , we show that there is an equal likelihood of finding the reciprocal event: that the sequence immediately upstream of the blocked fork has served as a template for a priming , reactive end that is located 50–1 , 000 bp more downstream . This argues that POLQ-mediated repair , as in repairing bona fide DSBs , here acts to connect two 3’ reactive ends . It is currently unknown whether POLQ-mediated repair of replication-associated DSBs necessitates end-resection to create sizable 3’ ssDNA regions ( which then function as primer or as template ) . In vitro , human POLQ can extend ssDNA molecules intra-molecularly through a fold-back-stimulated templated reaction [28] . Here , by probing the delins for inserts that had a reverse-complement orientation with respect to their flanking matches we indeed found in vivo support for 3’ extension in which both the primer and the template reside on the same DSB end ( S7 Fig ) .
In this study , we have shown that EMS and UV/TMP-induced DSBs are predominantly repaired via POLQ-mediated repair and in-depth analysis of ~7 , 000 unique deletion footprints allowed us to unveil important characteristics of the in vivo repair mechanism . We found that mutagen-induced deletions are the product of alternative DSB repair in which one end is produced by the replication machinery that approached the damage up to one nucleotide . Base pairing of the terminal nucleotide of the blocked nascent strand to single stranded DNA at the opposite break end primes POLQ to polymerize , resulting in DNA tracts that are templated by the sequence immediately flanking the DSB . Further processing of the ensuing stable joints produces simple deletions . However , in case DNA synthesis is interrupted , likely resulting from POLQ errors , a primer-template switch is induced in which the newly formed terminal nucleotides again pair in order for POLQ-mediated extension to continue . We find that one or more cycles of such templated DNA synthesis and primer-template switching can fully explain the composition of deletions that are associated with inserts . From a conservative point of view , POLQ-mediated repair is a surprisingly elegant solution to the problem how to repair a DSB while keeping the loss of genetic information to an absolute minimum: the repair reaction does not depend on removal of nucleotides to create ligatable ends . It is thus an intriguing idea that nature , perhaps because of the polarity in DNA synthesis being in a 5’ to 3’ direction , has evolved DNA repair and recombination mechanisms that use or tolerate extensive 5’ but not 3’ end-resection; it is obvious that having both these activities prominently used inside nuclei would constitute a great threat to genomes . We have shown here for POLQ-mediated repair of DSBs that the 3’ end of a DNA molecule is very stable and acts as a nucleation site in the repair reaction . Using a specialized polymerase to extend and as such stabilize minimally paired 3’ ends , as opposed to trimming by exonucleases provides a simple yet powerful and versatile solution to a complex problem . One striking aspect of C . elegans POLQ is the notion of single nucleotide homology . The degree of microhomology in ( POLQ-dependent and potentially POLQ-independent ) alternative end-joining in a number of other biological systems , such as mouse , human and also plants appear to concern more bases , frequently 3 to 4 bp [4 , 10 , 29] . It is yet unclear whether this difference reflects species specific adaptation to the enzyme or differences in the context in which POLQ was studied: a recent in vitro study using purified human POLQ demonstrated pairing and extension of 3’ overhangs with just two nucleotides of homology [11] . Another perhaps more striking difference in POLQ-mediated repair between species is the composition of insertions that are found in between the break junctions . While insertions in C . elegans are mostly derived from a single proximal location , footprints in other species suggest that POLQ is more promiscuous , because inserts often originate from multiple locations , which is suggestive of iterative rounds of abortive repair [4 , 29] . It is currently unknown what is the cause of this apparent discrepancy between POLQ-mediated repair in different species , but it is of interest to note that mammalian POLQ has evolved to include three additional loop regions in the polymerase domain . One of these loops , loop2 , was recently implicated in non-templated terminal transferase activity [28] . The ability to add random nucleotides to the 3’ end of a DSB-repair intermediate may help to generate more opportunity for microhomology-mediated templated resolution . We have previously shown that POLQ is the primary pathway acting on DSBs that result from DNA replication blocking endogenous lesions [5–7] . An intriguing question concerns the size distribution of resulting deletions: as also shown here , one junction is defined by the replication fork impediment , but what defines the other end ? Genetic and molecular dissection of replication-obstructing G-quadruplex structures has led to the model where a replication-stalling DNA lesion results in a ssDNA gap downstream of the impediment [5–7] . More recently , we provided evidence supporting the idea that it is this gap that is responsible for a DSB ( with ends 50 to a few hundred bps apart ) when the gapped strand is replicated in the next S-phase [7] . POLQ-mediated alternative end-joining subsequently acts on these replication-associated DSBs , instead of HR , which cannot repair the break using the sister chromatid as the latter still contains the replication-blocking impediment ( see [7] for details ) . In this study , we demonstrate an identical genetic requirement for the repair of DSBs resulting from mutagen exposure; however , it is yet uncertain which replication-blocking lesions are causative . EMS induces a plethora of lesions [30] some of which have been shown to be potent blocks of the replicative polymerases [31] , whereas UV/TMP treatment generates psoralen monoadducts on thymines and interstrand crosslinks with a great preference for thymines . Whether deletions induced by UV/TMP are the result of ICL or monoadducts is an outstanding question because the notion of preferential junction formation at 5’TA sites is not discriminatory . Although this outcome perfectly fits a scenario of replication up to the first damaged base of juxtaposed T-T ICLs , it also fits to replication blocking at monoadducts that are preferentially induced at 5’TA sites . The hypersensitivity of C . elegans POLQ mutant animals towards alkylating and crosslinking agents ( as also observed for POLQ/Mus308 mutant Drosophila ) may seem to contradict to an apparent lack of sensitivity in other systems , such as POLQ knockout mouse cells . We suspect this difference to primarily originate from the fact that C . elegans toxicity assays , especially those encompassing early embryonic cell divisions , are very sensitive to perturbations of DNA replication [12 , 32] . Exposure to mutagens , such as EMS and UV/TMP , is widely used to induce random mutations in a great variety of organisms other than C . elegans , such as Drosophila , Zebrafish , Arabidopsis , Tomato , and mouse . Although EMS-induced damage predominantly induces SNVs , in all these biological systems deletions have been observed ranging in size from a few base pairs to numerous kb [18 , 20 , 33–39] , and it will be of great interest to investigate whether the causal involvement of POLQ-mediated repair is evolutionary conserved . In this work , we have linked a specific type of mutations , i . e . deletions of small size , to carcinogenic mutagens that are used in clinical setting . It is becoming increasingly important to establish causal relationships between the exact type and nature of their DNA damaging agents and genome alterations , especially because of the growing interest in mutational signatures in cancer genomes . Recently , the altered genomes of cancer cells are not only inspected for potentially cancer promoting ( driver ) mutations but also for signatures that testify to the history of the tumour , with respect to genetic makeup and/or environmental exposure [40] . Currently , the majority of these signatures are based on single base substitutions and their surrounding DNA context , but cancer genomes are loaded with copy number variations , deletions and insertions , and also gross chromosomal rearrangements that are likely resulting from mutagenic DNA repair processes [41 , 42] . It will be interesting to inspect cancer genomes , especially those evolving in cancer cells that are characterized by a defect in homologous recombination for genomic scars that carry the signature of POLQ-mediated end joining , to also determine the contribution of this mutagenic pathway to tumorigenesis .
Standard methods and conditions for culturing C . elegans were used [15] . The alleles used in this study were: polh-1 ( lf31 ) ; polq-1 ( tm2026 ) ; fcd-2 ( tm1298 ) . Bristol N2 was used as wild type in all experiments . Mutagenesis with EMS was performed at 12 . 5mM , 25mM , 50mM or 100mM according to standard protocols [15] . In brief , populations were synchronized by alkaline hypochlorite treatment and eggs were allowed to hatch o/n . L1 worms were plated out on 9cm NGM agar plates seeded with E . coli ( OP50 ) and grown at 20 degrees . Two days later L4 worms were washed off the plates and treated for 4 hours with EMS dissolved in M9 . A similar staging protocol was used for UV/TMP mutagenesis . Subsequently , animals of the L4 stage were treated for one hour with 10μg/ml TMP ( Sigma , T6137 , stock: 100mg dissolved in 40ml acetone ) dissolved in M9 . Animals were distributed onto non-seeded NGM plates and exposed to UVA irradiation ( 366nm; CAMAG 29200 Universal UV LAMP ) at a dose rate of 160μW/cm2 ( Blak-Ray UV-meter model no . J221 ) , after which the animals were transferred to standard OP50/NGM plates . Staged animals were exposed to either EMS or UV/TMP at the L4 larval stage and per experimental condition four plates each containing three worms were started . After a 24-36-hour period of egg laying the mothers were removed . The number of ( dead ) eggs and hatched progeny ( after 24 hours ) was determined . All experiments were performed in triplicate . We determined the brood size for animals by collecting eggs from individual hermaphrodites in sequential periods of 24 hours . For each period the number of ( dead ) eggs and hatched progeny ( after 24 hours ) was determined and then added . For each deletion library ~80 , 000 animals were used for synchronization by hypochlorite treatment ( 0 . 5M NaOH , 2% hypochlorite ) and overnight starvation . Animals of the L4 stage were treated with EMS ( 50mM ) , UV/TMP ( 50 J/m2 ) or mock-treated . P0 animals were removed by hypochlorite treatment 24 hours post-UV/TMP-treatment , and after o/n hatching ~100 , 000 F1 animals were transferred to 10 9 cm plates and were grown for two days at 20 degrees . Then , animals were collected by rinsing the plates with M9 and distributed over 10 96-well plates such that each well contained ~100 worms in a 5 μl volume . To this 10 μl of lysis buffer was added and animals were subsequently subjected to a standard lysis protocol to liberate the DNA . All 10 plates were pooled into 1 master plate ( using 10 μl original DNA mixture ) , which was used for another round of pooling by combining 10μl from each of the eight wells in a column , finally yielding one row of 12 wells for library . Prior to performing nested PCRs for eight different genomic targets ( see S1 Table ) , the DNA was digested with the thermostable restriction enzyme PspGI . Upon detection of a smaller-than-wild-type product in the pools , PCRs were repeated on the master plate and then on individual plates . The PCR products of the samples that remained positive during this deconvolution exercise ( in duplicate ) were sequenced . We considered a result a false positive if the samples of lower complexity failed to reproduce the PCR product . The sequence information for publically available deletion alleles was retrieved from WormBase ( WS243 ) . A custom Java program was written to analyse and annotate the WormBase alleles ( available upon request ) . We included a number of additional stringency criteria: 1 ) the coordinates of the allele should match the information about the allele’s left and right border sequence , 2 ) insertions within deletions should be as minimal as possible , 3 ) insertions that contained one or more Ns were discarded . In addition , for cases where sequence homology at the junctions allowed for more than one possible mapping position we placed the homology at the retained flank of the 5’ side . To identify the origin of the insertions in the delins alleles we i ) performed BLAST for insertions ≥15 nt , and ii ) used a custom-made algorithm aimed to find the longest common substring , i . e . the longest possible match between a stretch of the insertion ( ≥5 nt ) and the sequence that is in close proximity of the junctions ( ≤50 nt of each flank and 50 nt within either side of the deletion ) . All deletion alleles used in our analyses can be found in S3 Table .
|
DNA damage poses a threat to cell survival as it impedes accurate and efficient copying of DNA that precedes mitotic division . If left unrepaired , DNA damage can give rise to DNA double-strand breaks ( DSBs ) , which is considered to be one of the most dangerous types of genomic insult . Repairing DSBs is vital to preserve genomic integrity and to promote cellular survival . Here , we demonstrate in C . elegans that exposure to mutagenic agents leads to replication-associated DSBs that require polymerase Theta ( POLQ ) -mediated end joining for their repair . We provide a mechanistic basis for understanding how mutagens that interfere with DNA replication induce the type of deletion mutations that have been generated in a great variety of organisms in order to establish genetic null alleles . Bio-informatical data-mining of many thousands of deletion alleles subsequently has allowed us to establish DNA repair pathway-specific signatures and to uncover a surprisingly simple and elegant solution of how cells can repair a broken chromosome , while keeping the loss of genetic information to a minimum .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
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"invertebrates",
"caenorhabditis",
"dna-binding",
"proteins",
"nucleotides",
"animals",
"invertebrate",
"genomics",
"thymine",
"animal",
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"polymerases",
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] |
2016
|
Genomic Scars Generated by Polymerase Theta Reveal the Versatile Mechanism of Alternative End-Joining
|
Improved helminth control is required to alleviate the global burden of schistosomiasis and schistosome-associated pathologies . Current control efforts rely on the anti-helminthic drug praziquantel ( PZQ ) , which enhances immune responses to crude schistosome antigens but does not prevent re-infection . An anti-schistosome vaccine based on Schistosoma haematobium glutathione-S-transferase ( GST ) is currently in Phase III clinical trials , but little is known about the immune responses directed against this antigen in humans naturally exposed to schistosomes or how these responses change following PZQ treatment . Blood samples from inhabitants of a Schistosoma haematobium-endemic area were incubated for 48 hours with or without GST before ( n = 195 ) and six weeks after PZQ treatment ( n = 107 ) . Concentrations of cytokines associated with innate inflammatory ( TNFα , IL-6 , IL-8 ) , type 1 ( Th1; IFNγ , IL-2 , IL-12p70 ) , type 2 ( IL-4 , IL-5 , IL-13 ) , type 17 ( IL-17A , IL-21 , IL-23p19 ) and regulatory ( IL-10 ) responses were quantified in culture supernatants via enzyme-linked immunosorbent assay ( ELISA ) . Factor analysis and multidimensional scaling were used to analyse multiple cytokines simultaneously . A combination of GST-specific type 2 ( IL-5 and IL-13 ) and regulatory ( IL-10 ) cytokines was significantly lower in 10–12 year olds , the age group at which S . haematobium infection intensity and prevalence peak , than in 4–9 or 13+ year olds . Following PZQ treatment there was an increase in the number of participants producing detectable levels of GST-specific cytokines ( TNFα , IL-6 , IL-8 , IFNγ , IL-12p70 , IL-13 and IL-23p19 ) and also a shift in the GST-specific cytokine response towards a more pro-inflammatory phenotype than that observed before treatment . Participant age and pre-treatment infection status significantly influenced post-treatment cytokine profiles . In areas where schistosomiasis is endemic host age , schistosome infection status and PZQ treatment affect the cellular cytokine response to GST . Thus the efficacy of a GST-based vaccine may also be shaped by the demographic and epidemiological characteristics of targeted populations .
Over 200 million people in 74 countries are currently infected with Schistosoma spp . parasites , which are responsible for an estimated 15 , 000 deaths and 1 . 76 million disability adjusted life years per annum [1]–[3] . Schistosoma haematobium is the causative agent of urogenital schistosomiasis which results from pathological immune responses to eggs excreted into the bladder and genital tract of their host by adult parasites residing in the adjacent venules . Effective schistosome control is required to alleviate schistosome-associated pathologies , to protect the 650 million people currently at risk from schistosome infection and to reach the estimated 88% of infected people currently without access to drug treatment [2] , [4] . Current control efforts rely on treatment with the anti-helminthic drug praziquantel ( PZQ ) , which has reported cure rates of over 80% [5] , [6] and can reduce the risk of urogenital lesions if administered during childhood [7] . There is also mounting evidence that PZQ boosts both innate and adaptive immune responses to schistosome antigens [8]–[10] due to increased worm death in the bloodstream and an associated increase in exposure of schistosome antigens to immune recognition after treatment [11] , [12] . However , although there is some evidence that this immunological boost promotes a degree of resistance to re-infection in humans [10] , [13] , both infection prevalence and associated pathologies return after treatment and therefore repeated treatment is required [14] , [15] . For nearly 30 years an anti-schistosome vaccine has been seen as a desirable long-term adjunct to drug treatment [3] , [16] . More recently , it has been proposed that a combination of PZQ treatment and an anti-pathology vaccine may improve schistosome control [12] , [16] , [17] . The 28 KDa S . haematobium vaccine candidate antigen glutathione-S-transferase ( GST [18] , [19] ) is a multifunctional enzyme expressed on the tegument and sub-tegument of adult worms [20] and larval schistosomes [21] and the current focus of vaccine trials in humans . The exact function of schistosome GST is unknown but its role in fatty acid metabolism and prostaglandin D2 synthesis may contribute to immune evasion by the parasite [19] . GST-based vaccination has been extensively studied in animal models , leading to a reduction in parasite fecundity in cattle [22] , goats [23] and primates [24] , which has been attributed to production of antibodies that neutralise GST enzyme activity [25]–[27] . Importantly , reducing egg production by adult schistosomes is an effective means of reducing immunopathology since schistosomes do not replicate in their definitive hosts [3] . The latter is supported by observations in S . haematobium infected Patas monkeys where bladder lesion intensity was reduced following GST vaccination [24] , [28] . A recent Phase I randomised clinical study has shown that elevated levels of GST-neutralising antibodies , which are associated with reduced parasite fecundity [25] , [29] , as well as increased peripheral blood cytokine responses were detectable 21 days after a double dose of the GST vaccine was administered to healthy Caucasian adult males [30] . Furthermore , GST-specific PBMC cytokine responses in the latter study appeared to be biased towards a CD4+ T helper ( h ) 2 phenotype [30] , which is associated with protective immune responses to schistosome homogenate antigens in cohorts endemically-exposed to S . haematobium [31] , [32] . Despite these promising observations in animal models and safety-immunogenicity trials in humans in a non-endemic setting , very little is known about the cellular immune phenotype elicited by purified GST in naturally schistosome-exposed populations who would be the target recipients of a GST-based vaccine . In particular , GST-specific cytokine responses have been investigated in S . haematobium-exposed adults [33] , but no studies to date have investigated the age-distribution of GST-specific cellular cytokine responses which is closely related to schistosome exposure history [11] , [34] . Furthermore , despite speculation that GST-based vaccine efficacy may be enhanced by co-administration with PZQ in human populations [12] , [16] , [17] , [35] there is no existing data on how PZQ treatment affects GST-specific cytokine responses . The aim of this study was to address two previously un-addressed hypotheses regarding cellular cytokine responses to purified GST in an S . haematobium-endemic community: firstly that these responses vary with age ( and by proxy , exposure to infection [34] ) , and secondly that they are boosted by PZQ treatment . Importantly , we have made use of statistical approaches that integrate data on multiple cross-regulatory cytokines associated with relevant cellular immune phenotypes ( innate inflammatory , Th1 , Th2 , Th17 and regulatory responses ) so that our analysis considers not only the dynamics of individual GST-specific cytokines , but also their patterns of production relative to one another .
Ethical approval was granted by the Medical Research Council of Zimbabwe and the University of Zimbabwe's Institutional Review Board . Local permission for the study was granted by the Provincial Medical Director of Mashonaland East . All prospective participants were informed of the study aims and procedures in their local language ( Shona ) . All adult participants provided informed written consent and children were recruited only if informed written consent was provided by a parent or guardian . The current study is part of on-going schistosome immuno-epidemiological research in Murehwa District , Mashonaland East province , Zimbabwe where S . haematobium is endemic [36]–[38] . Pre-studies in the area showed that S . mansoni and soil-transmitted helminth ( STH ) prevalence is low ( <2% ) and the region is classified as a low transmission area for Plasmodium spp . [39] . The study area had not been included in previous PZQ treatment programs . Baseline recruitment of participants was school-based but pre-school age children and adults were also informed of the study and invited to attend via community meetings prior to the commencement of baseline sampling . The following samples were collected from all recruited participants ( n = 284 ) ; 1 ) a minimum of 2 urine samples collected over 3 consecutive days for quantification of S . haematobium infection intensity , 2 ) a minimum of 2 stool samples collected over 3 consecutive days for quantification of soil-transmitted helminth ( STH ) and S . mansoni infections , and 3 ) 10 ml venous blood . Participants also completed a questionnaire to assess residential history , patterns of exposure to schistosome infective water and anti-helminthic drug treatment history . Participants were excluded from the study if: they did not provide samples 1–3 ( n = 5 ) , they provided insufficient blood volume for stimulation with GST and a control culture without antigen ( n = 13 ) or quantification of all cytokines ( n = 25 ) , they indicated in their questionnaire responses that they were not life-long permanent residents of the study area ( n = 23 ) , or they were positive for STH ( n = 0 ) , S . mansoni ( n = 5 ) , HIV ( n = 18 ) or Plasmodium spp . infection ( n = 0 ) . After baseline sampling all compliant participants were treated with a single dose of PZQ ( 40 mg/kg body weight ) and sampling was repeated 6 weeks post-treatment . For inclusion in the post-treatment cohort participants were required to provide a full set of samples 1–3 and remain negative for all co-infections 6 weeks post-treatment ( n = 126 ) . Ten eligible participants refused PZQ treatment for religious reasons and 9 eligible participants remained positive for S . haematobium infection following treatment , these participants were excluded from the post-treatment cohort . Based on these criteria , a total of 195 participants were included in the baseline cohort and , of these , 107 participants made up the post-treatment cohort . Re-infection was assessed at 6 and 18 months post-treatment in participants who provided samples 1 and 2 at these timepoints ( n = 75 ) . High community-wide prevalence and infection intensity at baseline precluded inclusion of an untreated control group according to WHO treatment guidelines [40] . Stool and urine samples were collected and processed following the standard microscopic procedures ( Kato Katz for stool and urine filtration methods for urine ) [41] , [42] . Infection intensity was expressed as the mean egg count per 10 ml urine for S . haematobium calculated from a minimum of 2 samples/participant before treatment , and 6 weeks , 6 months and 18 months post-treatment . Plasmodium spp . and HIV infection were identified serologically as previously described [10] . Recombinant 28 KDa GST of a Senegalese strain of S . haematobium was cloned and purified using previously described protocols [43] . GST preparations were confirmed to be endotoxin free ( <0 . 015 EU/ml ) using the Limulus amebocyte lysate assay ( Sigma-Aldrich , Lyon , France ) . Venous blood samples were collected from study participants into EDTA-coated tubes and cultured at a 1∶3 dilution with media ( RPMI 1640 supplemented with 2 mM L-glutamine and 100 U Penicillin/Streptomycin ( all Lonza , Verviers , Belgium ) ) in duplicate wells coated with either 2 µg/ml GST or without antigen ( i . e . culture media alone ) for 48 hours at 37°C in Anaerogen Compact anaerobic atmosphere generation pouches ( OXOID , Basingstoke , U . K . ) . Cell-free culture supernatants were frozen and assayed within 12 months . Interferon ( IFN ) γ , Tumour necrosis factor ( TNF ) α , Interleukin ( IL ) -2 , IL-4 , IL-5 , IL-6 , IL-8 , IL-10 , IL-12p70 , IL-13 and IL-21 ( BD Biosciences , Oxford , U . K . ) , IL-17A and IL23p19 ( eBiosciences Ltd . , Hatfield , U . K . ) were assayed in culture supernatants via enzyme-linked immunosorbent assay ( ELISA ) using published protocols [10] . S . haematobium infection intensity exhibited a negatively skewed distribution within the study cohort as is typical of schistosome infection in endemic populations [44] . Infection intensity was therefore log10 ( x+1 ) transformed and compared for infected participants by gender ( male and female ) and age group ( 4–9 , 10–12 and 13+ years ) via ANOVA ( adjusted sums of squares ) . Post-hoc pairwise comparisons between the 3 age groups were made using Fisher's least significant difference test . Cytokine levels present in culture supernatants were not normally distributed even following transformation , therefore all comparisons of cytokine levels were conducted using non-parametric statistical tests . Cytokine levels in GST-stimulated cultures were compared to those present in parallel cultures without antigen from the same individuals via the paired Wilcoxon test . Cytokine levels present in un-stimulated culture supernatants were then subtracted from those present in GST-stimulated cultures to give GST-specific cytokine levels . Where an individual did not produce a cytokine at levels above those in their parallel un-stimulated culture they were assigned a value of 0 pg/ml for that cytokine . The percentage of GST-specific cytokine producers ( i . e . levels above those in un-stimulated cultures ) was compared by gender , age group and S . haematobium infection status via Pearson's Chi-squared test . Comparisons between the percentage of GST-specific cytokine producers pre- and 6 weeks post-treatment were made using the paired McNemar's test . To confirm that treatment-related differences in cytokine responses were not due to sampling bias in the smaller post-treatment cohort , baseline GST-specific cytokine levels were compared between participants included in post-treatment follow up analyses and those that were not included using the Mann Whitney U test ( p>0 . 05 for all 13 cytokine responses; data not shown ) . GST-specific cytokine responses were reduced into a smaller number of variables ( principal components , PCs ) according to their shared patterns of expression via factor analysis as previously reported [10] . Due to the skewed nature of GST-specific cytokine responses ( i . e . few producers for some cytokines and a non-normal distribution of cytokine levels ) values were log10 ( x+1 ) transformed to minimise the influence of outlier values [45] and only GST-specific cytokines that were detectable in >30% of participants were included in the factor analyses . Dynamics of cytokines with a factor loading ≥0 . 5 or ≤−0 . 5 onto a PC were considered to be reflected by that PC . Separate factor analyses were conducted for baseline ( Table S1 ) and 6 weeks post-treatment cytokine responses ( Table S2 ) . PC regression factor scores at each timepoint were compared by gender , age group and S . haematobium infection status via ANOVA . Sequential sums of squares were used to account for demographic variation ( gender and age group ) before infection status . To characterise changes in the distribution of GST-specific cytokine responses for each participant 6 weeks after treatment relative to pre-treatment levels non-metric multidimensional scaling ( NMS ) was used to provide a visual representation of similarity/dissimilarity between participant responses . NMS was conducted as described previously [10] , [46] and the non-parametric multiple response permutation procedure ( MRPP ) was used to statistically compare pre- and post-treatment cytokine profiles . Pearson's correlation analysis was used to determine the amount of variation between participant NMS scores that were attributable to each spatial axis . Non-parametric Kendall correlations analysis was used to identify associations between NMS spatial axes and the original concentrations of the 13 individual cytokines . A cytokine was considered to be reflected by the spatial axis if Kendall's tau ( τ ) ≥0 . 4 . Statistical tests were conducted using SPSS Statistics version 19 software ( IBM , Hampshire , U . K . ) and NMS was implemented using PC-ORD software ( MJM Software Design , Gleneden Beach , U . S . A . ) [46] . Comparisons were considered to be significant at p<0 . 05 . Where >10 comparisons were made the p-value was adjusted for multiple comparisons via the sequential Bonferroni correction and comparisons that were significant post-correction were considered highly significant .
The baseline study cohort consisted of 94 males and 101 females ranging in age from 4–84 years . Baseline S . haematobium infection prevalence was 52 . 3% . A higher percentage of men ( 58 . 5% ) than women ( 46 . 5% ) were S . haematobium positive at baseline , and of the infected individuals men had a significantly higher mean infection intensity than women ( Figure 1A; F1 , 96: 6 . 56 , p = 0 . 012 ) . S . haematobium infection intensity also showed a non-linear relationship with age ( Figure 1B: F2 , 96: 4 . 00 , p = 0 . 021 ) as is typical of schistosome epidemiology [44] , with infection intensity peaking in children aged 10–12 years ( 4–9 vs . 10–12 years: Mean difference: −0 . 385 , p = 0 . 028; 13+ vs . 10–12 years: Mean difference: −0 . 486 , p = 0 . 007 ) . The demographic and S . haematobium infection characteristics of the study cohort are summarised in Table 1 . All cytokines were present at significantly higher levels in GST-stimulated whole blood cultures than in corresponding un-stimulated cultures ( p<0 . 001 for Wilcoxon comparisons of all 13 cytokines; data not shown ) indicating that a specific cytokine response to S . haematobium GST was elicited within the cohort . Only 4 . 6% of participants ( n = 9 ) produced no detectable GST-specific cytokines at levels greater than those present in un-stimulated cultures ( Table 1 ) . Having established that GST elicited a whole blood cytokine response , we next sought to characterise demographic factors that may influence these responses . We first compared the percentage of participants producing GST-specific cytokines and found no difference according to gender or infection status in any of the cytokines measured ( Table 2 ) . However , when compared by age , the youngest age group ( 4–9 years ) was found to have a significantly higher percentage of GST-specific IL-4 ( X2: 14 . 08 , p = 0 . 001 ) and IL-10 ( X2: 8 . 49 , p = 0 . 014 ) producers than either the 10–12 or 13+ year age groups ( Figure S1 , Table 2 ) . In addition to the presence/absence of individual cytokines , the relative levels of different cross-regulatory cytokines could also be an important determinant of the GST-specific immune response . To characterise patterns of GST-specific cytokines , all cytokines produced by >30% of participants ( i . e . IFNγ , TNFα , IL-5 , IL-6 , IL-8 , IL-10 , IL-12p70 , IL-13 , IL-21 and IL23p19 ) , were reduced into PCs according to their shared patterns of expression via factor analysis . This analysis identified 3 key patterns of GST-specific cytokine response accounting for variation between participants; PC1 accounted for the largest amount of variation ( 28 . 5% ) and corresponded to pro-inflammatory cytokine responses ( IFNγ , TNFα , IL-6 , IL-8 , IL-12p70 and IL23p19 ) , PC2 corresponded to a combination of Th2 ( IL-5 and IL-13 ) and regulatory ( IL-10 ) responses and PC3 reflected expression of the neutrophil chemoattractant ( IL-8 ) and was negatively associated with the Th1 cytokine IFNγ ( for factor loadings refer to Table S1 ) . None of these cytokine patterns varied according to participant gender or infection status ( Figure 2; Table 3 ) , however PC2 significantly differed between the 3 age groups ( Figure 2; F2 , 188: 6 . 940 , p = 0 . 001 ) . Pair-wise comparisons between age groups indicated that PC2 scores were significantly lower in 10–12 year olds than in either 4–9 ( Mean difference: −0 . 678 , p = 0 . 002 ) or 13+ year olds ( Mean difference: −0 . 777 , p<0 . 001 ) indicating a lower Th2/regulatory cytokine response to GST in this group . PCs 1 and 3 did not significantly differ between the 3 age groups ( Figure 2; Table 3 ) . Laboratory studies have proposed that co-administration of a GST-based vaccine with PZQ may promote vaccine efficacy [12] , [16] , [17] , therefore we investigated whether naturally-acquired GST-specific cytokine responses are affected by PZQ treatment . Six weeks after a single dose of PZQ there was a significant increase relative to baseline in the percentage of participants producing detectable levels of GST-specific cytokines associated with innate inflammatory ( TNFα , IL-6 and IL-8 ) , Th1 ( IFNγ , IL-2 and IL-12p70 ) , Th2 ( IL-13 ) and Th17 ( IL-23p19 ) immune responses ( Figure S2; Table 4 ) . In addition to an increase in the proportion of individuals producing cytokines in response to GST , we also investigated whether there was a post-treatment shift in combined cytokine responses to GST relative to pre-treatment patterns . The latter is an important addition to our understanding of GST-specific immune responses since post-treatment cytokine phenotype appears to be a determinant of resistance to re-infection both in human population studies [10] , [47] and murine models of schistosomiasis [48] . To visualise this comparison NMS was used to position each participant along two spatial axes according to their levels of all 13 GST-specific cytokines relative to those of all other participants both before and 6 weeks after treatment . Thus participants with similar combinations of GST-specific cytokines are arranged close together and those with dissimilar responses are further apart . The ordination plots of this analysis showed that pre- and post-treatment cytokine responses formed distinct clusters reflecting a shift in the whole blood cytokine responses elicited by GST ( Figure 3 ) and this dissimilarity between pre- and post-treatment cytokine responses was statistically significant ( MRPP; T: −53 . 438 , p<0 . 001 , A: 0 . 062 ) . Kendall's correlation between the original cytokine levels and the NMS spatial axes indicated that the majority of variation in pre- and post-treatment cytokine responses was attributable to the increase in levels of IFNγ ( τ: 0 . 449 ) , TNFα ( τ: 0 . 508 ) , IL-6 ( τ: 0 . 782 ) , IL-8 ( τ: 0 . 544 ) , IL-12p70 ( τ: 0 . 500 ) and IL23p19 ( τ: 0 . 617 ) 6 weeks after treatment ( Axis 2; Pearson's r2: 0 . 492 ) . To a lesser extent pre- and post-treatment cytokine responses also varied along Axis 1 ( Pearson's r2: 0 . 236 ) , which was positively correlated with IL-6 ( τ: 0 . 440 ) and negatively correlated with IL-21 ( τ: −0 . 391 ) . These cytokines are associated with innate inflammatory and effector Th1 and Th17 responses and thus the phenotype of the post-treatment cytokine response to GST is more pro-inflammatory than at baseline . Post-treatment cytokine responses produced in response to GST stimulation by >30% of participants ( i . e . IFNγ , TNFα , IL-2 , IL-5 , IL-6 , IL-8 , IL-10 , IL-12p70 , IL-13 , IL-21 and IL23p19 ) were reduced into post-treatment cytokine profiles via factor analysis ( for factor loadings refer to Table S2 ) . Similar to patterns observed before treatment , the majority of variation ( 32 . 5% ) between post-treatment responses was due to differences in pro-inflammatory cytokine responses ( IFNγ , TNFα , IL-6 , IL-8 , IL-12p70 and IL23p19; PC1 ) . Variation was also evident in a combination of IL-2 , IL-10 , IL-13 and IL-21 levels , reflecting responses associated with Th2 , regulatory and Th17 cells ( PC2; 13 . 2% of variance ) , and a profile that was positively associated with the type 2 effector cytokine IL-5 and negatively associated with the regulatory cytokine IL-10 ( PC3; 10 . 0% of variance ) . Post-treatment PC1 significantly differed according to participant age group ( Figure 4 , Table 3; F2 , 102: 3 . 547 , p = 0 . 032 ) with the youngest participants having significantly higher scores than those in the 10–12 ( Mean difference: 0 . 516 , p = 0 . 049 ) or 13+ age groups ( Mean difference: 0 . 508 , p = 0 . 026 ) . Post-treatment PC2 scores significantly differed according to infection status at baseline and were lower in participants with patent infection at the time of treatment than in their schistosome-negative counterparts ( Figure 4 , Table 3; F1 , 102: 6 . 070 , p = 0 . 015 ) , suggesting that the presence of live parasites at the time of treatment influenced levels of Th2 , Th17 and regulatory type cytokines 6 weeks later . PC3 scores were not significantly affected by participant gender , age group or pre-treatment infection status ( Figure 4 , Table 3 ) . It has been proposed that higher post-treatment schistosome-specific cytokine responses to schistosome antigens promote resistance to re-infection [10] , [31] and we therefore sought to investigate whether GST-specific cytokine responses differed between participants who were re-infected within 18 months of treatment and those who remained un-infected . Only 7 participants within the cohort were re-infected within 18 months of treatment ( 4 males , 3 females , aged 7–13 years ) and we therefore compared their 6 week post-treatment GST-specific cytokine responses to those of 7 un-infected children matched according to age , gender and pre-treatment infection status and intensity ( Table S3; intensity matched by ±57 . 34 eggs , no other age- and gender-matched participants within the post-treatment cohort matched the pre-infection intensity of the re-infected participants ) . Of the 13 cytokines assayed , only post-treatment GST-specific IL-12p70 levels differed significantly between the two groups ( Figure 5; Z: −1 . 992 , p = 0 . 046 , not significant after Bonferroni adjustment for multiple comparisons ) . GST-specific IL-12p70 levels were lower in the re-infected child than in the age- , gender- and pre-treatment infection intensity-matched child that remained uninfected post-treatment in 5 of the 7 pairs , higher in one pair , and the same in one pair of children ( Figure 5 ) .
S . haematobium GST has been extensively characterised as a vaccine candidate antigen for urogenital schistosomiasis in laboratory models and has also advanced further along the vaccine development pathway than any of the other potential anti-schistosome vaccines [3] , [16] , [30] . Despite the efficacy of GST vaccination in animal models [25] , [26] and immunogenicity in clinical trials [30] the phenotype of the cellular immune response to GST in populations endemically exposed to S . haematobium has been largely uncharacterised . The latter is particularly the case for innate inflammatory , regulatory and Th17 associated immune markers due to the relatively recent characterisation of the role played by these immune phenotypes in human schistosomiasis [10] , [49] , [50] . The current study addresses this gap in our understanding of how GST-specific whole blood cytokine responses , including cytokines associated with innate inflammatory ( TNFα , IL-6 and IL-8 ) , Th1 ( IFNγ , IL-2 and IL-12p70 ) , Th2 ( IL-4 , IL-5 and IL-13 ) , Th17 ( IL-17A , IL-21 and IL-17A ) and regulatory ( IL-10 ) immune phenotypes , are distributed both before and after PZQ treatment in an S . haematobium-endemic community . High intensity schistosome infections tend to be aggregated in school-age children and are comparatively lower in adults indicating that the relationship between infection intensity , exposure history and infection-related immune responses change with age [34] . However , the only study that has quantified cytokine responses to GST in schistosome-exposed humans focused on adults [33] . We therefore investigated a wider range of ages ( 4–84 years ) with the hypothesis that GST-specific cytokine responses would vary between 3 age groups reflecting age-dependent changes in S . haematobium infection distribution; increasing intensity of infection ( 4–9 year olds ) , peaking infection intensity ( 10–12 year olds ) and declining infection intensity ( 13+ year olds ) . Exclusion of co-infected and non-permanent residents of the study area meant that all participants included in this age stratified analysis had experienced life-long exposure to infection and thus their age was considered a proxy for their history of exposure to S . haematobium [34] , [51] . Our results show that whole blood samples from untreated schistosome-exposed participants of all ages produce detectable cytokine responses to GST stimulation , which is consistent with observations that immune responses to GST develop naturally in both resistant and susceptible individuals [27] , [33] , [52] and are evident from a young age [52] . In contrast , whole blood samples from schistosome and GST naïve people do not produce detectable levels of cytokines in responses to stimulation with GST in vitro [30] . We also demonstrate that participant age contributes to variation in GST-specific cytokine responses in a schistosome-endemic context by affecting both the capacity to produce different types of GST-specific cytokines and patterns of co-produced cytokines . The highest percentage of GST-specific IL-4 , a Th2-associated cytokine , and IL-10 , a regulatory cytokine , producers was in the youngest age group ( 4–9 years ) , which may reflect the more regulatory schistosome-specific immune profile of individuals with a short history of schistosome exposure . For example , at younger ages , the proportion of circulating T regulatory cells ( Treg ) is more positively associated with S . haematobium infection intensity than in older age groups ( 14+ years ) in whom this relationship is negatively correlated [49] . We also found that a combined phenotype of Th2 ( IL-5 and IL-13 ) and regulatory ( IL-10 ) cytokine responses to GST ( PC2 ) was lowest in children aged 10–12 years in whom infection intensity and prevalence are peaking , suggesting that this may be a particularly dynamic period in terms of GST exposure and development of GST-specific cellular immune responses . Taken together these observations indicate that the Th2-type responses most associated with protective immunity in previous studies ( i . e . IL-4 and IL-5 [30] , [31] ) are also the most age-dependent . Therefore , GST-based vaccine efficiency should be assessed across a range of ages during trials in schistosome-exposed populations in order to generate accurate predictions of population efficacy . An important area for future research will be to identify GST-specific cytokine-producing cell types within the whole blood milieu and determine whether these cells are influenced by host age and schistosome infection intensity . Interestingly neither GST-specific whole blood cytokine production nor phenotype differed according to gender despite evidence of a gender bias in both neutralising antibody and PBMC cytokine responses identified in previous studies in adults endemically exposed to S . haematobium [33] and S . mansoni [27] . At baseline , cytokine responses also did not differ between individuals without infection and those with S . haematobium infection who might be expected to have stronger cytokine responses to GST due to on-going exposure to live adult worms . We also found no significant correlation between pre-treatment GST-specific cytokine profiles ( PCs 1–3 ) and S . haematobium infection intensity ( data not shown ) . The absence of an infection-related difference in GST-specific cytokines may be due to the fact that many abundant somatic antigens ( including GST ) are sequestered from the immune system by live schistosome worms [9] , [11] , [52] . Therefore , recall responses of whole blood cells to GST stimulation in vitro may be more closely related to a person's history of exposure to dying worms than to the presence or absence of live worms in the bloodstream [11] , as described for age-related patterns of GST-specific cytokine responses above . It is also possible that exposure of un-infected individuals ( i . e . egg negative urine samples ) to GST-expressing schistosome larvae which do not develop into fecund adult worm pairs is sufficient to elicit similar GST-specific cytokine responses to those of individuals harbouring patent infections ( i . e . egg positive urine samples ) [53] . Given that PZQ treatment results in a specific increase in the intensity of GST recognition by serum antibodies [9] in addition to a generalised increase in immune responsiveness to whole adult schistosome homogenates [10] , we were interested to see whether GST-specific cytokine profiles changed post-treatment . Six weeks after treatment we observed a dramatic increase in the percentage of participants producing detectable GST-specific levels of all innate inflammatory ( TNFα , IL-6 and IL-8 ) and Th1-associated ( IFNγ , IL-2 and IL-12p70 ) cytokines , as well as the effector Th2-associated cytokine IL-13 and the Th17-associated cytokine IL-23p19 ( i . e . cytokines associated with pro-inflammatory and effector immune responses ) . Reflecting this boost in pro-inflammatory cytokine responses after treatment , a clear shift was evident in the combined pattern of GST-specific responses after PZQ treatment relative to baseline . The NMS analysis used to show this pattern was particularly informative since it incorporated all 13 GST-specific cytokines for each individual into a single analysis [46] and thus avoided focusing on variation in individual cytokines which are inherently cross-regulatory and therefore non-independent [54] . NMS has the added benefit of being based on relative differences in cytokine responses ( i . e . each NMS score is based on levels of all 13 cytokines ranked relative to those of the rest of the cohort [46] ) rather than quantitative differences between individuals and thus the analysis is not biased towards abundant cytokines which are not necessarily more bioactive than those present at low concentrations ( e . g . cytokine bioactivity is dependent on cytokine receptor expression in addition to cytokine concentration [54] ) . Ours is the first study to show that GST-specific cytokine responses are boosted by PZQ treatment but our observations are consistent with previous observations in the same Zimbabwean community that PZQ treatment leads to an increase in pro-inflammatory cytokine responses to antigens from whole S . haematobium cercariae and eggs , which both express GST [10] . Both the intensity of GST recognition and the range of GST isoforms bound by serum antibodies are also enhanced in PZQ-treated inhabitants of schistosome-endemic areas relative to that observed before treatment [9] , supporting our observations of a boost in cellular responsiveness specifically to GST after treatment . Increased levels of schistosome-specific cytokines have also been observed following treatment of S . mansoni-exposed populations , although cytokines associated with innate inflammatory and Th17 responses were not assayed in these studies [8] , [13] . Following treatment , the 4–9 years age group had the highest scores for pro-inflammatory cytokine profiles relative to the older age groups . Thus , children with the least exposure to schistosome infection and the most regulatory responses to crude schistosome antigens prior to treatment [49] experience the most prominent boost in pro-inflammatory cytokine responses to GST post-treatment . A more pronounced post-treatment increase in children relative to adults has previously been observed for antibody responsiveness to schistosome antigens [55] . PZQ treatment also resulted in schistosome infection-related differences in post-treatment GST-specific Th2-/Th17-/regulatory-type cytokine responses , which were lower in participants with patent infection at the time of treatment than in their un-infected counterparts . The difference between infected and uninfected participant cytokine responses after , but not before treatment , likely reflects the pronounced increase in GST exposure resulting from a PZQ-mediated adult worm death in infected but not uninfected individuals [9] , [11] . For example , the relative shift away from a Th2/Th17/regulatory profile following treatment of infected but not uninfected participants may result from a rapid decline in Th2 cells and immunosuppressive mechanisms following removal of live parasites , as described in previous studies [50] , [55] . Few participants were re-infected within 18 months of treatment ( n = 7 ) , however we observed that GST-specific IL-12p70 responses were lower in these re-infected children than in their gender , age and pre-treatment infection intensity-matched counterparts who remained uninfected . Although the number of participants included in this analysis is too low to draw firm conclusions on the influence of GST-specific cytokine responses on re-infection rates , this pattern is consistent with our previous observations in the same community that lower pro-inflammatory whole blood cytokine responses to S . haematobium egg antigens are associated with a higher risk of re-infection [10] . Assaying GST-specific cytokine responses over a longer period after PZQ treatment or in communities experiencing more intense re-infection rates are required to identify whether GST-specific cytokine responses contribute to schistosome re-infection risk . Collectively this study offers the first comprehensive characterisation of the distribution of GST-specific cytokine responses at a population level in humans naturally exposed to schistosome infection . Our results indicate that GST-specific cytokine profiles are influenced by participant age and PZQ treatment and post-treatment cytokine responses to GST are also influenced by pre-treatment infection intensity . Thus these factors may influence cellular responses to a GST vaccine formulation and should be taken into consideration in future immunogenicity and efficacy trials .
|
Schistosomiasis is caused by infection with Schistosoma spp . parasites , for which the main treatment is the drug praziquantel ( PZQ ) . Since PZQ does not prevent reinfection , an anti-schistosome vaccine based on the Schistosoma haematobium enzyme glutathione-S-transferase ( GST ) is being developed . In this study we investigated the GST-specific immune responses of people naturally exposed to schistosomes and the affect that PZQ has on these responses . We cultured blood samples from a schistosome-exposed community with GST before and six weeks after PZQ treatment and measured a range of soluble proteins ( cytokines ) in culture supernatants as indicators of blood cell activation and phenotype . Before treatment , GST-specific cytokine responses varied with host age , particularly in children with high intensity schistosome infections . Following treatment , GST activated blood samples from more individuals to produce a broader range of cytokines and the combination of GST-specific cytokine responses reflected a more pro-inflammatory immune phenotype than that observed pre-treatment . Post-treatment responses varied according to host age and pre-treatment infection status . Taken together , our study suggests that current and future GST-based vaccine trials should take host age , schistosome infection status and PZQ treatment history into account since these factors influence GST-specific immune activation .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"helminth",
"infections",
"infectious",
"diseases",
"schistosomiasis",
"medicine",
"and",
"health",
"sciences",
"neglected",
"tropical",
"diseases",
"tropical",
"diseases",
"parasitic",
"diseases"
] |
2014
|
Cytokine Responses to the Anti-schistosome Vaccine Candidate Antigen Glutathione-S-transferase Vary with Host Age and Are Boosted by Praziquantel Treatment
|
Adeno-associated virus type 2 ( AAV ) is known to establish latency by preferential integration in human chromosome 19q13 . 42 . The AAV non-structural protein Rep appears to target a site called AAVS1 by simultaneously binding to Rep-binding sites ( RBS ) present on the AAV genome and within AAVS1 . In the absence of Rep , as is the case with AAV vectors , chromosomal integration is rare and random . For a genome-wide survey of wildtype AAV integration a linker-selection-mediated ( LSM ) -PCR strategy was designed to retrieve AAV-chromosomal junctions . DNA sequence determination revealed wildtype AAV integration sites scattered over the entire human genome . The bioinformatic analysis of these integration sites compared to those of rep-deficient AAV vectors revealed a highly significant overrepresentation of integration events near to consensus RBS . Integration hotspots included AAVS1 with 10% of total events . Novel hotspots near consensus RBS were identified on chromosome 5p13 . 3 denoted AAVS2 and on chromsome 3p24 . 3 denoted AAVS3 . AAVS2 displayed seven independent junctions clustered within only 14 bp of a consensus RBS which proved to bind Rep in vitro similar to the RBS in AAVS3 . Expression of Rep in the presence of rep-deficient AAV vectors shifted targeting preferences from random integration back to the neighbourhood of consensus RBS at hotspots and numerous additional sites in the human genome . In summary , targeted AAV integration is not as specific for AAVS1 as previously assumed . Rather , Rep targets AAV to integrate into open chromatin regions in the reach of various , consensus RBS homologues in the human genome .
The family of adeno-associated virus ( AAV ) represents defective , helper-dependent viruses that need to establish latency to ensure persistence in their primate hosts [1] . Upon natural infections in humans AAV genomes were shown to persist mainly as episomes and integrated AAV genomes were rarely detected [2] . The molecular mechanisms leading to integration have only been characterized for AAV type 2 that prefers integration near a site on human chromosome 19q13 . 42 , called AAVS1 [3] . The specificity of AAV integration is mediated by the large regulatory AAV proteins , Rep78/68 [4] . During productive AAV replication in the presence of either adeno- or herpesvirus as a helper virus , Rep78/68 is required for AAV gene expression and DNA replication . The AAV origins of DNA replication reside in the 145 bp inverted terminal repeats ( ITRs ) that flank the 4 . 7 kb single-stranded AAV genome . Rep78 and/or Rep68 are expressed from the AAV p5 promoter and were shown to bind to the Rep-binding site ( RBS ) within the AAV-ITRs [5] . Rep unwinds the DNA and introduces a single-strand nick at the adjacent terminal resolution site ( trs ) [6] . The AAV-ITRs also serve as cis elements for chromosomal integration [4] . A RBS homologue present in the AAV p5 promoter was shown to mediate AAV integration in the absence of the ITRs [7] . DNA sequences homologous to the RBS and a nearby trs element were also found in AAVS1 [8] , [9] and , in vitro , ternary complex formation of Rep68 with the AAV-ITR and AAVS1 was shown [10] . A 33 bp sequence of AAVS1 spanning the RBS and the trs element was sufficient to mediate AAV integration in vivo [4] , [11] . AAV integrated at variable distances from the RBS in AAVS1 and sequence rearrangements were frequently found at AAV-chromosome junctions [8] , [9] , [12] , [13] , [14] , [15] . Quantitative real-time PCR analysis of AAVS1-specific AAV-2 integration within hours after AAV-2 infection and at increasing MOIs showed that 10 to 20% of infected cells displayed AAV integration within a 4 kb region of AAVS1 on chromosome 19q13 . 42 [16] , [17] . In AAV-infected and subsequently selected cell clones up to 80% of AAVS1-specific integration had been described before [18] . Although AAV has not been associated with disease in humans , it is well established that AAV Rep78/68 induces DNA damage , cell cycle arrest [19] and apoptosis [20] . In addition , AAV Rep interferes with helper adenovirus- [21] herpes simplex virus replication [22] . AAV holds much promise as a vector for gene therapy . As a rule , recombinant AAV vectors persist as non-integrated , nuclear episomes . AAV vectors lack the integration promoting rep gene and therefore only occasionally integrate into the host cell genome . The preferred integration of wildtype AAV-2 in chromosome 19q13 . 42 is unique and is commonly viewed as a specifically evolved virus-encoded targeting mechanism . Multiple attempts were published that aim to exploit Rep-mediated targeting specificity for chromosome 19q13 . 42 for the specific integration of gene therapy vectors [23] , [24] , [25] , [26] , [27] , [28] . Yet chromosome 19q13 . 42 is not the only target region . The presence of alternative integration sites has long been postulated and in silico analysis detected numerous consensus Rep-binding sites in the human genome . Many of these bound Rep in vitro [29] but their in vivo accessibility for AAV integration has not been explored so far . From an evolutionary standpoint the assumption that AAV latency is ensured by more than one target site or mechanism appeared reasonable . This study was designed to close the knowledge gap between AAVS1-specific and assumedly non-AAVS1-specific wildtype AAV integration and to compare the identified genomic sites to those preferred upon AAV vector transduction . An open survey of chromosomal integration preferences for wildtype AAV-2 was conducted and complemented by the bioinformatic analysis of genomic motifs and patterns in the genomic regions surrounding the integration loci .
The genomic structure of latent AAV in infected cells is highly variable . Wildtype AAV-2 was shown to integrate into the host cell genome , as well as persist as extrachromosomal , nuclear episomes [2] , [30] . In either case multicopy , concatemeric structures predominate and often lead to unpredictable rearrangements involving the 145 bp inverted terminal repeats ( ITRs ) . Therefore the retrieval of AAV-chromosome junctions suffers from the inherent problem of inefficient PCR reads through the hairpin ITR into the adjacent chromosomal sequences . This leads to a predominance of rearranged AAV genomes lacking chromosomal junctions in previous PCR-based studies [31] , [32] , [33] . Furthermore , previously cloned junctions often displayed unknown intervening sequences of varying lengths between AAV and the identified chromosomal sequence [12] , [15] , [16] , [27] , [34] , [35] , [36] . Therefore , unambiguous assignment of the AAV-derived and chromosome-derived parts of junctions requires sufficient DNA sequence lengths . Several methods to identify virus-chromosome junctions have been developed to study retrovirus integration , where generally a single proviral copy per chromosomal site is found [37] , [38] . The ultimate structure of the integrated long terminal repeat ( LTR ) is generally predictable in a way that allows an integration-specific PCR design . Linear amplification mediated ( LAM ) -PCR was initially designed to retrieve rare retroviral vector integration sites from small , clinical sample sizes [38] . We established a LAM-PCR with AAV primers in the “D” element of the AAV-ITR , the innermost and sole ITR region without internal inverse repetitions ( Figure 1A ) . Unfortunately , pure AAV sequences with rearranged ITRs predominated , AAV-chromosome junctions were rare and the chromosomal DNA part often too short for unambiguous assignment to a unique genomic site . We then tested ligation-mediated ( LM ) -PCR that had been employed for broad surveys of lentivirus ( HIV ) or γ-retrovirus ( MLV ) integrations [39] , [40] , [41] . LM-PCR relies on a first LTR-specific primer . A linker is ligated to the first PCR strand that typically ends at the chosen restriction site within the unknown chromosomal sequence . A primer complementary to this linker ensures second strand synthesis and retrovirus-chromosome junctions are amplified by using a combination of retrovirus LTR-specific and linker-specific primer sets . For this study a variation of LM-PCR , named linker-selection-mediated ( LSM ) -PCR was developed which enriched for bona fide AAV-chromosome fusion sequences . The genomic DNA of AAV-infected cells was cleaved with restriction enzymes that lead to sufficiently sized DNA segments to allow unambiguous genomic assignment of the chromosomal junction ( Figure 1B ) . DNA sequences were amplified with one primer for a unique AAV-sequence , either of the p5 promoter or of the cap gene . The other primer binds to the linker DNA attached to the unknown chromosomal site . The structure of the linkers forces the PCR to initiate within the AAV genome , thereby suppressing amplification of chromosomal DNAs lacking integrated AAV . The use of non-cut enzymes for AAV-2 DNA helped to circumvent the problem of ligating linkers to episomal , non-integrated AAV DNA sequences . To further enrich for AAV-chromosome junctions a biotin tag was attached to the 5′-end of the linker primer . Thus , chromosome-derived PCR products could be enriched by streptavidin-mediated magnetic bead selection . This lead to PCR products selected for both , the presence of AAV and of an unknown chromosomal DNA sequence . Using LSM-PCR a total of 1700 cloned PCR fragments were screened for DNA inserts of a minimal fragment size ( >500 bp ) to insure unambiguous detection of AAV-chromosome junctions . Out of 350 DNA sequence runs a total of 129 unique junction sites could be assigned to the human genome . Of these , 109 fulfilled the criteria outlined in the methods for unambiguous assignment of a single chromosomal site . Junctions were retrieved with non-cut enzymes for AAV-2 , PvuII or EcoRV or with DraI , which cuts once in AAV-2 DNA outside of the region covered by the PCR . In addition , 43 wildtype AAV-2 infected Hela-derived single cell clones were generated of which eight harboured AAV-chromosome junctions that fulfilled the criteria outlined in the methods . DNA sequence analysis revealed that AAV-2 wildtype integration sites were scattered over the entire human genome . The chromosomal distribution pattern is displayed in Figure 2A . Over one third of AAV integration sites were clustered at hotspots on chr . 19q13 . 42 , on chr . 5p13 . 3 and on chr . 3p24 . 3 ( Figure 2B–D ) . Infection with AAV in the absence of a helper virus leads to transient , low Rep expression . Many previous AAV integration studies used plasmid transfections of wildtype or vector AAV constructs often in combination with a high-level Rep expression construct . To evaluate whether high Rep expression influenced the target site preference of AAV , the sequence data of previously published transfection-based AAV integration sites [42] were reevaluated with the more stringent criteria outlined in the method . Of 157 DNA sequences retrieved after cotransfection of a rep-expression construct and an AAV vector plasmid 47 junction sequences fulfilled our criteria for unambiguous assignment of AAV to a unique chromosomal site ( Table 1 ) . For AAV wildtype 10% of all retrieved junctions were detected at the hotspot on chr . 19q13 . 42 spread over a total of 33 kb around AAVS1 ( Figure 2B ) . Only one out of twelve chr . 19q13 . 42-specific AAV junctions was located within the 4 kb region of AAVS1 , where a consensus Rep-binding site and an adjacent trs site had been defined [4] The reevaluated distribution pattern of junctions generated by transfection of AAV vector- and Rep expression plasmids [42] was similar ( Figure 2B ) . Latently AAV-infected Detroit 6 cells [43] , [44] were analyzed as control . Using cap-specific primers the junction was detected within AAVS1 at nucleotide position 60 , 319 , 992 . A second hotspot named AAVS2 was detected on the small arm of chr . 5p13 . 3 within an intergenic region , where ten independent integration sites were detected within 8 kb ( Figure 2C ) . In seven of these junctions clustered within 14 bp AAV had integrated directly into a consensus Rep binding site . The reanalyzed chromosomal integrations from AAV plasmid transfection [42] displayed a similar pattern with six integrations within 16 bp of the consensus RBS ( Figure 2C ) . The third hotspot named AAVS3 was found on chr . 3p24 . 3 ( Figure 2D ) . Out of 13 sites detected on chr . 3 , three integrations were clustered in a 8 kb region where a consensus Rep binding site GAGT GAGT GAGT GAGC GAGC was detected on the complement strand ( Figure 2D ) . To evaluate the binding affinities of Rep to the consensus RBS of the hotspots on chr . 5 and chr . 3 compared to the RBS of chr . 19 or within the AAV genome , double-stranded oligonucleotides spanning the respective RBS regions ( Figure 3 ) were submitted to mobility shift assays ( EMSA ) with increasing amounts of purified MBP-Rep78 . Since it was previously shown that GAGG repeats are deficient in binding to Rep [10] , [45] , a mutated oligo derived from the RBS of AAVS2 displaying GAGG GAGG GAGC GAGG was used as a control . As an additional control , a random oligonucleotide of similar length was used . As shown in figure 4 , the RBS of AAVS3 contained five instead of four GAGY repeats and bound Rep with a two-fold higher affinity than the oligonucleotide spanning the AAVS1 RBS and trs ( Figure 4B ) . The RBS of AAVS2 showed 76% of the Rep-binding affinity of the AAVS1 sequence ( Figure 4C ) . In contrast , the relative binding affinity normalized to the AAVS1 sequence dropped to 13% with the mutated AAVS2 oligonucleotide , which was in the range of the random oligonucleotide ( Figure 4C ) . These findings confirm the importance of the GAGY repeats in Rep binding . As expected , Rep78 displayed the highest affinities for oligonucleotides spanning the A-stem of the AAV-ITR or the AAV p5–promoter ( Figure 4A , 4D ) . In summary , the newly discovered hotspots for AAV integration , AAVS2 on chr . 5 and AAVS3 on chr . 3 display RBS similarly proficient for Rep-binding as AAVS1 . To evaluate whether AAV-2 wildtype prefers specific motifs or genomic features for chromosomal integration the detected chromosomal junctions were compared to integration sites described for infection of human cells with a rep-deleted AAV-2 based vector [46] . The published DNA sequence files were reanalyzed using the criteria as outlined in the methods . This led to 450 junctions that could be included as an AAV vector-specific data set ( Table 1 ) . The preference for integration next to selected genomic features was analyzed for rep-positive AAV wildtype and for rep-deficient AAV vectors ( Table 2 ) . The data showed that the integration frequency of AAV wildtype in genes was higher than expected by chance ( Table 2 ) . The frequency was comparable to that of rep-deficient AAV vectors , thus confirming the findings by Miller et al . [46] . To analyze the effect of epigenetic modifications on AAV integration the association of integration sites with histone modifications as markers for open or closed chromatin were assessed by chromatin immunoprecipitation sequencing ( ChIP-Seq ) analysis as outlined in the methods . Trimethylated lysine 27 of histone 3 ( H3K27me3 ) is correlated with gene repression ( closed chromatin ) [47] , while methylation of lysine 4 in H3K4me3 and H3K4me1 is indicative of promoter or enhancer regions ( open chromatin ) [48] . As shown in table 2 the association of AAV wildtype with open chromatin regions is significantly higher than expected from random controls . Conversely , the respective association with closed chromatin is significantly reduced . In summary , AAV wildtype prefers integration into open chromatin whereas closed chromatin was avoided . A series of publications have shown that fused combinations of two to four GAGC motifs bind to Rep78/68 of AAV-2 [4] , [49] , [50] , [51] , [52] , [53] . Moreover , in vitro ternary complex formation of Rep68 with the AAV-2 ITR and AAVS1 of chr . 19q13 . 42 [10] led to the concept of Rep acting as an adapter that targets AAV to the human genome . Although only AAV-2 has been analyzed for chromosomal integration so far , all known AAV serotypes displayed various combinations of GAGC and/or GAGT motifs in the ITR and the p5 promoter . An alignment of these AAV elements to the integration hotspots AAVS1 , AAVS2 and AAVS3 is displayed in Figure 3 . Based on these data we hypothesized that AAV-2 wildtype , due to the presence of Rep , prefers integration at chromosomal sites in closer proximity to consensus Rep binding sites than would be expected from control sites . The hypothesis was tested with the three sets of junctions derived from: 1 . Infection with AAV-2 wildtype , 2 . Cotransfection of plasmids coding for an AAV vector and a constitutive Rep-expression cassette , and 3 . Infection with Rep-deficient AAV vectors ( Table 1 ) . The distances between any one integration site and its nearest Rep-binding site were determined in the human genome and compared to similarly determined distances of individual control sites to the nearest Rep-binding sites . Calculations were repeated using various combinations of RBS as displayed in Figure 5 . The choice of randomly generated genomic control sites was considered optimal for comparative analysis of the three sets of data . Yet , a concern was the choice of restriction endonucleases for the identification of the wildtype AAV-2 integration sites by LSM-PCR . To control a bias introduced by a conceivable non-random genomic distribution of the restriction sites , the average distance of PvuII , EcoRV , or DraI-generated restriction sites to putative Rep-binding sites was compared to the average distances of random sites to Rep-binding sites . PvuII restriction sites were found to be closer to Rep-binding sites than random control sites ( Figure S1 ) . This was assumedly due to the high G+C content of the PvuII recognition sequence and of the consensus Rep-binding sites . Both EcoRV and DraI sites were found further apart from Rep-binding sites in accordance with their high A+T content ( Figure S1 ) . To circumvent any bias arising from the use of PvuII , the data set for AAV wildtype infection was calculated against the data set of random control sites as well as against the data sets for the restriction site–related controls . Since not more than two thirds of sites were generated with PvuII , the PvuII-related control sites would at most underestimate the association to Rep-binding sites and was therefore used as the most stringent control set . In addition all calculations were also performed with the set of random controls leading to similar findings ( Figure S2 ) . The bioinformatic calculations with GAGC GAGC as a minimal Rep-binding site strikingly confirmed our hypothesis that integration of wildtype AAV takes place close to Rep-binding sites with very high significance ( p <0 . 0001 ) . A comparable effect was seen with the data set for AAV vectors in the presence of Rep ( p<0 . 001 ) . Most importantly , the set of integration sites for AAV vectors in the absence of Rep did not show any difference of integration site preference compared to random control sites ( Figure 5A ) . With a frequency of 15 , 707 sites per human genome the Rep binding motif GAGC GAGC occurs sufficiently frequent to lead to a mean distance of around 50 kb to the next AAV integration site in the presence of Rep . In the absence of Rep the mean distance to AAV ( vector ) integration sites rises to around 130 kb ( Figure 5A ) . To ensure that the presence of repetitive DNA in the random controls did not lead to a bias in the analysis , an independent control calculation was performed for AAV wt data using AAV vector infection data as background . The high significance level was maintained ( data not shown ) . The significance of the Rep-associated preferential integration near GAGC GAGC sequences was further underlined by the results of similar calculations for the putative Rep-binding motif GAGT GAGC , where no such association was found . Only in the presence of presumably large amounts of Rep ( AAV vector transfection , Rep+++ ) a small effect was seen ( Figure 5B ) . Obviously the GAGT GAGC motif is not sufficient to attract Rep and the AAV genome for integration . When an additional GAGC repeat is added ( GAGY GAGC GAGC ) the integration preferences of AAV wildtype and Rep-expressing AAV vectors shifted to closer proximity to Rep-binding sites ( p<0 . 0001 ) . This is especially surprising since only 616 sites per human genome are found for GAGY GAGC GAGC ( Figure 5C ) . To allow more potential Rep-binding site permutations , calculations were repeated with the consensus GAGC GAGC GAGC with one or two random mismatches . This led to a significantly decreased mean distance to AAV junctions in spite of the fact that up to 100-fold more genomic hits were found for the motifs ( Figure 5D; E ) . A single nucleotide exchange in the GAGY GAGC GAGC motif ( Figure 5F , GAGY GAGC GAGA ) on the other hand led to a complete loss of association to AAV integration sites . This is surprising in view of the reported in vitro binding of Rep to this motif [45] and supports the assumption that the C at the 3′ end of the Rep binding motif is relevant for Rep-binding in vivo . Motifs GCCC GAGT GAGC and GAGT GAGC ACGC are part of the RBS in the viral p5 promoter . The individual motifs are found at very low frequency ( n = 85 , or n = 82 , respectively ) in the human genome , so that either no RBS was found in the same contig or the distance to the next RBS was more than several thousands kb . For these reasons we did not proceed with calculations for these motifs . To further exclude the possibility that the calculated associations with Rep binding sites were predominantly based on sequences assigned to the hotspots AAVS1 and AAVS2 , the significance of the associations was re-evaluated with data sets omitted for the hotspot sequences ( Table 3 ) . The robustness of the data becomes evident by the fact that the highly significant association of AAV junctions to motifs GAGC GAGC and GAGY GAGC GAGC is maintained . In summary , AAV prefers integration sites in the vicinity of consensus Rep-binding elements , most prominently on chr . 19q13 . 42 ( AAVS1 ) , chr . 5p13 . 3 ( AAVS2 ) , and chr . 3p24 . 3 ( AAVS3 ) . But even in the absence of hotspots AAV still shows a highly significant integration preference for Rep-binding motifs at numerous additional sites in the human genome .
At the hotspot on chr . 19q13 . 42 , up to 10% of all AAV junctions were scattered over a region of 33 kb , mostly in centromeric direction with regard to the previously defined core 4 kb AAVS1 site . AAV vectors in the absence of Rep expression do not show any preference for chr . 19q13 . 42 [46] . The here identified , novel hotspot AAVS2 on chr . 5p13 . 3 displayed roughly 8% of all junctions retrieved from wildtype AAV-2 infection and 23% of those retrieved from cotransfection of AAV vectors in the presence of Rep distributed over a region of 14 kb . A cluster of 13 independent junctions was found within 14 bp of the AAVS2 RBS that was shown to be similarly proficient in binding to Rep in vitro as is the RBS of AAVS1 ( Figure 4 ) . The high in vivo integration numbers may in part be due to the choice of HeLa as target cells . These are hypertriploid with up to 12 copies of the p-arm of chr . 5 [54] . The extra gain of integrations within the described 8 kb region is however unique for the AAVS2 site and not accompanied by a parallel increase of integrations at additional sites on the overrepresented p-arm of chr . 5 , where 201 additional GAGC GAGC repeats and three additional GAGY GAGC GAGC repeats were counted . The only fourfold tetranucleotide repeat on the chr . 5 p-arm is found in AAVS2 ( GAGT GAGT GAGC GAGC; Figure 2C ) . In addition , junctions of rep-deficient AAV vector were reported to be underrepresented on chr . 5 [46] . A major difference between the hotspots on chr . 5 and chr . 19 concerns the presence of genes . The junctions identified on chr . 19 span the region of the transcribed gene for protein phosphatase 1 , regulatory subunit 12C ( PPP1R12C ) . The 8 kb AAVS2 sequence identified on chr . 5p13 . 3 represents an intergenic region to the best of current knowledge . It is well known that Rep expression leads to extensive rearrangements of AAVS1 [18] , [55] , [56] . Apparently , PPP1R12C is essential , since the majority of latently infected cell lines display gene duplications [57] and simultaneous AAV integrations in both alleles have never been reported . A currently unresolved question concerns the presence of a terminal resolution site ( trs ) next to the RBS of AAVS2 and AAVS3 . In AAVS1 the spatial configuration of RBS and trs resembles that of the AAV-ITR . The trs element lies next to the RBS and serves as a nicking site for Rep [4] . In AAVS2 and AAVS3 the nearest perfect trs elements ( 5′-GTTGG-3′ ) are 400 and 500 bp away from the RBS , which represents the mean statistical occurrence for this motif . Unfortunately , the consensus nucleotide requirements for a functional trs element are not defined well enough to conduct a meaningful bioinformatic search . Therefore , the presence of nicking sites next to the RBS in AAVS2 or AAVS3 remains open at present . Besides the identified integration hotspots numerous additional chromosomal junction sites were found for integrated wildtype AAV-2 , scattered over the human genome . From the bioinformatic calculations it appeared that the perfect tetranucleotide repeat GAGC GAGC represented the minimal requirement for Rep-dependent targeted integration , and GAGY GAGC GAGC represents the optimized in vivo target sequence for wildtype AAV-2 . Hotspots AAVS1 , AAVS2 , and AAVS3 display this core sequence fused to additional imperfect GAGY repeats . Other AAV serotypes display RBS sequences with similar numbers of GAGC and/or GAGT repeats , extended by additional imperfect repeats . AAV5 Rep co-crystallised with the hairpin-structured AAV5-ITR revealed that five Rep monomers bind to five consensus tetranucleotide repeats of the RBS , each of which was contacted by two Rep monomers from opposite faces of the DNA [58] . AAV2-Rep78/68 was shown to simultaneously bind to the RBS of the AAV-2 ITR and to that of AAVS1 [10] . Although it is currently unknown whether other AAV serotypes integrate at all , this is highly likely in view of the ability of both AAV-2 Rep and the relatively distant AAV-5 Rep to multimerize and simultaneously bind to clustered GAGY repeats . In the initial descriptions of AAVS1 , site-specific nicking of the trs by Rep bound to the adjacent RBS was viewed as preferred entry site for AAV recombination [4] . Meanwhile the majority of AAV integrations on chr . 19q13 . 42 were found many kb away from the RBS-trs combination , and neither AAVS2 or AAVS3 display obvious trs homologues next to the RBS . Therefore alternative explanations for RBS-dependent AAV integration should be considered . The potential use of preexisting chromosomal breakage sites recalls a mechanism already proposed for the integration of rep-deficient AAV vectors [34] , [59] . Alternative integration concepts include the use of imperfect trs elements for nicking as shown in vitro [4] , [60] , [61] , or the ability of Rep78 to induce DNA damage in vivo by single-strand nicking of cellular chromatin [19] . It is conceivable that the introduction of single-strand nicks occurs anywhere in accessible chromatin , even if the nicking site is hundreds or thousands of bp apart from the RBS on an extended DNA strand . HMGB1 , an ubiquitous architectural protein that serves as key component of the chromatin remodelling complex may be of help [62] . Its long-known in vivo interaction with Rep [63] may help remodel the chromatin to make it accessible for nicking by Rep . Rep was also shown to contact other key players of the nucleosome remodelling complex as components of the transcription- or DNA replication machinery [64] , [65] , [66] . Any of these mechanisms can be exploited to open the chromatin for AAV integration . In summary , Rep with its combined DNA-binding and endonuclease activity appears to serve as a relatively imprecise targeting tool for AAV integration preferably in open chromatin regions in the reach of consensus Rep-binding sites prevalent in the human genome . The early finding that Rep would mediate site-specific AAV integration on chr . 19q13 . 42 had immediate implications for gene therapy . A variety of concepts were devised to incorporate Rep as an adapter to target AAV-ITR flanked transgenes to a specific site [26] , [27] , [28] , [57] , [67] . In the majority of cases appropriate cell selection or PCR for AAVS1 led to cells displaying the desired integration . The reported high frequencies of integration into AAVS1 are difficult to reconcile with our findings , unless the level of Rep expression is considered to have an impact on target site choice . Upon AAV infection Rep is only moderately expressed due to autoregulation of the AAV p5 promoter . Rep-dependent AAV vector transductions typically use strong heterologous promoters that lead to high and sustained Rep expression levels . Increasing Rep levels may increase the overall probability for integration anywhere in the genome , including at hotspots . Under these conditions AAVS1-specific integration will be detected more readily . This appears however to come at the price of genomic rearrangements in reach of alternative Rep-binding sites . Therefore , it is plausible that in the absence of any selection AAV integration into AAVS1 is typically unstable and difficult to detect . In summary , Rep expression increases the probability for integration next to one of several genomic hotspots . However , the net genotoxic effect is unpredictable both with respect to the integrity of the AAV integration locus itself and with respect to the numerous additional sites where Rep binds and initiates chromosomal damage . Therefore , the current concept of a relatively precise site-specific targeting of AAV should be extended to a concept of a relative preference for accessible chromatin regions in the neighbourhood of any of the numerous consensus Rep-binding sites . More recent approaches for site-specific vector targeting try to exploit DNA sequence-specific zinc-finger nucleases to target a genomic sequence of wish [68] . Although zinc-finger nucleases are not free from off-target genotoxicity , at least the genomic targeting site for the transgene can be more precisely defined , a goal that appears to be inherently unachievable using Rep as an adapter molecule .
Detroit 6 cells harbouring latent AAV-2 genomes and HeLa cells were grown in Dulbecco's modified Eagles's medium ( Gibco ) supplemented with 10% fetal calf serum , penicillin ( 100 U/ml ) , and streptomycin ( 100 µg/ml ) . Viral stocks of wildtype AAV-2 with infectious titers of 5×109 i . u . /ml were prepared on HeLa cells as described before [16] . For the analysis of AAV integration sites 1 . 7×106 HeLa cells were seeded overnight on 10 cm diameter dishes and infected with AAV-2 at a MOI of 500 . Cells were harvested at 96 hours post infection ( p . i . ) for the extraction of genomic DNA . The period of cell growth after infection was minimized to reduce the chances of selection of particular integration sites during cell proliferation . Alternatively , AAV-infected HeLa cells were seeded to microtiter plates at a dilution of 60 cells per plate and grown up as single-cell clones without drug selection . Plasmid pTAV2-0 covers the AAV-2 wildtype genome ( GenBank accession number AF043303 ) , pRVK the 4 kb fragment of the AAVS1 locus on chromosome 19 ( GenBank accession number S51329 ) , and pAAVS1-TR covers an AAV-ITR/AAVS1 junction [16] . Plasmid pMBP-Rep78 encoding Rep78 fused to maltose-binding protein ( MBP ) was described before [69] . MBP-Rep78 encoding Rep78 fused to maltose-binding protein was expressed und purified essentially as described [69] . Briefly , E . coli strain BL21 transformed with pMBP-Rep78 was grown at 30°C to an OD600 nm of 0 . 6 to 0 . 8 . Production of MBP-Rep78 was induced with 0 . 3 mM IPTG for 3 h at 30°C . Cells were harvested by centrifugation and lysed by sonication for 2 min ( 30% duty cycle ) in lysis buffer of 50 mM phosphate pH 7 . 8 , 300 mM NaCl , 1% ( v/v ) Triton X-100 , 0 . 1 mM PMSF . Cell debris was removed by centrifugation at 6500×g for 20 min at 4°C . The supernatant was adsorbed to amylose resin ( New England Biolabs ) in a batch process and the resin was washed extensively ( 5 washes with about 100 volumes of the resin ) with lysis buffer . The adsorbed proteins were eluted with lysis buffer containing 10 mM maltose and analyzed for purity by SDS-polyacrylamide gel electrophoresis . Binding of MPB-Rep78 fusion protein to 32P- labeled double-stranded oligonucleotide probes was detected by altered mobility of the probes in nondenaturating polyacrylamide gels essentially as described previously [70] . Briefly , oligonucleotides of 46–49 nt length were end-labeled with T4 polynucleotide kinase and annealed . EMSA reactions were performed for 20 min at 20°C as follows: 0 . 015 pmol of labeled DNA substrate was incubated with the indicated amounts of MBP or MBP-Rep78 in a binding buffer containing 25 mM HEPES-KOH ( pH 7 . 8 ) , 10 mM MgCl2 , 40 mM NaCl , 1 mM DTT , 2% glycerol , 12 . 5 µg/ml BSA , 0 , 01% Nonidet P40 and 5 µg/ml salmon sperm DNA . The following oligonucleotides were used: AAV-ITR ( nucleotide position 85–133 ) : GCCTCAGTGAGCGAGCGAGCGCGCAGAGAGGGAGTGGCCAACTCCATCA; AAV-ITR complementary strand: TGATGGAGTTGGCCACTCCCTCTCTGCGCGCTCGCTCGCTCACTGAGGC Chr . 19q13 . 42 ( AAVS1 ) : TGGCGGCGGTTGGGGCTCGGCGCTCGCTCGCTCGCTGGGCGGGCGGGC Chr19 ( AAVS1 ) complementary strand: GCCCGCCCGCCCAGCGAGCGAGCGAGCGCCGAGCCCCAACCGCCGCCA Chr . 5p13 . 3 ( AAVS2 ) : AGCTGGACCCCACGCTCGCTCACTCACTCTCCCCTCACCGCTTTGT Chr . 5 ( AAVS2 ) complementary strand: ACAAAGCGGTGAGGGGAGAGTGAGTGAGCGAGCGTGGGGTCCAGCT Chr . 3p24 . 3 ( AAVS3 ) GCTTCCCAAGGGGAATGAATGTGCGCTCGCTCACTCACTCACTCCTCAC Chr . 3 ( AAVS3 ) complementary strand: GTGAGGAGTGAGTGAGTGAGCGAGCGCACATTCATTCCCCTTGGGAAGC Chr . 5MUT ( AAVS2 mutated ) : AGCTGGACCCCACCCTCGCTCCCTCCCTCTCCCCTCACCGCTTTGT Chr . 5MUT ( AAVS2 mutated ) , complementary strand: ACAAAGCGGTGAGGGGAGAGGGAGGGAGCGAGGGTGGGGTCCAGCT AAV p5 ( nucleotide position 245–292 ) : TCACGCTGGGTATTTAAGCCCGAGTGAGCACGCAGGGTCTCCATTTTG AAV p5 complementary strand: CAAAATGGAGACCCTGCGTGCTCACTCGGGCTTAAATACCCAGCGTGA random control: CAGAGCAGCAGCACAGACGCTAGCAGATCTCCTGCGACCGGAGATGTG random control , complementary strand: CACATCTCCGGTCGCAGGAGATCTGCTAGCGTCTGTGCTGCTGCTCTG Total genomic DNA was extracted by SDS/proteinase K digestion followed by repeated phenol/chloroform extractions and ethanol precipitation , as described before [71] . High molecular weight DNA ( 2 µg ) was digested with restriction enzymes that lead to a mean genomic fragment size of around 4 kb and produce blunt-ends ready for linker/adapter ligation . Non-cut enzymes for AAV-2 DNA were preferred , PvuII , EcoRV . Additional junctions were retrieved with DraI ( one cut in AAV-2 wildtype DNA ) . Digested genomic DNA was purified by repeated phenol-chloroform extractions and precipitated with ethanol . A linker-based strategy described in [39] , [40] and outlined in more detail in the manual of the GenomeWalker kit ( Clontech ) was modified as outlined in Figure 1B . The following oligos were used for linker construction: “Linkerlong” ( 5′GTA ATA CGA CTC ACT ATA CGG CAC GCG TGG TCG ACG GCC CGG GCT GGT 3′ ) and “linkershort” ( 5′ACC AGC CC 3′modifikation: 2′ , 3′-dideoxyC ) . Equal amounts of “linkerlong” and phosphorylated “linkershort” ( 100pmol each ) were annealed and ligated to restriction enzyme-digested genomic DNA . PCR-primers: The linker-primers were “P linker outside” with biotin attached to its 5′ end ( 5′-GTA ATA CGA CTC ACT ATA CGG C; Tm = 58 . 4°C ) and “P linker nested” ( 5′-ACT ATA CGG CAC GCG TGG T; Tm = 58 . 8°C ) . Two AAV-2-specific primer sets were used . The first primer set covered the AAV p5 promoter: “AAV2p5” ( 5′-TCA AAA TGG AGA CCC TGC GTG CTC A; Tm = 64 . 6°C , AAV-2 , nt 293–269 ) , primer “AAV2p5 nested” ( 5′-TAA ATA CCC AGC GTG ACC ACA TGG TG; Tm = 64 . 8°C , AAV-2 , nt 260–235 ) . The other primer set is located in the cap gene region , as described before [2]: “CAPgsp1” ( 5′-GTC TGT TAA TGT GGA CTT TAC TGT GGA CAC; Tm = 65 . 4°C , AAV-2 , nt 4320–4349 ) and “CAPgsp2” 5′-GTG TAT TCA GAG CCT CGC CCC AT; Tm = 64 . 2°C , AAV-2 nt 4357–4379 ) . The PCR reaction contained 0 . 2 mM dNTPs , linker primer and AAV specific primer ( 0 . 25 µM , each ) , 2 . 5 U proofreading hot-start polymerase ( Herculase ) in reaction buffer , as provided by the supplier ( Stratagene ) . Of the preceding linker-ligation reaction 1–5 µl was added to a final volume of 50 µl . PCR conditions were as follows: 3 min at 98°C , followed by 10 cycles of 40 sec at 98°C , 30 sec at 65°C , and 4 min at 72°C , followed by 20 cycles of 40 sec at 98°C , 30 sec at 65°C , and 4 min + 10 sec per cycle at 72°C , terminated by an extension period of 10 min at 72°C . Biotin-labelled PCR products were further enriched on streptavidin-labelled Dynabeads M-280 , as outlined by the supplier ( Invitrogen ) . Subsequent nested PCR used conditions identical to the first round but with pairs of the nested PCR primers , as outlined above . Finally , to add overhangs of multiple As , PCR products were incubated with 1 U Taq polymerase ( New England Biolabs ) . Products of LSM-PCR reactions were separated on agarose gels . To ensure sufficient chromosomal fragment lengths , PCR bands of a calculated minimal length ( >500 bp ) were excised and purified by the QIAEX II Gel extraction kit ( Qiagen , Hilden , Germany ) . TOPO-TA cloning was performed as described [72] . Colonies were PCR-screened with the M13 forward ( -20 ) and reverse primer pair ( 0 . 4 µM , each ) with 0 . 2 mM dNTP , 2 U Taq polymerase ( New England Biolabs ) at the following conditions: 10 min at 94°C , followed by 30 cycles of 30 sec each at 94°C , 52°C , and 72°C , followed by 10 min at 72°C . Column-purified PCR products were submitted to DNA sequencing using the primer provided by the TOPO-TA cloning kit . DNA sequences were run on a CEQ2000 genetic analysis system ( Beckman ) using the CEQ Dye Terminator Cycle Sequencing Quick start kit ( Beckman ) and the run method LFR-a . Cycling conditions were as follows: 1 min at 96°C , followed by 30 cycles 20 sec at 96°C , 20 sec at 50°C and 4 min at 60°C . The genomic positions of AAV integration sites in the human genome ( assembly from March 2006 , hg18 ) were determined using the BLAT tool from the UCSC Genome Browser web site ( http://genome . ucsc . edu/cgi-bin/hgBlat ) [73] . A match was defined as a BLAT search result fulfilling all of the following criteria: In addition to the LSM-PCR derived sequences , the original DNA sequence files of 157 chromosomal junctions [42] kindly provided by Dr . G . W . Both , North Ride , Australia were reanalyzed applying the above inclusion criteria . This led to 47 DNA sequences suitable for our analysis ( Table 1 ) . In their study , HeLa cells had been cotransfected with plasmids for constitutive RSV-promoter-driven Rep78 expression and for recombinant AAV vectors expressing a SV40-promoter-driven neomycin gene [42] . Furthermore , 1100 DNA sequences from a published analysis of rep-deficient AAV vector integration sites in diploid human cells [46] were reanalyzed . Since the PCR methods employed in our study and in the one by Drew et al . [42] cannot detect the matching left and right junction sites generated by one AAV integration event , only one chromosomal junction was analyzed per rescued provirus . The original DNA sequence files ( DU711025 . 1 to DU709854 . 1 ) of Miller et al . [46] were downloaded from the Genome Survey Sequences ( GSS ) Database of NCBI ( http://www . ncbi . nlm . nih . gov/sites/entrez ? db=nucgss ) and reanalyzed using the UCSC March 2006 human genome build . The analysis led to a total of 450 junction sequences that fulfilled all of the above inclusion criteria for bioinformatic comparisons . For the subsequent data analysis we implemented software in C++ using the software library SeqAn [74] and several Python scripts . For different Rep binding motifs , we computed the average distance of virus integration sites to the closest occurrences of Rep binding motifs within the genome . We supposed that the observed integration events were independent from each other and the sample size was high enough for assuming the distance to be normally distributed . To assess whether these distances differ significantly from expectation , several background models were generated: The generation of both , the data analysis and the background model was confined to those genomic contigs that contained at least one Rep binding motif , since otherwise the distance to the “closest Rep binding motif” would not be defined . A given set of AAV integration sites was considered to be significantly closer to Rep binding motifs than expected by chance , if the significance was calculated for all relevant background models . Data sets of AAV vectors were analyzed with the “random” background model . We applied a Z-test for determining statistical significances for the distances of integration sites to Rep binding sites . For comparing integration sites from AAV wildtype infection sites against those from rep-deficient AAV vector infection we applied the Student's t-test . AAV integration sites were examined for the occurrence of various genomic features using tables available in the UCSC database . For the determination of significant divergences from expectations , we compared the actual integration sites with a set of 100 , 000 randomly chosen control sites in the human genome using a two-tailed binomial test . Chromatin immunoprecipitation sequencing ( ChIP-Seq ) data were used to define the state of histone modifications in genomic regions of AAV integration . H3K27me3 domains determined by Cuddapah et al . were used as markers for closed chromatin ( http://www . wip . ncbi . nlm . nih . gov/projects/geo/query/acc . cgi ? acc=GSM325898 ) [75] . Regions enriched for H3K4 methylation ( open chromatin ) were determined as follows: The raw ChIP-Seq reads by Robertson et al . [76] ( http://www . bcgsc . ca/data/histone-modification ) were mapped to the human genome using Bowtie [77] , and peaks were called using MACS [78] . H3K4me1/3 domains are then defined as 5 kb windows around the centers of the peaks .
|
This is the first unbiased genome-wide analysis of wildtype AAV integration combined with a thorough bioinformatic analysis of preferred genomic motifs and patterns in the neighbourhood of the integration sites identified . The preference of Rep-dependent AAV integration near multiple consensus Rep-binding sites was lost in the case of AAV vector integration in the absence of Rep expression . Our findings challenge the commonly accepted notion of site-specific AAV targeting to AAVS1 on chromosome 19q13 . 42 . Although AAVS1 contains a canonical Rep-binding site , numerous additional sites including the newly identified hotspots AAVS2 on chromosome 5p13 . 3 and AAVS3 on chromosome 3p24 . 3 harbour functional Rep-binding sites suitable for AAV integration . AAV vectors are quickly moving forward in the clinic and Rep-dependent vector targeting strategies are being actively pursued . Detailed information of AAV wildtype versus recombinant AAV vector integration sites and preferences are needed to evaluate the safety profile of AAV vectors in gene therapy .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"virology/persistence",
"and",
"latency",
"virology/virus",
"evolution",
"and",
"symbiosis",
"computational",
"biology/sequence",
"motif",
"analysis",
"computational",
"biology/comparative",
"sequence",
"analysis",
"virology"
] |
2010
|
Integration Preferences of Wildtype AAV-2 for Consensus Rep-Binding Sites at Numerous Loci in the Human Genome
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Drug development for neglected diseases has been historically hampered due to lack of market incentives . The advent of public domain resources containing chemical information from high throughput screenings is changing the landscape of drug discovery for these diseases . In this work we took advantage of data from extensively studied organisms like human , mouse , E . coli and yeast , among others , to develop a novel integrative network model to prioritize and identify candidate drug targets in neglected pathogen proteomes , and bioactive drug-like molecules . We modeled genomic ( proteins ) and chemical ( bioactive compounds ) data as a multilayer weighted network graph that takes advantage of bioactivity data across 221 species , chemical similarities between 1 . 7 105 compounds and several functional relations among 1 . 67 105 proteins . These relations comprised orthology , sharing of protein domains , and shared participation in defined biochemical pathways . We showcase the application of this network graph to the problem of prioritization of new candidate targets , based on the information available in the graph for known compound-target associations . We validated this strategy by performing a cross validation procedure for known mouse and Trypanosoma cruzi targets and showed that our approach outperforms classic alignment-based approaches . Moreover , our model provides additional flexibility as two different network definitions could be considered , finding in both cases qualitatively different but sensible candidate targets . We also showcase the application of the network to suggest targets for orphan compounds that are active against Plasmodium falciparum in high-throughput screens . In this case our approach provided a reduced prioritization list of target proteins for the query molecules and showed the ability to propose new testable hypotheses for each compound . Moreover , we found that some predictions highlighted by our network model were supported by independent experimental validations as found post-facto in the literature .
Neglected tropical diseases ( NTDs ) devastate the lives of approximately 1 billion people , with a further 1 billion at risk [1–3] . These diseases mainly affect those who live in poverty in Africa , Asia and the Americas . Current treatments for these diseases present several issues and limitations such as cost , difficulties in administration , poor safety profiles , lack of efficacy , and increasing drug resistance , among others [4] . Furthermore , there has been limited commercial interest in developing improved therapeutics , mostly because of the costly and risky nature of the drug discovery process [5 , 6] and the expected low return of investment when dealing with poor patient populations [7] . As a consequence , only ~1% of all new drugs that reached the market in recent years were for neglected diseases [1 , 4] . The situation for human diseases that affect the developed world is radically different . In this case , many important contributions to drug discovery are made every year from academic and government laboratories , leading to the approval of ~20 new drugs per year on average [8] . As part of this process of drug discovery , we accumulate information about many bioactive compounds ( their activities , targets and mechanisms of action ) , which can be used in repositioning strategies . Drug repositioning ( or repurposing , or reprofiling ) is the process of finding new indications for existing drugs [9] . The benefits of this approach are many , the main being the lower costs of development [5 , 9–11] . A number of success stories help support the case for these type of approaches . Two of the best known examples are sildenafil ( Viagra ) , which was repositioned from a common hypertension drug to a therapy for erectile dysfunction [11] and thalidomide , repurposed to treat multiple myeloma and leprosy complications [12] . Because of the enormous cost savings associated with repositioning an approved drug , this strategy is particularly attractive for NTDs . For these , there are also a number of successful repositioning stories: eflornithine , which was developed as an anticancer compound is being used to treat African trypanosomiasis ( sleeping sickness ) , whereas pentamidine , amphothericin B ( originally an antifungal drug ) and miltefosine were all repositioned from other indications for the chemotherapy of leishmaniasis ( other examples were discussed recently , see [13 , 14] ) . Target prioritization , and drug repositioning are particularly amenable to the use of computational data mining techniques , which offer high-level integration of available knowledge [15] . These strategies take advantage of bio- and chemoinformatic tools to make full use of known targets , drugs , and disease biomarkers or pathways , which in turn lead to a faster computer-to-bench or computer-to-clinic studies . Exploring a large pharmacological space in this way has led to novel insights on the targets and modes of action of existing drugs [16–24] . Unfortunately , these and other integrative mining strategies were focused in attacking the problem from the point of view of diseases of the developed world . Fortunately it is relatively straightforward to use a number of inference strategies to map informative associations to other species . Kruger and coworkers recently showed that ligand binding to > 150 human proteins is mostly conserved across mammalian orthologs , therefore providing support for this type of inferences [25] . It is also worthwhile mentioning that particularly in the case of neglected diseases , drug repositioning need not be taken in a strict sense to include only drugs approved for clinical use in humans . Widening the criteria to reposition drugs for veterinary use , or further , any bioactive compound ( hits/leads ) may significantly increase the chances of success by helping to guide efforts in academia and pharma . These will ultimately feed the pipeline of drug discovery for these important diseases . After completion of a number of key pathogen genome projects , we developed a database resource to help prioritize candidate targets for drug discovery in NTDs [26 , 27] . Initially , target prioritizations were based on gene and protein features , with limited use of information on availability of bioactive compounds to guide these prioritizations . Since then we have integrated information on a large number of bioactive compounds into the TDRtargets . org database [28] . These were derived from public domain resources , and from a number of high-throughput screenings of an unusual scale for NTDs [29–31] . This has brought the current status of chemogenomics data integration in NTDs to a stage where large scale data mining exercises are now feasible . Complex networks can efficiently describe pairwise similarity relations between drugs and between proteins . Under this paradigm non-trivial interconnectivity patterns can be mined to uncover hidden organization principles , or to identify unnoticed relevant entities and/or novel putative drug-target associations [18 , 23 , 32–40] . In this work we addressed the construction of a multilayer network of protein targets ( gene products ) , chemical compounds , and their relations , in order to guide drug discovery efforts . Because we focused on tropical diseases , we were interested in leveraging the information contained in the network ( mostly derived from well-studied organisms ) to direct the selection of targets and compounds for further experimentation in these neglected pathogens . In this context we tackled two well differentiated problems . First , we analyzed the prioritization of targets for drug discovery in the absence or scarcity of bioactivity data for an organism of interest . For a selected pathogen ( a query species ) , we took advantage of chemogenomics and bioactivity data available in the network , to get a global prioritized list of promising targets . In a second analysis , we used the information embedded in the network to suggest candidate targets for orphan compounds , i . e . chemicals that have been shown to be active in whole-cell or whole-organism screenings but whose targets are currently unknown . In this case , we aimed to obtain reduced prioritization lists of target proteins for the query molecule .
All target data used in this work was obtained from the TDR Targets database [26 , 28] , which includes complete genomes from a number of pathogens causing neglected tropical diseases , as well as model organisms: Plasmodium falciparum , Trypanosoma brucei , Trypanosoma cruzi , Leishmania major , Mycobacterium tuberculosis , Brugia malayi , Schistosoma mansoni , Toxoplasma gondii , Plasmodium vivax , Leishmania braziliensis , Leishmania infantum , Leishmania mexicana . In addition we integrated data from complete genomes from non-pathogen organisms: vertebrates ( human , mouse ) , plantae ( Arabidopsis thaliana , Oryza sativa ) , invertebrates ( Drosophila melanogaster ) , and nematodes ( Caenorhabditis elegans ) , fungi ( Saccharomyces cerevisiae ) , and bacteria ( Escherichia coli ) . Pfam domain annotations for all targets were obtained from the InterPro database resource , using interproscan [41] . Metabolic pathway , and EC number annotations for all targets were obtained from the KEGG database resource [42] . Orthology relationships between targets were obtained from the OrthoMCL database [43] or calculated by mapping proteins against OrthoMCL ortholog groups using BLASTP [44] . As a result we had our proteins mapped to 69 , 926 ortholog groups ( a singleton is considered also as a separate ortholog group of size = 1 ) . Information on chemical compounds ( structures , bioactivity information ) was obtained from the ChEMBL database [45] . This information was complemented by manually curated data from the TDR Targets database on compounds active against pathogens ( see below ) . We estimated chemical similarity between molecules by performing an all vs all fingerprint-based similarity analysis using checkmol [46] . The algorithm for fingerprint generation has been described [46] , but briefly , for each molecule the molecular graph is disassembled into all possible linear fragments with a length ranging from 3 to 8 atoms . Strings representing atom types as well as bond types of these linear fragments are then passed to two independent hash functions in order to compute two pseudo-random numbers in the range 1–512 , which are used to set two positions in the 512-bit binary fingerprint . For similarity search operations , the hash-based fingerprint of the query structure was used to compute the Tanimoto similarity coefficient ( Tc ) [47] for each pairwise combination of query/candidate hash-based fingerprints . Because pairs of molecules with low Tc values have insubstantial chemical similarity , for the Drug-network layer we only considered similarity relationships with Tc values ≥0 . 8 as these are expected to be both significant in statistical terms [48] and in terms of their expected biological activity [49] . As a result we retained about 44 . 4 106 informative pairwise relations and used the corresponding Tc values to weight the corresponding links . In addition , for each bioactive molecule d ∈ VD , we identified exact substructure relationships using matchmol . These substructure relationships , unlike other similarity measurements , were asymmetrical ( a 2D/graph representation of a molecule was completely included within another one , but not viceversa ) . We filtered out substructure relationships for very small molecules as these were more likely to be contained within larger and more complex molecules rather unspecifically without a strict correlation with expected targets or modes of action . After analyzing the distribution of molecular weight and number of parental structures of each compound ( parental molecules are those that contain a compound as part of its structure ) we filtered out edges involving molecules with low molecular weight ( MW < 150 ) and large number of parental structures ( Nparents>100 ) . We found that the adopted molecular weight threshold appeared as a reasonable and conservative maximal bound for filtering out highly promiscuous structures ( i . e . molecules included in more than 100 parental compounds ) . For larger molecular weights the number of affected molecules would have been much more sensitive to the adopted threshold level ( see S3 Fig ) . Taking into account Tanimoto similarities and substructure relationships , we set up the drug layer graph GD ( VD = {d1 , … , dM} , E = {cij}i , j = 1…M ) . We considered weighted inter-compounds edges cij ∈ R ( 0+ ) defined as: cij=max{TC ( di , dj ) *I ( TC ( di , dj ) ≥0 . 80 ) , 0 . 8*I ( di⊂dj ) } ( 1 ) where I ( x ) is an index function that equals 1 if its argument is a true proposition and 0 otherwise , and di ⊂ dj means that di is an exact substructure of dj . In words , each substructure edge received a weight value of 0 . 8 , and each valid Tanimoto edge ( Tc ≥ 0 . 8 ) was weighted considering the corresponding Tc value . The overall chemical similarity information between a pair of compounds was then integrated into a single link taking into account the maximal available weight that could be established between them . Links between compounds and proteins were derived from bioactivity information , obtained from different sources ( ChEMBL , PubChem , TDR Targets ) , as well as a focused manual curation of the literature performed for this work . Due to the great diversity of assays and forms of reporting bioactivity values , we selected a number of assays for which we have the greatest amount of data , and we defined a cutoff value for each bioactivity type , in order to classify the compound as active or inactive ( Table 1 ) . The bioactivity classes that were taken into account represent 95% of the total bioactivities in our dataset . In the case of orphan compounds that are active against P . falciparum ( see Results ) bioactive molecules correspond to the assays detailed in the Table 2 . For the i-th affiliation-type node , fi ∈ VF ( which represents a shared functional relation among proteins , such as an ortholog group , a Pfam domain , or a defined biochemical pathway , we defined a Relevance Score , RSi , as a proxy of its informative relevance with regard to drug-target predictions tasks . To this end , we performed an overrepresentation test ( Fisher exact test ) to quantify the overrepresentation in each affiliation category of druggable proteins , where the criteria for druggability are the cutoffs described in Table 1 . Taking into account the corresponding Fisher test p-value , pvi , we defined the attribute node’s relevance score as RSi=−log10 ( pvi ) ( 2 ) The protein and affiliation node layers defined a bipartite graph which can be represented by an adjacency matrix Mbip∈Rnp×nf: Mijbip={1if proteiniis annotated to categoryfj0otherwise ( 3 ) We projected this bipartite network into a mono-partite graph , the Projected Protein Layer ( PP-layer ) , where protein nodes were connected through weighted links if they share common affiliation nodes . The corresponding adjacency matrix MPP∈Rnp×np was defined as MPP=MbipS ( Mbip ) T ( 4 ) where S∈Rnf×nf was a diagonal scoring matrix for affiliation nodes . We considered two alternative definitions for the scoring matrix S . In the first case , S = Sr , diagonal elements were defined as Srii=f ( RSi ) ={1ifRSi≥quantile ( RS , 0 . 8 ) ( RSimax{RSi} ) αotherwise ( 5 ) where α was a tunable parameter that was set by maximizing the performance of recovering known druggable targets in cross validation exercises ( see below ) For the second alternative , in view of the broad degree distribution observed for affiliation nodes , we also considered an extra factor that relativized the score of large categories . In this case diagonal elements of S = Sr were defined as Srkii=f ( RSi ) ={1kiifRSi≥quantile ( RS , 0 . 8 ) 1ki ( RSimax{RSi} ) αotherwise ( 6 ) where ki is the degree of the i-th affiliation node , and α was a tunable parameter ( see below ) . Both scoring matrices , Sr and Srk , led to different projected PP-layers and induced two alternative two-layered weighted graphs G' ( V = {VD , VP} , E = {EDD , EDP , EPP} ) , namely Gr' and Grk' . These graphs were used to address different prioritization tasks throughout this manuscript . In either case the free parameter α was set by maximizing the performance of recovering druggable targets . Let’s consider a weighted graph G = G ( V = {ni}i = 1…N` , E = {eij}i , j = 1…N ) , where eij∈R0+ are weighted edges , and a vertex seed set S = {s1 , … , sk} . The voting scheme assigns to each node ni not included in the seed set a prioritization score , PS , according to the following expression: PSi=∑j=1…kwjeji ( 7 ) where wj is a real number that serves to weight the contribution of seed sj , and eji the weight value of the link joining nodes nj and ni . When we prioritized targets from a query proteome Q , we set wj = 1∀j ( i . e . we considered uniform and equally weighted seeds ) . On the other hand , when we prioritized candidate targets for an orphan compound dk , we set wj according to the similarity between dk , and its direct neighbor drugs which reported bioactivities against protein sj: wj=∑i:di∈N ( dk ) ckieijDP ( 8 ) where cki is the weight of the edge between dk and di molecules introduced in Eq [1] , eijDP is 1 if there was a bioactivity link between drug di and protein pj ( and 0 otherwise ) and N ( dk ) the set of direct neighbors of drug dk . The PP-layer results from a projection of a bipartite network graph . The procedure used for this projection is dependent on the single parameter α ( see Eqs 2 and 3 ) . In order to analyze the effect of α on the ability to recover known targets from an entire genome , we calculated ROC curves , and compared the partial AUC-0 . 1 for different α values following a tenfold cross validation procedure . The results are summarized in S4 Fig It can be noticed that the predictive performance remained near maximal , without significant variations , for a broad range of the parameter space , α ∈ [0 . 2 , 1] , suggesting that the method is robust to different α selections . From this point forward , we considered α = 0 . 6 , the midpoint in this interval . An important remark is that α = 0 - which corresponds to disregarding the relevance score in the definition of the S matrix ( see Eqs 4 and 5 ) —had a significantly lower performance than the α = 0 . 6 case ( pv < 10−24 , Wilcoxon test ) .
We integrated genomic , biochemical and medicinal chemistry data from several public domain resources ( see Methods ) . These data is available from the TDR Targets database and includes genome data from pathogen and model organisms . As a starting point we considered sequence information from ~ 1 . 7 105 proteins derived from 37 complete genomes ( S1 Table ) and from known druggable targets from other 184 species . We also considered a number of affiliation-type features for these proteins , which would allow us to establish relations between proteins , like sharing of protein domains , clustering in the same ortholog groups and participation in the same metabolic pathways . These features were selected because they provide complementary information on the similarity of these proteins , from the point of view of drug discovery , and because they can be easily computed for whole genomes . In addition , we considered structural information from ~1 . 5 106 bioactive compounds , and their associated bioactivity data against pathogen and non-pathogen organisms , obtained from open chemical databases and high throughput screenings [29–31 , 45 , 51] . In order to organize and provide a global description of the available heterogeneous data , we considered a multipartite , multilayered network graph G ( V = {VD , VP , VF} , E = {EDD , EDP , EPF} ) . In this network three types of vertices VD , VP , VF represented bioactive compounds , proteins , and functional affiliation entities , respectively . Relationships between pairs of compounds , between compounds and known protein targets , and between proteins and functional affiliation classes where represented by the corresponding edges EDD , EDP , EPF . Fig 1A depicts a graphical representation of this network , where three layers , each including a different type of vertex can be recognized . The first layer contained chemical compounds as nodes ( VD = {d1 , d2 , …} ) . Weighted pairwise links between compounds ( EDD ) were established if they were chemically similar based on their 2D representations . More specifically , we connected two compounds if the Tanimoto similarity coefficient of their 2D fingerprints was >0 . 8 ( which is a very conservative similarity cutoff [48] ) , or if a compound was an exact substructure of the other . In this case the directionality of the relationship was preserved ( see Methods for details ) . Nodes in the second layer ( VP = {p1 , p2 , …} ) represented proteins from 221 pathogen and non-pathogen ( model ) organisms . Complete proteome coverage in the network was available for 37 species representing a wide phylogenetic range ( S1 Table ) . No connections were initially established between nodes in this layer . Instead , we considered a third layer in which nodes ( VF = {f1 , f2 , …} ) represented functional affiliation-type entities as nodes . These entities were Pfam domains [52] , ortholog groups [53 , 54] and metabolic pathways [42] . We established links ( EPF edges ) between layer-2 nodes ( proteins ) and layer-3 nodes ( functional affiliation-type entities ) based on current predictions derived from standard sequence analysis pipelines and annotation ( see Methods ) . Lastly , we have used bioactivity data information to establish links ( EDP edges ) between protein targets ( layer-2 ) and chemical compounds ( layer-1 ) . These links were established after manual curation of the textual description of the assays , targets , and measured activities . Because bioactivities integrated into the TDR Targets resource contained also negative evidence ( inactive compounds at relevant concentrations against a particular target ) , a significant amount of manual curation of these data was required for construction of the network . Therefore , EDP edges in the final network graph represented sensible bioactivity information available for each protein target ( bioactivity thresholds and criteria are described in Methods ) . A summary of the information and entities included in the network is available in Table 3 . Once the data was integrated in our network model , we proceeded to identify informative functional affiliation-type annotations that were relevant for drug discovery . Therefore , in the next step , we discarded 52 , 916 VF nodes that were not linked to at least one druggable protein in our dataset ( in this context “druggable” was defined operationally as a protein with at least one link to a compound in layer-1 ) . The final resultant network comprises 2 , 252 informative affiliations to Pfam domains , 2 , 789 affiliations to ortholog groups , and 145 affiliations to metabolic pathways . The second and third layers of the network defined , on their own , an affiliation or membership network , which is a special type of bipartite network [55 , 56] . An important feature of this kind of networks is that the inter-layer connectivity pattern can be used to infer intra-layer associations for each layer , via projection procedures [56] . In our case , adjacent links of shared functional affiliation nodes , VF , were used to define weighted links , EPP , between protein nodes , VP . These inferred edges condensed similarity information at the level of the biological and functional concepts contained in layer-3 . We have implemented two projection methodologies . In the first case we took into account a relevance score , RS , for each affiliation node based on the statistical significance level of the over-representation of associated druggable proteins as obtained through a Fisher’s exact test ( see Methods , an example is provided in Table 4 ) . For the second alternative , in view of the broad degree distribution observed for affiliation nodes ( see S1 Fig ) , we also considered an extra factor that relativized the score of large categories ( see Methods for technical details ) . The rationale of this correction is to down-weight the contribution of very promiscuous annotation nodes ( e . g . highly frequent protein domains such as the ATP-binding cassette , present in many functionally-unrelated protein families and orthologs ) . Although their presence helps to increase the connectivity of the protein network , it also skews the protein prioritization scoring and , as a general rule , favors specific kind of proteins towards the first places in the resulting rankings ( see below ) . Taking into account either projection methodology , layer-2 and layer-3 could be collapsed into a single protein-projected directed and weighted layer ( PP-layer , see Fig 1B ) . The PP-layer along with the original drug-layer ( D-layer ) , defined a new graph1 ) 1 ) G' ( V = {VD , VP} , E = {EDD , EDP , EPP} ) that allowed us to propagate drug-target information to address different drug-discovery problems as described below in the next sections . When necessary , we will note the resulting graphs as Gr' ( projection using affiliation node’s relevance scores ) or Grk' ( projection using relevance scores and penalizing high degree affiliation nodes ) when the first and second projection methodologies were used , respectively . In this section we considered the problem of prioritizing targets from a query proteome Q for which compound bioactivity data is scarce or lacking altogether , as this is frequently the case for pathogens causing neglected tropical diseases . In this strategy we aimed to take advantage of the information contained in the network for other organisms to guide the prioritization of targets in our query species . The rationale of the approach relies on the assumption that relevant drug-target associations from other organisms , in concert with similarity relations between proteins ( embedded in the G’ network as EDP and EPP edges respectively ) could be used to propagate meaningful associations through the network and therefore suggest novel drug connections for proteins in Q . To prioritize targets , we devised the following algorithm . First we identified the set of druggable targets in the PP-layer of network G’ . These were protein nodes that were connected to at least one compound via an EDP edge ( e . g . protein cal . 575054in Fig 1A ) . In the next step , these nodes were used as seeds for a neighbor voting scheme algorithm ( VS ) implemented over the PP-layer . As a result of this voting procedure , proteins in Q will receive a score which essentially is the weighted sum of all the EPP direct links to seed nodes ( i . e . known targets ) . See Methods for further details . In order to illustrate the performance of this strategy we considered two query species Q each of which have known druggable targets: a mammalian proteome ( Q = M . musculus , often used as a model for human drug development ) , and a proteome from a protozoan parasite ( Q = T . cruzi , Chagas Disease ) . We deliberately chose a data-rich and a data-poor organism for this exercise to showcase the performance of the approach under these two contrasting situations . Whereas 8 , 429 EDP edges involving 280 VP nodes were present for M . musculus , only 319 EDP edges were adjacent to 19 T . cruzi protein nodes . The validation proceeds in each case by removing from the graph G , all EDP bioactivity edges involving proteins of Q before projecting layer-3 into layer-2 and weighting EPP edges . In this way , we ensured that no information extracted from the query organism was employed to build the two-layer G’ network used to prioritize targets in Q . After weighting and projecting the modified network graph , we assessed the performance of the prioritization strategy using Receiver Operating Characteristic ( ROC ) curves . Fig 2 depicts ROC curves for predicted drug-target associations considering G’rk ( black ) and G’r ( orange ) for M . musculus ( solid line ) and T . cruzi ( dashed line ) . Table 5 summarizes the performance of the prioritization procedures reporting the normalized AUC-0 . 1 values ( see inset in Fig 2 ) . The performance of a third prioritization strategy was also reported in the table for the sake of comparison . In this case , we considered a straightforward approach based on calculation of plain sequence similarity between druggable nodes in layer-2 against proteins in Q . For this purpose we used the FASTA sequence-alignment tool [57] , which produces longer alignments than BLAST ( as it does not split the region of similarity into high-scoring-pairs as BLAST does ) . The high performance of our network model at the task of recovering the known targets in each organism reflects the fact that data from close relatives of both organisms are contributing substantially to the connectivity of these nodes in the network graph . As an example there are 60 , 540 EDP edges connecting 455 VP nodes in the case of rat data , whereas there are 43 , 325 EDP edges connecting 3 , 567 VP nodes for other protozoan and bacterial targets . For both organisms , prioritizations based on the G’rk network model presented the best performance . Down-weighting the relevance score of affiliation nodes by their degree provided a significant improvement , as prioritizations considering G’r resulted in much poorer performances , especially for the T . cruzi case . Noticeably , the origin of the performance discrepancies between both network-based approaches were related to a strong correlation between prioritization scores in the G’r network and the strength ( a connectivity topological feature ) of Vp nodes . This finding makes evident that G’r prioritizations were a priori biased towards specific protein classes , i . e . those associated to high-strength Vp nodes ( see Supplementary S1 Text ) . It is worth mentioning that despite its simplicity , the voting scheme ( VS ) adopted for these network-based prioritization strategies has already proved to be competitive relative to more sophisticated algorithms in many scenarios , with the additional benefit of being extremely fast [59] . We verified that this was also the case in the context of our prioritization problem . In particular , we considered a prioritization strategy based on a network flow analogy ( functional flow methodology ) [60] and verified that it gave similar or inferior performance than VS ( see S2 Table ) . Finally , we compared the top ranked targets according to the network-based VS voting algorithm and the FASTA methodologies to see if the information provided by these alternative prioritization procedures were correlated . We considered the top 1% proteins ranked by the analyzed methodologies in each species ( top 136 and 66 targets for M . musculus , and T . cruzi , respectively ) ( see S2 Fig ) . Even though we found statistically significant overlaps between G’rk and FASTA predictions ( Fisher Exact Test , p = 9 . 45 10−28 and p = 2 . 79 10−2 for M . musculus , and T . cruzi , respectively ) most of these were specific to the considered prioritization strategy . This finding revealed that even if the two kinds of affiliation-type entities with the largest network coverage ( i . e . orthology groups and Pfam domains ) involved some sort of sequence similarity idea , the network based predictions were non-trivial from this point of view . Overall , these results also suggested that by considering different types of information in the network , we might gain alternative and complementary insights about potential targets for a query species . The most relevant and promising application of this kind of approach , is to prioritize new putative targets as interesting cases of study . To this end , we performed the procedure described above , hence taking advantage of the information contained in the network for known druggable targets across all species and analyzed the top ranked proteins for three kinetoplastids: Trypanosoma cruzi ( TCR ) , Trypanosoma brucei ( TBR ) and Leishmania major ( LMA ) ( the TriTryps [61] ) . The top 10 proteins resulting from this prioritization exercise are shown in the S3 Table . A detailed analysis of the candidate targets prioritized is not within the scope of this work . However , it is worth mentioning the finding of a number of interesting targets that have been already characterized in these parasites . As shown in S3 Table , the majority of the proteins obtained at the top of the ranking using this kind of prioritization method were mostly protein kinases , one of the largest known protein superfamilies [62] . Apart from also being a rich source of highly druggable targets , from the point of view of the network this is a protein class with strong ties ( abundant or heavy edges ) between family members ( both because of orthology and shared Pfam domains ) , and with abundant bioactivity links ( EDP edges ) due to the recognized target promiscuity of kinase inhibitors [63] . The first protein in the ranking obtained for Trypanosoma cruzi was demonstrated to interact with and phosphorylate several parasite proteins [64] , including some of the trans-sialidase family [65] . Transfection with a construct containing PKI ( inhibitor of PKA ) kills epimastigotes ( genetic experiment ) , whereas treatment with the isoquinolinesulfonamide compound H89 , a PKA inhibitor , killed 98% of the parasites within 48 hs ( pharmacologic experiment ) [64] . The 5th and 6th proteins obtained in the L . major and T . cruzi lists respectively is a casein kinase I isoform 2 . This protein has been proven to be a target for 4 inhibitors in L . major [66] . These compounds also inhibited the growth of cultured L . major promastigotes and T . brucei trypomastigotes . In another work , the L . major protein was found to be inhibited by three 2 , 3-diarylimidazo[1 , 2-a]pyridines [67] . This target was also studied in T . cruzi , where it was found to bind the compound purvalanol B [68 , 69] . Finally , the T . cruzi protein obtained in 10th place of the ranked list , TcMAPK2 , has been studied and characterized . Interestingly , this MAP kinase could not be inhibited by the mammalian ERK2 inhibitor FR180204 , raising the possibility of a differential inhibition profile , which would open the door to the development of selective inhibitors of the trypanosome vs mammalian proteins [70] . As shown in S3 Table , this kind of prioritization results in a more heterogeneous collection of protein classes at the top of the ranking . The first protein in the prioritized list of T . brucei ( listed 6th for T . cruzi ) is an inositol 1 , 4 , 5-trisphosphate receptor . Inositol triphosphate receptors are intracellular calcium release channels that play a key role in Ca2+ signaling in cells [71] . Recent work in T . brucei and T . cruzi show that this target is essential for growth and establishment of infection [72 , 73] . The 3rd protein in the prioritized list of T . cruzi is a phosphatidyl inositol 3-kinase ( PI3K ) . This protein has orthologs in several species and has 4 paralogs in humans . The PI3Ks can be divided into 3 classes ( I-III ) . The protein prioritized by our method is a class I PI3K [74] . These enzymes are inhibited at nanomolar concentrations by wortmannin , which binds to the conserved ATP binding site of PI3Ks , suggesting that the drug could be active against all three PI3K classes . The PI3K pathway is also being investigated as target for intervention in cancer [74 , 75] . Given that our method identifies these proteins as potential target in parasites , this could present an opportunity to test promising molecules found in cancer research on the parasites . In T . cruzi the treatment with wortmannin , a PI3K inhibitor , prevented the entry of parasites to the cells [76 , 77] . A class III PI3K was recently characterized in this parasite and shown to be inhibited by wortmannin and LY294000 [78] . Another protein that appeared prioritized in our list ( 6th for L . major , 9th for T . cruzi ) is the carbamoyl-phosphate synthetase II ( CPSII ) , a key regulatory enzyme of the de novo pyrimidine synthesis . This enzyme , which generates carbamoyl-phosphate from L-glutamine , bicarbonate , and two ATP molecules , is the first in the 6-enzyme cascade that catalyzes the formation of uridine 5'-monophosphate . In a recent study , a CPSII knock out strain of T . cruzi displayed significantly reduced growth ( in epimastigotes ) [79] . Also , in fibroblast infection assays with metacyclic trypomastigotes , a smaller number of intracellular amastigotes were found in the case of infection with KO parasites . These results indicate that the de novo pyrimidine biosynthesis pathway and in particular this enzyme could be important targets to block parasite replication [79] . Another target suggested by this method is a lanosterol 14α demethylase ( CYP51 , 3rdin L . major , 5thin T . brucei ) . This finding represents a special case that serves both to validate the strategy and to highlight a number of gaps in the data curation process ( see also Discussion ) . CYP51 enzymes belong to an ortholog group that contains 72 sequences , including human and trypanosomatid sequences . This protein is a cytochrome P450 that in fungi and kinetoplastid protozoa catalyzes a key biochemical step in the ergosterol biosynthesis pathway [80] . The enzyme is a known validated target for chemotherapy against T . cruzi . However , a careful analysis of the prioritized lists revealed a clear gap in the availability of curated bioactivity data: the T . cruzi enzyme was the only trypanosomatid ortholog in the network that was linked to bioactivity data ( and therefore our algorithm considered it as a seed target , and accordingly , the T . cruzi enzyme was not present in the final prioritized list ) . But a number of studies have already reported on the inhibition of the T . brucei and Leishmania enzymes with CYP51 inhibitors [81–83] . However , these data were not present in the TDR Targets and/or ChEMBL releases used to build the network . Therefore , these targets have been prioritized under the assumption that no bioactivity information was available . In this case , the target suggestions made by the network only served to identify these gaps , because the experimental work required to validate these targets and their inhibitors was already present in the literature . In drug discovery it is often the case that high-throughput phenotypic screenings are conducted on whole organisms or whole cells in culture . This is a good strategy to filter large libraries and identify reasonable "hit" compounds . However , to develop these compounds further it would be advantageous to know the target ( s ) of the compound , to gain an understanding of the mechanism of action of the drug . In this part of the work we took advantage of the information contained in the constructed network to obtain candidate targets for a given orphan compound , defined as a node in the D-layer of our network with no links to the PP-layer . We assume that these compounds have been selected based on one of the case scenarios described above ( i . e . from high-throughput phenotypic screenings ) . Such compounds ( here referred to as “orphan molecules” m ) have no links to the PP-layer but have bioactivities that meet the different specified cutoffs in Table 2 In these cases , we are interested in getting a prioritized list of putative targets for each orphan molecule m . For this , we only report here results obtained considering the G’rk network-based strategy , as the already observed bias for the G’r network-model affects the sensitivity of the corresponding prioritization results as shown in previous sections . We first proceeded by identifying the chemical similarity neighborhood of m , CSN ( m ) , taking into account molecules directly linked to m through Edd edges . Next , we considered the set of target proteins in the PP-layer that were associated to the CSN ( m ) through bioactivity annotations . These protein nodes were used as seeds for the prioritization procedure described in the previous sections . Each seed protein , sj , was associated to an initial score , wj ( see Eq ( 7 ) ) proportional to the overall chemical similarity reported between CSN ( m ) and the considered orphan compound of interest m ( see Methods ) . To validate this strategy , bioactive molecules with known targets were artificially “orphaned” by removing the bioactivity links that associated these drugs with their cognate targets . We considered a random set of 1 , 000 molecules ( out of ~105 ) with exactly one known protein target in our dataset , and assessed our ability to recover these targets in the prioritized lists after removing the corresponding bioactivity links . Under this cross-validation exercise , we first proceeded to analyze the global sensitivity of our recovery strategy . For each artificially orphaned drug m , we computed both a global ranking , rG , of putative target proteins from all available organisms in the network , and a species-specific ranking list , rSS , where the prioritized proteins come only from a single organism ( in this case the source of the original target ) . The plot in Fig 3A shows , for different thresholds l of the global rankings rG , the number of recovered targets , ρ ( rG ) , and the corresponding recovery rate , λ ( rG ) , defined as the ratio between the incremental gain in ρ , per ranking interval ( i . e . λ ( rG=l ) =Δρ ( rG ) /ΔrG|rG=l . In addition we found it useful to consider a third-order spline approximation , λ˜ ( rG ) to smooth out rapid fluctuations of λ ( rG ) . As can be appreciated in Fig 3 , the recovery rate of the original target for each compound , λ˜ ( rG ) λ˜ ( rG ) , rapidly drops converging to an asymptotic value near zero . This suggests that increasing the number of prioritized targets ( e . g . the prioritization list length ) above a given global ranking position gives on average no significant increment in the number of original targets recovered . We estimated the asymptotic recovery rate level , λ∞ , as the mean λ˜ value obtained disregarding the first 50 ranking positions , and estimated the corresponding noise level , σ , as the variance of the corresponding λ˜ values . Taking into account these quantities , we further defined an optimal list length l=rG* for which the recovery rate was significantly higher than the asymptotic value: rG*=maxlϵ[1 , 1000]{λ˜ ( l ) ≥λ∞+3σ} ( 9 ) This parameter serves to identify a global ranking range ( i . e . the r*G-top ranked molecules ) where reasonable predictions can be anticipated , in the sense that a high rate of success is expected to occur . In our cross-validation study we found that r*G = 38 . Considering this threshold level , the sought target proteins were globally ranked before r*G for ~70% of the 1 , 000 tested molecules . Fig 3B shows how these 703 targets were ranked according to the corresponding species-specific ranking lists ( rSS ) . We observed that 70% of these predicted target proteins appeared at the top three positions of the corresponding rSS ranking , and ~97% were ranked within the top 10 suggested targets . On the other hand , we observed that top-ranked target proteins for 297 out of the 1 , 000 tested molecules were globally ranked after the rG* position . For these cases we assumed that the information embedded in the network was not enough to successfully recover the original targets , as even the best predictions for the corresponding organism laid on a twilight-zone of the algorithm suggestions given the adopted threshold level . The considered threshold of 3σ , although arbitrary , represented a sensible value because , as shown in Fig 3B , the corresponding global ranking threshold , r*is found within a sharp change of regime ( i . e . an elbow ) of the recovery rate curve . In summary , our methodology was able to retrieve the correct association within experimentally affordable prioritization lists for 70% of the artificially ‘orphaned’ compounds . Noteworthy , we also introduced a metric based on the performance of recovery tasks of artificially orphaned compounds , to recognize problematic species-specific prioritization scenarios . Finally , we found it informative to analyze the way in which we were able to recover the original target in this exercise . As shown in Fig 4 there are essentially two ways in which we can guess the target of an orphan compound . The first is through a very short path in the network ( leftmost panel in Fig 4A ) , that directly connects the orphan compound with a bioactive compound that is in turn linked to the original ( artificially orphaned ) target . This was the case for 478 ( 68% ) of the 703 recovered targets . However , in 225 cases ( 32% ) the recovered target lacked direct bioactivity links to molecules that were neighbors of the orphan compound in the D-layer graph . In these cases , the corresponding target could not have been recommended without the adopted network approach ( rightmost panel in Fig 4 ) . These results thus show that the network contains redundant information that can still suggest the correct targets , with high specificity in the absence of direct bioactivity links . This performance suggests that our network model can be useful as an aid to propose experimental studies on orphan compounds . As a case study , we used the network to infer targets for compounds which presented significant activity against Plasmodium falciparum , but that did not appear listed in target-based assays in our dataset . There were 19 , 124 compounds derived from a number of recent high-throughput screenings against P . falciparum [29–31] . From this dataset , 9300 molecules were amenable to our prioritization methodology , as they had at least one neighbor drug presenting bioactivity on at least one protein target . Using the strategy described in the previous section , we were able to suggest candidate targets for 176 of these compounds when r*G = 38 ( see S4 Table ) . One example of this drug-target prediction is shown in Fig 5 . The orphan compound shown in the figure ( a benzothiazoline ) was found to be active against P . falciparum strain W2 . However its mechanism of action is currently unknown . In our network , the connectivity map of this compound , leads to the N-tetradecanoyltransferase of C . albicans . This enzyme catalyzes the N-myristoylation of proteins , in which a myristate molecule ( 14-C saturated fatty acid ) is added to the N-terminus of a glycine residue in specific target proteins [84 , 85] . We validated our prediction by doing a posteriori analysis of the literature . First , several studies show that this protein is indeed a promising target for development of new antimalarials [86–88] . Furthermore , a number of benzothiazole compounds have already been tested against the Plasmodium enzyme [88] . Interestingly , none of the compounds reported in these papers were part of our dataset , and therefore were not included in our network model ( see Discussion on data curation gaps below ) . Therefore , though similar , both the orphan compound , and the compound that has been shown to inhibit the C . albicans enzyme are different compounds . Another interesting case is shown in Fig 6 . In this case the orphan compound ( TDR Targets ID 599594 ) [29] was shown to be active at 2 μM against the wild-type P . falciparum strain 3D7 and the multidrug-resistant strain Dd2 ( 100% and 97% growth inhibition , respectively ) . In our network model this compound is connected with other active compounds , with varying levels of similarity , as shown in the figure . All these compounds are hydroxamic acid derivatives , some of which are known to inhibit bacterial peptide deformylases [89] . The most frequently used inhibitor of peptide deformylases , actinonin , was also shown to be active against P . falciparum [90] , as well as other hydroxamates [91] . Although it remains to be seen if these orphan compounds are active against this enzyme , or if they hit other cellular targets ( compounds containing the hydroxamic acid moiety often possess a wide spectrum of biological activities [92] ) , this example serves to highlight the types of target/chemical hypotheses that our network model generates . As mentioned above , the best candidate target from P . falciparum for this orphan compound was ranked in the prediction zone , under 3σ ( r*G < 38 ) . Other orphan compounds with antimalarial activity ( Fig 7 ) were connected in our network model to a Plasmodium falciparum M1 alanyl aminopeptidase ( PfA-M1 ) . This enzyme has been shown to be an essential hemoglobinase , catalyzing the final stages of hemoglobin break-down within intra-erythrocytic parasites [93 , 94] . A number of inhibitors have been described for PfA-M1 [95–98] , and some of these have been shown to control both laboratory and murine models of malaria [97] . In our network model , some of these inhibitors are part of the chemical similarity neighborhood of a series of structurally related orphans ( shown in the figure ) . Five orphan compounds ( Fig 8 ) where proposed to act through the enoyl-acyl carrier reductase ( FabI ) . This enzyme is involved in fatty acids biosynthesis type II , a pathway that is essential for correct liver stage parasites development [99] . FabI has been validated as drug target for antibacterials and antimalarials , such as triclosan , a drug that inhibits this enzyme in several species , including E . coli , M . tuberculosis , S . aureus and P . falciparum [100 , 101] . Several other compounds have been tested recently as potential inhibitors of this target in P . falciparum [99 , 102–104] and in other parasites [105]; however the suggestions made by our network model constitute novel hypotheses . In some other cases , the compounds had proposed targets that , to our knowledge , have not yet been characterized experimentally as potential drug targets in P . falciparum . This is the case of a putative 3-demethylubiquinone-9 3-methyltransferase ( PF3D7_0724300 ) , a putative 3-oxo-5-alpha-steroid 4-dehydrogenase ( PF3D7_1135900 ) , and a putative polyprenol reductase ( DFG-like protein , PF3D7_1455900 ) [106] . An exception is perhaps the putative glycerol-3-phosphate acyltransferase ( LPAAT , PF3D7_1444300 ) , an ortholog of which was recently validated as an essential gene for blood stage replication in a murine Malaria model [107] . The bioactive orphan compounds shown in S4 Table therefore can serve as potential starting points to explore the chemical space around these targets .
We and others have previously devised a number of target-centric prioritization strategies that were focused on target features with only minor integration of chemical information [26 , 27 , 108 , 109] . In these prioritizations , targets were assigned scores based on a priori defined sets of criteria by different users and different ad-hoc scoring systems for target features . In contrast , in this work we show how the availability of target-drug associations in our network model ( EDP edges , derived from curated bioactivity assays ) can be used to guide the scoring of targets ( weighting of graph edges ) through a simple statistical assessment of enrichment of seed proteins ( known targets of bioactive compounds ) for functional annotation classes ( target features ) , followed by prioritization of first-neighbors using a voting algorithm . As a result , we are now able to prioritize targets without resorting to ad-hoc hypotheses about desirable or undesirable target features . The network model ( when normalized affiliation relevance scores were considered ) showed an increased performance when compared to a simple ( naïve ) sequence similarity search against known druggable targets , ( Table 5 ) . Moreover , our methodology provides additional flexibility as two different graphs , G’r and G’rk , can be derived from the original network to perform prioritization tasks . Differences in the respective ranking lists could be understood in terms of the observed prioritization dependency on the strength of target nodes in the G’r graph . The strength of a node in a weighted graph takes into account not only its degree ( i . e . the number of connections to other adjacent nodes ) but also the weighted values of these connections . As discussed in detail in Supp . Text S1 , prioritizations based on uncorrected scores ( G’r network ) were a priori heavily driven by strong nodes . A bias towards these high-strength nodes may not be necessarily bad , as the strength reflects embedded information on functional categories enriched in links to active compounds ( initial score or weight of a seed node . In the particular case of prioritizations derived from the G’r graph , the high enrichment in targets from the highly druggable protein kinase superfamily may be a desirable outcome . In spite of this , host toxicity and inhibitor promiscuity are potential concerns in this case , as this is the largest family of druggable targets that binds to a common substrate ( ATP ) with numerous examples of inhibitors targeting several kinases at low micromolar concentrations [63] . Additionally , when considering the prospects of testing the compounds associated with these targets in whole-cell assays against other organisms , it is worth considering that perhaps because of this demonstrated promiscuity , there have been many cases of success in the identification of non-kinase targets of kinase inhibitors [110–114] . This provides a counter example of the utility of these highly biased G’r prioritizations . Finally , as shown in S2 Fig , there is a negligible overlap between the sets of recovered targets following each strategy . This result highlights the complementarity nature of the different explored prioritization methodologies suggesting that by considering different types of information , we might gain alternative and complementary insights about potential targets for a query species . Prediction of candidate targets for orphan compounds is not straightforward . Several approaches rely on chemical similarity to relate ligands to candidate targets [17 , 18] . However , this type of similarity-based strategies can only provide starting points that should be further validated experimentally . It is well known that only a fraction of chemically similar compounds ( Tanimoto coefficient > 0 . 85 ) are active against the same given target [49] . Furthermore , some compounds are able to modulate several targets [115 , 116] , introducing another layer of complexity . In our case we have taken advantage of the integrated data to connect protein targets to bioactive compounds that lack target-based assay information . Inspired by how medicinal chemists search for putative targets , we have done this by essentially prioritizing targets that are connected to the “chemical similarity neighborhood” of orphan compounds . However we believe our approach improves over current methods for deorphanizing compounds by i ) doing this in an automated and unified way ( e . g . applying the same rules and parameters for all compounds ) at a large scale; and ii ) introducing a different approach when identifying candidate pathogen targets by using a combined metric that results from the projection of 3 functional features instead of solely relying on sequence similarity ( e . g . as in the FASTA approach we performed for comparative purposes ) . Moreover we have introduced a data-driven methodology to identify a priori reliable species-specific rankings , given observed global ranks of protein targets along the entire network . Some of the connections highlighted by our model were supported by independent experimental validations as found post-facto in the literature . However , further experimentation should be carried out to test the activities of other orphan compounds ( and their analogs ) . In this context it is appropriate to bear in mind the high attrition rate that is usually associated with confirmatory assays , even when performing these on the very same pathogen species [117] . The utility of this approach lies not only in the search for new chemical leads for drug discovery , but also to identify and map tool/probe compounds [118 , 119] . Although good drugs and good tool compounds must meet different criteria [118 , 119] , we argue that particularly for neglected tropical diseases , integrative approaches that help leverage any available chemical information for advancing basic research would also have an impact in the long term in the drug discovery process . In this sense , by providing connections between orphan bioactive compounds and putative targets , our network model has the ability to propose new testable hypotheses . As part of this work we have identified some significant gaps in the curation of bioactive compounds . When looking for recent reports that could serve as a post-facto validation of our findings , we noticed a number of publications with relevant information but that pre-dated the initial data gathering exercise for this paper ( see Results ) . These represent a set of papers that passed unnoticed to a number of curation efforts . One example is the paper by Bowyer et al published in 2007 in which the authors show that a number of benzothiazoles were active against P . falciparum NMT [88] . Because these compounds were not present in our data sources , they were not included in our network model . Luckily for us , they could be used to independently validate the proposed target for one of our orphan compounds ( see Fig 5 ) . However , and perhaps more importantly , this case also helps to raise awareness of the ever important problem of manual curation of data present in the literature . Construction of our network model also required some manual curation , which represents a huge bottleneck in terms of time invested at this task . The single most laborious step in our approach has been the manual curation required to classify compounds into active vs inactive . This was necessary because bioactivity databases such as ChEMBL include negative data as well ( e . g . curated data for all assayed compounds ) . However , upon detailed scrutiny , the disparate ways and units in which bioactivities are reported ( IC50s , EC50s , Kis , %inhibition , etc . ) demanded a serious and very time consuming curation effort . This is the main reason limiting the number of links between the D-layer and the PP-layer in our network model . Adding more proteomes ( and calculating their annotation-type affiliations ) , or more compounds ( and calculating their substructure and similarity relationships ) , is just a matter of throwing more computational resources at the problem . However , increasing the number of links between targets and compounds still requires a heavy investment in data curation . Another critical issue in our network model that was directly related to this data curation gap was the definition of active vs inactive compounds in cases where the activity of a compound was reported as a relative measure ( e . g . a percentage ) of a defined outcome . We have decided to use 80% activity as a cutoff ( see Methods ) , but we are aware of many examples in the TDR Targets and ChEMBL databases where activity >80% is due to compounds tested at concentrations that exceed reasonable or physiological concentrations . But because this information is present in the textual descriptions of the assays ( and not as part of a separately queryable field ) , either a big investment in manual curation or in the use of natural language processing of these data is required to further extract and correct for these cases . During data curation we accepted all compounds with >80% activity , in whatever assay was performed , and we only checked the concentrations of the inhibitors used in a case by case basis for the examples shown in the figures . The network model developed in this work can certainly be expanded further , connecting more targets from other proteomes of interest , and connecting more compounds . We have already identified recent datasets listing bioactivities of new and existing compounds ( DNDi Chagas and Human African Trypanosomiasis screenings , GSK TCAMS Tuberculosis and Chagas HTS , among others ) . These are already in the public domain [45 , 120] . We are also working to expand the TDR Targets resource to include more pathogen genomes , including a number of helminths causing important human diseases , such as Echinococcus spp . ( Hydatid disease ) [121] , Loa loa ( loiasis ) [122] , Fasciola hepatica [123] , and other protozoan pathogens such as Trichomonas vaginalis [124] and Giardia [125 , 126] . This would allow scientists interested in these pathogens to take advantage of the integrated chemogenomics datasets in the network to prioritize candidate targets and compounds for these diseases . Finally , although theoretically the model can also be expanded to include other types of affiliation-type annotations , or relations , these would have to be amenable to obtain from scalable computational analyses , in order to avoid the curation bottleneck . For example , one of the most valuable query types supported by TDR Targets is based on integration of phenotypic annotations ( e . g . ‘is the target essential for the cell ? ’ ) . These functional genomics data are mostly derived from genome-wide experiments ( knockouts or knockdowns ) . However , it takes a sustained curation effort to identify , and integrate these data for all the genomes of interest . Our network model provides a way to query large chemogenomics datasets by integrating data from both phenotypic and target-based screening strategies . As a result , we enable a cohesive view of these different approaches to drug discovery . Once built , the network can sustain fast queries on these diverse data types and a simple rationalized navigation through the connected drug-target space .
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Neglected tropical diseases are human infectious diseases that are often associated with poverty . Historically , lack of interest from the pharmaceutical industry resulted in the lack of good drugs to combat the majority of the pathogens that cause these diseases . Recently , the availability of open chemical information has increased with the advent of public domain chemical resources and the release of data from high throughput screening assays . Our aim in this work was to make use of data from extensively studied organisms like human , mouse , E . coli and yeast , among others , to prioritize and identify candidate drug targets in neglected pathogen proteomes , and drug-like bioactive molecules to foster drug development against neglected diseases . Our approach to the problem relied on applying bioinformatics and computational biology strategies to model large datasets spanning complete proteomes and extensive chemical information from publicly available sources . As a result , we were able to prioritize drug targets and identify potential targets for orphan bioactive drugs .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2016
|
A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases
|
Regulatory T cells ( Tregs ) play a cardinal role in the immune system by suppressing detrimental autoimmune responses , but their role in acute , chronic infectious diseases and tumor microenvironment remains unclear . We recently demonstrated that IFN-α/β receptor ( IFNAR ) signaling promotes Treg function in autoimmunity . Here we dissected the functional role of IFNAR-signaling in Tregs using Treg-specific IFNAR deficient ( IFNARfl/flxFoxp3YFP-Cre ) mice in acute LCMV Armstrong , chronic Clone-13 viral infection , and in tumor models . In both viral infection and tumor models , IFNARfl/flxFoxp3YFP-Cre mice Tregs expressed enhanced Treg associated activation antigens . LCMV-specific CD8+ T cells and tumor infiltrating lymphocytes from IFNARfl/flxFoxp3YFP-Cre mice produced less antiviral and antitumor IFN-γ and TNF-α . In chronic viral model , the numbers of antiviral effector and memory CD8+ T cells were decreased in IFNARfl/flxFoxp3YFP-Cre mice and the effector CD4+ and CD8+ T cells exhibited a phenotype compatible with enhanced exhaustion . IFNARfl/flxFoxp3YFP-Cre mice cleared Armstrong infection normally , but had higher viral titers in sera , kidneys and lungs during chronic infection , and higher tumor burden than the WT controls . The enhanced activated phenotype was evident through transcriptome analysis of IFNARfl/flxFoxp3YFP-Cre mice Tregs during infection demonstrated differential expression of a unique gene signature characterized by elevated levels of genes involved in suppression and decreased levels of genes mediating apoptosis . Thus , IFN signaling in Tregs is beneficial to host resulting in a more effective antiviral response and augmented antitumor immunity .
Regulatory T cells ( Tregs ) are a subset of CD4+ T cells , which express the transcription factor Foxp3 , and are critical in forestalling both self- and non-self-reactive immune responses [1 , 2] . Tregs primarily mediate their suppressive function by targeting conventional effector T cell activation and differentiation , mainly by decreasing the functional activity of antigen presenting cells ( APCs ) [3] . The critical role of Tregs in autoimmunity is best observed in scurfy mice or patients with IPEX syndrome that are completely deficient in Tregs and succumb to systemic autoimmune disease at a young age . While Tregs must control the activation of T effector cells to prevent autoimmunity , it is also clear that enhanced activation of Tregs may result in the inhibition of host immunity directed against microbes ( virus , bacteria , protozoa , fungi and helminth ) or tumors leading to poor antimicrobial or antitumor immune response with the persistence of pathogens , and defective tumor immunity [4–6] . Many animal models of bacterial infection are characterized by the expansion of Foxp3+ Tregs including Listeria monocytogenes , Salmonella enterica , and Mycobacterium tuberculosis infections and the suppressive function of Tregs can result in increased bacterial load with systemic tissue invasion [7–9] . Similarly in viral infection , higher frequencies of Tregs are associated with enhanced titers of Hepatitis C virus RNA and Dengue virus [10 , 11] . Paradoxically , Tregs have been described to play an early protective role in local infection in animals models of Herpes simplex virus 2 and West Nile virus [12 , 13] . During early phases of human immunodeficiency virus infection , Tregs have been postulated to control virus replication in target CD4+ T cells [14] . On the other hand Tregs may play an important beneficial role in preventing exuberant inflammatory responses during infection with parasites such as Pneumocystis carinii [15] and Schistosoma mansoni [16] . Similarly , Tregs protect the host from parasitic infections such as Plasmodium sp . , Toxoplasma gondii , as well as infection with the fungus , Candida albicans [17–19] . These complex roles played by Tregs during acute and chronic microbial infections necessitate a delicate balance between the Foxp3+ Tregs and effector T cells to mount effective immune responses against pathogens without the induction of destructive autoimmunity . The immune response towards viruses and intracellular bacteria are mediated by type I interferons ( IFNs ) which control the replication of pathogens within host cells . IFNs are members of a multi-gene family of cytokines , which encode IFN-α and IFN-β . Both IFN-α and IFN-β signal through a shared common heterodimeric receptor IFN-α/β receptor ( IFNAR ) composed of IFNAR1 and IFNAR2 [20] . The interactions of IFNs with the IFNAR mediates activation of Janus family protein kinases to induce the phosphorylation of signal transducer and activator of transcription ( STAT ) . The canonical pathway of Type I IFN signaling is initiated by phosphorylation of STATs ( STAT1 , STAT2 ) , induction of IFN-regulatory factor-9 , resulting in the formation of a tri-molecular complex , IFN-stimulated gene factor-3 , which translocates into the nucleus to induce transcription of IFN-stimulated genes through binding of IFN-stimulated response elements [21] . Additionally IFNAR signaling can trigger non-canonical pathways such as activation of γ-activated sequences through homodimerization of STATs ( STAT1 , STAT3 , STAT4 , STAT5 , STAT6 ) , phosphoinositide-3-kinase/mammalian target of rapamycin pathway , and mitogen-activated protein kinase pathway [22] . IFNs may mediate an array of host protective functions including restricting viral replication [23] , activation of NK cell cytotoxicity , maturation of APCs , clonal expansion and survival of antigen-specific CD4 and CD8 T cells during viral infection , promotion of B cell responses , and induction of apoptosis [24–30] . Type I IFNs have proven to be clinically useful in the treatment of chronic viral infections and certain types of leukemias [31] . Detrimental effects of type I IFNs have also been extensively documented during viral infections as well as during bacterial , fungal and parasitic infections [32] . One of the best examples of the complex regulation of antiviral immunity by type I IFNs is lymphocytic choriomeningitis virus infection ( LCMV ) . Blockade of IFN signaling in acute infection with LCMV Armstrong infection results in abrogation of CD8+ T cell responses and defective control of infection [33] . In contrast , blockade of IFN signaling during persistent LCMV Clone ( Cl ) -13 infection diminished immunosuppressive signals and decreased levels of IL-10 and PD-L1 expressing immunoregulatory DCs . Virus titers in both serum and kidneys were also reduced . The cell type ( s ) mediating the immunosuppressive effects of IFN have not been defined [33 , 34] . Studies on the effects of type I IFNs on Treg function yielded conflicting results [35 , 36] and have not used experimental systems to examine the direct effects of IFNs on Treg cell homeostasis and functions . Recently , Srivastava et al ( 2014 ) demonstrated that mice infected with LCMV Armstrong manifested a decrease in the absolute numbers of splenic Tregs between days 4 and 7 post infection and that this reduction correlated with the expansion of both CD4+ and CD8+ T effector cells which peak on day 7 post infection . Furthermore , they also demonstrated a selective depletion of wild type ( WT ) Tregs on day 7 post infection of mixed bone marrow chimeras between WT mice and mice with a global deletion of IFNAR ( IFNAR-/- ) . This latter result is difficult to interpret as our recent studies [37] have shown that IFNAR-/- Tregs in such chimeric ( IFNAR-/- x WT ) mice are at a competitive disadvantage as are IFNAR-/- Tregs in heterozygous female IFNARfl/fl x Foxp3Cre/WT mice . In this study , we used IFNARfl/fl x Foxp3YFP-Cre mice to determine the role of IFNAR signaling specifically in Tregs during acute and chronic LCMV infection as well as in models of colon adenocarcinoma and melanoma . We demonstrate that IFNAR signaling in Tregs during the course of both acute and chronic viral infection results in a decrease in their activation status and a decrease in their suppressive function in vivo . The hypersuppressive state of Tregs in the absence of IFNAR signaling results in decreased CD8+ effector T cells , enhanced T effector cell exhaustion , defective generation of antiviral memory CD8+ T cells , and enhanced LCMV persistence . Similarly , in the tumor models , enhanced tumor growth and failure to efficiently generate antitumor T effector cells were observed in the absence of IFNAR signaling in Tregs . The enhanced suppressor function in the absence of IFNAR signaling in Tregs was accompanied by the induction of a gene expression pattern which was similar in the acute and chronic infection models and may be responsible for the heightened suppressor function .
Studies performed by Srivastava et al . ( 2014 ) , provided preliminary evidence that IFNAR signaling inhibits the function of Tregs during an acute LCMV infection and that the absence of this inhibitory effect resulted in enhanced Treg function and impaired antiviral effector T cell function . Because this study did not definitively prove that the target of the suppressive function of IFNAR signaling was the Foxp3+ Treg , we generated Treg-lineage specific IFNAR deficient mice by crossing IFNARfl/fl mice with Foxp3YFP-Cre mice . We confirmed that the IFNAR was specifically deleted in CD4+Foxp3+ Tregs and not in CD4+Foxp3- T cells , CD8+ T cells or B220+ B lymphocytes ( S1A Fig ) . First , we compared the clearance of LCMV Armstrong from the sera of IFNARfl/fl , IFNARfl/fl x Foxp3YFP-Cre , and IFNAR-/- mice at early time points post-infection . We observed that IFNARfl/fl x Foxp3YFP-Cre mice showed significantly higher viral titers ( D3 , D7 and D10 ) than IFNARfl/fl mice , and as expected IFNAR-/- mice had the highest titers among the three groups [33 , 38] ( Fig 1A ) . However , IFNARfl/fl x Foxp3YFP-Cre mice cleared LCMV Armstrong on day 14 post-infection . This result is consistent with the studies of Srivastava et al . ( 2014 ) suggesting that the responses of the antiviral effector T cells early during LCMV Armstrong infection are compromised . Indeed , while both the frequencies and absolute numbers of CD8+CD44+ T cells specific for GP33-41 and NP396-404 did not differ between IFNARfl/fl and IFNARfl/fl x Foxp3YFP-Cre mice on day 14 post-infection ( Fig 1B and 1C ) , the production of the effector cytokines IFN-γ and TNF-α was markedly diminished ( Fig 1E and 1F ) . While the frequency and absolute number of CD8+CD44+ T cells specific for GP276-286 were increased , the frequency of IFN-γ producing cells recognizing GP276-286 was still reduced ( Fig 1D and 1G ) . We did observe a modest decrease in the frequency , but not absolute numbers of CD4+Foxp3-CD44+ T cells specific for LCMV GP66-76 ( Fig 1H ) and this was accompanied by a marked decrease in the production of both IFN-γ and TNF-α by the GP66-76 specific cells ( Fig 1I ) . Taken together , these studies are consistent with the possibility that the absence of signaling via the IFNAR in Tregs during LCMV Armstrong infection potentiated their suppressive activity resulting in a failure to fully activate LCMV-specific T effector cells [39] . We observed that Treg cell numbers from infected WT and IFNARfl/fl x Foxp3YFP-Cre mice on day 4 and day 5 are similar and that Treg cells from both the WT and IFNARfl/fl x Foxp3YFP-Cre mice decrease similarly on day 7 post-infection ( S1B Fig ) . While Srivastava et al ( 2014 ) reported a marked decrease in WT Foxp3+ Tregs on day 7 post infection in mixed bone marrow chimeras , we did not observe a decrease in Tregs on day 5 and the reduction in Treg frequencies and absolute numbers on day 7 was seen in both IFNARfl/fl and IFNARfl/fl x Foxp3YFP-Cre mice ( S1B Fig ) . In contrast , Foxp3+ Tregs frequencies and numbers were increased on day 14 post LCMV Armstrong infection in IFNARfl/fl x Foxp3YFP-Cre mice . Most notably , the percentages and absolute numbers of activated Tregs were increased in IFNARfl/fl x Foxp3YFP-Cre mice compared to IFNARfl/fl mice on day 5 , 7 and 14 post Armstrong infection ( S1C Fig ) . In addition to elevated levels of CD44 , Tregs in IFNARflf/fl x Foxp3YFP-Cre mice also expressed higher percentages of other activation markers , including Ki-67+ , ICOS+ and TIGIT+ ( S1D and S1E Fig ) , consistent with an activated phenotype and greater degree of proliferation at day 5 post Armstrong infection . We did not see any differences in the frequencies of activated CD4+Foxp3- and CD8+ T cells ( S1F Fig ) in IFNARfl/fl x Foxp3YFP-Cre mice . The role of Tregs in the maintenance of chronic viral infection and effector T cell exhaustion has been difficult to define as it has been technically challenging to specifically deplete Tregs without the induction of autoimmune disease [40–42] . To evaluate the role of IFNAR signaling in Tregs during persistent chronic viral infection , mice were infected with LCMV Cl-13 . We initially examined viral titers by plaque assay in serum at different time points during infection . On days 8 , 25 , 35 and 43-post infection , IFNARfl/fl x Foxp3YFP-Cre mice had significantly higher viral titers compared to IFNARfl/fl mice , and as expected IFNAR-/- mice had significantly higher titers than IFNARfl/fl mice ( Fig 2A ) . Notably , both the lungs and kidneys of IFNARfl/fl x Foxp3YFP-Cre mice on day 46 post infection had significantly higher viral titers than IFNARfl/fl controls ( Fig 2B ) . These data indicate that IFNAR deficiency specifically in Tregs enhances LCMV persistence . The persistence of Cl-13 infection among IFNARfl/fl x Foxp3YFP-Cre mice led us to examine the kinetics and activation of Tregs during chronic LCMV infection . The frequencies and absolute numbers of Tregs were higher in IFNARfl/fl x Foxp3YFP-Cre mice on day 25-post infection , but not on day 46-post infection ( Fig 2C ) . However , the activation state of the Tregs as measured by CD44 expression was higher on both days 25 and 46 in IFNARfl/fl x Foxp3YFP-Cre mice compared to IFNARfl/fl mice ( Fig 2D ) . In contrast , no significant differences were observed in the frequencies or absolute numbers of CD4+Foxp3- or CD8+ T cells and their levels of CD44 expression on day 25 post-infection; however , on day 46 post-infection , the percentages of CD4+Foxp3-CD44hi T cells were higher in IFNARfl/fl x Foxp3YFP-Cre mice ( S2A–S2D Fig ) . Furthermore , Cl-13 infected IFNARfl/fl x Foxp3YFP-Cre mice exhibited greater morbidity as manifest by a greater reduction in body weight than IFNARfl/fl mice ( S2E Fig ) . Taken together , these results demonstrate similar to acute infection , failure of signaling via the IFNAR in Tregs results in enhanced Treg activation accompanied by decreased viral clearance . To determine if the enhanced Treg activation and diminished viral clearance in Cl-13 infected IFNARfl/fl x Foxp3YFP-Cre mice results in decreased antiviral T effector cell responses , we examined the LCMV-specific responses of effector T cells . On day 25-post infection , both the absolute numbers of GP33 and NP396 tetramer positive T cells were similar ( Fig 3A and 3B ) , while the frequencies of IFN-γ and TNF-α producing cells were lower ( Fig 3C and 3D ) . However , on day 46-post infection , the absolute numbers of both antigen-specific CD8+ T cells were significantly decreased ( Fig 3A and 3B ) and this was accompanied by a marked decrease in the frequencies and absolute numbers of IFN-γ and TNF-α producing cells ( Fig 3C and 3D ) . A moderate increase in the absolute number of CD4+Foxp3-CD44+GP66 Tet+ T cells frequencies was observed in the IFNARfl/fl x Foxp3YFP-Cre mice on day 46-post infection , but not on day-25 post infection ( S3A Fig ) . However , only low levels of IFN-γ and TNF-α were produced and no differences were observed in cytokine production by CD4+Foxp3-CD44+GP66 Tet+ T cells among IFNARfl/fl and IFNARfl/fl x Foxp3YFP-Cre mice on both day 25 and 46-post infection ( S3B Fig ) . Thus , decreased IFNAR signaling in Tregs resulted in reduced number and frequencies of CD8+ virus specific IFN-γ and TNF-α producing cells . High levels of PD-1 expression are one of the hallmarks of T cell exhaustion . On both days 25- and 46-post infection , the frequency of PD1 expressing CD8+ and CD4+Foxp3- T cells were higher in IFNARfl/fl x Foxp3YFP-Cre mice ( Fig 4A and 4B ) . Two other markers of T cell exhaustion , the transcription factor eomesodermin ( EOMES ) , and CD39 can be co-expressed with PD-1 on exhausted T cells [43 , 44] . Higher percentages and absolute numbers of EOMES+PD-1+ cells within the CD8+ and CD4+Foxp3- populations were present in the IFNARfl/fl x Foxp3YFP-Cre mice ( Fig 4C and 4D ) . Correspondingly , PD1+CD39+ frequencies and total numbers were higher in gated CD8+ T cells from IFNARfl/fl x Foxp3YFP-Cre mice ( Fig 4E ) . While the frequencies of gated CD4+Foxp3-PD1+CD39+ T cells did not differ between IFNARfl/fl and IFNARfll/fl x Foxp3YFP-Cre mice , the absolute numbers of CD4+Foxp3-PD1+CD39+ T cells were higher in Treg-specific IFNAR deficient mice ( Fig 4F ) . Similarly , the frequencies of PD-1+ T cells were greater among gated CD8+CD44+GP33 and CD8+CD44+GP276 Tet+ T cells in IFNARfl/fl x Foxp3YFP-Cre mice ( Fig 4G and 4H ) . CD8+CD44+NP396 Tet+ and CD4+Foxp3-CD44+GP66 Tet+ populations from day 46 Cl-13 infected IFNARfl/fl x Foxp3YFP-Cre mice also had higher proportions of PD1 expressing cells ( S4A and S4B Fig ) . In addition , it has been demonstrated that Tregs with higher levels of PD1 expression can mediate enhanced suppression in LCMV infection [45] , we also found that Tregs from Cl-13 infected IFNARfl/fl x Foxp3YFP-Cre mice had significantly higher expression of PD1 than controls on days 25 and 35 post infection ( S4C Fig ) . These data demonstrate that the enhanced Treg suppression seen in the absence of IFNAR signaling during Cl-13 infection results in markedly reduced cytokine production by virus-specific CD8+ T cells as well as a phenotype consistent with exhaustion . Exhausted CD8+ T cells have reduced memory cell potential which is secondary to higher LCMV antigen persistence in infected mice [46] . To determine whether the enhanced T cell exhaustion phenotype observed in IFNARfl/fl x Foxp3YFP-Cre mice is associated with a reduction in the formation of virus-specific memory T cells , we examined the levels of expression of three memory cell makers ( CD62L , CD127 , CXCR3 ) on gated CD8+CD44+ GP276 Tet+ T cells ( Fig 5A ) . The frequencies and the absolute numbers of all three memory populations were reduced in IFNARfl/fl x Foxp3YFP-Cre mice on day 46 post infection compared to IFNARfl/fl control mice ( Fig 5B–5D ) . Similar results were seen within the CD8+CD44+GP33 Tet+ population ( S5A–S5D Fig ) . While the number of memory CD8+ T cells is usually inversely correlated with terminally differentiated T cells as measured by KLRG-1 expression [47] , the frequencies and absolute numbers of CD8+CD44+GP276/GP33 Tet+ KLRG-1+ T cells were also lower in IFNARfl/fl x Foxp3YFP-Cre mice ( Fig 5E and S5E Fig ) . We further examined the protective capacity of memory CD8+ T cells by re-infecting the day 30 Armstrong infected mice with Cl-13 virus . On day 5 post Cl-13 infection , IFNARfl/fl x Foxp3YFP-Cre mice had reduced frequencies and numbers of CD8+CD44+NP396 Tet+ cells , and in addition GP33- and GP276-stimulated CD8+CD44+ T cells from IFNARfl/fl x Foxp3YFP-Cre infected mice produced significantly less Granzyme B ( GrB ) positive and GrB/IFN-γ double positive cells compared to CD8+ T cells from control mice ( Fig 5F and 5G ) , however IFN-γ positive cells are tended to be more in infected IFNARfl/fl x Foxp3YFP-Cre mice but they are not significant compared to control mice . Collectively , these results demonstrate that the higher load of virus is associated with a defect in the generation of virus-specific memory T cells in the absence of IFNAR signaling in Tregs . In order to better understand the molecular basis for the enhanced activation and suppressive function of Tregs from Treg-specific IFNAR-deficient mice during acute and chronic LCMV infection , we performed high-throughput RNA sequencing on sorted CD4+YFP+ Tregs isolated from day 5 Armstrong-infected Foxp3YFP-Cre and IFNARfl/fl x Foxp3YFP-Cre mice . Principal component analysis ( PCA ) showed distinct clustering of Tregs from Foxp3YFP-Cre mice relative to Tregs from IFNARfl/fl x Foxp3YFP-Cre mice ( Fig 6A ) . A total of 586 genes were significantly differentially expressed ( 249 genes were down , and 337 genes were up ) in IFNARfl/fl x Foxp3YFP-Cre mice ( fold change 1 . 5 and above , adjusted P < 0 . 05 ) ( Fig 6B ) . Among the 586 genes , 174 genes were identified in the interferome database [48] ( interferome . its . monash . edu . au ) as IFN-signaling related ( fold change 1 . 5 and above , adjusted P < 0 . 05 ) ( S6A Fig ) , and were excluded from further analysis . We elected to exclude IFNAR regulated genes in order to perform an unbiased downstream analysis , as IFNAR signaling regulates the transcription of up to 2000 genes . The remaining 412 differentially expressed genes were exclusively non-IFN related . Of these , 156 genes were upregulated in infected Foxp3YFP-Cre mice , and 256 genes were upregulated in infected IFNARfl/fl x Foxp3YFP-Cre mice . Gene set enrichment analysis ( GSEA ) of the 412 non-IFN related genes revealed that the natural Treg vs conventional T cell gene set was enriched to a greater extent in IFNARfl/fl x Foxp3YFP-Cre mice [36 genes out of 42 were in core enrichment , Enrichment score ( ES ) : 0 . 566 , P < 0 . 01 , FDR:0 . 0] ( Fig 6C ) . We observed that 32 out of 412 non-IFN related genes were differentially expressed ( fold change 1 . 5 and above , adjusted P < 0 . 05 , genes normalized by z-score; 24 genes in IFNARfl/fl x Foxp3YFP-Cre mice and 8 genes in Foxp3YFP-Cre mice were upregulated ) and could be classified as Treg-signature genes as previously reported [49 , 50] ( Fig 6D ) . Representative upregulated genes in IFNARfl/fl x Foxp3YFP-Cre mice include Areg , Arhpag20 , Bub1b , Ccl12 , Ccr5 , Il1r1 , Mki67 ( Ki67 ) , Ncf1 , Nrp2 , Tnfrsf9 ( CD137 ) , Tcf19 , Uhrf1 , and Wnt3; representative downregulated genes in IFNARfl/fl x Foxp3YFP-Cre include Cybb , Dapl1 , Fam160a1 , Il1r2 , and Tnfsf8 ( CD153 ) . Some of the above upregulated genes from Tregs include Areg , Ccl12 , Mki67 , Ncf1 , Tnfrsf9 , Uhrf1 are well characterized to modulate the enhanced Treg suppressive and proliferative function [49 , 50] . Further , we also performed ingenuity pathway analysis ( IPA ) for non-IFN related genes which resulted in 45-top canonical pathways ( adjusted p value < 0 . 1 ) ( S6B Fig ) . Specifically , cell cycle: G2/M DNA damage checkpoint regulation pathway ( genes involved: Aurka , Ccnb2 , Cdk1 , and Top2a ) , cyclins and cell cycle regulation pathway ( genes involved: Ccnb2 , Ccne2 , Cdk1 , and E2f1 ) are enriched positively in IFNARfl/fl x Foxp3YFP-Cre Tregs compared to Tregs from Foxp3YFP-Cre mice , suggesting that cell cycle genes are more functional in Treg-specific IFNAR deficient mice . Furthermore , the c-AMP mediated signaling pathway ( genes involved: Akap1 , Camk2b , Chrm4 , Crem , Fpr1 , Prkar1b , and Ptger3 ) is also enriched positively in IFNAR deficient Tregs . Through IPA , we analyzed non-IFN related genes for top networks based on co-expression , transcription factor binding site predictions and protein-protein interactions . The top two networks identified included cell cycle , DNA replication , recombination , repair , cancer; and cellular movement , hematological system development and function and immune cell trafficking ( S6C Fig ) , differential expression of these associated genes in the pathways are shown ( S1 and S2 Tables ) . Some of the associated genes in the networks include , transcription factors: Depdc1 , E2f1 , E2f8 , Foxm1 , Mybl2 , and Uhrf1 are downregulated , and pydc4/Ifi16 ( interferon gamma inducible protein 16 ) is upregulated in Tregs from Foxp3YFP-Cre mice; cell cycle kinases: Ccnb2 , Aurkb , and Chek1 are also downregulated in Foxp3YFP-Cre mice Tregs; immune cell genes such Tnfrsf9 ( CD137 ) , Ccl2 , Ccr5 , and Il1r1 are downregulated , in contrast C5ar1 , CD19 , Il1r2 , Itga2b ( CD41 ) , Ly6c1 , and Tlr7 are upregulated in Foxp3YFP-Cre mice Tregs . We also tested whether the reduced cell cycle gene signature in Tregs from Foxp3YFP-Cre mice contributed to a greater degree of apoptosis , but Active caspase-3 staining showed no significant increase in the staining of Tregs from day 5 Armstrong infected Foxp3YFP-Cre mice compared to Tregs from IFNARfl/fl x Foxp3YFP-Cre mice ( S6D Fig ) . In parallel , we also performed RNA sequencing on Tregs from day 25 post LCMV Cl-13 infection . PCA showed less distinct clustering ( Fig 6E ) , and surprisingly , only 36 genes were significantly differentially expressed ( 23 genes were downregulated , and 13 genes were upregulated in IFNARfl/fl x Foxp3YFP-Cre mice , fold change 1 . 5 and above , adjusted P < 0 . 05 ) in Tregs from Foxp3YFP-Cre and IFNARfl/fl x Foxp3YFP-Cre mice ( Fig 6F ) . Among those differentially expressed genes , 14 genes were identified in the interferome database [48] as IFN-signaling related ( fold change 1 . 5 and above , adjusted P < 0 . 05 ) ( S7A Fig ) . Of the remaining 22 genes , 11 genes were upregulated in their expression in Tregs from Foxp3YFP-Cre mice and IFNARfl/fl x Foxp3YFP-Cre mice , respectively ( Fig 6G ) . Additionally , IPA for non-IFN related genes resulted in 18-top canonical pathways ( adjusted p value < 0 . 1 ) ( S7B Fig ) , importantly , c-AMP mediated signaling pathway ( genes involved: Akap1 , and Camk2b ) is enriched positively in Cl-13 infected IFNARfl/fl x Foxp3YFP-Cre mice Tregs , this was shown similar pattern in Armstrong infected IFNARfl/fl x Foxp3YFP-Cre mice . One of the top networks for non-IFN related genes include lipid metabolism , molecular transport and small molecule biochemistry ( S7C Fig ) . Few of the associated genes in the network include , kinases: Camk2b , and Hunk and cytoplasmic enzymes: Cpta1 , and Scpep1 are down regulated , while proapoptotic factor Erdr1 is upregulated in Foxp3YFP-Cre mice Tregs . We identified fourteen genes ( fold change 1 . 5 and above , adjusted P < 0 . 05 , normalized by z-score ) differentially expressed in Tregs from LCMV Armstrong infected mice which were similarly differentially expressed in Tregs from LCMV Cl-13 infected mice including 7 that were up- and 7 down-regulated ( Fig 6G and 6H ) . We further validated the differential expression of some of these non-IFN related genes during chronic infection which are common to both infection model or unique to chronic infection alone by quantitative real-time PCR ( S7D Fig ) . Several of the upregulated genes include a-kinase anchoring protein 1 ( Akap1 ) , calcium/calmodulin-dependent protein kinase II b ( Camk2b ) , Hormonally upregulated Neu-associated kinase ( Hunk ) , Rab4a and Rasgrf2 . Akap1 is associated with cAMP signaling , and it can act as a gap junction protein in facilitating the transfer of cAMP from Treg to effector T cells leading to inhibition of T cell receptor ( TCR ) signaling [51 , 52] . Furthermore , CamK2b , Hunk , Rab4a and Rasgrf2 have also been implicated in enhancement of Treg function [53–57] . Taken together , all these upregulated genes participate in heightened Treg suppressive function observed in the Tregs from IFNARfl/fl x Foxp3YFP-Cre mice during both acute and chronic LCMV infections . Enhanced Treg cell function is very well documented in various tumor models and it has been associated with a poor prognosis [6] . To determine whether the absence of IFNAR signaling was associated with enhanced Treg suppression in a non-infectious setting , we utilized the mouse colon adenocarcinoma MC38 and mouse B16 . F10 melanoma models . IFNARfl/f x Foxp3YFP-Cre mice showed higher tumor incidence ( MC38: n = 11/11 , 100%; B16 . F10: n = 5/5 , 100% ) and significantly increased volume than IFNARfl/fl mice ( MC38: n = 8/10 mice , 80% , B16 . F10: n = 4/5 , 80% ) ( Fig 7A , left and right panels ) . Tregs and CD4+Foxp3- cells isolated from tumor infiltrating lymphocytes ( TIL ) showed comparable frequencies in both strains of mice , however CD8+ T cell frequencies from TIL of IFNARfl/fl x Foxp3YFP-Cre mice were increased . Nevertheless , both CD4+Foxp3- and CD8+ T cells from IFNARfl/fl x Foxp3YFP-Cre mice tended to proliferate less as assayed by Ki-67 expression ( S8A–S8C Fig ) . Importantly , Tregs from IFNARfl/fl x Foxp3YFP-Cre mice TIL expressed significantly higher levels of CD44 , enhanced proliferation and expression of PD-1 ( Fig 7B ) . Conversely , both CD4+Foxp3- and CD8+ TIL from IFNARfl/fl x Foxp3YFP-Cre mice expressed lower levels of CD44 and markedly reduced levels of IFN-γ and TNF-α production compared to TIL from IFNARfl/fl mice ( Fig 7C: gated on CD4+Foxp3- TILs and Fig 7D: gated on CD8+ TILs ) . These data strongly suggest that Tregs in TIL from IFNARfl/fl x Foxp3YFP-Cre mice have enhanced suppressor activity in the tumor microenvironment and the phenotype of these Tregs within TIL closely resembles the activated hypersuppressive phenotype observed during acute and chronic LCMV infections .
Tregs mediate a multifaceted role in modulating the immune response to acute and chronic infectious agents . While their beneficial effects in decreasing immune pathology during the resolution phase of many infections is clear , Tregs can also mediate immune suppression resulting in pathogen persistence . During viral infections , rapid activation of the innate immune system generates inflammatory signals that can initially control the infection and ultimately influence the quality and magnitude of the adaptive antiviral effector T cell response . The best characterized innate inflammatory signals are the type I IFNs . During LCMV infection type I IFNs are produced in large quantities immediately following viral infection by plasmacytoid DCs as well as virus infected cells and primarily exert their effect on CD8+ T cells by extending their survival . In this report , we have demonstrated that type I IFNs can also exert beneficial effects by acting on Tregs to down-modulate their suppressive functions both early during the course of acute LCMV Armstrong infection and also later during virus persistence in chronic Cl-13 infection . Srivastava et al . ( 2014 ) , have previously examined the effects of type I IFN on Tregs during the course of acute LCMV infection . They concluded that type I IFNs down-modulated Treg function but postulated that the effects of type I IFNs were secondary to a selective decrease in the number of highly suppressive effector Tregs , and secondary to the pro-apoptotic and anti-proliferative actions of type I IFNs early in the course of infection . The major difficulty in the interpretation of this study is that the experimental model they used did not allow them to selectively examine the effects of IFNs on Tregs in the absence of its effects on other cell types . Similarly , one previous study also showed that Tregs were reduced in infected wild type compared to control mice during first week post LCMV-Docile infection , but Tregs expanded to a greater extent from the second weeks onwards . Treg expansion was more pronounced in IL-21R deficient mice , suggesting IL-21 signaling restricts proliferation of Tregs during LCMV infection [58] . The availability of mice with a conditional deletion of the IFNAR in Tregs allowed us to dissect the mechanistic basis of IFNAR signaling in Tregs resulting in their reduced suppressive function and in more efficient antiviral and antitumor immune responses . Similar to the previous study [39] , we found that the generation of antigen-specific CD8+ and CD4+ T cells was comparable in Treg-specific IFNAR-deficient mice and WT controls during acute LCMV infection , but that both the virus-specific CD8+ and CD4+ T cells in IFNARfl/fl x Foxp3YFP-Cre mice produced markedly reduced amounts of IFN-γ and TNF-α accompanied by a slower rate of viral clearance than the controls . Most importantly , we did not observe a decrease in the percentages or absolute numbers of Tregs in the WT control mice that differed from IFNARfl/fl x Foxp3YFP-Cre mice on day 4 or 5 post-infection . We did detect a decrease in Tregs in the IFNARfl/fl X Foxp3YFP-Cre mice on day 7 post-infection , but we observed an identical decrease in Tregs in the control IFNARfl/fl mice . In contrast to the loss of memory/effector Tregs observed in WT mice by Srivastava et al . ( 2014 ) , we observed an enhanced percentage of memory/effector Treg as defined by CD44 expression on days 5 , 7 and 14 post-infection in IFNARfl/fl x Foxp3YFP-Cre mice , as well as higher levels of expression of Ki-67 , ICOS and TIGIT . Taken together , our results are most consistent with an enhanced suppressive phenotype of Tregs in the absence of IFNAR signaling in acute virus infection albeit the mice ultimately cleared the infection . We observed a similar but more profound suppressive phenotype in IFNARfl/fl x Foxp3YFP-Cre mice following Cl-13 infection , as the mice had higher serum titers of virus and also had higher viral titers in lungs and kidneys for as long as 46 days post infection . We observed decreased numbers of antiviral antigen-specific CD8+ T cells accompanied by a profound decrease in effector cytokine production . Increased viral persistence resulted in marked expression of markers associated with T cell exhaustion ( PD-1 , CD39 , EOMES ) [43 , 44 , 46] and decrease in generation of antigen-specific memory CD8+ T cells . The decrease in the formation of memory T cells in IFNARfl/fl x Foxp3YFP-Cre mice in Cl-13 infection should be contrasted to the effects of IL-10 producing Treg cells in augmenting memory T cell formation following Armstrong infection [47] . Slight increases in both the percentages , but not the absolute numbers of Tregs were seen on days 25 and 46 post infection . However , at both times points , we observed a significant increase in the percentages of activated/effector Tregs . To determine if the hyperactivated/hypersuppressive phenotype observed in the absence of IFNAR signaling in Tregs was unique to viral infections , we also examined the responses of IFNARfl/fl x Foxp3YFP-Cre mice to transplantable tumor models . Markedly enhanced growth of the tumor was observed in these mice accompanied by an enhanced percentage of activated PD-1+ tumor infiltrating Tregs . In addition , the activation and cytokine production by both CD4+Foxp3- and CD8+ tumor infiltrating T cells were markedly suppressed . Taken together , these studies demonstrate that IFNAR signaling in Tregs plays a critical role in down-modulating , but certainly not abolishing , their suppressive function and may in viral infections orchestrate the balance between immunopathology and eradication of the virus . To begin to elucidate the mechanistic basis for the suppressive function of IFNAR-deficient Tregs during both acute and Cl-13 infection , we performed high-throughput RNA sequencing of Foxp3+ Tregs from both controls and IFNARfl/fl x Foxp3YFP-Cre mice on day 5 Armstrong and day 25 Cl-13 infection . A group of Treg-signature genes ( Areg , Arhpag20 , Bub1b , Ccl12 , Ccr5 , Il1r1 , Mki67 ( Ki67 ) Ncf1 , Nrp2 , Tnfrsf9 , Tcf19 , Uhrf1 , and Wnt3 ) were expressed at higher levels in IFNARfl/fl x Foxp3YFP-Cre mice than WT controls on day 5 Armstrong infection . These genes have previously been identified as Treg-Up signature genes [49 , 50] and their enhanced expression is consistent with the hyperactivated phenotype of the Tregs at that time point . We did not observe upregulation of this group of genes on day 25 of Cl-13 infection . Interestingly , both in Armstrong and Cl-13 infection , we observed the differential expression of a number of genes in IFNARfl/fl x Foxp3YFP-Cre Tregs which might also play a role in their enhanced suppressive function including Akap1 , Camk2b , Rasgrf2 and Hunk . Akap1 , which serves as a gap junction protein , is involved in transferring pools of cAMP from Treg to effector T cells resulting in inhibition of TCR signaling [51 , 52] . Camk2b participates in the activation of nuclear factor kappa-B , which in turn plays a role in Treg development by stabilizing Foxp3 [53 , 54] . Both Camk2b and Hunk have been shown to be have higher levels of expression in human Tregs than conventional effector T cells [55] . Lastly , Rasgrf2 is involved in stimulation of TCR signaling through activation of nuclear factor for activated T cells ( NF-AT ) [57] . Conversely , we also observed group of genes ( Erdr1 , Rell1 , Tlr7 ) whose expression is downregulated in Tregs from both IFNARfl/fl x Foxp3YFP-Cre Armstrong and Cl-13 infected mice . These genes have been described as potentially playing a role in apoptosis [59–61] and thus may be involved in the reduced suppressive function of Tregs after IFNAR signaling . We did not observe any differences between IFNARfl/fl x Foxp3YFP-Cre and WT mouse Tregs in expression of Active caspase-3 on day 5 post Armstrong infection again consistent with our data that cell death is not playing a role in reduced Treg suppression in WT mice , although , we cannot exclude the involvement of other cell death pathways . Future studies involving over expression and/or deletion of these genes in Tregs will be needed to specifically implicate one or several of these genes in Treg-mediated suppression during viral infections . We have not yet performed similar gene expression studies in IFNAR sufficient and deficient Tregs derived from the tumor microenvironment and compared such data with Tregs from LCMV-infected mice . Our study demonstrates that one of the multiple cellular targets of Type I IFNs during viral infection are Treg cells and that the functional result of this interaction is a downregulation of Treg suppressor function . A similar process may take place in the tumor microenvironment and may be responsible for some of the antitumor effects of this group of cytokines [62 , 63] . Thus , type I IFNs should be added to the long list of cytokines ( IL-1β , IL-4 , IL-6 , IL-15 , IL-21 ) [64–72] and members of the tumor necrosis factor superfamily ( TNFSF ) ( GITR-L , 4-1BB-L , OX40-L and TNF-α ) [73–76] that are purported to decrease Treg suppressive function in autoimmune and infectious disease models . However , the abrogation of suppression is more frequently mediated by the action of the cytokine or TNFSF member on the responder T cells resulting in resistance to suppression [73 , 77] , whereas we have definitively demonstrated that Tregs are the targets cells in this model . While type I IFNs may attenuate Treg suppression , it remains clear that the major and undefined cellular target for the immunosuppressive effects of type I IFNs in chronic LCMV infection is not the Tregs , as IFNARfl/fl x Foxp3YFP-Cre mice have elevated viral titers , while LCMV Cl-13 infected mice treated with a neutralizing antibody against IFNAR have decreased viral titers [33 , 34] . Thus , an approach to target IFNAR in normal hosts for inhibition of Treg suppressive function in chronic infection or in cancer would be difficult .
This study was carried out in strict accordance with the recommendations for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by National Institute of Allergy and Infectious Diseases Animal Care and Use Committee ( Protocol No: LI-5E ) . Foxp3YFP-Cre ( expressing Cre recombinase regulated by Foxp3 promoter ) mice were purchased from Jackson Laboratories ( Bar Harbor , ME ) . IFNAR-/- mice were obtained by National Institute of Allergy and Infectious Diseases ( NIAID ) , and maintained in Taconic Farms ( Germantown , NY ) . IFNARfl/fl mice were generously provided by Ulrich Kalinke ( Paul-Ehrlich Institut , Langen , Germany ) , and crossed with Foxp3YFP-Cre mice to generate Treg-lineage specific IFNAR-deficient mice . All strains of mice used in this study were age 8–12 weeks of age ) , gender matched , and bred in-house . LCMV Armstrong and Cl-13 viruses ( Shevach Laboratory ) were propagated in baby hamster kidney-21 fibroblast cells [American Type Culture Collection ( ATCC ) , Manassas , VA] . Viral titers were determined by plaque assay using Vero African-green-monkey kidney cells ( ATCC ) . Viral stocks were frozen at -80 oC until use . Mice were infected with the diluted virus in 1x sterile phosphate buffer saline ( PBS ) ( Armstrong virus , 2x105 plaque forming unit ( pfu ) /mouse , i . p . , or Cl-13 virus , 2x106 pfu/mouse , i . v . ) . LCMV titers in sera and organs were determined by plaque assay using Vero cells as described [78] . Spleens were harvested from naive ( uninfected ) and infected mice on indicated days and homogenized the tissues using cell strainer ( 70 μm , Nest Scientific USA , Rahway , NJ ) . Red blood cells were lysed using sterile ACK lysing buffer [NH4Cl ( 0 . 15 M ) , KHCO3 ( 10 mM ) and Na2EDTA ( 0 . 1 mM ) , pH 7 . 3] . Lymphocytes were washed , suspended in sterile complete medium [RPMI medium supplemented with 10% heat-inactivated fetal bovine serum ( FBS ) , L-glutamine ( 2 mM ) , sodium pyruvate ( 1 mM ) , HEPES ( 1 mM ) , non-essential amino acids ( 0 . 1 mM ) , 2-mercaptoethanol ( 50 μM ) , and penicillin and streptomycin ( 100 U/ml ) ] , and total live cells were counted . Cell surface staining was performed as described [79] . Briefly after harvest , spleen cells ( 3x106 cells ) or tumor infiltrating lymphocytes ( TIL ) were suspended in sterile complete medium . For surface staining , cells in staining buffer ( PBS , 10% heat-inactivated FBS , and 0 . 05% sodium azide ) were incubated for 30 min at 4 oC , then stained with the following surface murine conjugate antibodies: anti-CD4 , anti-CD62L , anti-CD39 , anti-CD127 , anti-IFNAR1 , anti-B220 ( all are from eBioscience , San Diego , CA ) ; anti-CD8a , anti-CD44 , anti-TIGIT ( all are from BD Biosciences , San Jose , CA ) ; anti-PD1 , anti-KLRG1 , anti-CXCR3 , and anti-ICOS ( all are from BioLegend , San Diego , CA ) and live/dead fixable aqua dead cell stain kit ( Life Technologies , Carlsbad , CA ) . For intracellular Foxp3 , Ki67 , Eomes and YFP detection , fixation and permeabilization were done according to the manufacturer’s guidelines ( Foxp3 transcription factor buffer set , eBioscience ) and cells stained with anti-Foxp3 , anti-Ki67 , anti-Eomes ( eBioscience ) , and anti-GFP rabbit polyclonal antibody ( Life Technologies , Carlsbad , CA ) . For intracellular cytokine detection , spleen cells ( 3x106 ) in complete medium were stimulated with LCMV peptides ( Research Technologies Brach , Protein Chemistry , NIAID ) : GP33-41 ( GP33 , 1 μg/ml ) , GP 276–286 ( GP276 , 1 μg/ml ) , NP396-404 ( NP396 , 1 μg/ml ) and GP 61–80 ( GP61 , 10 μg/ml ) along with GolgiStop ( 2 mM/ml , BD Biosciences ) for 5 hrs at 37 oC . TIL were stimulated with cell stimulation cocktail ( eBioscience ) containing PMA , ionomycin , Brefeldin A , and monensin for 5 hrs at 37 oC . Later cells were washed , fixed and permeabilized and stained with intracellular cytokine antibodies ( anti-IFN-γ and anti-GrB , BD Biosciences , and anti-TNF-α , eBioscience ) for overnight at 4 oC . For MHC class I tetramer staining , H-2Db GP33 , H-2Db GP276 and H-2Db NP396 ( NIH tetramer core facility ) were used at 1:100 dilutions and staining was done at 4 oC for 1 hr , and for MHC class II tetramers , IAb GP66-77 ( GP66 ) ( NIH tetramer core facility ) used at 1:75 dilution and staining performed for 90 mins at 37 oC . Cells were washed and acquired by BD LSRII and LSRFortessa ( BD Biosciences ) flow cytometers with FASCDiva software . Foxp3YFP-Cre and IFNARfl/fl x Foxp3YFP-Cre mice ( four to five mice per group ) were infected with Armstrong and Cl-13 virus . On day 5 post Armstrong and day 25 post Cl-13 infection , spleen and lymph nodes were harvested and single cell suspension were prepared . T cells were isolated by labeling single suspension with CD90 . 2 microbeads ( Miltenyi Biotec , San Diego , CA ) and purified through LS columns ( Miltenyi Biotec ) . Purified T cells were stained with anti-CD4 ( RM 4–5 ) for 30 minutes on ice and CD4+YFP+ cells ( 5x105/sample ) sorted ( purity ~95% ) by using FACSAria flow cytometer ( BD Biosciences ) . Armstrong ( day 5 ) and chronic LCMV infected ( day 25 ) Foxp3YFP-Cre and IFNARfl/flxFoxp3YFP-Cre mice CD4+YFP+ sorted cells were lysed in RLT buffer ( Qiagen , Valencia , CA ) . Total RNA was extracted using Qiagen AllPrep 96 DNA/RNA kit as described by the manufacturer ( Qiagen , Valencia , CA ) , with one exception prior to the extraction , the RLT lysate was homogenized using Qiagen QIAShredder columns ( Qiagen ) to shear any contaminating gDNA . Samples were then subjected to on-column Dnase I treatment . All steps were performed using PCR amplicon-free laboratory equipment to further minimize background signal during RNA sequencing and library generation . A 150 ng aliquot from each sample was individually adjusted to 50 μl using nuclease-free water . Each sample was processed using Truseq Stranded mRNA Sample Preparation , Rev . E ( Illumina Inc . , San Diego , CA ) using the included barcodes with the following modification: post-amplification libraries were purified with Ampure XP beads twice . The resulting DNA libraries were fragment-sized using a DNA1000 Bioanalyzer Chip ( Agilent Technologies , Santa Clara , CA ) and quantitated using KAPA Library Quant Kit with universal qPCR Mix ( Kapa Biosystems , Wilmington , MA ) on a CFX96 Real-Time System ( BioRad , Hercules , CA ) . All eight-ten samples were diluted to a 2 nM working stock and pooled using equal volume amounts . An 11 pM titration point was used to cluster a paired end , RAPID 2-lane flowcell on a Hiseq 2500 DNA sequencer ( Illumina ) . Libraries were run as 2 x 100 bp paired end reads on 2 lanes of an Illumina Hiseq 2500 sequencer , which produced ~28 . 7 million reads per sample . Reads were trimmed for adapter sequence and filtered for low quality sequence using the FASTX-Toolkit . Remaining reads were mapped to the mouse genome assembly mm10 using Hisat2 [80] . Reads mapping to genes were counted using htseq-count [81] . Differential expression analysis was performed using the Bioconductor package DESeq2 [82] . Further analysis was performed using Partek Genomic Suite ( Partek Incorporated ) and Ingenuity pathway analysis ( IPA ) is used for obtaining top canonical pathways , networks based on co-expression , transcription factor binding sites and protein-protein interactions . GSEA were performed on the set of 412 genes ( Armstrong infection ) using GSEA v2 . 2 . 3 from The Broad Institute [83] . GSEA was run using molecular signature database v . 5 . 2 gene sets , except the C1: positional gene sets , with 1000 permutations and all default parameters except minimum size of 5 . Total RNA samples from Foxp3YFP-Cre and IFNARfl/fl x Foxp3YFP-Cre mice were extracted as described in the NGS gene expression profiling method section . cDNAs were prepared from Superscript IV first-strand cDNA synthesis kit ( Thermo Fisher Scientific , Waltham , MA ) according to the manufacturer’s instructions . Presynthesized Taqman gene expression assays ( Thermo Fisher Scientific ) were used to amplify Akap1 , Car2 , Cpe , Eomes , Erdr1 , Gpat2 , Rab4a , Rell1 , Rasgrf2 , Sdc3 , Tlr7 , and Actb was used as internal control . Real time qPCR was performed using QuantStudio7 Flex Real time PCR system ( Thermo Fisher Scientific ) using Taqman universal master mix II with UNG ( Thermo Fisher Scientific ) . Target gene expressions were calculated by 2-dct and expressed as relative to Actb . Murine colon adenocarcinoma cells , MC38 cells ( ATCC ) and melanoma cells , B16 . F10 ( ATCC ) were grown in complete DMEM medium [DMEM/RPMI supplemented with 10% heat-inactivated FBS , L-glutamine ( 2 mM ) , sodium pyruvate ( 1 mM ) , HEPES ( 1 mM ) , non-essential amino acids ( 0 . 1 mM ) , 2-mercaptoethanol ( 50 μM ) , and penicillin and streptomycin ( 100 U/ml ) ] . Sex- and age-matched IFNARfl/fl and IFNARfl/flxFoxp3YFP-Cre mice were injected with 2x105 MC38 cells and or 1 . 25x105 B16 . F10 cells diluted in sterile 1xPBS , subcutaneously ( right flank region ) . Tumor growths were measured in regular intervals by digital calipers ( Fisher Scientific ) , and tumor volumes were calculated by the formulas: length x width x depth . On day 18 post tumor implant , tumors were excised in sterile conditions , and TIL were prepared after the mincing the tumor , and digesting with 1x HBSS containing collagenase type IV ( 0 . 5mg/ml ) , Dnase I ( 0 . 1 mg/ml ) and Hyaluronidase ( 2 . 5 units/ml ) for 1 hr at 37 oC . Later , digested cells were washed and treated with ACK lysing buffer to lyse RBCs , and then TIL were purified by density gradient centrifugation using buffered percoll ( Sigma-Aldrich , 80%/40% ) . Flow cytometry data were analyzed using FlowJo software version 10 . 2 and or 10 . 3 ( FlowJo LLC , Ashland , OR ) . Graphs were prepared by GraphPad Prism software version 7 . 0 ( GraphPad Software , Inc . La Jolla , CA ) . Statistical analysis was done through unpaired two-tailed Student’s t-test . All data in the graphs presented as Mean±SEM values , and error bars represent SEM . Data were considered statistically significant when P < 0 . 05 , and represented as * P < 0 . 05 , ** P < 0 . 01 , *** P < 0 . 001 , and **** P < 0 . 0001 . RNA sequence information reported in this study is deposited in NCBI GEO under the accession number: GSE104517 .
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Type I interferons ( IFNs ) play a predominant role in the immune response to infectious pathogens . The cellular targets of IFNs have been difficult to dissect because of the ubiquitous expression of the type I interferon receptor ( IFNAR ) . The immune response of mice to lymphocytic choriomeningitis virus ( LCMV ) is one of the major models for analyzing the action of IFNs . Regulatory T cells ( Tregs ) have been implicated in the control of LCMV and it has been proposed that IFN may influence their function . The major goal of this study was to define the contribution of IFN signaling on Treg function during different stages LCMV infection . Tregs from mice with selective deletion of IFNAR manifested enhanced suppressive activity during acute/chronic LCMV infection resulting in increased CD8 T cell anergy , defective generation of memory T cells and persistence of virus . Similar effects of IFNAR signaling in Tregs were seen in a tumor model . We identified a unique set of genes in Tregs modulated by IFN signaling that may contribute to the enhanced suppressive function of IFNAR deficient Tregs . IFNs play a beneficial role during acute/chronic viral infections not only by contributing to viral clearance but also by attenuating the function of Tregs .
|
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2018
|
Type I interferon signaling attenuates regulatory T cell function in viral infection and in the tumor microenvironment
|
Brugia malayi , like most human filarial parasite species , harbors an endosymbiotic bacterium of the genus Wolbachia . Elimination of the endosymbiont leads to sterilization of the adult female . Previous biochemical and genetic studies have established that communication with its endobacterium is essential for survival of the worm . We used electron microscopy to examine the effects of antibiotic treatment on Wolbachia cell structure . We have also used microarray and quantitative RT-PCR analyses to examine the regulation of the B . malayi transcripts altered in response to the anti-Wolbachia treatment . Microscopy of worms taken from animals treated with tetracycline for 14 and 21 days ( 14 d and 21 d ) demonstrated substantial morphologic effects on the Wolbachia endobacterium by 14 d and complete degeneration of the endobacterial structures by 21 d . We observed upregulation of transcripts primarily encoding proteins involved in amino acid synthesis and protein translation , and downregulation of transcripts involved in cuticle biosynthesis after both 7 d and 14 d of treatment . In worms exposed to tetracycline in culture , substantial effects on endobacteria morphology were evident by day 3 , and extensive death of the endobacteria was observed by day 5 . In a detailed examination of the expression kinetics of selected signaling genes carried out on such cultured worms , a bimodal pattern of regulation was observed . The selected genes were upregulated during the early phase of antibiotic treatment and quickly downregulated in the following days . These same genes were upregulated once more at 6 days post-treatment . Upregulation of protein translation and amino acid synthesis may indicate a generalized stress response induced in B . malayi due to a shortage of essential nutrients/factors that are otherwise supplied by Wolbachia . Downregulation of transcripts involved in cuticle biosynthesis perhaps reflects a disruption in the normal embryogenic program . This is confirmed by the expression pattern of transcripts that may be representative of the worms' response to Wolbachia in different tissues; the early peak potentially reflects the effect of bacteria death on the embryogenic program while the second peak may be a manifestation of the adult worm response to the affected bacteria within the hypodermis .
Nematodes are the most common parasitic infections of humans [1] with filarial worms infecting more than 150 million individuals worldwide [2] , [3] . Brugia malayi and Wuchereria bancrofti are filarial parasites of the lymphatic and circulatory system , and infection with these parasites can result in lymphatic pathologies leading to elephantiasis . In contrast , Onchocerca volvulus resides in the connective tissue and dermis , and infection can result in onchocerciasis , or river blindness and severe skin disease , or onchodermatitis . Approximately 30 years ago , bacteria-like structures residing within cells of the filarial parasites were first observed [4] , [5] . Experiments suggested that treatment with certain antibiotics that target bacteria , including tetracycline and chloramphenicol , could interrupt the third-stage ( L3 ) to fourth-stage ( L4 ) larval molt of the worm [6] and also affect embryogenesis in adult parasites [7] , [8] . Later studies revealed the presence of Wolbachia DNA in the majority of filaria , including all of the human parasites with the exception of Loa loa [9] , [10] and Mansonella perstans [9] . Treatment with both ivermectin ( the microfilaricidal drug that is the major tool for onchocerciasis control today ) and the antibiotic doxycycline resulted in a rapid and apparently irreversible decline in the burden of skin microfilariae in O . volvulus-infected individuals and an apparent permanent sterilization of the adult female parasite [11] . Studies on W . bancrofti infections suggest that a doxycycline treatment regimen can successfully target worm embryogenesis and stop microfilarial production in individuals infected with this parasite as well [12] . Although the doxycycline treatment studies demonstrate an effect on Wolbachia – and consequently on the survival of the filaria – the use of this antibiotic is not a practical choice for the treatment of human filarial infections . First , doxycycline is a relatively toxic drug that is contraindicated in a fairly large number of patient groups , including children and pregnant or lactating women . Second , clearance of the Wolbachia endosymbiont requires a very prolonged antibiotic treatment course , something that is impractical in developing countries where human filarial infections are endemic . Finally , studies employing other antibiotics generally used to treat endocellular bacterial infections were shown to be uniformly ineffective against filarial Wolbachia [13] . For these reasons , additional research is critically needed to develop new tools for control and treatment of these infections . If the Wolbachia endosymbiont is to be exploited as a practical chemotherapeutic target , a better understanding of its effects on its host is crucial . In the present study we focused on the bacteria-host relationship by characterizing the effect of eliminating the Wolbachia of B . malayi ( wBm ) on worm gene expression . Transcriptomic approaches have proven useful in studying gene expression patterns in other parasites [14] , [15] , as well as the host response to pathogens [16] . Previous studies have shown that tetracycline has no direct effect on filarial parasites that do not carry an endosymbiont , such as Acanthocheilonema viteae [8] . However , similar to what was seen when doxycycline was given to W . bancrofti and O . volvulus-infected humans , tetracycline treatment of animals infected with Litomosoides sigmodontis ( an endosymbiont-containing filarial parasite commonly used as a model for the human filaria ) resulted in the elimination of the endosymbiont and reduced the fertility of the adult female worm [8] . While prolonged treatment with tetracycline is effective for the elimination of the endobacteria , the specific molecular effects of the affected bacteria on fertility and molting in its parasite host are unknown . We hypothesized that B . malayi genes that respond early to wBm clearance are likely to have an important role in the symbiotic relationship . As a first step in understanding this process we set out to identify genes whose expression is altered early in response to the targeting of the wBm endosymbiont by tetracycline treatment .
For morphological studies , B . malayi female worms were fixed with 3% glutaraldehyde in 0 . 1 M sodium cacodylate buffer , pH 7 . 4 , for 2 hours at room temperature , post-fixed in 1% osmium tetroxide and then grouped within a 3 . 5% Sea Plaque agar pad . The worms were then dehydrated in graded ethanol solutions ( 50–100% ) , embedded in EMbed-812 media , and cured for 24 hours at 56°C . Ultrathin sections ( 65–70 nm ) were cut on an MT-XL ultra-microtome and stained with Uranyl Acetate and Reynold's Lead Citrate . All reagents were from the EMS Company ( Hatfield , PA ) . Samples were observed using a Philips EM-410 Transmission Electron Microscope ( Phillips/FEI Corporation , Eindhoven , Holland ) at an accelerating voltage of 80 kV .
We conducted an ultrastructural analysis to determine the effect of tetracycline on the endosymbiont after in vivo drug treatment . Infected jirds were exposed to 2 . 5 mg/ml of tetracycline in their drinking water for 14 or 21 days ( 14 d and 21 d ) . B . malayi worms were collected from treated and control hosts for ultrastructural studies . In female worms from control hosts , large numbers of wBm were present within the hypodermal cord ( Figure 1A ) . In parasites recovered from animals treated for 14 d ( Figure 1B ) or 21 d ( Figure 1C ) , degenerating Wolbachia could be seen in the hypodermis of the worms ( see insert in each panel ) and the total number of bacteria present appeared to decline compared to the untreated worms . In addition , while the Wolbachia were also present in all stages of the uterine progeny of the untreated worms , no wBm were observed in the oocytes , embryos , or in the microfilariae within the worms collected from the treated animals ( data not shown ) . In the 21 d treated worms , many of the bacteria within the hypodermis were also degenerated , and the cell vacuoles contained only remnants of bacteria or membrane whorls ( see insert in Figure 1C ) . A similar observation was made in tetracycline-treated O . ochengi where the Wolbachia were eliminated resulting in the resolution of the filarial infection [29] . These morphological changes are consistent with ultrastructural images of killed bacteria [30] . Therefore , it was concluded that 21 days of tetracycline treatment of the B . malayi-infected jirds would lead to complete wBm cell death . Based on these results , we determined that 14 days of drug exposure was likely to be the maximum time for an efficient evaluation of the effect unhealthy Wolbachia have on their host . A set of experiments ( ArrayExpress E-MEXP-2185; Source Name 012607 ) performed using random primed RNA isolated from parasites collected from treated animals ( in order to capture bacterial transcripts in addition to nuclear B . malayi transcripts ) , confirmed that at 14 d wBm were dying as the vast majority of their transcripts were found to be downregulated compared with wBm from untreated worms . Of the 295 hybridized oligos ( P-value<0 . 05 ) corresponding to endosymbiont encoded genes , 94% indicated transcript downregulation by more than 2-fold , while only 4% were upregulated ( Table 1 ) , consistent with the hypothesis that tetracycline treatment results in the death of the Wolbachia endosymbiont . In contrast , 36% of B . malayi nuclearly-encoded transcripts were downregulated more than 2-fold , while 55% were upregulated more than 2-fold ( data not shown ) . Notably , some of the wBm transcripts that were upregulated at 14 d encoded chaperone proteins and two proteins involved in cytochrome c biogenesis ( Table 1 ) . In order to capture the effect of tetracycline on gene expression before complete bacteria death and clearance , a second set of microarray experiments was performed . A number of biological replicates were carried out employing groups of parasites collected from animals exposed to tetracycline for 7 d or 14 d . RNA was isolated from groups of 8–10 worms and used in these microarray experiments . In order to focus specifically on B . malayi gene expression , the experiments were conducted using oligodT-primed RNA . In analyzing the results , we concentrated upon one set of microarray experiments ( ArrayExpress E-MEXP-2185; Source Name 011508 - referred herein as 011508 ) in which the RNA used was collected at both time points ( 7 d and 14 d ) during the course of the same treatment experiment . In other experiments , worms were collected from groups of animals treated for either 7 d or 14 d but not at both time points . These experiments were , however , used to provide biological replicate support to the conclusions drawn from the 011508 experimental data . The initial analysis of the data collected from experiment 011508 indicated that expression of only a relatively limited number of B . malayi genes was affected by exposure to tetracycline . At 7 d post-treatment in the 011508 data , 212 oligos on the array indicated upregulation of their corresponding transcripts while 51 oligos indicated downregulated transcripts ( Table S2A ) . At 14 d post-treatment , 285 oligos on the array indicated upregulation of their corresponding transcripts , while 34 indicated downregulation ( Table S2B ) . At 7 d , upregulation was predominantly restricted to B . malayi genes involved in translation , such as ribosomal proteins ( 40S ribosomal proteins S4 and S23 and 60S ribosomal proteins L3 , L4 , L5 , L10 , L14 , L22 , L24 ) , the eukaryotic translation initiation factor eIF5A-2 ( 15549 . m00017/Bm1_57565 ) , and the alpha ( 14894 . m00090/Bm1_27170 ) and gamma ( 14992 . m11155/Bm1_51865 ) subunits of the translation elongation factor 1 ( EF-1 ) . A subset of genes appeared to be substantially upregulated in response to tetracycline . These were characterized by treated/untreated ratios of greater than 3 . 0 in the microarray data . These strongly regulated genes included the B . malayi peptidyl-prolyl cis-trans isomerase ( 15451 . m00017/Bm1_56870 ) which is important for cuticular collagen processing [31] , and a homologue of a highly immunogenic Gln-rich protein of O . volvulus ( gb#:AAC48290 . 1 ) . However , most of the upregulated transcripts encoded proteins involved in regulated degradation of intracellular proteins . These included a member of the serpin family , Bm-SPN-2 ( gb#:AAB65744 . 1 ) , peptidases such as the cathepsin L-like cysteine protease Bm-cpl-3 ( 12633 . m00021/Bm1_02075 ) , the hydrolase alpha amylase ( 12556 . m00067/Bm1_01300 ) , a ubiquitin-conjugating enzyme family protein ( 14990 . m08098/Bm1_49860 ) , a 26S proteasome non-ATPase regulatory subunit ( 14971 . m02852/Bm1_36060 ) , and asparaginyl-tRNA synthetase ( 14971 . m02889/Bm1_36235 ) . Together , these data point towards B . malayi going into increased synthesis of amino acids and protein translation in response to the death of its endosymbiont . Such upregulation of proteins involved in protein synthesis ( such as the ribosomal proteins ) has been described in several other organisms placed under stress , including bacteria [32] , plants [33] and mammalian cells [34] . The upregulation of these mRNAs may indicate a generalized stress response induced in B . malayi due to shortage of essential nutrients/factors that are otherwise supplied by wBm . Downregulated genes at 7 d post-treatment included the B . malayi superoxide dismutase ( gb#AAR06638 . 1 ) and cuticular collagens such as an alpha-1 collagen type IX ( 15377 . m00007/Bm1_56350 ) , the nematode cuticular collagen ( 15378 . m00020/Bm1_56360 ) , and other putative collagens ( 12495 . m00012/Bm1_00775 , 14845 . m00009/Bm1_26670 ) . These genes are involved in cuticle biosynthesis and perhaps reflect a disruption in the normal embryogenic program . The majority of the genes involved in energy metabolism also appeared to be downregulated at 7 d post-treatment . These included transcripts encoding proteins located in the inner mitochondrial membrane and involved in the respiratory chain , such as cytochrome c oxidase subunit II ( gb#AAN17813 . 1 ) , ATP synthase F0 subunit 6 ( gb# AAN17812 . 1 ) , and NADH dehydrogenase subunit 4L ( gb# AAN17810 . 1 ) . Interestingly , in contrast to this general pattern , cytochrome c oxidase subunit IV ( 12902 . m00232/Bm1_03920 ) was upregulated above the three-fold level . This is of interest as tetracycline was shown to affect host mitochondrial metabolism and reduce cytochrome c oxidase in insects that carry Wolbachia [35] . This observation may reflect some direct effect of the antibiotic on host metabolism rather than an indirect effect due to bacteria death . Figure 2 provides an overview of genes whose expression was found to be changed at both 7 d and 14 d as a result of exposure to tetracycline . At 14 d post-treatment , various transcripts corresponding to proteins involved in translation and in amino acid synthesis ( for example ribosomal proteins , elongation factors , and asparaginyl-tRNA synthetase ) continued to be overexpressed ( Table S2B ) . Similarly , the majority of downregulated genes seen at 14 d were those involved in cuticle biosynthesis , including the cuticular collagens and cuticular glutathione peroxidase . The transcript encoding asparaginyl-tRNA synthetase was also constantly upregulated at both 7 d and 14 d ( Figure 2; details in Table S3 ) . This enzyme was shown in B . malayi to be immunodominant and to activate a strong human immunoglobulin G3 response that is thought to contribute to the chronic inflammation seen in lymphatic filariasis [36] . Upregulation of such an immunogenic protein might contribute to the clearance of microfilaria in tetracycline treated individuals . Alternatively , the increased production of such immunogens might temporarily exacerbate the pathologies associated with these infections , since much of the pathology is believed to be immune mediated [37] . Contrary to what was observed at 7 d , at 14 d the majority of the genes that were strongly over-expressed ( characterized by treated/untreated ratios of greater than 3 . 0 ) corresponded to various proteins located in the inner mitochondrial membrane and involved in the respiratory chain . These include cytochrome c oxidase subunits I ( gb#AAN17806 . 1 ) and III ( gb#AAN17809 . 1 ) , NADH dehydrogenase subunits 2 ( gb#AAN17804 . 1 ) , and 5 ( gb#AAN17815 . 1 ) , and cytochrome b ( gb#AAN17808 . 1 ) . ATP synthase F0 subunit 6 ( gb#AAN17812 . 1 ) was also upregulated but at a lower level . Other genes that are seen to be over-expressed at 14 d and not at 7 d included a trypsin family protein ( 14979 . m04643/Bm1_45620 ) , a superoxide dismutase ( gb#AAR06638 . 1 ) , an ecdysone receptor homolog ( 14944 . m00537/Bm1_29350 ) , and a cathepsin L-like non-peptidase homolog ( #BAD11761 . 1 ) . Bm-cpl-6 , a member of the group 1c of cathepsin L-like cysteine proteases , was downregulated at 7 d , but upregulated at 14 d . Interestingly , another member of this family , Bm-cpl-4 , ( which belongs to group 1a ) , was downregulated at both 7 d and 14 d post-treatment . The proteins that belong to group 1a of the cathepsin-L like proteases have been studied extensively because of their function during embryogenesis and larval development in filarial parasites [38]–[40] . Another group of genes of interest included those which were significantly upregulated at 7 d and then downregulated at 14 d . These could be characterized as ‘early responders’ and are most likely to be involved in a direct effect of Wolbachia disruption on B . malayi transcriptome . This is the case for the excretory/secretory protein Juv-p120 precursor that is similar to the 120 kDa antigen produced by the juvenile female of Litomosoides sigmodontis [41] . At 7 d , oligos corresponding to two full length genes are upregulated ( 14597 . m00048/Bm1_21750 and 14478 . m00108/Bm1_19955 ) ( Table S2A ) while at 14 d an oligo corresponding to a truncated version of the protein is downregulated ( 12501 . m00019/Bm1_00865 ) ( Table S2B ) . The physiological role of this protein family is uncertain . The KEGG classification helps to highlight the most important B . malayi pathways that are affected by the tetracycline treatment . From the KEGG analysis ( Figure 3; Table S4 ) it appears that of the upregulated pathways , translation accounts for 30% of functionally annotated proteins both at 7 d and 14 d post-treatment . Energy metabolism is also highly upregulated at 14 d ( 25% of functionally annotated genes ) , primarily oxidative phosphorylation ( cytochrome c oxidase and NADH dehydrogenase genes ) likely due to an effect of wBm death on mitochondria and potentially leading to cytochrome c-mediated apoptosis [42] . To confirm the upregulation or downregulation trends observed in the microarray experiments , qRT-PCR assays for specific genes were performed . In conducting these studies the same RNA preparation used in the 7 d microarray experiment was tested , as well as RNA from biological replicates consisting of worms recovered from other animals at 7 d or 14 d post-treatment . In choosing the genes to be included in these confirmatory assays , we used the KEGG annotation to select genes that corresponded to signaling molecules and the signal transduction pathway . We hypothesized that the regulation of this pathway was likely to reflect an early response to Wolbachia cell death . Results of the qRT-PCR agreed well with those obtained from the microarray experiments ( Table 2 ) . In the worms collected from animals given tetracycline for 7 d , the qRT-PCR and microarray data agreed for 14/15 ( 93% ) of the genes tested . The only exception was BMC05356 , which appeared to be downregulated in the microarray analysis while slightly upregulated in the qRT-PCR assay . For the RNA samples collected from parasites in animals given tetracycline for 14 d , the microarray and qRT-PCR data agreed for 12/15 ( 75% ) of the genes tested . Again , the microarray data indicated that BMC05356 was downregulated at 14 d , while the qRT-PCR indicated upregulation of this transcript . Similarly , the microarray data suggested that expression of Bm1_15985 and Bm1_26670 were not changed by tetracycline treatment at 14 d , while the qRT-PCR suggested that both genes were in fact upregulated . Although the microarray and qRT-PCR data were in general agreement regarding the effect of tetracycline treatment , the magnitude of the changes in gene expression reported by the qRT-PCR was consistently larger than those reported by the microarray . This suggests that the qRT-PCR might be a more sensitive assay to detect changes in transcript levels than microarray hybridization , and that the microarray might be best considered as a semi-quantitative indicator suitable for defining , but not quantifying , a change in transcript level . A list of GO terms relevant for B . malayi was generated and used for comparative analyses of 7 d and 14 d post-treatment . Table S5A and Table S5B provide GO terms associated with upregulated and downregulated genes , respectively . The assignment ( made using GOEAST as described in the Methods ) was done in a hierarchical manner , i . e . genes could be assigned more than one GO term in this analysis . Most of the significant GO associations were found to be in the upregulated genes ( Table S5A ) . Figure 4 provides a pie chart of GO terms for 7 d ( inner circle ) and 14 d ( outer circle ) post-treatment generated using InterProScan which only assigns one GO term per gene for each top level category . From this graphic representation it also appears that translation is the predominantly upregulated biological process at 7 d , while at 14 d proteolysis along with translation was upregulated . A few GO terms corresponding to molecular function are found only at 14 d , such as catalytic activity , endopeptidase , protein kinase , transcription factor , hydrolase , and proteins with dimerization activities . On the other hand , cellular components were well conserved across both time points . Although gene annotation and pathway analyses allow a clearer understanding of which functional pathways are affected during Wolbachia death , a significant proportion of the regulated genes have no known function . For example , of the genes or ESTs represented by oligos on the array , at 7 d 36% of the upregulated genes and 39% of downregulated genes code for uncharacterized proteins with no domain matches and are unique to B . malayi; at 14 d , 16 . 5% of the upregulated and 41% of the downregulated genes are uncharacterized ( Tables S2A and S2B ) . These represent a pool of genes that will eventually need to be studied as they may be important in the endosymbiotic relationship . While the data presented above indicate that tetracycline consistently affected the Wolbachia endosymbiont when given to infected animals for a week , individual variability in drug uptake and availability among individual animals made it difficult to study the detailed kinetics of changes in gene expression at a time scale that was shorter than one week . To overcome the problem posed by animal to animal variation , B . malayi adult females were exposed to tetracycline in culture , where the process of drug exposure could be more carefully controlled . To accomplish this , female worms collected from ∼120 day infected jirds ( obtained from the FR3 ) were cultured for 6 days in the presence or absence of 40 µg/ml tetracycline , as described in the Materials and Methods . This dose of drug was chosen as previous studies had demonstrated that this was the minimum concentration capable of reducing microfilariae release by close to 100% [18] . Initially , worms cultured for varying times in the presence or absence of tetracycline were collected and fixed for ultrastructural analysis ( Figures 5–8 ) . In untreated worms , as before , numerous Wolbachia were found in the hypodermal cord ( Figure 5A ) and in all stages of embryonic development within the uterus ( Figures 6A , 7A , 8A ) . Wolbachia within the hypodermal cord of the worms treated for one day appeared to be normal ( Figure 5B ) , while some of the bacteria had clearly degenerated by day 3 ( Figure 5C ) showing vacuoles with membrane whorls . By day 5 ( Figure 5D ) most of the bacteria were completely degenerated and morphologically resembled dead bacteria [29] , [30] . The bacteria within oocytes ( Figure 6B ) , embryos ( Figure 7B ) and microfilaria ( Figure 8B ) looked similarly normal after one day of treatment with tetracycline . However , by day three , in all three stages of development , the Wolbachia were completely degenerated and the majority of the vacuoles contained few bacterial remnants or membrane whorls ( Figures 6C , 7C , and 8C ) . By day 5 , not only the Wolbachia were completely degenerated , but the structure of the B . malayi oocytes ( Figure 6D ) , embryos ( Figure 7D ) and microfilaria ( Figure 8D ) also appeared to be abnormal , degenerated and vacuolated . RNA was prepared from groups of 4 female worms each cultured for 1 to 6 days in the presence or absence of tetracycline , and used for a time course analysis of transcript levels for selected genes , using the qRT-PCR approach . Four genes that are part of the signal transduction or the signaling molecules and interaction pathways , and which were found to be regulated in the microarray and qRT-PCR experiments , were included in these studies . All four transcripts examined produced a similar pattern of gene regulation ( Figure 9 ) and appeared to be upregulated at 1 day post in vitro treatment . After three days in culture , the transcript levels in the treated parasites were equivalent to or slightly less than those in the similarly cultured untreated parasites . However , after six days in culture , the transcripts in the treated parasites were again upregulated relative to those in the untreated parasites , thus exhibiting a bimodal pattern of regulation . Filarial parasites afflict hundreds of millions of individuals worldwide , and represent significant public health problems in many of the poorest countries in the world . There is a need to develop new chemotherapeutic approaches that can practically exploit the vulnerability of the human filarial parasites to the loss of the Wolbachia . The effects of depleting Wolbachia by antibiotic treatment suggest that the worms have become dependent on the bacteria for a diverse range of biological processes . From our analysis of the genomic data [43] , we suspect that B . malayi is incapable of de novo purine synthesis as it lacks 9 of the 10 enzymes required to make inosine monophosphate ( IMP ) from phosphoribosyl pyrophosphate ( PRPP ) . However the parasite does have the capability of converting IMP to adenosine monophosphate ( AMP ) . Although B . malayi worms may be able to salvage purines from the host environment using a multitude of nucleobase and nucleoside transporters , wBm appear to be able to compensate for B . malayi's defective pathway by providing purines [44] . Conversely , a major role of the worm in this symbiotic relationship is likely to be provision of amino acids required for bacterial growth , since wBm can only synthesize one amino acid ( meso-diaminopimelate ) [44] . The upregulation of translation and amino acid biosynthesis genes observed upon the depletion of Wolbachia by antibiotic treatment may represent some kind of feedback loop in this process . Interestingly , KEGG maps of D . melanogaster and its endosymbiont Wolbachia ( Wmel ) indicate that they may compensate for each other's metabolic gaps in a similar fashion [45] . B . malayi also lacks 6 of the 7 genes required for heme biosynthesis [43] . Heme produced by wBm could be vital for worm embryogenesis and development as there is evidence that molting and reproduction are controlled by ecdysteroid-like hormones whose synthesis requires heme [46]–[48] . A recent study demonstrates that the heme biosynthetic genes in wBm might be essential for B . malayi survival [49] . Heme is also an essential cofactor for proteins such as hemoglobins and cytochromes , among others . The depletion of heme in B . malayi as a result of endosymbiont cell death may in part explain the differential regulation of the cytochromes observed in our experiments . Previous studies have identified two genes upregulated in response to anti-Wolbachia antibiotic treatment . Using differential display PCR , the L . sigmodontis phosphate permease ( Ls-ppe-1 ) was identified as a tetracycline upregulated gene by days 3–6 of treatment in vivo and expression of this gene remained elevated through to 70 days post-treatment [50] . In another study using immunogold electron microcopy , immunohistochemistry , and qRT-PCR , it was shown that the mitochondrial heat shock protein 60 ( HSP60 ) is upregulated in O . volvulus after the depletion of Wolbachia [51] . The increased expression of these genes in O . volvulus and L . sigmondontis in the absence of Wolbachia is thought to be due to a disruption of the homeostasis of the endosymbiosis . However , neither of these two genes was found to be differentially regulated in our B . malayi microarray experiments . Transcriptomics is a powerful method for the identification of potential new helminth drug targets [52] . Our studies demonstrate the strength of using microarray analyses combined with bioinformatics in highlighting the pathways that are most affected by disruption of the normal endosymbiotic relationship . These pathways might not have been previously identified based on the genetic information of both the host and the endosymbiont , and thus would not be expected to be vulnerable targets of Wolbachia elimination . The microarray data might therefore be useful in identifying new pathways targeted by efforts to disrupt the host-endosymbiont relationship . Although the data derived from the B . malayi microarray were generally comparable to those derived from qRT-PCR , they appeared to be more useful in detecting general trends and pathways affected rather than providing a precise quantification of changes in the expression levels of specific genes . Using qRT-PCR on worms that were treated in vitro , a bimodal pattern of gene expression was observed for the four genes tested . A similar pattern was also observed in treated L . sigmodontis worms [49] where it was hypothesized that the first peak was due to the effect of tetracycline on the pre-embryonic and embryonic stages of the worm ( which are hypothesized to be more sensitive to the death of the endosymbiont ) , while the second peak was a response to the death of the endosymbiont in the hypodermal tissues of the adult . The electron microscopic studies have supported this assumption as it was observed that the oocytes and the embryos were more vulnerable to the elimination of the Wolbachia by tetracycline treatment . Furthermore , preliminary studies on male worms that were treated with tetracycline from 1 to 6 days indicate that for the transcripts tested there is one peak of overexpression , and it is only found at day 6 ( data not shown ) . Since male worms lack developing embryos , this finding provides further support to the hypothesis that the bimodal pattern is related to the differential effect of tetracycline on embryos and somatic tissues in the adult female . In summary , our studies have highlighted a few pathways and proteins that are potentially involved in the relationship between the endosymbiont wBm and its B . malayi host . However , testing for their relevance in the symbiotic relationship will demand further characterization of these proteins and identifying putative Wolbachia factors that regulate their expression .
|
Filarial parasites afflict hundreds of millions of individuals worldwide , and cause significant public health problems in many of the poorest countries in the world . Most of the human filarial parasite species , including Brugia malayi , harbor endosymbiotic bacteria of the genus Wolbachia . Elimination of the endosymbiont leads to sterilization of the adult female worm . The need exists for the development of new chemotherapeutic approaches that can practically exploit the vulnerability of the filaria to the loss of the Wolbachia . In this study we performed ultrastructural and microarray analyses of female worms collected from infected jirds treated with tetracycline . Results suggest that the endosymbiotic bacteria were specifically affected by the antibiotic . Furthermore , in response to the targeting of the endosymbiont , the parasites modulated expression of their genes . When exposed to tetracycline , the parasites over-expressed genes involved in protein synthesis . Expression of genes involved in cuticle biosynthesis and energy metabolism was , on the other hand , limited .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"and",
"Discussion"
] |
[
"genetics",
"and",
"genomics/genomics",
"genetics",
"and",
"genomics/gene",
"expression"
] |
2009
|
Brugia malayi Gene Expression in Response to the Targeting of the Wolbachia Endosymbiont by Tetracycline Treatment
|
Leaves of Codiaeum variegatum ( “garden croton” ) are used against bloody diarrhoea by local populations in Cameroon . This study aims to search for the active components from C . variegatum against Entamoeba histolytica , and thereby initiate the study of their mechanism of action . A bioassay-guided screening of the aqueous extracts from C . variegatum leaves and various fractions was carried out against trophozoites of E . histolytica axenic culture . We found that the anti-amoebic activity of extracts changed with respect to the collection criteria of leaves . Thereby , optimal conditions were defined for leaves' collection to maximise the anti-amoebic activity of the extracts . A fractionation process was performed , and we identified several sub-fractions ( or isolated compounds ) with significantly higher anti-amoebic activity compared to the unfractionated aqueous extract . Anti-amoebic activity of the most potent fraction was confirmed with the morphological characteristics of induced death in trophozoites , including cell rounding and lysis . Differential gene expression analysis using high-throughput RNA sequencing implies the potential mechanism of its anti-amoebic activity by targeting ceramide , a bioactive lipid involved in disturbance of biochemical processes within the cell membrane including differentiation , proliferation , cell growth arrest and apoptosis . Regulation of ceramide biosynthesis pathway as a target for anti-amoebic compounds is a novel finding which could be an alternative for drug development against E . histolytica .
Medicinal plants are recognized by the World Health Organization as alternatives in the treatment of various diseases and the interest of health professionals for medicinal plants is increasing everyday [1] . Medicinal plants contain a variety of secondary metabolites , which can be used to prevent or cure diseases , or to promote general health and well-being [2] , [3] . During the last decades , scientific evidences of the medicinal values of plant products ( through in vitro investigation ) aroused public concerns about the conservation of such plants , in order to retain their economic and therapeutic significance [4] . Modern pharmaceutical industry relies mainly on the diversity of secondary metabolites in medicinal plants for the discovery of new compounds with novel biological properties . It is estimated that natural products and their derivatives and analogues represent over 50% of all drugs in clinical use [5] , [6] . Therefore , further evaluation of drugs derived from plants requires the screening of large numbers of plant extracts , isolation and identification of the active compounds , the study of their mechanism of action , as well as the proof of its non-toxicity to human cells . In Cameroon , biodiversity is an important source of bioactive natural compounds and exploration of this biodiversity , based on ethnopharmacology approach from traditional healers , represents a promising strategy to fight against diseases such as intestinal infections . We have focused on amoebiasis , a human infectious disease caused by the amoebic parasite Entamoeba histolytica , which mainly targets intestine and liver . Humans are the only relevant host of this parasite and infection occurs upon ingestion of contaminated water or food containing cysts forms of E . histolytica . In rural areas of some developing countries , up to 20% of the population is infected with E . histolytica . Trophozoites ( the vegetative form ) are released in the intestine by excystation . Once the trophozoite has penetrated the intestinal mucosal layer , it induces intestinal amoebiasis responsible of colitis and bloody diarrhoea [7] , [8] . An acute immune response is triggered during the early stages of the parasite infection . Amoebic liver abscesses are the most frequent with severe extra-intestinal clinical manifestations of amoebiasis [8] . The morbidity and the economic impact of dysentery make of amoebiasis a prominent public health problem . Metronidazole ( MTZ ) is the drug of choice used in clinical practice for the treatment of amoebiasis since 45 years [9] . This drug has been reported to be potentially carcinogenic to humans due to the facts that it is mutagenic in bacterial systems , genotoxic to human cells and carcinogenic to animals [10] . Also , a significant increase in DNA damage was found in lymphocytes from healthy subjects one day after treatment with therapeutic doses of MTZ [11] . Moreover , the current use and long term treatment with MTZ is responsible for many side effects such as toxic symptoms of metallic taste , headache and dry mouth and to a lesser extent nausea , glossitis , urticaria , pruritus , urethral burning and dark colored urine [12] . Some clinical isolates of E . histolytica present diverse susceptibility to MTZ [13] and drug resistance has been induced in axenic cultures of amoebic virulent strains following continuous exposure to increasing MTZ concentrations [14] . MTZ resistance in E . histolytica has been associated to increased expression of iron-containing superoxide dismutase and peroxiredoxin and decreased expression of flavin reductase and ferredoxin 1 , which are enzymes involved in redox pathways of E . histolytica [14] . Recent data report thiol-containing redox proteins ( Thioredoxin and Thioredoxin Reductase ) covalently modified and inactivated by MTZ [15] , [16] . To provide alternatives to MTZ clinical uses , several efforts are underway . Recently , a screening of US Food and Drug Administration ( FDA ) -approved drugs identified auranofin as active against E . histolytica in culture and also in a mouse model of amoebic colitis or in a hamster model of amoebic liver abscess [17] . Auranofin , is a US FDA approved drug used for treatment of rheumatoid arthritis . This drug is reported to be an inhibitor of thioredoxin reductase ( TrxR ) thereby suggesting that E . histolytica TrxR is likely its target [17] . Additionally , a common reaction to auranofin is persistent diarrhoea reported in 50% of patients , a fact precluding its use for amoebiasis treatment . A galacto-glycerolipid isolated from Oxalis corniculata has shown a strong anti-amoebic activity with no effect on intestinal microbial flora or on the mammalian cell line HEK-293 [18] , despite the fact that the mechanism of its action is still unclear . Fifty-five medicinal plants belonging to different families , selected on the basis of their traditional use against intestinal and liver disorders , were tested for their anti-amoebic activities on polyxenic cultures of E . histolytica . From these plants , the aqueous extract of leaves of C . variegatum exhibited a pronounced anti-amoebic activity [19] . Identification of its active compounds and characterization of their mechanism of action might provide new candidates for development of anti-amoebic drugs . The present study goes further in the characterization of C . variegatum amoebicide fraction . A bioassay-guided screening of various fractions of the aqueous extracts from C . variegatum leaves was carried out against trophozoites in axenic culture . The EC50 values were determined for toxic fractions inducing parasite death . Then , an attempt to understand the mode of action of the compounds within active fraction was addressed by differential gene expression analysis using high-throughput RNA Sequencing . The data suggested a multi-target mechanism of action inducing cell death through the disturbance of lipid metabolism in the parasite . This cellular response is different when compared to results obtained by MTZ treatment . We therefore hypothesize that cell death might occur through the disturbance of certain biochemical processes within the cell membrane involving ceramide , a bioactive lipid known as cellular signal implicated in induction of apoptosis and cell growth inhibition . This study suggests a new mechanism of action for anti-amoebic compounds , which can be further explored as a strategy for drug development .
Leaves of C . variegatum were harvested in Yaoundé ( Cameroon ) according to several criteria: sites of cultivation ( forest and garden ) , period of the day ( morning , midday , afternoon and midnight ) and stage of development ( young and old leaves ) . It should be noted that young or old leaves as well as leaves from the forest and the garden were all collected in the morning . Leaves from more than 20 different plants were collected . The leaves were thoroughly washed with tap water , rinsed with distilled water , dried at room temperature and ground . The powder obtained , 200 grams ( g ) for each batch , was mixed with 2 litres of distilled water for the preparation of aqueous extracts by decoction for 1 hour . After filtration with Whatman No . 1 filter paper , the filtrate collected was dried by lyophilization . The sequential decoction of powdered leaves ( start with 4100 g ) yielded 992 . 34 g of aqueous extract which after washing with methanol led to 470 . 18 g extract . The methanol extract was then partitioned on silica gel by flash chromatography using a gradient of ethyl acetate ( EtOAc ) and methanol ( MeOH ) . Eight stages of polarity were used: EtOAc ( Fraction 1 ) ; EtOAc/MeOH 10% ( Fraction 2 ) ; EtOAc/MeOH 20% ( Fraction 3 ) ; EtOAc/MeOH 30% ( Fraction 4 ) ; EtOAc/MeOH 40% ( Fraction 5 ) ; EtOAc/MeOH 50% ( Fraction 6 ) ; EtOAc/MeOH 80% ( Fraction 7 ) and MeOH ( Fraction 8 ) . Fraction 1 ( 30 . 67 g ) was further partitioned with a gradient polarity of methylene chloride ( CH2Cl2 ) /methanol ( MeOH ) solvent using a silica gel column chromatography . Four solvent systems ( CH2Cl2; CH2Cl2/MeOH 2%; CH2Cl2/MeOH 5% and CH2Cl2/MeOH 10% ) were used during the elution and more than 100 samples ( 80 ml each ) were collected and grouped in 14 sub-fractions according to their chemical profiles analysed by thin layer chromatography . In all the fractionation , solvent was removed in collected samples by using a rotary evaporator . The final fraction or powder was stored at 4°C . Figure 1 depicts the general scheme of fractionation . The virulent strain of E . histolytica ( HM1:IMSS ) was grown in 15 ml screw cap glass tubes at 37°C on TYI-S-33 axenic medium supplemented with 15% ( v/v ) complement-inactivated bovine serum ( PAA laboratories GmbH , Austria ) , 3% Diamond vitamin Tween 80 ( Sigma-Aldrich , Saint Quentin Fallavier , France ) and 1% Penicillin-Streptomycin ( Sigma-Aldrich , Saint Quentin Fallavier , France ) [20] . The culture medium was renewed twice in a week and trophozoites at the exponential phase of growth were used in all experiments . Plant extracts , fractions , sub-fractions and isolated compounds were prepared using sterile DMSO ( Sigma-Aldrich , Saint Quentin Fallavier , France ) and culture medium leading to concentrations of 100 , 50 or 10 mg/ml respectively . Each mixture was filtered with sterile syringe filters ( Ø 22 µm ) and aliquots of two-fold serial dilutions were prepared from these stock solutions . A fresh culture of 5×103 trophozoites per milliliter was introduced in each well of the 48 well microtiter plate and after allowing the parasite to adhere at the bottom of the well , 5 µl of the tested extract or compound was added . The concentration of DMSO did not exceed 0 . 5% in all assays performed . Each test included a blank ( medium only ) and two controls ( one consist of trophozoites with medium only and the other consist of trophozoites with medium containing DMSO ) . Metronidazole ( Sigma-Ultra , CA , USA ) was used as the positive control in each assay ( see tables and figures in the results section for the concentrations tested ) . For microarray experiments , MTZ was used at 8 µg/ml , which correspond to 50 µM . The plates were introduced in Genbag anaer ( Biomerieux , Marcy l'Etoile , France ) and incubated for 48 to 72 hours at 37°C and the cell viability was evaluated with a hemocytometer using the trypan blue ( Sigma-Aldrich , Saint Quentin Fallavier , France ) exclusion technique . In some cases ( as indicated in the tables ) cells were incubated only for 24 hours . The mortality rate of trophozoites was calculated for each concentration tested according to the formula below . The 50% efficient concentrations ( EC50 ) were determined by plotting the graph of mortality rate versus the concentration tested and using a normalised sigmoidal function of the software Statgraphics , Plus Version 5 . 0 . The human colon carcinoma cell line TC7 ( Caco-2 ) was grown to 21 days confluence in Dulbecco's modified Eagle's medium ( Life Technologies , Saint Aubin , France ) supplemented with 15% fetal calf serum ( Eurobio , Les Ulis , France ) and 1% non-essentials amino acids ( Life Technologies , Saint Aubin , France ) at 37°C in a 10% CO2 incubator . Differentiated Caco-2 cells were incubated for 48 hours with varying concentrations of ethyl acetate fraction ( F1 ) , sub-fractions ( SF9 , SF10 , SF11 and SF9B ) and the aqueous extract . The highest concentration tested on these cells was 1 mg/ml; over this concentration the aqueous extract was no longer dissolved in DMSO . Staurosporine 0 . 1 µM ( a chemical which induces apoptosis ) was used as a control for cell death and the solvent ( DMSO ) was the control for viability . After incubation , the culture medium was removed and the viability count was performed using the trypan blue exclusion technique . The tests were performed in triplicate and all data are presented as mean ± SD ( standard deviation ) values . Statistical analysis was performed using GraphPad Instat and student's t-test was used to determine P-values for the differences observed between test compounds and control . Results were considered significantly different when P≤0 . 05 . Trophozoites of E . histolytica ( approximately 1×106 ) grown in 15 ml glass tubes were treated with plant extract sub-fraction SF9B ( at EC50 , discussed later ) or DMSO ( control ) for 12 and 24 hours ( in 3 biological replicates , n = 4×3 ) . Total RNA was extracted from these trophozoites using Trizol reagents ( Invitrogen , Saint Aubin , France ) and poly ( A ) + RNA was purified from 10 µg of total RNA using oligo ( dT ) coated Sera-Mag Magnetic Particles according to manufacturer's instructions ( Thermo Scientific , Fremont , USA ) . PolyA enriched RNA is chemically fragmented to ∼100 bp ( Ambion , USA ) and purified with RNeasy MinElute Cleanup Kit ( Qiagen , Venlo , Netherlands ) according to manufacturer's instructions . Strand-specific cDNA libraries ( n = 12 ) were prepared using an RNA ligation protocol based on Illumina TruSeq Small RNA Sample Preparation Kit [21] . Sequencing of these libraries was performed on a HiSeq 2000 ( Illumina ) in a multiplexed single-ended setting for 50 cycles using TruSeq SR Cluster kit v3 cBot HS and TruSeq SBS kit v3 HS ( Illumina ) . After sequence files generation using CASAVA 1 . 7 ( Illumina ) , 3′ adapter sequence was trimmed using Cutadapt [22] . These processed short reads data have been deposited in the European Nucleotide Archive ( http://www . ebi . ac . uk/ena/data/view/ PRJEB3953 ) . Sequence reads were mapped to E . histolytica genome assembly ( AmoebaDB v1 . 7 , http://amoebadb . org/amoeba/ ) using Tophat version 2 . 0 . 6 [23] with default parameters . Coding genes differentially expressed in cells treated with SF9B versus control ( in triplicates ) at 12 or 24 hours were identified using Cuffdiff version 2 . 0 . 2 [23] and DESeq version 1 . 12 . 0 [24] with default parameters . Coding gene models were based on the bona fide gene models defined in previous work [25] . Differentially expressed genes were defined as genes at ≤5% false discovery rate with ≥2-fold change identified in either Cuffdiff or DESeq analyzes . Trophozoites of E . histolytica ( 4×106 ) grown in axenic culture and treated or not with metronidazole ( at 50 µM for one hour ) , were lysed with Trizol reagent and total RNA isolated according to the manufacturer's protocol . RNA was analyzed for integrity and the concentration determined by capillary electrophoresis using the Agilent Bioanalyzer 2100 RNA nanochip Assay ( Agilent Technologies ) . Agilent microarrays EH-IP2008 , scanning the entire amoebic genome , were used as previously described [26] . Dye swap hybridizations were performed for the three biological replicates leading to a total of 6 competitive hybridizations . The whole data set was submitted to the ArrayExpress database ( Accession number: E-MTAB-1763 ) . After pooling data from technical and biological replicates , differential analysis was carried out as published [26] and includes paired Student's t-test . The raw P-values were adjusted by the Benjamini and Yekutieli method which controls the false discovery rate ( FDR ) [27] . We considered as being differentially expressed the genes with a Benjamini and Yekutieli P-value <0 . 05 and expression fold change ≥2 . Trophozoites of E . histolytica ( 5×103 ml−1 ) were mixed with 5 µl of the active sub-fractions to obtain final concentrations of EC50 . The microtiter plate was introduced in Genbag anaer and then incubated at 37°C for 12 , 24 and 48 hours and cell viability was evaluated as above described . The same assay was carried out on 8-wells Chamber Slide System ( Brumath , France ) , the chamber was introduced in a Genbag anaer for 12 hours and the morphology of amoebae was examined using indirect immunofluorescence assay . Briefly , amoebae cells were fixed with 500 µl of formaldehyde 3 . 7% ( Thermo scientific , Waltham-MA , USA ) for 30 minutes , washed with 500 µl of 3% BSA in PBS and then incubated for 30 minutes at 37°C . The primary antibody Gal/GalNAc lectin ( 1∶100 diluted in 1% BSA-PBS ) was added and the plates incubated for one hour at 37°C in humidified atmosphere . The plates were washed twice with 1% BSA-PBS . The secondary antibody Alexa Fluor 546 goat anti-rabbit IgG ( 1∶200 diluted in 1% BSA-PBS ) was added and incubated for 45 minutes at 37°C . At the end of the experiment , the plates are washed thrice with PBS and the mounting medium Vectashield with nuclear stain DAPI ( Vector-ABCYS ) was used . For every assay , DMSO is used as negative control . The cells were observed by epifluorescence microscopy ( Olympus ) .
The anti-amoebic action of C . variegatum was assessed on axenic culture of trophozoites and the results are presented as follow: in the presence of the plant aqueous extract , the growth inhibition or mortality of E . histolytica increases in a concentration dependent manner and the collection criteria of leaves for extract preparation as well as the period of incubation significantly influenced the mortality rate . By plotting the mortality rate against concentration , EC50 of the extracts were determined ( Table 1 ) . Despite the fact that no extract induced total mortality ( 100% ) in the performed assay , we did not observe any stationary phase in amoebic growth , ( Figure 2 ) . We noticed that the anti-amoebic activity of the extracts depends on the leaves harvest criteria and it increases with the time of incubation . No significant difference was observed among the extracts from different sites of plant collection; extract from plants harvested at midnight ( E6 ) showed significantly higher anti-amoebic activity compared to extracts from plants harvested at other period of the day . Extract obtained from old leaves and collected in the morning ( E8 ) exhibited the highest significant anti-amoebic activity amongst all samples tested and displayed a EC50 of 120 . 00 µg/ml after 48 hours of incubation and 60 . 54 µg/ml after 72 hours of incubation . However , when compared to pure MTZ ( EC50 = 0 . 73 µg/ml after 72 hours of incubation ) , extract E8 showed significantly lower anti-amoebic activity . Due to its complex chemical composition , which may prevent activity of some compounds , we promptly initiated the identification and characterization of active compounds in E8 . After extraction with methanol ( MeOH ) , we attempted to identify the active components in different fractions derived from chromatography ( Figure 1 ) . Three fractions ( F1 , F2 and F8 ) showed significant anti-amoebic activity , while F1 incubation for 48 hours was the most active amongst all conditions tested . Then , these three active fractions were further tested during 72 hours of incubation . The first observation was that the unfractionated MeOH extract achieved total mortality ( 100% ) at the concentration of 500 µg/ml . Determination of EC50 was carried out for the unfractionated MeOH extract and three active fractions , which all exhibited at least 50% mortality ( Table 2 ) . The unfractionated MeOH extract was more potent than any of the three active fractions alone , with EC50 of 126 . 50 µg/ml and 53 . 00 µg/ml after 48 and 72 hours of incubation , respectively . Although the fraction F1 did not achieve total mortality , more than 90% of trophozoites were killed and this fraction was significantly more potent than other two active fractions , with EC50 of 202 . 00 µg/ml and 61 . 83 µg/ml after 48 and 72 hours of incubation , respectively . F1 was further explored owing to its relatively simpler chemical composition and its relatively higher efficacy compared to the other two active fractions . Silica-gel column chromatography was performed on F1 , yielding 14 sub-fractions grouped according to their frontal ratio on thin layer chromatography profiles ( Figure 1 ) . Three of these sub-fractions ( SF9 , SF10 and SF11 ) exhibited significant anti-amoebic activity . Table 3 summarises EC50 of the active sub-fractions . Mortality due to these sub-fractions increased in a concentration dependent manner and 100% mortality was observed for sub-fractions SF9 at 125 µg/ml and for SF11 at 250 µg/ml after 72 hours of incubation . SF9 showed significantly higher anti-amoebic activity compared to other sub-fractions , with EC50≤15 . 62 µg/ml after 72 hours of incubation . The chemical analysis of the 3 sub-fractions ( SF9 , SF10 and SF11 ) using thin layer chromatography and nuclear magnetic resonance revealed a common spot at the same frontal ratio and similarity between the three spectra meaning that these sub-fractions contain similar compounds , respectively . Interestingly , the presence of a small amount of observable crystals in these sub-fractions might imply the existence of certain compounds in the sub-fractions at a considerably high purity . In order to identify these compounds , the most active sub-fraction SF9 was further analysed chemically and the fractionation process is described in Figure 3 . In fact , the sub-fraction SF9 was separated into a crystal fraction ( SF9A ) and a soluble fraction ( SF9B ) . The crystal fraction was unfortunately less efficient than the soluble fraction . Chemical analysis of the soluble fraction suggested that SF9B is likely consisted of mainly 3 compounds ( SF9B1 , SF9B2 and SF9B3 ) . The comparison of nuclear magnetic resonance ( NMR ) spectra of these sub-fractions suggests that they contain similar compounds with a common skeleton and some additional chemical groups which are important for their potency . Figure 4 described the superposition of different spectra of isolated sub-fractions or compounds . Further assays showed that SF9B1 , SF9B2 and SF9B3 kill trophozoites with different potencies , while SF9B2 exhibited a pronounced activity against trophozoites comparable to the unfractionated soluble fraction ( i . e . SF9B ) and MTZ . EC50 of these active compounds were showed in Table 4 . Based on the calculated EC50 , the soluble fraction SF9B , which contained the mixture of at least 3 compounds , appeared as the most efficient killer of trophozoites compared to any of the isolated compounds alone ( Figure 5 ) . The high potency of SF9B can result from synergistic or additional action between isolated compounds and therefore SF9B was used in the following experiments . After incubating the trophozoites with SF9B for various durations ( 12 , 24 and 48 hours ) and concentrations ( 1 . 56–50 µg/ml ) , we determined an optimal condition which is sufficient to visualize cell morphology changes while keeping cell viability . The optimal condition is to expose trophozoites at EC50 with SF9B fraction and for a maximum period of 24 hours . The treatment of trophozoites with 3 . 78 µg/ml of SF9B2 and 2 . 75 µg/ml of SF9B caused different mortality rate according to the period of incubation ( Figure 6 ) . Death of trophozoites is firstly reflected by cell rounding and finally cell lysis . Dying cells detached from the bottom of the microtiter plate and attached viable cells could be counted . Treatment of Caco-2 cells with the aqueous extract , fraction F1 and sub-fractions SF9 , SF10 , SF11 and SF9B at a wide range of concentrations did not show significant difference in cell death when compared to the negative control ( DMSO ) . Therefore , at the tested concentrations , extracts and active fractions from C . variegatum had no observable cytotoxic effect on Caco-2 cells up to 1 mg/ml , while the positive control ( Staurosporine 0 . 1 µM ) induced substantial cytotoxicity between 30–40% of these cells . To gain insight into the molecular basis of the anti-amoebic activity of SF9B , a transcriptome analysis was performed using high-throughput RNA sequencing . Briefly , the trophozoites were treated with SF9B at EC50 ( or DMSO as a control ) for 12 and 24 hours in biological triplicates ( n = 4×3 , see methods ) . Totally 12 libraries were sequenced and on average ∼13 millions reads ( ranging from ∼5 to ∼23 millions ) were mapped to the coding genes ( n = 7312 ) in each of the libraries . Differentially expressed genes ( DEG ) were identified by comparing SF9B treated cells versus control cells of the same time points ( i . e . DEG at 12 and 24 hours , see methods for DEG definition ) . We identified 9 and 30 DEG at 12 and 24 hours respectively ( Table 5 , Tables S1 and S2 ) . All 9 DEG at 12 hours overlap with DEG at 24 hours and their fold-changes are comparable between time points , suggesting that the transcriptomic changes are generally consistent between time points and progressed in a time-dependent manner . Interestingly , 28 of the 30 DEG were down-regulated upon SF9B treatment , including 9 genes involved in the biosynthesis of ceramide . Ceramide , which is composed of sphingosine and a fatty acid , is found within the cell membrane as a bioactive lipid implicated in a variety of physiological functions including apoptosis and cell growth arrest . These down-regulated DEG includes: acid shingomyelinase ( EHI_040600 ) that mediates production of ceramide from shingomyelin ( major lipid in the membrane bilayer ) , and several genes encoding enzymes involved in production of Acyl-CoA ( fatty acid with CoA ) or in the synthesis of fatty acid ( Table 5 ) . Down-regulation of these genes might imply a diminution of ceramide level in SF9B treated trophozoites . Moreover , two DEG encoding distinct orthologues of the longevity-assurance ( Lag ) proteins were up-regulated ( 56% amino acid identity and 72% homology ) . These two proteins ( EHI_139080 and EHI_130860 ) contain a TLC domain ( common to TRAM , LAG1 and CLN8 which are members of a novel family of lipid-sensing proteins ) , and EHI_139080 in addition carries one ER-targeted motif . The TLC family may possess multiple functions such as lipid trafficking , metabolism , or sensing . Proteins containing TLC domains should catalyse the synthesis of ceramide and in particular Lag1 from Saccharomyces cerevisiae is essential for acyl-CoA-dependent ceramide synthesis . According to this function , the upregulation of Lag genes may attempt to overcome the deficiency of ceramide in amoebae treated with SF9B . However , other suggested functions for TLC containing proteins are their role in protecting proteins from proteolysis through their binding to vacuolar ATPases [28] and their function as linkers of lipid transporters between the endoplasmic reticulum ( ER ) -to-Golgi traffic [29] . The categories of other downregulated genes include stress and oxyreduction , ATP binders , two cysteine proteinases ( CP ) , cysteine synthase and a protein carrying myb transcription factor homology . Almost all of these genes are transcriptionally downregulated after 24 hours of compound treatment . The downregulation of heat shock proteins ( Hsp 70 and Hsp 90 ) , known to act as chaperones for signal transducers by blocking some steps of apoptotic pathways [30] , [31] , revealed the inhibition of any cell damage repair therefore impairing cell survival upon exposure to SF9B . Moreover , it is known that cysteine , a major thiol which replaces glutathione in E . histolytica and which plays a major role in growth and survival of E . histolytica [32] , [33] , is synthesized via a pathway consisting of two steps catalyzed by serine acetyltransferase and cysteine synthase [34] , [35] . The reduced expression of cysteine synthase by treatment with SF9B implies low level of cysteine which is supposed to protect E . histolytica against oxidative stress and external environment that may cause cell death . Furthermore , down-regulation of two cysteine proteinases ( CP-A5 and CP-A8 ) demonstrated loss or reduction of cytolytic activity of treated trophozoites . In fact , CP , especially CP-A5 was found to be associated with the trophozoite membrane and has been suggested to play a key role in host tissue invasion and destruction [36] , [37] . Overall the findings of the RNASeq experiment were reinforced by transcriptome analysis of E . histolytica treated in the presence of MTZ ( 92% of cell survival determined by trypan blue assay ) . The expression of the entire genes set of E . histolytica was examined using EH-IP2008 microarray [26] . By MTZ treatment , we highlighted the downregulation of peroxiredoxin encoding gene but no changes in ceramide biosynthesis genes were found ( Table S3 ) . Notice that genes whose transcription was modified by the presence of MTZ were not significantly modulated by SF9B treatment . A dual role of acid shingomyelinase ( ASM ) has been suggested . First , it has an essential housekeeping function within the lysosomes and late endosomes of virtually all cells , participating in membrane turnover . Second , ASM translocates from intracellular compartments to the cell membrane , where hydrolysis of sphingomyelin into ceramide initiates membrane reorganization and facilitates the formation and coalescence of lipid microdomains , bringing inactive monomeric signalling proteins into active oligomers responsible for cell death . High levels of cholesterol and sphingolipid characterize these membrane domains . In E . histolytica , lipid rafts are enriched in Gal/GalNAc lectin , a surface protein complex involved in parasite adhesion to cells [38] . An immunofluorescence assay characterizing the Gal/GalNAc lectin , was thus used to examine the morphology changes and localization of the Gal/GalNAc lectin induced by active components from SF9B . In general , SF9B treatment caused significant changes on trophozoites surface after 12 hours of incubation . These changes were characterized by the accumulation of the cell surface Gal/GalNAc lectin in an agglomerate patches at certain points of the parasite surface ( Figure 7 ) .
This study described a guided process of isolating compounds from the aqueous extract of C . variegatum which is active against trophozoites of E . histolytica growing on an axenic culture . A group of compounds was identified with strong anti-amoebic activity and their characterization and structure-activity modifications in the near future may identify a source of new anti-amoebic drugs . So far the most active sub-fraction SF9B induced substantial changes in cell morphology before leading to cell death . We hypothesize that the active components within SF9B might act through destabilization of cell architecture caused by changes in levels of ceramide , a membrane lipid involved in apoptosis and cell growth inhibition .
|
Amoebiasis is a disease caused by a protozoan parasite , Entamoeba histolytica , with or without clinical symptoms . Humans are the only relevant host of this parasite , which mainly targets the large intestine and the liver . The current drug , metronidazole , has been successfully used against this parasite for several years . However , some reports have shown either parasite resistance or adverse effects due to its long term usage . Our study thereby pointed to alternative treatment of this infection by investigating the rational use of Codiaeum variegatum also referred as “garden croton” which is a medicinal plant used in Cameroon against bloody diarrhoea . We moved into the identification of the most efficient fraction of the aqueous extract of this plant , and initiated the characterization of the mechanism of action of this fraction . Upon treatment with the active fraction , parasite death occurs within two days through morphological changes such as cell membrane disorganization and cell destruction . More deeply , we found that components of the active fraction modify expression of genes involved in ceramide biosynthesis , a pathway responsible for cell death and growth inhibition . Our study therefore suggests a novel finding which could be further explored for screening of anti-amoebic drugs .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"parastic",
"protozoans",
"entamoeba",
"histolytica",
"microbial",
"pathogens",
"microbial",
"control",
"protozoology",
"biology",
"microbiology",
"pathogenesis",
"parasitology",
"parasite",
"physiology"
] |
2014
|
Bioassay-Guided Fractionation of Extracts from Codiaeum variegatum against Entamoeba histolytica Discovers Compounds That Modify Expression of Ceramide Biosynthesis Related Genes
|
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